Cognitive reflection correlates with all cognitive abilities and numeracy skills
Cognitive reflection is accounted for by a general factor of intelligence plus a second-stratum factor of numerical ability
Intelligence and numerical ability have direct and indirect effects on cognitive reflection through numeracy skills
This paper presents a series of psychometric meta-analysis on the relationship between cognitive reflection (CR) and several cognitive abilities
(ie. cognitive intelligence, numerical ability, verbal ability, mechanical-spatial ability, and working memory), and skills (ie. numeracy skills). Also, the paper presents a bifactor analysis carried out to determine whether CR is a related but independent
factor or a second-stratum factor in a hierarchical model of cognitive
intelligence. Finally, the study also tested a path meta-analytic model of the CR-cognitive ability relationships.
The results showed that CR correlated substantially with all the cognitive abilities and skills (k ranged 3–44 and n ranged 624–20,307). The
bifactor analysis showed that CR variance was
mainly accounted for by a general factor of cognitive intelligence plus a second-stratum factor of numerical ability. The results of the bifactor analysis were
similar for numerical-CRT and verbal-CRT. It was not found evidence supporting
the existence of a cognitive reflection factor. Finally, the path meta-analytic model showed that the combination of cognitive intelligence and numerical
ability accounted for 69% of CR variance. The path model showed that cognitive intelligence and numerical ability have direct and indirect (through numeracy skills) effects on CR.
Theoretical and practical implications are discussed, and future research is suggested.
This review discusses evidence across a number of popular brief interventions designed to enhance cognitive abilities and suggests that these interventions
often fail to elicit reliable improvements. Consequences of exaggerated claims are discussed, together with a call for constructive criticism when evaluating this
body of research.
A number of popular research areas suggest that cognitive performance can be manipulated via relatively brief interventions. These findings have generated a lot
of traction, given their inherent appeal to individuals and society. However, recent evidence indicates that cognitive abilities might not be as malleable as
preliminary findings implied and that other more stable factors play an important role.
In this article, I provide a critical outlook on these trends of research, combining findings that have mainly remained segregated despite shared
characteristics.
Specifically, I suggest that the purported cognitive improvements elicited by many interventions are not reliable, and that their ecological validity remains
limited.
I conclude with a call for constructive skepticism when evaluating claims of generalized cognitive improvements following brief interventions.
Background: Intellectual disability (ID) aggregates in
families, but factors affecting individual risk and heritability estimates remain unknown.
Methods: A population-based family cohort study of 4,165,785 individuals born 1973–2013 in Sweden, including 37,787 ID individuals and their
relatives. The relative risks (RR) of ID with 95% confidence intervals (95% CI) were obtained from stratified Cox proportional-hazards models. Relatives of ID individuals were
compared to relatives of unaffected individuals. Structural equation
modeling was used to estimate heritability.
Results: Relatives of ID individuals were at increased risk of ID compared to individuals with unaffected relatives. The RR of ID among
relatives increased proportionally to the degree of genetic relatedness with ID probands; 256.70 (95% CI 161.30–408.53) for monozygotic twins, 16.47
(13.32–20.38) for parents, 14.88(12.19–18.16) for children, 7.04 (4.67–10.61) for dizygotic twins, 8.38 (7.97–8.83) for full siblings, 4.56 (4.02–5.16) for
maternal, 2.90 (2.49–3.37) for paternal half-siblings, 3.03 (2.61–3.50) for nephews/nieces, 2.84 (2.45–3.29) for uncles/aunts, and 2.04 (1.91–2.20) for
cousins. Lower RRs were observed for siblings of probands with chromosomal abnormalities (RR 5.53, 4.74–6.46) and more severe ID (mild RR 9.15, 8.55–9.78, moderate
RR 8.13, 7.28–9.08, severe RR 6.80, 5.74–8.07, and profound RR 5.88, 4.52–7.65). Male sex of relative and maternal line of relationship with proband was related to
higher risk (RR 1.33, 1.25–1.41 for brothers vs. sisters and RR 1.49, 1.34–1.68 for maternal vs. paternal half-siblings). ID was substantially
heritable with 0.95 (95% CI 0.93–0.98) of the variance in liability attributed to genetic influences.
Conclusions: The risk estimates will benefit researchers, clinicians, families in understanding the risk of ID in the family and the whole
population. The higher risk of ID related to male sex and maternal linage will be of value for planning and interpreting etiological studies in ID.
Understanding the relationships between cognitive abilities and fitness is integral to an evolutionary study of brain and behavior. However, these relationships
are often difficult to measure and detect.
Here we draw upon an opportunistic sample of brown-headed cowbird
(Molothrus ater) subjects that had 2 separate research experiences: First, they engaged in a large series of cognitive tests in David Sherry’s Lab
in the Advanced Facility for Avian Research (AFAR) at Western University, then subsequently moved to the Field Avian
Research Megalab (FARM) at Wilfrid Laurier University where they lived in large breeding flocks in aviaries with
other wild-caught cowbirds. Thus, we had extensive measures of cognitive abilities, breeding behavior, and reproductive success for these birds.
We report here, for the fist time, the surprisingly strong connections we found among these different measures. Female cowbirds’ spatial cognitive abilities
correlated positively with how intensely they were courted by males, and with their overall egg production. Males’ spatial cognition correlated positively with
their ability to engage in singing contests (“countersinging”) with other males. In addition, a separate non-spatial cognitive ability correlated positively with
the attractiveness of the songs they sung.
In sum, these results suggest the cognitive skills assessed in the lab were strongly connected to breeding behavior and reproductive success. Moreover, since
certain cognitive abilities related to different aspects of breeding success, it suggests that cognitive modules may have specialized adaptive value, but also that
these specialized skills may interact and influence fitness in surprising ways.
Background: Although the ICD and DSM differentiate between
different psychiatric disorders, these often share symptoms, risk factors, and treatments. This was a population-based, case–control, sibling study examining familial
clustering of all psychiatric disorders and low IQ, using data from the Israel Draft-Board Registry on all Jewish adolescents assessed between 1998 and 2014.
Methods: We identified all cases with autism spectrum disorder (ASD,n = 2128),
severe intellectual disability (ID, n = 9572), attention-deficit hyperactive disorder (ADHD) (n = 3272), psychotic (n = 7902), mood (n = 9704), anxiety (n = 10 606), personality
(n = 24 816), or substance/alcohol abuse (n = 791) disorders, and low IQ (⩾2 SDs below the population mean, n= 31 186).
Non-CNS control disorders were adolescents with Type-1 diabetes (n = 2427), hernia (n = 29 558) or
hematological malignancies (n = 931). Each case was matched with 10 age-matched controls selected at random from the Draft-Board Registry, with
replacement, and for each case and matched controls, we ascertained all full siblings. The main outcome measure was the relative recurrence risk
(RRR) of the sibling of acase having the same (within-disorder RRR) or a
different(across-disorder RRR) disorder.
Results: Within-disorder RRRs were increased for all diagnostic categories, ranging from 11.53
[95% confidence interval (CI): 9.23–14.40] for ASD to 2.93 (95% CI: 2.80–3.07) for personalitydisorders.
The median across-disorder RRR between any pair ofpsychiatric disorders was 2.16 (95% CI: 1.45–2.43); the median
RRR between low IQ and any psychiatric disorder was 1.37 (95% CI: 0.93–1.98). There was no consistent increase in
across-disorder RRRsbetween the non-CNS disorders and psychiatric disorders
and/or low IQ.
Conclusion: These large population-based study findings suggest shared etiologies among most psychiatric disorders, and low IQ.
Data from natural settings and laboratories imply Panworking memory (WM) is 2 ± 1
WM increases until puberty but puberty occurs at half the age for Pan as for humans
Claims for extraordinary working memory in Pan are not supported by data
WM increase during hominin evolution parallels complexity increase in stone artifacts
Cumulative WM changes in Homo sapiens evolution led to qualitative cognitive changes
In this article we review publications relevant to addressing widely reported claims in both the academic and popular press that chimpanzees working memory (WM)
is comparable to, if not exceeding, that of humans. WM is a complex multidimensional construct with strong parallels in humans to prefrontal cortex and cognitive development. These parallels occur in chimpanzees, but to
a lesser degree.
We review empirical evidence and conclude that the size of WM in chimpanzees is 2 ± 1 versus Miller’s famous 7 ± 2 in humans. Comparable differences occur in
experiments on chimpanzees relating to strategic and attentional WM subsystems. Regardless of the domain, chimpanzee WM
performance is comparable to that of humans around the age of 4 or 5.
Next, we review evidence showing parallels among the evolution of WM capacity in hominins ancestral to Homo sapiens, the phylogenetic evolution of
hominins leading to Homo sapiens, and evolution in the complexity of stone tool technology over this time period.
[Keywords: working memory, human evolution, cognitive evolution, comparative psychology, chimpanzee, hominin evolution, theory of mind,
planning]
The strong correlation between education and voting is among the most robust findings in social science. We show that genes associated with the propensity to
acquire education are also associated with higher voter turnout. A within-family analysis suggests education-linked genes exert direct effects on voter turnout but
also reveals evidence of genetic nurture in second-order elections. Our findings have important implications for the study of political inequality. Scholars have
argued that parental education is the main driver of the reproduction of political inequality across generations. By separating the effect of genes from parental
nurturing, our findings suggest that the roots of individual-level political inequality run deeper than family background.
Twin and adoption studies have shown that individual differences in political participation can be explained, in part, by genetic variation. However, these
research designs cannot identify which genes are related to voting or the pathways through which they exert influence, and their conclusions rely on possibly
restrictive assumptions.
In this study, we use 3 different US samples and a Swedish sample to test whether genes that have been identified as associated with educational attainment, one
of the strongest correlates of political participation, predict self-reported and validated voter turnout.
We find that a polygenic score capturing individuals’ genetic propensity to
acquire education is statistically-significantly related to turnout. The strongest associations we observe are in second-order midterm elections in the United
States and European Parliament elections in Sweden, which tend to be viewed as less important by voters, parties, and the media and thus present a more
information-poor electoral environment for citizens to navigate. A within-family analysis [n = 10,000 sibling pairs] suggests that individuals’
education-linked genes directly affect their voting behavior..after controlling for the EDU PGS, the effect of
education shrinks by 8%–17%, signaling that genes associated with education partially confound the relationship between education and turnout…but, for second-order
elections, it also reveals evidence of genetic nurture. Finally, a mediation analysis suggests that educational attainment and cognitive ability combine to account
for between 41% and 63% of the relationship between the genetic propensity to acquire education and voter turnout.
…Figure 1 illustrates that the polygenic score’s explanatory power is on par with that of personal income, parental income, and parental
education and accounts for about half as much variation as years of education…Another possible mediator is personality, given that the EA PGS is correlated with personality traits(34, 35), a growing literature has demonstrated personality traits to
be important for turnout(36), and personality and turnout have been shown to be influenced by shared genetic factors(9, 10).
Belief in astrology is on the rise, although the reasons behind this are unclear. We
tested whether individual personality traits could predict such epistemically unfounded beliefs.
Data was collected for 264 participants through an anonymous online survey shared on social media. The survey consisted of 4 instruments: Belief in
Astrology (BAI), theBig Five
personality traits(IPIP-30),narcissism (SD3 [Short Dark Triad]), and intelligence (ICAR16-R3D). Data analysis was done
with multiple linear regression.
Narcissism was surprisingly the strongest predictor, and intelligence showed a negative relationship with belief in astrology.
Overall, our novel results suggest that something as innocent as astrology could both attract and possibly reinforce individual differences.
[Keywords: belief in astrology, pseudoscience, Big Five, narcissism, intelligence]
Duckworth & Seligman 2005’s seminal work found that self-discipline (self-control) was more salient for
academic achievement than intelligence. Very little replication work exists, including in different cultures; the current study addressed these gaps.
Data were collected from 6th and 7th grade cohorts of early adolescents [Brno Longitudinal Study of Youth (BLSY), an accelerated longitudinal study of 6th and 7th grade Czech adolescents] (n = 589; age: Mean
= 12.34 years, and SD = 0.89; 58% female) over 2 years. The study tested whether self-control was a stronger predictor than intelligence in explaining academic
performance 2 years later as well as in explaining developmental changes over the course of 2 years.
Path analyses provided evidence that both self-control and intelligence longitudinally predicted teacher-reported academic competence as well as school-reported
grades; however, intelligence was a substantially stronger predictor than self-control. In addition, only intelligence predicted developmental changes in each
measure of academic performance over time, self-control did not.
This study investigated the systematic rise in cognitive ability scores over generations, known as the Flynn Effect, across middle childhood and early adolescence (7–15 years; 291 monozygotic pairs, 298 dizygotic pairs; 89% White).
Leveraging the unique structure of the Louisville Twin Study (longitudinal data collected continuously
from 1957 to 1999 using the Wechsler Intelligence Scale for
Children[WISC], WISC-R, andWISC-III editions), multilevel analyses revealed between-subjects Flynn Effects—as both decrease in mean scores upon test
re-standardization and increase in mean scores across cohorts—as well as within-child Flynn Effects on cognitive growth across age. Overall gains equaled
approximately 3 IQ points per decade.
Novel genetically informed analyses suggested that individual sensitivity to the Flynn Effect was moderated by an interplay of genetic and environmental
factors.
…Within-level and between-level FEs: The FE has usually been documented as a between-subjects phenomenon, either as mean increases in cognitive
ability scores over generations or mean decreases between test versions. There is reason to suspect that environmental influences associated with between-subjects
FEs also influence cognitive ability at the individual level, boosting intellectual growth across development above and beyond typical age-related gains. Dickens &
Flynn 2001, for example, proposed that environmental enrichment makes it easier for children to select into environments that match their cognitive ability.
Cognitively beneficial environments, in turn, boost cognitive growth, which facilitates further self-selection into more positive environments, in turn boosting
cognitive ability, and so on, creating a reciprocal cycle that makes individual children exhibit greater intellectual growth across development. The individual
gains brought about by individual multipliers, as Dickens & Flynn 2001 called them, can be thought of as within-person FEs. If enough children in a given
population show such within-person FEs, the group mean will also rise, eventually resulting in a between-subjects FE across cohorts. A reciprocal process of social
multipliers, which is the between-subjects analog of the individual multipliers process, can compound mean cognitive ability gains over time.
Although the possible connection between within-level and between-level FEs has been discussed for 2 decades, few studies have examined this empirically.
Effective investigation of within-person FEs requires longitudinal data to model individual cognitive growth across age and isolate within-person FEs from
age-related gains, as well as multilevel data across cohorts to distinguish within-level FEs from between-level FEs. Datasets meeting those criteria are rare and,
perhaps because of this rarity, nearly all previous FE studies have performed solely crosssectional, between-subjects analyses. Only 2 previous reports have
investigated within-person FEs using a multilevel approach. In 2 distinct multilevel analyses of math scores collected longitudinally across childhood between
1986 and 2012, O’Keefe & Rodgers 2017 observed statistically-significant within-person FEs, along with between-subjects gains. Later, O’Keefe & Rodgers 2020 performed a followup analysis
of the same data. Results highlighted the utility of examining within-person FEs using longitudinal, multilevel approaches, to arrive at a more nuanced
understanding of the FE.
…Current study: In this study, we examined the FE in data from the Louisville Twin Study (LTS), an
intensive longitudinal study of cognitive development (Rhea 2015; Wilson 1983). Analyses
focused on middle childhood and early adolescence (ages 7–15 years). Several features of the LTS data make them
particularly well-suited for FE analyses and for addressing the gaps in the literature described above. First, initial data were collected continuously from
1957 to 1999, making it possible to test for rising IQ scores across generational cohorts of U.S. boys and girls over a long time span. Second, 3 versions of
the WISC were administered over the course of the study (WISC, WISC-R, and WISC, 3rd
ed. [WISC-III]). This allowed us to examine whether test restandardization resulted in systematic drops in mean
IQ scores. Third, children were followed longitudinally, with some taking multiple versions of the WISC over the course
of their participation. This enabled us to test for FEs not only between subjects (ie. rises in mean scores), but also within children (ie. rate of
within-person cognitive growth), all while taking advantage of the statistical benefits offered by longitudinal models (eg. distinguishing age effects from cohort
effects, increased power). Finally, because the LTS is a twin study, we were able to partition thevariance of the within-person FE into genetic and environmental components (also referred to as biometric components) and examine the
relative influence of genetic and environmental factors on individual sensitivity to the FE. In doing so, we performed the first-ever genetically informed analyses
of the FE.
Thus, the unique structure of the LTS data enabled us to examine the FE as both cohort effects and test version
effects simultaneously in a single sample. This data structure also made it possible to analyze FEs both within children and between children, and to examine the
relative influence of genetic and environmental factors on within-person FEs. By modeling all of these elements, we were able to isolate specific aspects of the FE
while controlling for alternate effects (ie. cohort vs. test version effects, within-level vs. between-level effects, genetic vs. environmental
components). At the between-subjects level, we hypothesized that we would observe evidence of the FE in 2 ways: (1) for a given age and test version,
children who participated more recently in the LTS testing period would have higher cognitive ability scores on
average than previous cohorts; (2) for a given age and cohort, children who took newer WISC versions would score
lower on average than children who took older versions. Within individual children, we expected that within-person FEs would boost the rate at which children grew
intellectually between ages 7 and 15 beyond expected age-related growth. Because this was the first genetically formed study of the FE, we treated our biometric
analyses as exploratory.
…Developmental changes in cognitive ability can be difficult to observe when cohort, test version, and age are all varying simultaneously. To our knowledge,
this was the first study to document cohort and test version FEs together in a single sample. Studies that use either the cohort or test version approach face
major limitations inherent in each method (limited representativeness of military conscripts in the former, vulnerability to changes in content between test
versions in the latter). The fact that we documented both types of effects substantially increases our confidence that the FE is robust in the LTS sample. Furthermore, modeling both cohort and test version effects enabled us to document the full manifestation of the FE
in the LTS, which otherwise might not have been apparent. Although mean IQ scores were approximately 100 at each age
(Table 1), this apparent stability was the result of a complex process in which gains across cohorts and within individuals across age were
balanced out by decreases in scores due to test restandardization. Analyzing one type of FE without controlling for the other would have revealed only half of the
story…These results suggest that the FE boosted both individual cognitive growth between ages 7 and 15 relative to age-based norms and mean cognitive ability
scores across generations. Our results provide novel evidence of within-person FEs not only on fluid intelligence, as documented previously (O’Keefe & Rodgers 2017), but also crystallized and general cognitive ability (as
measured by VIQ and FSIQ, respectively). Moreover, our within-person FE findings
speak to the importance of modeling the FE at multiple levels of analysis, where possible. By capturing both within-level and between-level FEs, multi-level models offer a more nuanced understanding of how the FE operates across
development. At least in our sample, the FE was not only a population-level phenomenon that drives broad gains in mean cognitive ability across generations. The FE
also appeared to influence the cognitive development of individual children, boosting their intellectual growth beyond what would have occurred without positive
environmental inputs. Had we only measured between-level FEs, as is traditionally done in FE research, we would have missed this important aspect of cognitive
development.
…Our finding that sensitivity to the FE on FSIQ, VIQ, and PIQ all showed substantial heritability (A) serves as a fascinating example of gene-environment interplay—the extent to which a
child’s growth in cognitive ability received a boost from the environment was influenced by genetic factors. The environment also plays an important role, as
variance in shared (C) and non-shared (E) environmental factors were both associated with individual-level sensitivity to the FE. Given the magnitudes of the
observed standard errors, interpretations about possible biometric differences across cognitive domains should be made with some caution. That being said, results
suggested that sensitivity to the FE on FSIQ may be more heritable than sensitivity to the FE on more specific
cognitive domains (ie. crystallized intelligence and fluid intelligence as estimated by VIQ and PIQ, respectively). If robust, this variability speaks to the utility of analyzing the FE in multiple cognitive domains, as
biometric results from FE analyses of general intelligence (eg. IQ) may not apply directly to more specific measures of cognitive ability.
Background: Almost 2 decades of research produced mixed findings on the relationship between celebrity worship and cognitive skills.
Several studies demonstrated that cognitive performance slightly decreases with higher levels of celebrity worship, while other studies found no association
between these constructs. This study has 2 aims: (1) to extend previous research on the association between celebrity worship and cognitive skills by applying the
two-factor theory of intelligence by Cattell on a relatively large sample of Hungarian adults, and (2) to
investigate the explanatory power of celebrity worship and other relevant variables in cognitive performance.
Methods: A cross-sectional study design was used. Applying an online survey, a total of 1,763 Hungarian adults (66.42% male,
Mage = 37.22 years, SD = 11.38) completed 2 intelligence subtests designed to measure ability in vocabulary (Vocabulary Test) and digit symbol
(Short Digit Symbol Test). Participants also completed the Celebrity Attitude Scale and the Rosenberg Self-esteem Scale. Subjective material wealth, current family
income and general sociodemographics were also reported by participants.
Results: Linear regression models indicated that celebrity worship was associated with lower performance on the cognitive tests even after
controlling for demographic variables, material wealth and self-esteem, although the explanatory power was limited.
Conclusions: These findings suggest that there is a direct association between celebrity worship and poorer performance on the cognitive tests
that cannot be accounted for by demographic and socioeconomic factors.
Some research has investigated the Big Five personality dimensions among gifted individuals, but these individual studies have provided
inconclusive results.
The current meta-analysis examined the nature of the relationship between the Big Five dimensions and giftedness among
individuals. Hedge’s unbiased g was used as the effect size metric, and a 3-level multilevel meta-analytic approach was applied, due to the dependency
among the effect-sizes obtained from the same study.
Cognitive variation is common among-individuals within populations, and this variation can be consistent across time and context. From an evolutionary
perspective, among-individual variation is important and required for natural selection. Selection has been hypothesised to favour high cognitive performance, however directional selection
would be expected to erode variation over time. Additionally, while variation is a prerequisite for natural selection, it is
also true that selection does not act on traits in isolation. Thus, the extent to which performance covaries among specific cognitive domains, and other aspects of
phenotype (e.g. personality traits) is expected to be an important factor in shaping evolutionary dynamics. Fitness trade-offs could shape patterns of
variation in performance across different cognitive domains, however positive correlations between cognitive domains and personality traits are also known to
occur. Here we aimed to test this idea using a multivariate approach to characterise and test hypothesised relationships of cognitive performance across multiple
domains and personality, in the Trinidadian guppy (Poecilia
reticulata). We estimate the among-individual correlation matrix (ID) in performance across three cognitive domains; association learning in a colour
discrimination task; motor cognition in a novel motor task and cognitive flexibility in a reversal learning task, and the personality trait boldness, measured as
time to emerge. We found no support for trade-offs occurring, but the presence of strong positive domain-general correlations in ID, where 57% of the variation is
explained by the leading eigen vector. While highlighting caveats of how non-cognitive factors and assay composition may affect the structure of the ID-matrix, we
suggest that our findings are consistent with a domain-general axis of cognitive variation in this population, adding to the growing body of support for
domain-general variation among-individuals in animal cognitive ability.
The use of spoken and written language is a capacity that is unique to humans. Individual differences in reading-related and language-related skills are
influenced by genetic variation, with twin-based heritability estimates of 30–80%, depending on the trait. The relevant genetic architecture is complex,
heterogeneous, and multifactorial, and yet to be investigated with well-powered studies.
Here, we present a multi-cohort genome-wide association study (GWAS) of 5 traits assessed individually using
psychometric measures: word reading, non-word reading, spelling, phoneme awareness, and non-word repetition, with total sample sizes ranging from 13,633 to 33,959
participants aged 5–26 years (12,411 to 27,180 for those with European ancestry, defined by principal component analyses).
We identified a genome-wide statistically-significant association with word reading (rs11208009, p = 1.098 x 10–8) independent of known loci associated
with intelligence or educational attainment. All five reading/language-related traits had robust SNP-heritability estimates (0.13–0.26), and genetic correlations between them were modest to high. Using genomic structural equation modelling, we found evidence
for a shared genetic factor explaining the majority of variation in word and non-word reading, spelling, and phoneme awareness, which only partially overlapped
with genetic variation contributing to non-word repetition, intelligence and educational attainment.
A multivariate GWAS was performed to jointly analyse word and non-word reading, spelling, and phoneme
awareness, maximizing power for follow-up investigation. Genetic correlation analysis of multivariate GWAS results with neuroimaging traits identified association with cortical surface area of the banks of the left superior temporal
sulcus, a brain region with known links to processing of spoken and written language.
Analysis of evolutionary annotations on the lineage that led to modern humans showed enriched heritability in regions depleted of Neanderthal variants.
Together, these results provide new avenues for deciphering the biological underpinnings of these uniquely human traits.
The past 30 years of research in intelligence has produced a wealth of knowledge about the causes and consequences of differences in intelligence between
individuals, and today mainstream opinion is that individual differences in intelligence are caused by both genetic and environmental influences. Much more
contentious is the discussion over the cause of mean intelligence differences between racial or ethnic groups. In contrast to the general consensus that
interindividual differences are both genetic and environmental in origin, some claim that mean intelligence differences between racial groups are completely
environmental in origin, whereas others postulate a mix of genetic and environmental causes.
In this article I discuss 5 lines of research that provide evidence that mean differences in intelligence between racial and ethnic groups are partially
genetic. These lines of evidence are:
I also discuss future potential lines of evidence regarding the causes of average group differences across racial groups.
However, the data are not fully conclusive, and the exact degree to which genes influence intergroup mean differences in intelligence is not known. This
discussion applies only to native English speakers born in the United States and not necessarily to any other human populations.
Focal cortical lesions lead to local, not global, deficits.
Measurement models to explain the positive manifold are causal models with unique predictions going beyond model fit statistics.
Correlated factor, network, process sampling, mutualism, investment models, make causal predictions inconsistent with lesion evidence.
Hierarchical and bifactor models are consistent with the pattern of
lesion effects, as well as possibly one form of bonds sampling models.
Future models and explanations of the positive manifold have to accommodate focal lesions leading to local not global deficits.
Here we examine 3 classes of models regarding the structure of human cognition: common cause models, sampling/network models, and interconnected models. That
disparate models can accommodate one of the most globally replicated psychological phenomena—namely, the positive manifold—is an extension of underdetermination of
theory by data. Statistical fit indices are an insufficient and sometimes intractable method of demarcating between the theories; strict tests and further evidence
should be brought to bear on understanding the potential causes of the positive manifold. The cognitive impact of focal cortical lesions allows testing the
necessary causal connections predicted by competing models. This evidence shows focal cortical lesions lead to local, not global (across all abilities), deficits.
Only models that can accommodate a deficit in a given ability without effects on other covarying abilities can accommodate focal lesion evidence.
After studying how different models pass this test, we suggest bifactor models (class: common cause models) and bond models (class: sampling models) are best
supported. In short, competing psychometric models can be informed when their implied causal connections and predictions are tested.
[Keywords: human intelligence, structural
models, causality, statistical model fit, cortical lesions]
[This would seem to explain the failure of dual n-back & WM training in general.
Training the specific ability of WM could only cause g increases in models with ‘upwards causation’ like hierarchical models or dynamic mutual
causation like mutualism/investment models; these are ruled out by the lesion literature which finds that physically-tiny lesions damage specific abilities but
not g, and if decreasing a specific ability cannot decrease g, then it’s hard to see how increasing that ability could ever increase g.
See also Lee et al 2019.]
Self-reported mate preferences suggest intelligence is valued across cultures, consistent with the idea that human intelligence evolved as a sexually selected trait. The validity of self-reports has been questioned though, so it
remains unclear whether objectively assessed intelligence is indeed attractive.
In Study 1, 88 target men had their intelligence measured and based on short video clips were rated on intelligence, funniness, physical attractiveness and
mate appeal by 179 women. In Study 2 (n = 763), participants took part in 2 to 5 speed dating sessions in which their intelligence was measured and they rated each other’s intelligence, funniness, and mate appeal.
Measured intelligence did not predict increased mate appeal in either study, whereas perceived intelligence and funniness did. More intelligent people were
perceived as more intelligent, but not as funnier.
Results: suggest that intelligence is unimportant for initial attraction, which raises doubts concerning the sexual selection theory of
intelligence.
[Keywords: intelligence, mate choice, sexual selection]
The human brain is organised into networks of interconnected regions that have highly correlated volumes. In this study, we aim to triangulate insights into
brain organisation and its relationship with cognitive ability and ageing, by analysing genetic data.
We estimated general genetic dimensions of human brain morphometry within the whole brain, and 9 predefined canonical brain networks of interest. We did
so based on principal components analysis (PCA) of genetic correlations among grey-matter volumes for 83 cortical and
subcortical regions (nparticipants = 36,778).
We found that the corresponding general dimension of brain morphometry accounts for 40% of the genetic variance in the individual brain regions across the whole
brain, and 47–65% within each network of interest. This genetic correlation structure of regional brain morphometry closely
resembled the phenotypic correlation structure of the same regions. Applying a novel multivariate methodology for calculating SNP effects for each of the general dimensions identified, we find that general genetic dimensions of morphometry within
networks are negatively associated with brain age (rg = −0.34) and profiles characteristic of age-related neurodegeneration, as
indexed by cross-sectional age-volume correlations (r = −0.27). The same genetic dimensions were positively associated with a genetic general factor of
cognitive ability (rg = 0.17–0.21 for different networks).
We have provided a statistical framework to index general dimensions of shared genetic morphometry that vary between brain networks, and report evidence for a
shared biological basis underlying brain morphometry, cognitive ability, and brain ageing, that are underpinned by general genetic factors.
…This indicates that the genetic association between brain morphometry and cognitive ability was not driven by specific network configurations. Instead,
dimensions of shared genetic morphometry in general indexed genetic variance relevant to larger brain volumes and a brain organisation that is advantageous for
better cognitive performance. This was regardless of how many brain regions and from which regions the measure of shared genetic morphometry was extracted. This
lack of differentiation between networks, in how strongly they correlate with cognitive ability, is in line with the suggestion that the total number of neurons in
the mammalian cortex, which should at least partly correspond to its volume, is a major predictor of higher cognitive ability.37 These findings suggest
that highly shared brain morphometry between regions, and its genetic analogue, indicate a generally bigger, and cognitively better-functioning brain.
Predictive processing is emerging as a common computational hypothesis to account for diverse psychological functions subserved by a brain, providing a
systems-level framework for characterizing structure-function relationships of its distinct substructures. Here, we contribute to this framework by examining
gradients of functional connectivity as a low dimensional spatial representation of functional variation in the brain and demonstrating their computational
implications for predictive processing. Specifically, we investigated functional connectivity gradients in the cerebral cortex, the cerebellum, and the hippocampus using
resting-state functional MRI data collected from large samples of healthy young adults. We then evaluated the degree to
which these structures share common principles of functional organization by assessing the correspondence of their gradients. We show that the organizing
principles of these structures primarily follow two functional gradients consistent with the existing hierarchical accounts of predictive processing: A model-error
gradient that describes the flow of prediction and prediction error signals, and a model-precision gradient that differentiates regions involved in the
representation and attentional modulation of such signals in the cerebral cortex. Using these gradients, we also demonstrated triangulation of functional
connectivity involving distinct subregions of the three structures, which allows characterization of distinct ways in which these structures functionally interact
with each other, possibly subserving unique and complementary aspects of predictive processing. These findings support the viability of computational hypotheses
about the functional relationships between the cerebral cortex, the cerebellum, and the hippocampus that may be instrumental for understanding the brain9s dynamics
within its large-scale predictive architecture.
The dark triad of personality (D3)—consisting of psychopathy, Machiavellianism, and narcissism—is a set of socially aversive
personality traits. All 3 traits encompass disagreeable behavior and a particular disregard for the well-being of others, but also a tendency to strategic and
deceptive manipulation of social environments in order to attain one′s goals. To exercise these complex manipulations effectively it seems beneficial to have high
cognitive abilities.
Therefore, a meta-analysis was conducted to examine possible relationships between
intelligence and the dark triad. A total of 143 studies were identified to estimate the strength of relationships between the D3 and general, verbal, and nonverbal intelligence.
The results indicate that none of the constructs of the dark triad are meaningfully related to intelligence. However, there was a small negative correlation
between intelligence and Factor 2 psychopathy. The substantial heterogeneity regarding the observed effect-sizes could not be
explained with meta-regression for the most part. There was no evidence for a
publication bias.
In total, the results challenge the notion that the dark triad is an adaptive set of personality traits that enables individuals to effectively manipulate their
social surroundings.
Participants (n = 275) completed a questionnaire about 35 intelligence myths.
18 myths were rated as true (definitely or partly), 2 as definitely false and 6 a probably false.
There were no statistically-significant demographic or personality correlates of the total correct score.
The paper considers why myths, misconceptions and ignorance seem so difficult to dispel.
This study is concerned with the extent to which people believe in, and endorse, various myths about intelligence and intelligence testing.
It examined the prevalence of myths about intelligence as set out in a recent book (Warne 2020). Participants (n = 275) completed a questionnaire in which they rated the
extent to which they thought various statements/facts about intelligence were essentially true or false.
In all, 18 of these myths were rated as true (definitely or partly), 2 as definitely false and 6 probably false by the majority of the participants. There were
no statistically-significant demographic or personality correlates of the total correct score (determined by rating the myth as false).
The discussion considers why, in this important area of psychology, myths, misconceptions and ignorance seem so difficult to dispel. Limitations of this, and
similar, studies are noted, and implications are discussed.
Genetic and environmental sources of variance in IQ were estimated from 486 adoptive and biological families
Families include 419 mothers, 201 fathers, 415 adopted and 347 biological fully-adult offspring (Mage = 31.8 years; SD = 2.7)
Proportion of variance in IQ attributable to environmentally mediated effects of parental IQs was estimated at 0.01 [95% CI 0.00, 0.02]
Heritability was estimated to be 0.42 [95% CI 0.21, 0.64]
Parent-offspring correlations for educational attainment polygenic scores show no evidence of adoption placement effect
While adoption studies have provided key insights into the influence of the familial environment on IQ scores of adolescents and children, few have followed
adopted offspring long past the time spent living in the family home.
To improve confidence about the extent to which shared environment exerts enduring effects on IQ, we estimated genetic and environmental effects on adulthood IQ
in a unique sample of 486 biological and adoptive families. These families, tested previously on measures of IQ when offspring averaged age 15, were assessed a
second time nearly 2 decades later (Moffspring age = 32 years).
We estimated the proportions of the variance in IQ attributable to environmentally mediated effects of parental IQs, sibling-specific shared environment, and
gene-environment covariance to be 0.01 [95% CI 0.00, 0.02], 0.04 [95% CI 0.00, 0.15], and 0.03 [95% CI 0.00, 0.07] respectively; these components jointly accounted
for 8% of the IQ variance in adulthood. The heritability was estimated to be 0.42 [95% CI 0.21, 0.64].
Together, these findings provide further evidence for the predominance of genetic influences on adult intelligence over any other systematic source of
variation.
…The question of persistence is perhaps the most important in considering the effects of the rearing environment on IQ, especially since other types of studies
have documented a “fadeout” of environmental improvements over time (eg. Protzko 2015). Kendler and colleagues have
used a cosibling control design to examine the effect of the rearing environment on IQ in a sample of 436 adoptive-biological sibships (Kendler et al 2015).
These male, 18–20 year old adopted Swedish conscripts showed a mean gain in 4.41 IQ points relative to their biological siblings, who were raised by the original
biological family. This finding, which they replicated in a larger sample of half-sibs (with a mean gain of 3.18 IQ points associated with adoption), is a strong
indicator that IQ can be, to some extent, affected up to late adolescence by the family environment. These results are consistent with those from the classic
cross-fostering study of 14-year-old French children by Capron & Duyme 1989.
Studies such as these do suggest that although this effect is small relative to the genetic effects on IQ, it is not zero; however, the size of this effect
diminishes substantially after adolescence. Sandra Scarr, a pioneer of modern IQ adoption studies, was perhaps the first to note this fadeout phenomenon (eg.
Scarr & Weinberg 1978). With respect to the
tapering correlations in IQ between children and their adoptive parents as the child matured, observed in the Minnesota Adolescent Adoption Study, Scarr & Weinberg
remarked:
“We interpret the results to mean that younger children, regardless of their genetic relatedness, resemble each other intellectually because they share a
similar rearing environment. Older adolescents, on the other hand, resemble one another only if they share genes. Our interpretation is that older children
escape the influences of the family and are freer to select their own environments. Parental influences are diluted by the more varied mix of adolescent
experiences.” (Scarr & Weinberg, 1983, p. 264).
Figure 2: Scatter plots and associated regression lines for measures of cognitive ability g taken at intake and follow-up 3 for both
biological (left panel) and adopted (right panel) offspring and their rearing parents.
Intake measure of g is full-scale Wechsler IQ score, and follow-up 3 measure is ICAR-16 score. All parent-offspring pairs are included, which means that the data points are not
independent. All values are standardized.
Table 3: Decomposition of variance [95% CI] for each measure and subtest of cognitive ability. Note: 95% CIs are computed from each
parameter’s 200 bootstrap iterations
(Efron & Tibshirani 1993) for each scale. Non-shared environment is computed by subtracting the heritability, parental environment, sibling environment,
and gene-environment (G-E) covariance from 1. For full parameter estimates, see SI Table S12. Column values add up to 1, total phenotypic variance.
…We tested for placement effects using polygenic scores for educational attainment (PGSEA) derived from
the largest genome-wide association study to date (Lee et al 2018)…In an aggregated sample consisting of all white participants (offspring and both
parents), an R2 of 0.154 [95% CI 0.113, 0.195] in our prediction of Verbal IQ with a PGS surpasses all
previous benchmarks known to us (Allegrini et al 2019; Lee et al 2018;
Rietveld et al 2014; Savage et al 2018;
Selzam et al 2016; Sniekers et al 2017), and an R2 of 0.114 [95% CI 0.077,
0.151] for Total IQ is near the upper end of previous predictions (SI Table S13). However, we acknowledge that our sample is not large by
the standards of PGS validation…These scores also enable a unique test for the so-called “placement effect”, wherein
adoptees (typically twins reared apart) are thought by some skeptics to resemble their adoptive parents prior to placement, thus biasing biometrical estimates. By
demonstrating a total lack of evidence (p = 0.514) for a correlation between parents and adoptive offspring in polygenic scores, we provide support for
the validity of at least some adoption studies in establishing causal inference…the similarity of these correlations to their theoretically predicted values
provides evidence that the placement of adoptees in their homes was not strongly purposive or selective, implying that the adoption process may somewhat
approximate a true experiment.
…IQ has been subject to a large number of twin and adoption studies, many of which have found a small but
statistically-significant effect of parental transmission in adoptive samples up until late adolescence…Our biometric decomposition of variance is consistent with
this figure: the parental environment contributing 4% of the variance in fullscale IQs at age ~15 (Table 3), with a standard deviation of 14.2 for
full-scale IQ in adopted offspring, indicates that a 1-SD increase in the quality of the parental environment would increase IQ by approximately 2.83 points (ie.
14.2 × √0.04;
Burks 1938).
The evidence for parenting effects on Wechsler IQ subtests is more equivocal, and biometric decomposition reveals a moderate but statistically-significant
effect of gene-environment covariance on Vocabulary in childhood. While a similarly-sized G-E covariance is observed for childhood Total IQ, this effect has
completely disappeared in adulthood; the same cannot be said unambiguously for Vocabulary, which retains weak evidence in adulthood for a persistent parenting
effect.
Many but not all cognitive abilities decline during ageing. Some even improve due to lifelong experience. The critical capacities of attention and executive functions have been widely posited to decline. However, these capacities are
composed of multiple components, so multifaceted ageing outcomes might be expected. Indeed, prior findings suggest that whereas certain attention/executive
functions clearly decline, others do not, with hints that some might even improve.
We tested ageing effects on the alerting, orienting and executive (inhibitory) networks posited by Posner and Petersen’s influential theory of attention, in a
cross-sectional study of a large sample (n = 702) of participants aged 58–98. Linear and nonlinear analyses revealed that whereas the efficiency of the
alerting network decreased with age, orienting and executive inhibitory efficiency increased, at least until the mid-to-late 70s. Sensitivity analyses indicated
that the patterns were robust.
The results suggest variability in age-related changes across attention/executive functions, with some declining while others improve.
Students’ socioeconomic status(SES) is central to much researchand policy deliberation on educational inequalities. However, the SES model is under severe stress for several reasons.
SES is an ill-defined concept, unlike parental education or familyincome. SES measures are frequently based on proxy reports from students; these are generally unreliable, sometimes endogenous to student
achievement, only low to moderately intercorrelated, and exhibit low comparability across countries and over time.
There are many explanations for SES inequalities in education, none of which achieves consensus among
research and policy communities.
SES has only moderate effects on student achievement, and its effects are especially weak when considering
prior achievement, an important and relevant predictor.
SES effects are substantially reduced when considering parentability, which is causally prior to family SES.
The alternative cognitive ability/genetic transmission model has far greater explanatory power; it provides logical and compelling explanations for a wide
range of empirical findings from student achievement studies.
The inadequacies of the SES model are hindering knowledge accumulation about student performance and the
development of successful policies.
Context and implications:
Rationale for this study:
This review was written in response to the disconnect between the literature surrounding student achievement studies, and the cognitive psychology and
behavioural genetic academic literatures. It is well-established that student achievement is closely related to cognitive ability and both have sizable genetic
components, findings largely ignored in achievement studies. This review’s aim is for more considered responses to socioeconomic inequalities in student
achievement by both researchers and policymakers.
Why the new findings matter:
The review provides overwhelming evidence that much of the current thinking about SES and student achievement is
mistaken.
Implications for researchers and policymakers:
The current emphasis on SES is misleading and wastes considerable human and financial resources that could
much better be utilized. The focus should be on student performance ensuring that low achievers have rewarding educational and occupational careers, and
raising the overall skill levels of students, not on the nebulous, difficult to measure, concept of SES, which is
only moderately associated with achievement.
Objectives: Despite the broad appeal of abstract notions of political tolerance, people vary in the degree to which they support the political
rights of groups they dislike. Prior research highlighted the relevance of individual differences in the cognitive domain, claiming the application of general
tolerance ideals to specific situations is a cognitively demanding task. Curiously, this work has overwhelmingly focused on differences in cognitive style, largely
neglecting differences in cognitive ability, despite compelling conceptual linkages. We remedy this shortcoming.
Methods: We explore diverse predictors of tolerance using survey data in 2 large samples from Denmark (n = 805) and the United States
(n = 1,603).
Results: Cognitive ability was the single strongest predictor of political tolerance, with larger effects than education, openness to
experience, ideology, and threat. The cognitively demanding nature of tolerance judgments was further supported by results showing cognitive ability predicted
tolerance best when extending such tolerance was hardest. Additional small-sample panel results demonstrated substantial 4-year stability of political tolerance,
informing future work on the origins of political tolerance.
Conclusions: Our observation of a potent role for cognitive ability in tolerance supports cognitively oriented accounts of tolerance judgments
and highlights the need for further exploration of cognitive ability within the political domain.
…Our Danish sample was selected using a registry of military draftees, which has been in operation since 2006. We drew our sample from the subset of the
registry which had taken a cognitive ability test…For our American sample, 2,766 respondents completed our survey using Mechanical Turk in September &
October 2014.
This paper explores inequalities in IQ and economic preferences between children from families of high and low socioeconomic status (SES). We document that children from high-SES families are more intelligent, patient, and
altruistic as well as less risk seeking. To understand the underlying mechanisms, we propose a framework of how SES,
parental investments, as well as maternal IQ and preferences influence a child’s IQ and preferences. Our results indicate that disparities in the level of
parental investments hold substantial importance. In light of the importance of IQ and preferences for behaviors and outcomes, our findings offer an explanation
for social immobility.
[blog] A recent study by Dutton et al 2019 found that the religiousness-IQ nexus
is not on g when comparing different groups with various degrees of religiosity and the non-religious. It suggested, accordingly, that the nexus related
to the relationship between specialized analytic abilities on the IQ test and autism traits, with the latter predicting atheism. The study was limited by the fact
that it was on group-level data, it used only one measure of religiosity that measure may have been confounded by the social element to church membership and it
involved relatively few items via which a Jensen effect could be calculated.
Here, we test whether the religiousness-IQ nexus is on g with individual-level data using archival data from the Vietnam Experience Study, in which
4,462 US veterans were subjected to detailed psychological tests. We used multiple measures of religiosity—which we factor-analysed to a religion-factor—and a
large number of items.
We found, contrary to the findings of Dutton et al 2019, that the IQ differences with regard to whether or not subjects believed in God are
indeed a Jensen effect. We also uncovered a number of anomalies, which we explore.
We develop a novel graphical paradigm of a strict-dominance-solvable game to study the developmental trajectory of steps of reasoning between 8 years old and
adulthood.
Most participants play the equilibrium action either always or only when they have a dominant strategy. Although age is a determinant of equilibrium choice,
some very young participants display an innate ability to play at equilibrium. Finally, the proportion of equilibrium play increases statistically-significantly
until fifth grade and stabilizes afterward, suggesting that the contribution of age to equilibrium play vanishes early in life.
…To minimize these concerns, we propose a novel graphical interface in which subjects possess 3 objects with 3 attributes each: a shape, a color, and a letter.
Their goal is to select an object with a certain characteristic, which depends on the object selected by another player in the game. This is true for all but one
player, who must simply match a feature of a specific single object. This player’s decision constitutes the starting point of the iteration process, and the
problem of the other players can be iteratively solved by successive elimination, with a maximum of 3 steps of reasoning.
To analyze the developmental trajectory of behavior in our paradigm, we recruited 3 populations. The first experiment involves a population of children and
adolescents (8–18 years old) recruited at a single private school in Los Angeles, as well as a control young-adult population from the University of Southern
California. This experiment tests the effect of age on strategic sophistication. In the second experiment, we recruited younger children (5–8 years old) from that
same school and we implemented a simpler version of the same game. This experiment is designed to assess whether the skills detected in children older than 8 years
old are already developing before that age. Last, we recruited a third population of middle schoolers (11–14 years old) from a single public school also in Los
Angeles. This experiment aims to inform us on the potential impact of school characteristics and student demographics on sophistication.
Our analysis yields 3 main results. First, the vast majority of participants either play always at equilibrium or they play at equilibrium only when they have a
dominant strategy. There are few random players, and virtually no one exhibits an “intermediate” level of reasoning (ie. plays at equilibrium when it requires 2
steps of reasoning but not when it requires 3 steps). This is in sharp contrast with the existing adult literature that emphasizes large heterogeneity in levels of
reasoning and abundance of intermediate types (Costa-Gomes, Crawford, and Broseta 2001; Johnson et al 2002; Costa-Gomes & Crawford 2006;
Brañas-Garza, Espinosa, and Rey-Biel 2011; Brocas et al 2014; Kneeland 2015; Gill & Prowse 2016; Brocas, Carrillo, and Sachdeva 2018).
Second, although age is an important determinant of equilibrium thinking, there is an ability component that is either innate or acquired at a very young age.
Furthermore, the evolution over the entire window of observation is not as steep as one might expect. Indeed, the proportion of individuals who consistently play
at equilibrium is statistically-significantly above 0 at 8 years old (24%) and statistically-significantly below 1 at 17 years old (59%). Third and related, the
change in equilibrium play is not constant. Choice improves statistically-significantly between third and fifth grade and stabilizes afterward. In other words, the
contribution of age to equilibrium behavior vanishes relatively early in life (between 12 and 13 years old). Our data reveal important predictors of performance.
We find that female participants and subjects with a self-reported preference for science subjects perform statistically-significantly better. Finally, differences
across schools and across tracks within schools are also associated with differences in sophistication. In particular, we find that students enrolled in
different programs or in different GPA-based tracks within programs exhibit different levels of sophistication.
[IQ/intelligence was not measured.] Overall, even though the main pattern of behavior (namely, the absence of an intermediate level of reasoning) is replicated
in all populations, the distribution of sophistication is modulated by individual and group characteristics.
…We designed a simple paradigm in which subjects were matched in groups of 3 and assigned a role as player 1, player 2, or player 3, from now on referred to as
role 1, role 2, and role 3. Each player in the group had 3 objects, and each object had 3 attributes: a shape (square, triangle, or circle), a color (red, blue, or
yellow), and a letter (A, B, or C). Players had to simultaneously select one object. Role 1 would obtain points if the object he chose matched a given
attribute of the object chosen by role 2. Similarly, role 2 would obtain points if the object he chose matched a given attribute of the object chosen by role 3.
Finally, role 3 would obtain points if the object he chose matched a given attribute of an extra object. The attributes to be matched were different for different
roles and specified by the experimenter. Accordingly, in each game any number of participants could obtain points. All options and objectives of players were
common knowledge and displayed on the computer screen. Figure 1 provides a screenshot of the game as seen by role 2. The game can be easily
solved with an inductive argument starting from role 3. In the example of Figure 1, role 3 has to match the shape of the outside object, so
he obtains the points if he chooses the red square C. Conditional on that choice, role 2 obtains points if he chooses the red triangle B, and, again conditional on
that choice, role 1 obtains points if he chooses the yellow circle B (the original software uses easily distinguishable colors).9
Figure 1: Screenshot of the game (as seen by role 2).
Figure 2: Proportion of equilibrium choices by grade and role.
…Figure 3 reports the proportion of subjects by grade [strategy type] who are classified under each type, from most sophisticated
(bottom) to least sophisticated (top). In strong support of hypothesis 1, our theoretical model provides a very solid behavioral template.
Indeed, the choice of 76% of LILA students and 97% of USC students can be accounted
for by one of the 4 types described in section II.B. The proportion of subjects who do not fit in one of these types (O) decreases with age, although it
is statistically smaller only for tenth graders. In other words, the level-k behavioral theory that has proved successful in explaining nonequilibrium
behavior of adults performs well also with children and adolescents.
Figure 3: Proportion of subjects by type and grade.
…Hypothesis 2 is not supported by the data. Subjects either recognize only a dominant strategy or always play at equilibrium. Also, some
very young players display an innate ability to play always at equilibrium while some young adults are unable to perform 2 steps of dominance.
…Hypothesis 3 is weakly supported by the data. Equilibrium performance increases with age very statistically-significantly during elementary
school but it stabilizes in 6th grade.
…While equilibrium performance increases with age, there is also a substantial innate component: some of our youngest participants play perfectly from the first
trial whereas some of our oldest participants do not go beyond one step of reasoning. Even though there is some evidence of learning, repeated exposure is
ineffective at bringing participants to play Nash. Finally, performance increases statistically-significantly between 8 and 12 years of age and stabilizes
afterward, suggesting that most of what is needed to solve dominance-solvable games is acquired by the end of elementary school. Interestingly, most students
acquire complex mathematical skills during adolescence. Our observations suggest that this extra knowledge does not translate into better strategic decision
making.
…Adolescents are particularly exposed to situations in which strategic sophistication is crucial to avoid wrong decisions. Examples include engaging in risky
activities, such as accepting drugs from peers or engaging in unprotected sex. Also, with the development of the internet, naive users are often preyed upon, asked
to provide personal information, or tricked into making harmful decisions. Information deliberately intended to deceive young minds also circulates through social
media. Making correct decisions in such environments requires understanding the intentions of others and anticipating the consequences of following their advice or
opinions. More generally, children and adolescents are gradually discovering the dangers hiding behind social interactions and need to come equipped to detect
them, assess them, and navigate around them. We conjecture that failures in these abilities are closely related to underdeveloped logical abilities, and we predict
that the level of sophistication of an individual detected through a simple task matches their behavior in social settings.
Using blood-based epigenome-wide analyses of general cognitive function (g; n= 9,162) we show that individual differences in
DNAmethylation (DNAm) explain 35.0% of the variance ing. A DNAm predictor explains ~4% of the variance in g, independently of a polygenic score, in
two external cohorts. It also associates with circulating levels of neurology-related and inflammation-related proteins, global brain imaging metrics, and regional
cortical volumes. As sample sizes increase, our ability to assess cognitive function from DNAm data may be informative in
settings where cognitive testing is unreliable or unavailable.
Personality traits relate to both STEM preferences and STEM
specialization.
Openness and Agreeableness are the best predictors of STEM preferences.
Extraversion is the strongest predictor of actual choice for STEM.
Cognitive skills become more important when moving from preferences to actual choice.
There are markedly different patterns for boys compared to girls.
Around the developed world, the need for graduates from Science, Technology, Engineering and Mathematics (STEM) fields
is growing. Research on educational and occupational choice has traditionally focused on the cognitive skills of prospective students, and on how these
determine the expected costs and benefits of study programs. Little work exists that analyzes the role of personality traits on study choice.
This study investigates how personality traits relate to preferences of students for STEM studies and occupations, and
to specialization choice in high school. We use a rich data set that combines administrative and survey data of Dutch secondary education students.
We find that personality traits are related to both the preference that students have for STEM as the actual decision
to specialize inSTEM studies, but to different degrees. We identify statistically-significant relations
with preference indicators for all Big Five traits, especially for Openness to Experience (positive), Extraversion and Agreeableness (both negative). The size of these relations is
often larger than those between cognitive skills and STEM preferences. Personality traits are comparatively less
important with respect to the actual specialization choice, for which we identify a robust (and sizable) negative relation with Extraversion, and for girls find a
positive relation with Openness to Experience.
The results suggest that once students have to make actual study choice decisions, they rely more on cognitive skills rather than personality traits, in
contrast to their expressed preferences.
There has been some controversy as to whether baseline pupil size is related to individual differences in cognitive ability. Previously, we had shown that a
larger baseline pupil size was associated with higher cognitive ability and that the correlation to fluid intelligence was larger than that to working memory
capacity (Tsukahara et al 2016). However, other researchers
have not been able to replicate our findings—though they only measured working memory capacity and not fluid intelligence. Many of the studies showing no
relationship had major methodological issues, namely small baseline pupil size values—down to the physiological minimum—that resulted in reduced variability on
baseline pupil size.
We conducted 2 large-scale studies to investigate how different lighting conditions affect baseline pupil size values and the correlation with cognitive
abilities. We found that fluid intelligence, working memory capacity, and attention control did correlate with baseline pupil size except in the brightest lighting
conditions. We showed that a reduced variability in baseline pupil size values is due to the monitor settings being too bright. Overall, our findings demonstrated
that the baseline pupil size-working memory capacity relationship was not as strong or robust as that with fluid intelligence or attention control.
Our findings have strong methodological implications for researchers investigating individual differences in task-free or task-evoked pupil size. We conclude
that fluid intelligence does correlate with baseline pupil size and that this is related to the functional organization of the resting-state brain through the
locus coeruleus-norepinephrine system.
[Keywords: fluid intelligence, working memory capacity, pupil size, luminance]
…Our pupils respond to more than just the light. They indicate arousal, interest or mental exhaustion. Pupil dilation is even used by the FBI to detect deception. Now work conducted in our laboratory at the Georgia Institute of Technology suggests that baseline pupil
size is closely related to individual differences in intelligence. The larger the pupils, the higher the intelligence, as measured by tests of reasoning, attention
and memory. In fact, across 3 studies, we found that the difference in baseline pupil size between people who scored the highest on the cognitive tests and those
who scored the lowest was large enough to be detected by the unaided eye.
…We found that a larger baseline pupil size was correlated with greater fluid intelligence, attention control and, to a lesser degree, working memory
capacity—indicating a fascinating relationship between the brain and eye. Interestingly, pupil size was negatively correlated with age: older participants tended
to have smaller, more constricted, pupils. Once standardized for age, however, the relationship between pupil size and cognitive ability remained.
But why does pupil size correlate with intelligence? To answer this question, we need to understand what is going on in the brain. Pupil size is
related to activity in the locus coeruleus, a nucleus situated in
the upper brain stem with far-reaching neural connections to the rest of the brain. The locus coeruleus releases norepinephrine, which functions as both a
neurotransmitter and hormone in the brain and body, and it regulates processes such as perception, attention, learning and memory. It also helps maintain a healthy
organization of brain activity so that distant brain regions can work together to accomplish challenging tasks and goals. Dysfunction of the locus coeruleus, and
the resulting breakdown of organized brain activity, has been related to several conditions, including Alzheimer’s disease and attention deficit hyperactivity disorder. In fact, this organization of activity is so important that the brain devotes most of its
energy to maintain it, even when we are not doing anything at all—such as when we stare at a blank computer screen for minutes on end.
One hypothesis is that people who have larger pupils at rest have greater regulation of activity by the locus coeruleus, which benefits cognitive performance
and resting-state brain function. Additional research is needed to explore this possibility and determine why larger pupils are associated with higher fluid
intelligence and attention control. But it’s clear that there is more happening than meets the eye.
We introduce the first game-based intelligence assessment in Minecraft.
Three intelligence tasks were implemented in the interactive game environment.
Two of the three tasks exhibit satisfactory psychometric properties.
Process data from game-logs encodes information about ability levels.
Minecraft is a promising platform for game-based assessment research.
Video games are a promising tool for the psychometric assessment of cognitive abilities. They can present novel task types and answer formats, they can record
process data, and they can be highly motivating for test takers. This paper introduces the first game-based intelligence assessment implemented in
Minecraft, an exceptionally popular video game with more than 200m copies sold.
A matrix-based pattern completion task (PC), a mental rotation task (MR) and a spatial construction task (SC) were implemented in the three-dimensional,
immersive environment of the game. PC was intended as a measure of inductive reasoning, whereas MR and SC were measures of spatial ability. We tested 129 children
aged 10–12 years old on the Minecraft-based tests as well as equivalent pen-and-paper tests. All three scales fit the Rasch model and were moderately
reliable. Factorial validity was good with regard to the distinction between PC and SC, but no distinct factor was found for MR. Convergent validity was good as
abilities measured with Minecraft and conventional tests were highly correlated at the latent level (r = 0.72). Subtest-level correlations were
in the moderate range. Furthermore, we found that behavioral log-data collected from the game environment was highly predictive of performance in the
Minecraft test and, to a lesser extent, also predicted scores in conventional tests. We identify a number of behavioral features associated with spatial
reasoning ability, demonstrating the utility of analyzing granular behavioral data in addition to traditional response formats.
Overall, our findings indicate that Minecraft is a suitable platform for game-based intelligence assessment and encourage future work aiming to explore
game-based problem solving tasks that would not be feasible on paper or in conventional computer-based tests.
[Keywords: Game-based assessment Intelligence assessment, Minecraft, Project
Malmo, process data, game log-data]
Polygenic indexes (PGIs) are DNA-based predictors. Their value for research
in many scientific disciplines is rapidly growing. As a resource for researchers, we used a consistent methodology to construct PGIs for 47 phenotypes in 11 datasets. To maximize the PGIs’ prediction accuracies, we
constructed them using genome-wide association studies—some of which are novel—from multiple data sources, including 23andMe and UK Biobank. We present a theoretical framework to help
interpret analyses involving PGIs. A key insight isthat a PGI can be
understood as an unbiased but noisy measure of a latent variable we call the “additive SNP factor.”
Regressions in which the true regressor is the additive SNPfactor but the PGI is used as its proxy therefore suffer from errors-in-variables bias. We derive an estimator that corrects for the bias,
illustrate the correction, and make a Python tool for implementing it publicly available.
Greater Vasa parrots are prospectively highly intelligent but critically understudied
An individual is found to spontaneously solve the string-pulling problem, and to be able to re-solve it after 7 years
This replicates previous findings, and expands on them
A general insight factor is identified among 14 parrot species
Covariance associates strongly with fission-fusion intensity, weakly with brain size and species differences
Spontaneous solving of an insight-based means-end reasoning task (the string-pulling problem) is observed in an adult male captive bred Greater Vasa parrot
(Coracopsis vasa (Shaw 1812)), with an efficiency of 66%,
replicating previous work in a singleton context. This case report adds to the existing literature on this species by also demonstrating longitudinal retention,
specifically the same bird was found to be able to re-solve the simple form of the problem after a period of 7 years (the bird was first tested in 2013, and
re-tested in 2020), with an efficiency of 43% (the difference between efficiencies was not statistically-significant, χ2 = 0.991, p =
0.319).
In a second analysis, species-level data across 5 patterned string-pulling tasks involving 14 parrot species were reanalysed, revealing that the Greater Vasa
parrot exhibited the greatest general competence among those evaluated. A ‘general insight factor’ (GIF) was also
found across taxa, the loadings onto which exhibit positive and large-magnitude associations with the correlation between fission-fusion flocking intensity and
indicator level performance (r = 0.831), and also positive small and modest-magnitude associations with the correlation between relative brain size and
indicator-level performance, and the magnitude of average pair-wise species differences in performance across indicators (r = 0.219 and 0.365
respectively).
Finally, the theoretical implications of these findings are discussed.
Cognitive enhancement interventions aimed at boosting human fluid intelligence (gf) have targeted executive functions (EFs), such as
updating, inhibition, and switching, in the context of transfer-inducing cognitive training. However, even though the link between EFs and gf
has been demonstrated at the psychometric level, their neurofunctional overlap has not been quantitatively investigated. Identifying whether and how EFs and
gf might share neural activation patterns could provide important insights into the overall hierarchical organization of human higher-order
cognition, as well as suggest specific targets for interventions aimed at maximizing cognitive transfer.
We present the results of a quantitative meta-analysis of the available fMRI and PET literature on EFs andgf in humans, showing the similarity between gf and (1) the
overall global EF network, as well as (2) specific maps for updating, switching, and inhibition. Results highlight a higher degree of similarity between
gf and updating (80% overlap) compared with gf and inhibition (34%), and gf and switching (17%).
Moreover, 3 brain regions activated for both gf and each of the 3 EFs also were identified, located in the left middle frontal gyrus, left
inferior parietal lobule, and anterior cingulate cortex. Finally, resting-state functional connectivity analysis on 2 independent fMRI datasets showed the preferential behavioural correlation and anatomical overlap between updating and gf.
These findings confirm a close link between gf and EFs, with implications for brain stimulation and cognitive training interventions.
Relation between intelligence and functional connectivity exhibited by P-FIT regions
2 independent samples comprising a total of 1140 healthy individuals
Matrix reasoning tests and fMRI resting-state imaging
Brodmann areas 7, 40 and 46 exhibit relevant connections across both samples
[See also “Multi-Task Brain Network
Reconfiguration is Inversely Associated with Human Intelligence”, Thiele et al 2021] The Parieto-Frontal Integration Theory (P-FIT) predicts that human intelligence is closely linked to structural and functional properties of several brain regions mainly
located in the parietal and frontal cortices. It also proposes that solving abstract reasoning tasks involves multiple processing stages and thus requires the
harmonic interplay of these brain regions. However, empirical studies directly investigating the relationship between intellectual performance and the
strength of individual functional connections related to the P-FIT network are scarce.
Here we demonstrate, in 2 independent samples comprising a total of 1489 healthy individuals, that fMRI resting-state
connectivity,especially between P-FIT regions, is associated with interindividual differences in matrix
reasoning performance. Interestingly, respective associations were only present in the overall samples and the female subsamples but not in the male subsamples,
indicating a sex-specific effect. We found 5 statistically-significant connections which replicated across both samples. These were constituted by BAs 8, 10, 22,
39, 46, and 47 in the left as well as BAs 44 and 45 in the right hemisphere.
Given that many of these brain regions are predominantly involved in language processing, we hypothesized that our results reflect the importance of inner
speech for solving matrix reasoning tasks. Complementary to previous research investigating the association between intelligence and functional brain connectivity
by means of comprehensive network metrics, our study is the first to identify specific connections from the P-FIT network
whose functional connectivity strength at rest can be considered an indicator of intellectual capability.
[Keywords: resting-state fMRI, functional connectivity, matrixreasoning,
Parieto-Frontal Integration Theory (P-FIT)]
The field of cognitive epidemiology studies the prospective associations between cognitive abilities and health outcomes. We review research in this field over
the past decade and describe how our understanding of the association between intelligence and all-cause mortality has consolidated with the appearance of new,
population-scale data.
To try to understand the association better, we discuss how intelligence relates to specific causes of death, diseases/diagnoses and biomarkers of health
through the adult life course. We examine the extent to which mortality and health associations with intelligence might be attributable to people’s differences in
education, other indicators of socioeconomic status, health literacy and adult environments and behaviours. Finally, we discuss whether genetic data provide new
tools to understand parts of the intelligence-health associations.
Social epidemiologists, differential psychologists and behavioural and statistical geneticists, among others, contribute to cognitive epidemiology; advances
will occur by building on a common cross-disciplinary knowledge base.
In 10 years, the ability to predict intelligence from DNA has gone from 0% to 10%.
Genome-wide polygenic scores (GPS) are transforming research on intelligence.
GPS will transport intelligence to many new areas of science.
The availability of GPS at birth, prenatally, and before conception will impact society.
We need to maximize benefits and minimize risks of DNA prediction of intelligence.
The DNA revolution made it possible to use DNA to predict intelligence. We
argue that this advance will transform intelligence research and society.
Our paper has 3 objectives:
First, we review how the DNA revolution has transformed the ability to predict individual differences in
intelligence. Thousands of DNA variants have been identified that—aggregatedinto genome-wide polygenic
scores (GPS)—account for more than10%of the variance in phenotypic
intelligence. The intelligence GPS is now one of the most powerful predictors in the behavioral sciences.
Second, we consider the impact of GPS on intelligence research.The intelligence GPS can be added as a genetic predictor of intelligence to any study without the need to assess phenotypic intelligence. This
feature will help export intelligence to many new areas of science. Also, the intelligence GPS will help to
address complex questions in intelligence research, in particular how the gene-environment interplay affects the development of individual differences in
intelligence.
Third, we consider the societal impact of the intelligence GPS,focusing on DNA testing at birth, DNA testing before birth (eg.embryo selection), and DNA testing before conception (eg. DNA dating).
The intelligence GPS represents a major scientific advance, and, like all scientific advances, it can be used
for bad as well as good. We stress the need to maximize the considerable benefits and minimize the risks of our new ability to use DNA to predict intelligence.
Despite a long-standing expert consensus about the importance of cognitive ability for life outcomes, contrary views continue to proliferate in scholarly and
popular literature. This divergence of beliefs presents an obstacle for evidence-based policymaking and decision-making in a variety of settings. One commonly held
idea is that greater cognitive ability does not matter or is actually harmful beyond a certain point (sometimes stated as > 100 or 120 IQ points). We
empirically tested these notions using data from four longitudinal, representative cohort studies comprising 48,558 participants in the United States and United
Kingdom from 1957 to the present. We found that ability measured in youth has a positive association with most occupational, educational, health, and social
outcomes later in life. Most effects were characterized by a moderate to strong linear trend or a practically null effect (mean R2 range = 0.002–.256).
Nearly all nonlinear effects were practically insignificant in magnitude (mean incremental R2 = 0.001) or were not replicated across cohorts or survey
waves. We found no support for any downside to higher ability and no evidence for a threshold beyond which greater scores cease to be beneficial. Thus, greater
cognitive ability is generally advantageous—and virtually never detrimental.
Changes in mean intelligence test scores were minimal in Denmark in 2006–2019 [2006–2010: 111.5, 111.1, 110.8, 110.7, 110.6, | 2011–2019: 109.1, 109.2,
109.0, 109.1, 109.3, 109.2, 109.1, 108.7, 108.8].
A change in the format of the intelligence test resulted in a sudden drop in scores.
Neither changes in parental age, dysgenics, or immigration can explain the findings.
Changes in sample composition may conceal a true decline in intelligence test scores.
The present register-based study investigated the secular trend of intelligence test scores during the period from 2006 through 2019 in a Danish
population-representative sample, as well as whether the observed trend could be explained by changes in parental age, dysgenics, and immigration or changes in the
format of the intelligence test and sample characteristics.
The study population consisted of all Danish men appearing before a draft board during the study period (n = 400,288). Intelligence test scores were
obtained by the use of Børge Priens Prøve, typically at age 19. For each of the included draft board cohorts, the intelligence test score mean and standard
deviation were estimated.
The results showed that changes in mean intelligence test scores were minimal during the study period. A slight decline was observed from 2006 to 2010.
Furthermore, there was a drop of 1.5 IQ points from 2010 to 2011, which coincided with the change in the format of the intelligence test from paper-and-pencil to
computer-based, but there was essentially no change after 2011. Neither changes in parental age, dysgenics, or immigration seem to have influenced the
observations. However, changes in sample composition may conceal a true decline in intelligence test scores given that a larger proportion of individuals with low
intelligence seems to be exempted from testing.
In conclusion, the study findings suggest no systematic change in intelligence test scores during the last decade, but due to changes in sample composition, it
cannot be excluded that there has been a negative secular trend.
…A slight decline in mean IQ score was observed from 2006 to 2010, which can be seen as a continuation of the decline previously reported between 1998 and 2004
(Teasdale & Owen 2008)…We have had the opportunity to rescale the mean intelligence test scores from the Danish draft board examinations reported by Teasdale
& Owen 2008 against our baseline year 1960 to compare them with our observations. The rescaled mean IQ scores are as follows: 1988: 111.0 (SD: 13.0);
1998: 112.4 (SD: 12.7); 2003–4: 111.1 (SD: 12.8). As can be seen, there was an increase from 1988 to 1998 followed by a small decline from 1998 to 2003–4. The mean
IQ score in 1998 remains the highest recorded using Danish draft board data, whereas the mean IQ score in 2003–4 is comparable with our mean intelligence test
score in 2006. As such, there has been a decline of 1.8 IQ points during the period from 1998 through 2010 followed by a drop of 1.5 IQ points which is probably
due to the change in the format of the intelligence test and virtually no change from 2011 through 2019. However, the variance has declined statistically-significantly throughout the study period, corresponding to a decline of 0.15 SD per year
(p < 0.001). A previous study has suggested that the negative secular trend observed in developmental test performances may be rooted in declining
performances of the top percentiles (Flynn & Shayer 2018),
leading to declining variances. If this is also true in our study where the proportion of individuals with low test intelligence scores who were exempted from
testing has increased over time, this might explain our observation of no change in mean intelligence test scores, but a declining variance.
Intelligence predicts important life and health outcomes, but the biological mechanisms underlying differences in intelligence are not yet understood. The
use of genetically determined metabotypes (GDMs) to understand the role of genetic and environmental factors, and their
interactions, in human complex traits has been recently proposed. However, this strategy has not been applied to human intelligence.
Here we implemented a 2-sample Mendelian randomization(MR)
analysis using GDMs to assess the causal relationships between genetically determined metabolites and human
intelligence. The standard inverse-varianceweighted (IVW) method was used for the
primary MR analysis and 3 additional MR methods (MR-Egger,
weighted median, and MR-PRESSO) were used for sensitivity analyses.
Using 25 genetic variants as instrumental variables
(IVs), our study found that 5-oxoproline was associated with better performance
in human intelligence tests (pIVW = 9.25 × 10−5). The causal relationship was robust when
sensitivity analyses were applied (pMR-Egger = 0.0001, pWeighted median = 6.29 × 10−6, PMR-PRESSO = 0.0007), and repeated analysis yielded consistent result (pIVW = 0.0087). Similarly, also dihomo-linoleate (20:2n6) and p-acetamidophenylglucuronide showed robust association with
intelligence.
Our study provides novel insight by integrating genomics and metabolomics to estimate causal effects of genetically determined metabolites on human
intelligence, which help to understanding of the biological mechanisms related to human intelligence.
Objectives: Debate about the cause of IQ score gaps between Black and White populations has persisted within genetics, anthropology, and
psychology. Recently, authors claimed polygenic scores provide evidence that a substantial portion of differences in cognitive performance between Black and White
populations are caused by genetic differences due to natural selection, the “hereditarian hypothesis.” This study aims to
show conceptual and methodological flaws of past studies supporting the hereditarian hypothesis.
Materials and methods: Polygenic scores for educational attainment were constructed for African and European samples of the 1000 Genomes
Project. Evidence for selection was evaluated using an excess variance test. Education associated variants were further evaluated for signals of selection by
testing for excess genetic differentiation (Fst). Expected mean difference in IQ for populations was calculated under a neutral evolutionary scenario
and contrasted to hereditarian claims.
Results: Tests for selection using polygenic scores failed to find evidence of natural selectionwhen the less biased within-family GWAS effect sizes were used. Tests for selection using Fst values
did not find evidence of natural selection. Expected mean difference in IQ was substantially smaller than postulated by
hereditarians, even under unrealistic assumptions that overestimate genetic contribution.
Conclusion: Given these results, hereditarian claims are not supported in the least. Cognitive performance does not appear to have been under
diversifying selection in Europeans and Africans. In the absence of diversifying selection, the best case estimate for genetic contributions to group differences
in cognitive performance is substantially smaller than hereditarians claim and is consistent with genetic differences contributing little to the Black-White
gap.
Water fluoridation is a common but debated public policy. In this paper, we use Swedish registry data to study the causal effects of fluoride in drinking water.
We exploit exogenous variation in natural fluoride stemming from variation in geological characteristics at water sources to identify its effects. First, we
reconfirm the long-established positive effect of fluoride on dental health. Second, we estimate a zero effect on cognitive ability in contrast to several recent
debated epidemiological studies. Third, fluoride is furthermore found to increase labor income. This effect is foremost driven by individuals from a lower
socioeconomic background.
…Let us continue to our main results. We begin with cognitive ability for men born between 1985 and 1987. Our conclusion from Table 4 is that
fluoride does not affect cognitive ability. Column 1 displays the unconditional treatment effect. In columns 2 and 3, we add fixed effects for cohort and
municipality of birth. We then include parental covariates, which results in a reduced sample since we have data on fathers’ cognitive ability only from 1969 and
onward. To make the samples comparable with and without these covariates, we run column 4 for the same sample as in column 5. We also run two subsample analyses:
in column 6, we run the analysis for those who have lived in the same SAMS in a municipality for the entire period
from age 0 to 18, and in column 7 we restrict the sample to those who have moved only within a municipality.
Table 4: cognitive ability
Looking at the estimates, they are very small and often not statistically-significantly different from zero. Sometimes the estimates are negative and sometimes
positive, but they are always close to zero. If we take the largest negative point estimates (−0.0047, col. 1) and the largest standard error for that
specification (0.0045), the 95% confidence interval would be −0.014 to 0.004. We may thus rule out negative effects larger than 0.14 standard deviations in
cognitive ability if fluoride is increased by 1 milligram/liter (the level often considered when artificially fluoridating the water).
…We now continue with the long-term outcome of annual labor income in 2014 for individuals born between 1985 and 1992. Given our results for cognitive ability,
we do not expect negative effects of fluoride. However, positive effects are possible given the results found for dental health.
The results are presented in Table 5. The point estimates are often statistically-significant, and the coefficients are always positive. Taking
column 6 as an example, where all covariates and fixed effects are included, we find that the point estimate equals 0.0044, meaning that income increases by 4.4%
if fluoride is increased by 1 milligram/liter. These reduced form estimates may be compared with Glied & Neidell 2010, who, by using American data, found that women who drink fluoridated water
have on average 4% higher earnings. Our estimated effect on income may also be compared with estimated education premiums. The return of one additional year of
education yields an increase in income by 6%–10%, according to the instrumental variable estimates in the review in Card (1999). An increase in fluoride by 1
milligram/liter would thus yield a similar increase as roughly half a year of additional education. Nonlinear specifications are presented in figure
A1 and tables A8–A10, which overall supports the findings presented here. In section B5 in the appendix, we present the result for employment status
(another margin for labor market status), and we find that fluoride has a positive effect.
Differences in human general intelligence or reasoning ability can be quantified with the psychometric factor g, because individual performance across
cognitive tasks is positively correlated. g also emerges in mammals and birds, is correlated with brain size and may similarly reflect general reasoning
ability and behavioural flexibility in these species. To exclude the alternative that these positive cross-correlations may merely reflect the general biological
quality of an organism or an inevitable by-product of having brains it is paramount to provide solid evidence for the absence of g in at least some
species. Here, we show that wild-caught cleaner fish Labroides
dimidiatus, a fish species otherwise known for its highly sophisticated social behaviour, completely lacks g when tested on ecologically
non-relevant tasks. Moreover, performance in these experiments was not or negatively correlated with an ecologically relevant task, and in none of the tasks did
fish caught from a high population density site outperform fish from a low-density site. g is thus unlikely a default result of how brains are designed,
and not an automatic consequence of variation in social complexity. Rather, the results may reflect that g requires a minimal brain size, and thus explain
the conundrum why the average mammal or bird has a roughly 10× larger brain relative to body size than ectotherms. Ectotherm brains and cognition may therefore be
organized in fundamentally different ways compared to endotherms.
Important questions remain about the profile of cognitive impairment in psychotic disorders across adulthood and illness stages. The age-associated profile of
familial impairments also remains unclear, as well as the effect of factors, such as symptoms, functioning, and medication. Using cross-sectional data from
the EU-GEI and GROUP studies, comprising 8455 participants aged 18 to 65, we
examined cognitive functioning across adulthood in patients with psychotic disorders (n = 2883), and their unaffected siblings (n = 2271),
compared to controls (n= 3301). An abbreviated WAIS-III measured verbal knowledge, working memory,
visuospatial processing, processing speed, and IQ. Patients showed medium to large deficits across all functions (ES range = −0.45 to −0.73, p <
0.001), while siblings showed small deficits on IQ, verbal knowledge, and working memory (ES = −0.14 to −0.33, p < 0.001). Magnitude of impairment was
not associated with participant age, such that the size of impairment in older and younger patients did not statistically-significantly differ. However,
first-episode patients performed worse than prodromal patients (ES range = −0.88 to −0.60, p < 0.001). Adjusting for cannabis use, symptom severity,
and global functioning attenuated impairments in siblings, while deficits in patients remained statistically-significant, albeit reduced by half (ES range = −0.13
to −0.38, p < 0.01). Antipsychotic medication also accounted for around half of the impairment in patients (ES range = −0.21 to −0.43, p <
0.01). Deficits in verbal knowledge, and working memory may specifically index familial, ie., shared genetic and/or shared environmental, liability for psychotic
disorders. Nevertheless, potentially modifiable illness-related factors account for a substantial portion of the cognitive impairment in psychotic disorders.
Using two nationally representative datasets, we find large differences between Black and White children in teacher-reported measures of noncognitive skills. We
show that teacher reports understate true Black-White skill gaps because of reference bias: teachers appear to rate children relative to others in the same school,
and Black students have lower-skilled classmates on average than do White students. We pursue three approaches to addressing these reference biases. Each approach
nearly doubles the estimated Black-White gaps in noncognitive skills, to roughly 0.9 standard deviations in third grade.
Power of cognitive ability and social class contrasted.
Large representative sample from longitudinal study, waves 1–3, of 6,216 children
Outcomes were attainments, difficulties and relationships.
Cognitive ability explained large amounts of variance.
Social background only minor effects
The paper examines the effects of socioeconomic background (SES)—measured by social class, family income and
parental education—cognitive ability, and gender on a variety of key outcomes from a large longitudinal study based on a representative sample of
13-year-olds.
The data analysed comprised 6,216 children who participated in waves 1 to 3 of the Growing Up in Ireland (GUI)
longitudinal survey. The outcome measures drawn from wave 3, when respondents were aged about 17, were: examination results and several cognitive measures,
life difficulties, and quality of relationships. 3 regression models were compared with and without, SES measures
(occupational class, household income and parental education) and cognitive ability.
On academic and cognitive attainments, cognitive ability at age 13 had substantially more explanatory power than the SES measures together. On measures of adolescent difficulties and on family relationships, cognitive ability was important, but
gender and to a lesser extent, household income and parental education had some effects.
Claims that class background and family income are of central importance for adolescent outcomes are not supported.
[Keywords: intelligence, school tests, family background, household income, social class]
Human children show unique cognitive skills for dealing with the social world but their cognitive performance is paralleled by great apes in many tasks dealing
with the physical world. Recent studies suggested that members of a songbird family—corvids—also evolved complex cognitive skills but a detailed understanding of
the full scope of their cognition was, until now, not existent. Furthermore, relatively little is known about their cognitive development.
Here, we conducted the first systematic, quantitative large-scale assessment of physical and social cognitive performance of common ravens with a special focus
on development. To do so, we fine-tuned one of the most comprehensive experimental test-batteries, the Primate Cognition Test Battery(PCTB), to raven features enabling also a direct,
quantitative comparison with the cognitive performance of 2 great ape species. Full-blown cognitive skills were already present at the age of 4 months with
subadult ravens’ cognitive performance appearing very similar to that of adult apes in tasks of physical (quantities, and causality) and social cognition (social
learning, communication, and theory of mind).
These unprecedented findings strengthen recent assessments of ravens’ general intelligence, and aid to the growing evidence that the lack of a specific cortical
architecture does not hinder advanced cognitive skills. Difficulties in certain cognitive scales further emphasize the quest to develop comparative test batteries
that tap into true species rather than human specific cognitive skills, and suggest that socialization of test individuals may play a crucial role.
We conclude to pay more attention to the impact of personality on cognitive output, and a currently neglected topic in Animal Cognition—the linkage between
ontogeny and cognitive performance.
Why do some individuals learn more quickly than others, or perform better in complex cognitive tasks? In this article, we describe how differential and
experimental research methods can be used to study intelligence in humans and non-human animals. More than one hundred years ago, Spearman (1904)
discovered a general factor underpinning performance across cognitive domains in humans. Shortly thereafter, Thorndike (1935) discovered positive correlations between cognitive
performance measures in the albino rat. Today, research continues to shed light on the underpinnings of the positive manifold observed among ability measures.
In this review, we focus on the relationship between cognitive performance and attention control: the domain-general ability to maintain focus on task-relevant
information while preventing attentional capture by task-irrelevant thoughts and events. Recent work from our laboratory has revealed that individual differences
in attention control can largely explain the positive associations between broad cognitive abilities such as working memory capacity and fluid intelligence. In
research on mice, attention control has been closely linked to a general ability factor reflecting route learning and problem solving.
Taken together, both lines of research suggest that individual differences in attention control underpin performance in a variety of complex cognitive tasks,
helping to explain why measures of cognitive ability correlate positively. Efforts to find confirmatory and disconfirmatory evidence across species stands to
improve not only our understanding of attention control, but cognition in general.
Cognitive training and brain stimulation show promise for ameliorating age-related neurocognitive decline. However, evidence for this is controversial. In a
Registered Report, we
investigated the effects of these interventions, where 133 older adults were allocated to four groups (left prefrontal cortex anodal transcranial direct current
stimulation (tDCS) with decision-making training, and three control groups) and trained over 5 days. They
completed a task/questionnaire battery pre-training and post-training, and at 1- and 3-month follow-ups. COMT and
BDNF Val/Met polymorphisms were also assessed. Contrary to work in younger adults, there was evidence against
tDCS-induced training enhancement on the decision-making task. Moreover, there was evidence against transfer of training
gains to untrained tasks or everyday function measures at any post-intervention time points. As indicated by exploratory work, individual differences may have
influenced outcomes. But, overall, the current decision-making training and tDCS protocol appears unlikely to lead
to benefits for older adults.
The study of intelligence in humans has been ongoing for over 100 years, including the underlying structure, predictive validity, related cognitive measures,
and source of differences. One of the key findings in intelligence research is the uniform positive correlations among cognitive tasks. This has been replicated
with every cognitive test battery in humans. Nevertheless, many other aspects of intelligence research have revealed contradictory lines of evidence. Recently,
cognitive test batteries have been developed for animals to examine similarities to humans in cognitive structure. The results are inconsistent, but there is
evidence for some similarities. This article reviews the way intelligence and related cognitive abilities are assessed in humans and animals and suggests a
different way of devising test batteries for maximizing between-species comparisons.
Macphail’s “null hypothesis”, that there are no differences in intelligence, qualitative, or quantitative, between non-human vertebrates has been controversial.
This controversy can be useful if it encourages interest in acquiring a detailed understanding of how non-human animals express flexible problem-solving capacity
(“intelligence”), but limiting the discussion to vertebrates is too arbitrary.
As an example, we focus here on Portia, a spider with an especially
intricate predatory strategy and a preference for other spiders as prey. We review research on pre-planned detours, expectancy violation, and a capacity to solve
confinement problems where, in each of these 3 contexts, there is experimental evidence of innate cognitive capacities and reliance on internal representation.
These cognitive capacities are related to, but not identical to, intelligence.
When discussing intelligence, as when discussing cognition, it is more useful to envisage a continuum instead of something that is simply present or not; in
other words, a continuum pertaining to flexible problem-solving capacity for “intelligence” and a continuum pertaining to reliance on internal representation for
“cognition.” When envisaging a continuum pertaining to intelligence, Daniel Dennett’s notion of 4 Creatures (Darwinian, Skinnerian, Popperian, and Gregorian) is of
interest, with the distinction between Skinnerian and Popperian Creatures being especially relevant when considering Portia. When we consider these
distinctions, a case can be made for Portia being a Popperian Creature. Like Skinnerian Creatures, Popperian Creatures express flexible problem solving
capacity, but the manner in which this capacity is expressed by Popperian Creatures is more distinctively cognitive.
The literature on the relationship between socioeconomic background (SES) and university education is inconsistent.
Some studies concludeSES is important to university entry and course completion, othersfind trivial
SES effects, net of students’ prior performance, and athird group concludes that SES effects are important and policy relevant even when considering prior performance. Parallel arguments apply to demographic,
school sector, and institutional differences in the university career, that is, are they unimportant when considering student performance? Using
comprehensive and accurate measures of SES and student performance, and a statistical method that utilizes all
non-missing data, this study quantifies the effects of socioeconomic, demographic, and institutional factors and prior student performance. SES has only weak effects on university entry and attrition, and no effects on course completion. Student performance has strong effects on entry and has
moderate effects on attrition and completion. Demographic other differences mostly disappear when controlling for student performance.
[Keywords: PISA test scores, tertiary entrance performance(ATAR), university participation, university course attrition, university course completion]
The relation between working memory capacity (WMC) and baseline pupil diameter was examined. Participants
(n= 341) performed several WMC tasks and baseline pupil diameter was measured in a dark room with a
black background screen. The results indicated a weak and non-significant correlation between WMC and baseline pupil
diameter consistent with some prior research. A meta-analysis of available studies (k = 26; n = 4356) similarly indicated a weak and
non-significant correlation between WMC and baseline pupil diameter. Moderator analyses indicated that the primary
moderator responsible for heterogeneity across studies was where the study was conducted. Studies from one laboratory tend to demonstrate a
statistically-significant positive correlation, whereas other laboratories have yet to demonstrate the correlation. Broadly, the results suggest that the
correlation between WMC and baseline pupil diameter is weak and not particularly robust.
We investigate whether elite Chicago public high schools differentially benefit high-achieving students from more and less affluent neighborhoods. Chicago’s
place-based affirmative action policy allocates seats based on achievement and neighborhood socioeconomic status (SES).
Using regression discontinuity design(RDD), we find that these schools do not raise test scores overall,
but students are generally more positive about their high school experiences. For students from low-SES neighborhoods, we
estimate negative effects on grades and the probability of attending a selective college. We present suggestive evidence that these findings for
students from low-SES neighborhoods are driven by the negative effect of relative achievement ranking.
Figure 3B: Relationship between the Centered Application Score and Select Outcomes, Tiers 1 and 4.
Genetic quality may be expressed through many traits simultaneously, and this would suggest a phenotype-wide fitness factor. In humans, intelligence has been
positively associated with several potential indicators of genetic quality, including ejaculate quality. We conducted a conceptual replication of one such study by
investigating the relationship between intelligence (assessed by the Raven Advanced Progressive Matrices Test-Short Form) and ejaculate quality (indexed by sperm
count, sperm concentration, and sperm motility) in a sample of 41 men (ages ranging 18 to 33 years; M = 23.33; SD = 3.60). By self-report, participants had not had
a vasectomy, and had never sought infertility treatment. We controlled for several covariates known to affect ejaculate quality (eg. abstinence duration before
providing an ejaculate) and found no statistically-significant relationship between intelligence and ejaculate quality; our findings, therefore, do not match those
of Arden, Gottfredson, Miller et al or those of previous studies. We discuss limitations of this study and the general research area and highlight the need for
future research in this area, especially the need for larger data sets to address questions around phenotypic quality and ejaculate quality.
…An important limitation of the current research is the small sample of 41 men, as small sample sizes increase the risk of both Type I and Type II errors. Our
analyses, therefore, may have lacked sufficient power to detect the small effect sizes, r = 0.14 to 0.19, reported by Arden, Gottfredson, Miller, and
Pierce (2009). Small sample sizes are a recurrent limitation of psychological research investigating ejaculate quality (eg. Baker & Bellis, 1989;
Pook et al 2005), perhaps due to difficulties recruiting participants outside a clinical setting. Arden, Gottfredson, Miller, and Pierce analyzed
data from a sample of 425 men, which afforded the analyses over 80% power to detect small effects. However, it is important to note that the correlation
coefficients we obtained were similar in magnitude to those reported by Arden, Gottfredson, Miller, and Pierce, ranging from −0.18 to 0.30, and the
repeated-measures nature of our study gave it greater power despite the small sample size.
Objective: Deleterious copy number variants (CNVs) are identified in up to 20% of individuals with autism. However, levels of
autism risk conferred by most rare CNVs remain unknown. The authors recently developed statistical models to
estimate the effect size on IQ of all CNVs, including undocumented ones. In this study, the authors extended this
model to autism susceptibility.
Methods: The authors identified CNVs in two autism populations (Simons Simplex
Collection and MSSNG) and two unselected populations(IMAGEN and Saguenay
Youth Study). Statistical models were used to test nine quantitative variables associated with genes encompassed in CNVs to explain their effects on IQ, autism susceptibility, and behavioral domains.
Results: The “probability of being loss-of-function intolerant” (pLI) best explains the effect of CNVs on IQ and autism risk. Deleting 1 point of pLI decreases IQ by 2.6 points in autism and unselected populations.
The effect of duplications on IQ is threefold smaller. Autism susceptibility increases when deleting or duplicating any point of pLI. This is true for individuals
with high or low IQ and after removing de novo and known recurrent neuropsychiatric CNVs. When
CNV effects on IQ are accounted for, autism susceptibility remains mostly unchanged for duplications but decreases for
deletions. Model estimates for autism risk overlap with previously published observations. Deletions and duplications differentially affect social communication,
behavior, and phonological memory, whereas both equally affect motor skills.
Conclusions: Autism risk conferred by duplications is less influenced by IQ compared with deletions. The model applied in this study, trained
on CNVs encompassing >4,500 genes, suggests highly polygenic properties of gene dosage with respect to
autism risk and IQ loss. These models will help to interpret CNVs identified in the clinic.
It has been known since 1904 that, in humans, diverse cognitive traits are positively intercorrelated. This forms the basis for the general factor of
intelligence (g). Here, we directly test whether there is a partial genetic basis for individual differences in g using data from seven different
cognitive tests (n = 11,263–331,679) and genome-wide autosomal single-nucleotide polymorphisms. A genetic g factor accounts for an average of
58.4% (s.e. = 4.8%) of the genetic variance in the cognitive traits considered, with the proportion varying widely across traits (range, 9–95%). We distill genetic
loci that are broadly relevant for many cognitive traits (g) from loci associated specifically with individual cognitive traits. These results contribute
to elucidating the aetiology of a long-known yet poorly understood phenomenon, revealing a fundamental dimension of genetic sharing across diverse cognitive
traits.
Executive functions cannot be reduced to intellectual abilities.
Certain part of the genetic variance is common to these 2 phenomena.
Some aspects of executive control have higher heritability than others.
Executive functions include a series of specific abilities, with specific genetic foundations.
The first aim of this study was to explore the aetiology of phenotypic relationships between different measures of executive functions. The second objective was
to examine sources of the covariation between different measures of executive functions and the measure of general cognitive ability.
The study sample consisted of 468 twins (154 pairs of monozygotic twins and 80 pairs of dizygotic twins) of the same and different gender who grew up together.
Executive functions were evaluated by the Wisconsin Card Sorting Test, the Trail Making Test—form B, and verbal fluency tests. Raven’s Advanced Progressive
Matrices were used as a measure of general cognitive ability.
The study results suggest a primarily genetic origin of the mutual covariation of different executive measures and their covariation with the general cognitive
ability construct. While the shared genetic variance primarily lies in the bases of similarity/unity of the used cognitive measures, their
particularity/difference is determined by a specific unshared environment.
The obtained result on the presence of a single general genetic factor, which can be singled out in the case of different executive measures, at least partially
speaks in favor of the thesis about the unity of various executive measures and the existence of a common basic ability. Together with the specific unshared
environment, the specific genetic influence speaks in favor of a difference between each of the individual measures.
[Keywords: behavioral genetics, cognitive abilities, executive functions, general cognitive ability]
Objective: This study examined how the lower cognitive skills in children who consumed iron-fortified formula in infancy relate to outcomes in
young adulthood.
Methods: Participants were 443 Chilean young adults (Mage = 21.2y, 55% female) who took part in a randomized controlled
iron-deficiency anemia preventive trial during infancy (6–12 m). Slightly over half of participants (n = 237) received iron-fortified formula
(12.7 mg/L) and 206 received a low-iron formula (2.3 mg/L). Spatial memory, IQ, and visual-motor integration were measured at age 10, and neurocognition,
emotion regulation, educational level, and attainment of adult developmental milestones were assessed at age 21.
Results: Consumption of iron-fortified formula in infancy was associated with poorer performance on neurocognitive tests in childhood, and
these effects related to poorer neurocognitive, emotional, and educational outcomes in young adulthood. Dosage effects associated with consumption of
iron-fortified formula were found for lower educational attainment and, marginally, slower mental processing. Those who received iron-fortified formula and had low
age 10 cognitive abilities performed most poorly on neurocognitive tests at age 21.
Conclusion: Findings suggest that the long-term development of infants who consume iron-fortified formula may be adversely affected.
Clinical Trials number: NCT01166451.
[Keywords: Iron supplementation, neurocognition, emotion regulation, memory, executive function, Chile]
Terman’s study was the first to systematically document the lives of the intellectually gifted. This cross-sectional study replicates and extends some of
Terman’s findings on characteristics of the gifted in childhood, comparing largely unselected samples of gifted (n = 50) and average-ability (n =
50) adolescents matched by means of propensity score matching. Students were compared on their school performance (standardized math and reading tests and grades),
motivation (math ability self-concept, intrinsic motivation, vocational interests, and educational aspirations), parental educational expectations, students’
evaluation of school instruction (perceived quality and pressure), and subjective well-being. The gifted scored higher on math performance (rank-biserial
r = 0.66/0.81), math ability self-concept (0.71), intrinsic motivation (0.62), and investigative vocational interests (0.65). Some smaller differences
were found for realistic (0.42) and social interests (−0.37) and for pressure in math lessons (−0.52). Results support Terman’s findings on gifted individuals’
psychological functioning and contradict negative stereotypes about the gifted.
We compare the relative contribution of grit and intelligence to educational and job-market success in a representative sample of the American population. We
find that, in terms of Δ R 2, intelligence contributes 48–90× more than grit to educational success and 13× more to job-market success. Conscientiousness also contributes to success more than grit
but only twice as much. We show that the reason our results differ from those of previous studies which showed that grit has a stronger effect on success is that
these previous studies used nonrepresentative samples that were range restricted on intelligence. Our findings suggest that although grit has some effect on
success, it is negligible compared to intelligence and perhaps also to other traditional predictors of success.
Student sex can often be predicted based on a set of achievement and attitude data.
Student sex can often be predicted based on classification models from other countries.
Universal patterns in academic sex differences are larger than hitherto thought.
Academic sex differences are stronger in societies with more socioeconomic equality.
The extent of sex differences in psychological traits is vigorously debated. We show that the overall sex difference in the pattern of adolescents’ achievement
and academic attitudes is relatively large and similar across countries. We used a binomial regression modeling approach to predict the sex of 15 and 16 year olds
based on sets of academic ability and attitude variables in three cycles of the Programme for International StudentAssessment (PISA) data (n = 969,673 across 55 to 71 countries and regions). We found that the sex of
students in any country can be reliably predicted based on regression models created from the data of all other countries, indicating a common (universal)
sex-specific component. Averaged over three different PISA cycles (2009, 2012, 2015), the sex of 69% of students
can be correctly classified using this approach, corresponding to a large effect. Moreover, the universal component of these sex differences is stronger in
countries with relative income equality and women’s participation in the labor force and politics. We conclude that patterns in academic sex differences are larger
than hitherto thought and appear to become stronger when societies have more socioeconomic equality. We explore reasons why this may be the case and possible
implications.
We study the impact of lead exposure from birth to adulthood and provide evidence on the mechanisms producing these effects. Following 800,000 children
differentially exposed to the phaseout of leaded gasoline in Sweden, we find that even a low exposure affects long-run outcomes, that boys are more affected, and
that changes in noncognitive skills explain a sizeable share of the impact on crime and human capital. The effects are greater above exposure thresholds still
relevant for the general population, and reductions in exposure equivalent to the magnitude of the recent redefinition of elevated blood lead levels can increase
earnings by 4%.
Gender differences in mathematics are largely explained by a regional gradient in Italy.
Gender differences in reading are not influenced by a regional gradient and are stable across Italy.
A number of factors, could influence the gender gap in mathematics.
Whether males outperform females in mathematics is still debated. Such a gender gap varies across countries, but the determinants of the differences are unclear
and could be produced by heterogeneity in the instructional systems or cultures and may vary across school grades. To clarify this issue, we took advantage
of the INVALSI dataset, that offered over 13 million observations covering one single instructional system (ie., the
Italian system) in grades 2, 5, and 8, in the period 2010–2018. Results showed that males outperformed females in mathematics (and vice versa in reading), with
gaps widening from the 2nd through to the 8th grade. The gender gap in mathematics was larger in the richer northern Italian regions (also
characterized by greater gender equality) than in southern regions. This was not explained by average performance or fully accounted for by economic factors. No
such north-south difference of the gap emerged in reading. Results are discussed with reference to the literature showing that the gender gap varies across world
regions.
In a meta-analysis, we determine the average correlation among broad intelligences.
Based on model type, the average correlation was between r = 0.58 and r = 0.65.
We conduct factor analyses on a composite correlation matrix of broad intelligences.
Our results indicate the degree and nature of relations among broad intelligences.
The broad intelligences include a group of mental abilities such as comprehension knowledge, quantitative reasoning, and visuospatial processing that are
relatively specific in their focus and fall at the second stratum of the Cattell-Horn-Carroll (CHC) model of
intelligence. In recent years, the field has seen a proliferation of mental abilities being considered for inclusion among the broad intelligences, which poses
challenges in terms of their effective and efficient assessment. We conducted a meta-analysis of 61 articles that reported correlations among the broad
intelligences. Results indicated that the average correlation among broad intelligences fell between r = 0.58, 95% CI [0.53, 0.64], and r = 0.65,
95% CI [0.62, 0.68], depending upon the model employed to estimate the relations. Applying factor analysis to a composite correlation matrix drawn from the
studies, we obtained dimensions of broad intelligence that may be useful to organizing the group. Finally, we discuss the implications of the correlations among
broad intelligences as an evaluative tool for candidate intelligences.
General cognitive ability (g) does not explain sex differences in academic test performance by the end of compulsory education. Instead, individual
differences in specific reasoning abilities, after removing the effects of g, may contribute to the observed gender gaps. Associations between general or
specific cognitive abilities, sex, and educational attainments were analysed in a cross-sectional study of 11-year-olds (M = 133.5 months, SD = 3.5), at an age
before substantive gender-related selection-bias occurred. The 178,599 pupils (89,545 girls and 89,054 boys) attending English state schools represented 93%
of the UK’s local education authorities. In 2004 each student completed the Cognitive Abilities Test—Third Edition (CAT3), assessing verbal, quantitative, and nonverbal reasoning abilities. These data were linked to each child’s attainment scores
on national Key Stage 2 tests in English, mathematics and science. A sex difference in g, favoring girls, was statistically-significant but of
negligible effect size (Cohen’s d = 0.01). Girls scored 26% of a SD higher than boys on a verbal residual factor, and boys scored 28% of a SD higher than
girls on a quantitative residual factor, with negligible sex differences on a nonverbal residual factor (1% of a SD). In education, 10% more girls than boys
achieved UK government targets in English. In mathematics and science, sex differences were less apparent at the government target grade (Level 4), although a 5%
greater proportion of boys than girls performed at the highest level in mathematics (Level 5). General cognitive ability (g) was strongly related to an
educational factor score (r = 0.83) as expected, and did not explain sex differences in academic performance. In general linear models, a verbal residual
factor explained up to 29% of girls’ higher English attainment, and better quantitative skills among boys explained 50% of their higher attainment in mathematics.
Besides the substantial contributions of specific cognitive abilities to gender differences in English and mathematics, there remains substantive variance of the
educational gender gap left to explain.
We investigated intergenerational educational and occupational mobility in a sample of 2,594 adult offspring and 2,530 of their parents. Participants completed
assessments of general cognitive ability and five noncognitive factors related to social achievement; 88% were also genotyped, allowing computation of
educational-attainment polygenic scores. Most offspring were socially mobile. Offspring who scored at least 1 standard deviation higher than their parents on both
cognitive and noncognitive measures rarely moved down and frequently moved up. Polygenic scores were also associated with social mobility. Inheritance of a
favorable subset of parent alleles was associated with moving up, and inheritance of an unfavorable subset was associated with moving down. Parents’ education did
not moderate the association of offspring’s skill with mobility, suggesting that low-skilled offspring from advantaged homes were not protected from downward
mobility. These data suggest that cognitive and noncognitive skills as well as genetic factors contribute to the reordering of social standing that takes place
across generations.
Individual differences in cognitive control have been suggested to act as a domain-general bottleneck constraining performance in a variety of cognitive ability
measures, including but not limited to fluid intelligence, working memory capacity, and processing speed. However, owing to psychometric problems associated with
the measurement of individual differences in cognitive control, it has been challenging to empirically test the assumption that individual differences in cognitive
control underlie individual differences in cognitive abilities. In the present study, we addressed these issues by analyzing the chronometry of
intelligence-related differences in midfrontal global theta connectivity, which has been shown to reflect cognitive control functions. We demonstrate in a sample
of 98 adults, who completed a cognitive control task while their electroencephalogram was recorded, that individual differences in midfrontal global theta
connectivity during stages of higher-order information-processing explained 65% of the variance in fluid intelligence. In comparison, task-evoked theta
connectivity during earlier stages of information processing was not related to fluid intelligence. These results suggest that more intelligent individuals benefit
from an adaptive modulation of theta-band synchronization during the time-course of information processing. Moreover, they emphasize the role of interregional
goal-directed information-processing for cognitive control processes in human intelligence and support theoretical accounts of intelligence, which propose that
individual differences in cognitive control processes give rise to individual differences in cognitive abilities.
There are no undebated definitions of “creativity”, and any definition will reflect how this rich topic is treated. Nearly 20 years ago I discussed how
behavior analysis might contribute—or not—to an understanding of creativity. I revisit this topic, expanding on some issues and reconsidering others. As before, my
focus is on scientific and mathematical accomplishments, which, though tied closely to Weisberg’s placement of creative achievements in the domains of problem
posing and problem solving, places emphasis on the extraordinary and productive giftedness of certain individuals. From the massive empirical, theoretical, and
historical literature at least three essential and dynamically interlocking dimensions of their creative achievements emerge: talent, expertise, and motivation. I
emphasize “interlocking” because the productive expression of each of these elements depends on the others. The role of behavior analysis in these elements is
modest at best. It has nothing to say about talent—and even in some cases might deny its role altogether. As for expertise, with some notable exceptions, behavior
analysis has had little to say about the acquisition of truly complex performances; this has been left to other fields. As for motivation, one must go well beyond
naïve “pleasure and pain” accounts to more elusive, yet more powerful behavior-consequence relations. Many challenges to understanding remain for all behavioral
scientists.
Intelligence quotient (IQ) is a common measure of intelligence that associates with many important life outcomes. Research over several decades has indicated
that the average IQ test score among Black Americans is lower than the average IQ test score among White Americans, but in weighted results from a national
nonprobability survey, only about 41% of US adults indicated awareness of this IQ gap. Results from a follow-up convenience survey indicated that, in the
aggregate, White participants’ rating of White Americans’ average IQ and average intelligence is higher than Blacks Americans’ average IQ test score and average
intelligence and was not driven by White participants’ belief in a universal White intellectual superiority. These and other results could have implications
regarding the US public’s perceptions about the reasons for Black/White inequality and implications for the use of intelligence stereotype scales as measures of
racial prejudice.
With just one exception, all of the volumes in Terman’s Genetic Studies of Genius report the results of a longitudinal study of more than a thousand
intellectually gifted children. That single exception is Volume II, Cox’s single-authored The Early Mental Traits of Three Hundred Geniuses, which instead
was a retrospective study of 301 eminent creators and leaders, using historiometric methods to estimate their IQs (as well as to assess a subset of 100 on 67
character traits). This article discusses how this volume actually fits with the other four volumes in the set. After giving the historical background, discussion
turns to the emergence of Cox’s doctoral dissertation. Then comes a narrative of the aftermath, including subsequent contributions by Cox, Terman, and numerous
other researchers extending into the 21st century. The article closes by treating the ways that the intellectually gifted and the historic geniuses are
not comparable, thus indicating the need for more recent replications and extensions of her work.
[Keywords: archival, biographical, historical analysis, early childhood, gifted, intelligence]
Several previous studies reported relationships between speed of information processing as measured with the drift parameter of the diffusion model (Ratcliff,
1978) and general intelligence. Most of these studies utilized only few tasks and none of them used more complex tasks. In contrast, our study (n = 125)
was based on a large battery of 18 different response time tasks that varied both in content (numeric, figural, and verbal) and complexity (fast tasks with mean
RTs of ca. 600 ms vs. more complex tasks with mean RTs of ca. 3,000 ms). Structural equation models indicated a strong relationship between a domain-general
drift factor and general intelligence. Beyond that, domain-specific speed of information processing factors were closely related to the respective domain scores of
the intelligence test. Furthermore, speed of information processing in the more complex tasks explained additional variance in general intelligence. In addition to
these theoretically relevant findings, our study also makes methodological contributions showing that there are meaningful interindividual differences in content
specific drift rates and that not only fast tasks, but also more complex tasks can be modeled with the diffusion model.
Evolutionary rates of G vs. neuroanatomical proxies are compared.
G exhibits greater evolutionary lability.
This suggests different selection regimes.
cerebellar volume residualised against body size is the best proxy.
Various neuroanatomical volume measures (NVMs) are frequently used as proxies for intelligence in comparative
studies, such as the size of the brain, neocortex, and hippocampus, either absolute or controlled for other size measures (eg. body size, or rest of the brain).
Mean species NVMs are moderately correlated with aggregate general intelligence (G), however Gand NVMs are yet to be compared in their evolutionary patterns (eg. conservatism and evolutionary rates) and
processes (ie., their fit to diverse models of evolution reflecting selection regimes).
Such evolutionary information is valuable for examining convergence in the evolutionary history among traits and is not available from simple correlation
coefficients. Considering accumulating evidence that non-volumetric neurological measures may be as important as (or more so than) volumetric measures as
substrates of intelligence, and that certain NVMs negatively predict neuronal density, we hypothesized that
discrepancies would be found in evolutionary patterns and processes of Gcompared to NVMs.
We collated data from the literature on primate species means for G, the volumes of the brain, neocortex, cerebellum, and hippocampus, and body mass,
and employed phylogenetic comparative methods that examine phylogenetic signal (λ, K), evolutionary rates (σ2), and several parameters of evolutionary
models (Brownian motion, Early-burst, acceleration, and Ornstein-Uhlenbeck).
Evolutionary rates and acceleration trends were up to an order of magnitude higher for Gthan for most NVMs,
and a strong selection optimum toward which clades evolved was found for G, whereas NVMs conformed
mostly to Brownian motion. Brain size was the most contrasting NVM compared to intelligence across most
phylogenetic indices examined, showing signs of deceleration and extreme conservativeness. Only certain operationalizations of neocortical and hippocampal
volume showed convergence with G, albeit still notably weakly. The NVM with results that most strongly
approached the patterns identified for G is residual cerebellar size (relative to body size).
In comparison to the most commonly used volumetric measures (operationalization of brain and neocortex size), G must be seen as an evolutionarily
labile trait under considerable selection pressure, necessitating that the role of the cerebellum be more aptly recognized and that other neurological factors be
invoked as potential substrates for its evolutionary trajectory.
[Keywords: general intelligence, phylogenetic comparative methods, cerebellum, brain size, neocortex]
Conventional tests of the Dunning-Kruger hypothesis are shown to be confounded.
The Glejser test is argued to be a valid test of the Dunning-Kruger hypothesis.
Nonlinear regression is argued to be a valid test of the Dunning-Kruger hypothesis.
Failed to identify the Dunning-Kruger effect with IQ data and both valid tests.
The Dunning-Kruger hypothesis states that the degree to which people can estimate their ability accurately depends, in part, upon possessing the ability in
question. Consequently, people with lower levels of the ability tend to self-assess their ability less well than people who have relatively higher levels of the
ability. The most common method used to test the Dunning-Kruger hypothesis involves plotting the self-assessed and objectively assessed means across four
categories (quartiles) of objective ability. However, this method has been argued to be confounded by the better-than-average effect and regression toward the
mean. In this investigation, it is argued that the Dunning-Kruger hypothesis can be tested validly with two inferential statistical techniques: the Glejser test of
heteroscedasticity and nonlinear (quadratic) regression. On the basis of a
sample of 929 general community participants who completed a self-assessment of intelligence and the Advanced Raven’s Progressive Matrices, we failed to identify
statistically-significant heteroscedasticity, contrary to the Dunning-Kruger hypothesis. Additionally, the association between objectively measured intelligence
and self-assessed intelligence was found to be essentially entirely linear, again, contrary to the Dunning-Kruger hypothesis. It is concluded that, although the
phenomenon described by the Dunning-Kruger hypothesis may be to some degree plausible for some skills, the magnitude of the effect may be much smaller than
reported previously.
Research in educational psychology consistently finds a relationship between intelligence and academic performance. However, in recent decades, educational
fields, including gifted education, have resisted intelligence research, and there are some experts who argue that intelligence tests should not be used in
identifying giftedness. Hoping to better understand this resistance to intelligence research, we created a survey of beliefs about intelligence and administered it
online to a sample of the general public and a sample of teachers. We found that there are conflicts between currently accepted intelligence theory and beliefs
from the American public and teachers, which has important consequences on gifted education, educational policy, and the effectiveness of interventions.
On a planet experiencing global environmental change, the governance of natural resources depends on sustained collective action by diverse populations.
Engaging in such collective action can only build upon the foundation of human cognition in social-ecological settings. To help understand this foundation, we
assess the effect of cognitive abilities on the management of a common pool resource. We present evidence that two functionally distinct cognitive abilities,
general and social intelligence, improve the ability of groups to manage a common pool resource. Groups high in both forms of intelligence engage in more effective
collective action that is also more consistent, despite social or ecological change. This result provides a foundation for integrating the effects of cognitive
abilities with other dimensions of cognitive diversity to explain when groups will and will not sustainably govern natural resources.
The human cerebral cortex is important for cognition, and it is of interest to see how genetic variants affect its
structure. Grasby et al 2020 combined genetic data with brain magnetic resonance imaging from more than 50,000 people to generate a genome-wide
analysis of how human genetic variation influences human cortical surface area and thickness. From this analysis, they identified variants associated with cortical
structure, some of which affect signaling and gene expression. They observed overlap between genetic loci affecting cortical structure, brain development, and
neuropsychiatric disease, and the correlation between these phenotypes is of interest for further study.
Introduction: The cerebral cortex underlies our complex cognitive capabilities. Variations in human
cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance
imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known
about common genetic variants that affect human cortical structure.
Rationale: To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a
genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the
surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations.
Results: We identified 306 nominally genome-wide statistically-significant loci (p < 5 × 10−8) associated with cortical
structure in a discovery sample of 33,992 participants of European ancestry. Of the 299 loci for which replication data were available, 241 loci influencing
surface area and 14 influencing thickness remained statistically-significant after replication, with 199 loci passing multiple testing correction (p <
8.3 × 10−10; 187 influencing surface area and 12 influencing thickness).
Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed
a negative genetic correlation (rg = −0.32, SE = 0.05, p = 6.5 × 10−12), which
suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by
genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active
regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When
considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in
thickness.
To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the
regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 10 that influence regional thickness. Loci
that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity.
We observed statistically-significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive
functioning and educational attainment. We found additional positive genetic correlations between total surface area and
Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface
area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and
neuroticism.
Conclusion: This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its
regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas.
Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive
function.
Foreign language learning in older age has been proposed as a promising avenue for combatting age-related cognitive decline. We tested this hypothesis in a
randomized controlled study in a sample of 160 healthy older participants (aged 65–75 years) who were randomized to 11 weeks of either language learning or
relaxation training. Participants in the language learning condition obtained some basic knowledge in the new language (Italian), but between-groups differences in
improvements on latent factors of verbal intelligence, spatial intelligence, working memory, item memory, or associative memory were negligible. We argue that this
is not due to either poor measurement, low course intensity, or low statistical power, but that basic studies in foreign
languages in older age are likely to have no or trivially small effects on cognitive abilities. We place this in the context of the cognitive training and
engagement literature and conclude that while foreign language learning may expand the behavioral repertoire, it does little to improve cognitive processing
abilities.
Religious belief is a topic of longstanding interest to psychological science, but the psychology of religious disbelief is a relative newcomer. One prominently
discussed model is analytic atheism, wherein analytic thinking overrides religious intuitions and instruction. Consistent with this model,
performance-based measures of reliance on analytic thinking predict religious disbelief in WEIRD (Western,
Educated, Industrialized, Rich, & Democratic) samples. However, the generality of analytic atheism remains unknown.
Drawing on a large global sample (n = 3,461) from 13 religiously, demographically, and culturally diverse societies, we find that analytic atheism is
in fact quite fickle cross-culturally, only appearing robustly in aggregate analyses and in 3 individual countries.
Such complexity implies a need to revise simplistic theories of religious disbelief as primarily grounded in cognitive style. The results provide additional
evidence for culture’s effects on core beliefs, highlighting the power of comparative cultural evidence to clarify core mechanisms of human psychological
variation.
A two-year old rat, R222, survived a life-time of extreme hydrocephaly affecting the size and organization of its brain. Much of the cortex was severely thinned
and replaced by cerebrospinal fluid, yet R222 had normal motor function, could hear, see, smell, and respond to tactile stimulation. The hippocampus was malformed
and compressed into the lower hindbrain together with the hypothalamus midbrain and pons, yet R222 showed normal spatial memory as compared to age-matched
controls. BOLDMRI was used to study the reorganization of R222’s brain
function showing global activation to visual, olfactory and tactile stimulation, particularly in the brainstem/cerebellum. The results are discussed in
the context of neuroadaptation in the face of severe hydrocephaly and subsequent tissue loss, with an emphasis on what is the “bare minimum” for survival.
The lottery ticket hypothesis, initially proposed by researchers Jonathan Frankle and Michael Carbin at MIT, suggests
that by trainingdeep neural networks (DNNs) from “lucky” initializations, often referred to as “winning
lottery tickets”, we can train networks which are 10–100× smaller with minimal losses—or even while achieving gains—in performance. This work has exciting
implications for potentially finding ways to not only train with fewer resources, but also run faster inference of models on smaller devices, like smartphones and
VR headsets. But the lottery ticket hypothesis is not yet fully understood by the AI community. In particular, it has remained unclear whether winning tickets are
dependent on specific factors or rather represent an intrinsic feature of DNNs.
New research from Facebook AI finds the first definitive evidence that lottery tickets generalize across related, but distinct datasets and can extend to
reinforcement learning (RL) and natural language
processing (NLP). We’re sharing details on the results of our experiments using winning tickets, and we’re also
introducing a new theoretical framework on the formation of lottery tickets to help researchers advance toward a better understanding of lucky initializations.
…there are many more open questions about the underlying properties and behaviors of neural networks, such as how do these winning tickets form, why do they
exist, and how do they work?
To begin to analyze these questions in the context of deep ReLU networks, we used a student-teacher setting, in which a larger student network must learn to
mimic exactly what the smaller teacher is doing. Since we can define the teacher network with fixed parameters in this setting, we can quantitatively measure the
student network’s learning progress, and, critical to our investigation of lottery tickets, how the student network’s initialization affects the learning
process.
In the student-teacher setting, we see that after training, the activity patterns of select student neurons correlate more strongly with those of teacher
neurons than with the activity of other student neurons—a concept that is referred to as “student specialization.” This stronger correlation suggests that, during
training, the student network not only learns the teacher’s network output but also the internal structure of the teacher by mimicking individual teacher
neurons.
In our analysis, we show this occurrence happens locally in a 2-layer ReLU network: if the initial weights of a student neuron happen to be similar to those of
some teacher neurons, then specialization will follow. The size of the neural network is important because the larger the student network, the more likely that one
of the student neurons will start out close enough to a teacher neuron to learn to mimic its activity during training. What’s more, if a student neuron’s initial
activation region has a more substantial overlap with a teacher neuron, then that student neuron specializes faster. This behavior corroborates the lottery ticket
hypothesis, which similarly proposes that some lucky subset of initializations exist within neural networks, and “winning tickets” are the lucky student neurons
that happen to be in the right location at the beginning of training. In our follow-up research, we strengthen our results by removing many mathematical
assumptions, including independent activations and locality, and still prove that student specialization happens in the lowest layer in deep ReLU networks after training. From our analysis, we
find certain mathematical properties in the training dynamics resonate with the lottery ticket phenomenon: those weights with a slight advantage in the
initialization may have a greater chance of being the winning tickets after training converges.
Her son, Henry, endured hundreds of seizures a day. Despite receiving high doses of medication, his little body seemed like a rag doll as one episode blended
into another. He required several surgeries, starting when he was 3 1⁄2 months old, eventually leading to a complete anatomical hemispherectomy, or the removal of
half of his brain, when he turned 3. The procedure was first developed in the 1920s to treat malignant brain tumors. But its success in children who have brain
malformations, intractable seizures or diseases where damage is confined to half the brain, has astonished even seasoned scientists. After the procedure, many of
the children are able to walk, talk, read and do everyday tasks. Roughly 20 percent of patients who have the procedure go on to find gainful employment as
adults.
Now, research published Tuesday in the journal Cell Reports suggests that some individuals recover so well from the surgery because of a reorganization
in the remaining half of the brain. Scientists identified the variety of networks that pick up the slack for the removed tissue, with some of the brain’s
specialists learning to operate like generalists. “The brain is remarkably plastic”, said Dorit Kliemann, a cognitive neuroscientist at the California Institute of
Technology, and the first author of the study. “It can compensate for dramatic loss of brain structure, and in some cases the remaining networks can support almost
typical cognition.”
…Instead, researchers found that while the type of connections remained the same in the individuals with just one hemisphere, different regions responsible for
processing sensorimotor information, vision, attention and social cues strengthened existing connections, communicating more frequently with each other compared
with ordinary brains. It was almost as if parts of the brain that may have normally been specialized, say, as trumpet players, had talked to the rest of the band
and taken additional responsibilities to play percussion instruments as well, Dr. Behrmann said. “Their brain networks seem to be multitasking.”
The results are encouraging for researchers and families trying to understand how the brain adapts and functions after a hemispherectomy. “I think there’s more
and more evidence to suggest that brain plasticity is a really long-lasting phenomena”, said Dr. Ajay Gupta, a pediatric neurologist at the Cleveland Clinic,
who has followed nearly 200 children after the surgery. Until recently, the scientific consensus has been that hemispherectomy surgery is best performed at a very
young age, before a child reaches the age of 4 or 5. That way, they can regain normal function as they grow older. While neuroplasticity is stronger in early
childhood, the new study suggests that surgery should not be withheld after an arbitrary end date, Dr. Gupta said. Adults in the study had undergone
hemispherectomy surgery at ages ranging from 3 months to 11 years old.
A factor that may play a more important role in patient outcomes is the age at which seizures begin to occur. The surgery is still considered a last resort
after medical treatment. But if the duration of seizures and resulting brain damage can be limited, patients may recover more function. “The other hemisphere is
already having to handle extra responsibilities before patients get treated”, said Lynn K. Paul, a neuroscientist at California Institute of Technology and a
co-author of the study. “It continues to do so when you take out the damaged hemisphere. So what we really want is to protect the hemisphere that’s working.”
…After the operation, children become substantially weaker in their hands and arms on the side opposite the operation. Their vision becomes blocked on that
side, and they may also lose some ability to recognize where sounds are coming from. “There are some things that definitely require a higher level of rehab and
learning. For example, reading and writing and math”, Dr. Gupta said. In many cases, however, those skills have already been compromised by the underlying
diseases…For now, she is happy that her son can walk independently, communicate with an iPad and eat meals without a feeding tube.
[Summary of investigation into David Rosenhan: like the Robbers Cave or Stanford Prison Experiment, his famous fake-insane patients experiment cannot be
verified and many troubling anomalies have come to light. Cahalan is unable to find almost all of the supposed participants, Rosenhan hid his own participation &
his own medical records show he fabricated details of his case, he throw out participant data that didn’t match his narrative, reported numbers are inconsistent,
Rosenhan abandoned a lucrative book deal about it and avoided further psychiatric research, and showed some character traits of a fabulist eager to please.]
Numerous studies have found a negative relationship between religiousness and IQ. It is in the region of −0.2, according to meta-analyses. The reasons for this relationship are, however, unknown. It has been
suggested that higher intelligence leads to greater attraction to science, or that it helps to override evolved cognitive dispositions such as for religiousness.
Either way, such explanations assume that the religion-IQ nexus is on general intelligence (g), rather than some subset of specialized cognitive
abilities. In other words, they assume it is a Jensen effect.
Two large datasets comparing groups with different levels of religiousness show that their IQ differences are not on g and must, therefore, be
attributed to specialized abilities [but see Dutton et al 201
which finds the opposite, using much stronger IQ testing]. An analysis of the specialized abilities on which the religious and non-religious groups differ reveals
no clear pattern.
We cautiously suggest that this may be explicable in terms of autism spectrum
disorder traits among people with high IQ scores, because such traits are negatively associated with religiousness.
We conduct field experiments on time preferences with children ages 3–12.
Time preferences evolve statistically-significantly during this period, with older children displaying more patience.
Neither assignment to early schooling or parent preferences can explain child time preferences.
Interestingly, we observe that black children are more impatient than white or Hispanic children.
Time preferences have been correlated with a range of life outcomes, yet little is known about their early development. We conduct a field experiment to elicit
time preferences of over 1200 children ages 3–12, who make several intertemporal decisions. To shed light on how such primitives form, we explore various channels
that might affect time preferences, from background characteristics to the causal impact of an early schooling program that we developed and operated. Our results
suggest that time preferences evolve substantially during this period, with younger children displaying more impatience than older children. We also find a strong
association with race: black children, relative to white or Hispanic children, are more impatient. Finally, assignment to different schooling opportunities is not
statistically-significantly associated with child time preferences.
[Keywords: Time preferences, Child behavior, Experiment, Inter-generational transmission]
We used a large sample from UK Biobank (N = 29,004, age range = 44–81 years).
The association between brain volume and intelligence (‘g’) was r = 0.276.
Multiple global tissue measures explained twice the g variance in older than middle age.
The size of the association between g and global brain measures did not vary by sex.
We investigate the regional cortical, subcortical and white matter correlates of g.
The associations between indices of brain structure and measured intelligence are unclear. This is partly because the evidence to-date comes from mostly small
and heterogeneous studies. Here, we report brain structure-intelligence associations on a large sample from the UK Biobank study. The overall N = 29,004, with N = 18,426 participants providing both brain
MRI and at least one cognitive test,and a complete four-test battery with MRI
data available in a minimumN = 7201, depending upon the MRI measure. Participants’ age range was
44–81 years (M = 63.13, SD = 7.48). A general factor of intelligence (g) was derived from four varied cognitive tests, accounting for one third of the
variance in the cognitive test scores. The association between (age-corrected and sex-corrected) total brain volume and a latent factor of general intelligence is
r = 0.276, 95% C.I. = [0.252, 0.300]. A model that incorporated multiple global measures of grey and white matter macrostructure and microstructure
accounted for more than double the g variance in older participants compared to those in middle-age (13.6% and 5.4%, respectively). There were no sex
differences in the magnitude of associations between g and total brain volume or other global aspects of brain structure. The largest brain regional
correlates of g were volumes of the insula, frontal, anterior/superior and medial temporal, posterior and paracingulate, lateral occipital cortices,
thalamic volume, and the white matter microstructure of thalamic and association fibres, and of the forceps minor. Many of these regions exhibited unique
contributions to intelligence, and showed highly stable out of sample prediction.
The ability of parasites to manipulate host behavior to their advantage has been studied extensively, but the impact of parasite manipulation on the evolution
of neural and endocrine mechanisms has remained virtually unexplored. If selection for countermeasures has shaped the evolution of nervous systems, many aspects of
neural functioning are likely to remain poorly understood until parasites—the brain’s invisible designers—are included in the picture.
This article offers the first systematic discussion of brain evolution in light of parasite manipulation. After reviewing the strategies and mechanisms employed
by parasites, the paper presents a taxonomy of host countermeasures with four main categories, namely: restrict access to the brain; increase the costs of
manipulation; increase the complexity of signals; and increase robustness. For each category, possible examples of countermeasures are explored, and the likely
evolutionary responses by parasites are considered.
The article then discusses the metabolic, computational, and ecological constraints that limit the evolution of countermeasures. The final sections offer
suggestions for future research and consider some implications for basic neuroscience and psychopharmacology.
The paper aims to present a novel perspective on brain evolution, chart a provisional way forward, and stimulate research across the relevant disciplines.
Although the accomplishments of the 1,528 subjects of the Genetic Studies of Genius are impressive, they do not represent the pinnacle of human achievement.
Since the early 1990s, commentators (eg. Bond, 2014; Gladwell, 2006; Heilman, 2016; Shurkin, 1992) have drawn attention to the fact that two future
Nobelists—William Shockley and Luis Alvarez—were among the 168,000 candidates screened for the study; but they were
rejected because their IQ scores were too low. Critics see this as a flaw of Terman’s methodology and/or intelligence testing. However, events with a low base
rate (such as winning a Nobel prize) are difficult to predict (Taylor & Russell 1939).
This study simulates the Terman’s sampling procedure to estimate the probability that Terman’s sampling procedure would have selected one or both future
Nobelists from a population of 168,000 candidates. Using data simulations, we created a model that realistically reflected the test-retest and split-half
reliability of the IQ scores used to select individuals for the Genetic Studies of Genius and the relationship between IQ and Nobelist status.
Results showed that it was unlikely for Terman to identify children who would later earn Nobel prizes, mostly due to the low base rates of such high future
achievement and the high minimum IQ needed to be selected for Terman’s study.
Changes to the methodology that would have been required to select one or both Nobelists for the longitudinal study were not practical. Therefore, Alvarez’s and
Shockley’s absence from the Genetic Studies of Genius sample does not invalidate intelligence testing or Terman’s landmark study.
The relative importance of different factors in the development of human skills has been extensively discussed. Research on expertise indicates that focused
practice may be the sole determinant of skill, while intelligence researchers underline the relative importance of abilities at even the highest level of skill.
There is indeed a large body of research that acknowledges the role of both factors in skill development and retention. It is, however, unknown how intelligence
and practice come together to enable the acquisition and retention of complex skills across the life span. Instead of focusing on the 2 factors, intelligence and
practice, in isolation, here we look at their interplay throughout development. In a longitudinal study that tracked chess players throughout their careers, we
show that both intelligence and practice positively affect the acquisition and retention of chess skill. Importantly, the nonlinear interaction between the 2
factors revealed that more intelligent individuals benefited more from practice. With the same amount of practice, they acquired chess skill more quickly than less
intelligent players, reached a higher peak performance, and arrested decline in older age. Our research demonstrates the futility of scrutinizing the relative
importance of highly intertwined factors in human development.
There exists a moderate correlation between MRI-measured brain size and the general factor of IQ performance
(g), but the question of whether the association reflects a theoretically important causal relationship or spurious confounding remains somewhat open. Previous small studies (n
< 100) looking for the persistence of this correlation within families failed to find a tendency for the sibling with the larger brain to obtain a higher test
score. We studied the within-family relationship between brain volume and intelligence in the much larger sample provided by the Human Connectome Project
(n = 1022) and found a highly statistically-significant correlation (disattenuated ρ = 0.18, p < 0.001). We replicated this result in
the Minnesota Center for Twin and Family Research (n = 2698), finding a highly statistically-significant within-family correlation between head
circumference and intelligence (disattenuated ρ = 0.19, p < 0.001). We also employed novel methods of causal inference relying on summary statistics from genome-wide association studies
(GWAS) of head size (n ≈ 10,000) and measures of cognition (257,000 < n < 767,000). Using
bivariate LD Score regression, we found a
genetic correlation between intracranial volume (ICV) and years of education (EduYears) of 0.41 (p <
0.001). Using the Latent Causal Variable(LCV) method, we found a genetic causality proportion of 0.72 (p < 0.001); thus the genetic correlation arises from an asymmetric pattern, extending to sub-significant loci, of genetic variants associated with
ICV also being associated with EduYears but many genetic variants associated with EduYears not being associated with
ICV. This is the pattern of genetic results expected from a causal effect of brain size on intelligence. These
findings give reason to take up the hypothesis that the dramatic increase in brain volume over the course of human evolution has been the result of natural
selection favoring general intelligence.
Not all neural network architectures are created equal, some perform much better than others for certain tasks. But how important are the weight parameters of a
neural network compared to its architecture? In this work, we question to what extent neural network architectures alone, without learning any weight parameters,
can encode solutions for a given task. We propose a search method for neural network architectures that can already perform a task without any explicit weight
training. To evaluate these networks, we populate the connections with a single shared weight parameter sampled from a uniform random distribution, and measure the
expected performance. We demonstrate that our method can find minimal neural network architectures that can perform several reinforcement learning tasks without weight training. On a supervised learning domain, we find network architectures that achieve much
higher than chance accuracy on MNIST using random weights. Interactive version of this paper athttps://weightagnostic.github.io/
The present register-based study investigated the influence of familial factors on the association of IQ with educational and occupational achievement among
young men in Denmark. The study population comprised all men with at least one full brother where both the individual and his brothers were born from 1950 and
appeared before a draft board in 1968–1984 and 1987–2015 (n = 364,193 individuals). Intelligence was measured by Børge Priens Prøve at age 18. Educational
and occupational achievement were measured by grade point average (GPA) in lower secondary school, time to
receiving social benefits at ages 18–30, and gross income at age 30. The statistical analyses comprised two distinct statistical analyses of the
investigated associations: A conventional cohort analysis and a within-sibship analysis in which the association under investigation was analysed within siblings
while keeping familial factors shared by siblings fixed. The results showed that an appreciable part of the associations of IQ with educational and occupational
achievement could be attributed to familial factors shared by siblings. However, only the within sibling association between IQ and GPA in lower secondary school clearly differed from the association observed in the cohort analysis after covariates had been taken
into account.
The study of human individual differences has matured substantially, in the last decade or so owing, in part, to the notable advances in neuroimaging
techniques. There are three major domains of inquiry within individual differences research: personality, creativity, and intelligence. Each has a discrete,
testable definition (a new definition for intelligence is offered: rapid and accurate problem solving), and each has been associated with distinct brain regions
and interactive networks.
Here, we outline commonalities between these constructs, which appear to conform to two major axes: exploratory behavior and restraint. These axes, in turn,
conform largely to two major brain networks dedicated to novelty generation (ie. default mode network—DMN), and refinement of ideas (ie. cognitive control network—CCN).
Thus, human individual differences represent the expression of adaptive behaviors leading to exploratory and/or restrained action arising from brain structure
and function.
Heritability, the proportion of phenotypic variance explained by genetic factors, can be estimated from pedigree data 1, but such estimates are uninformative with respect to the underlying genetic
architecture. Analyses of data from genome-wide association studies (GWAS) on unrelated individuals have shown that for
human traits and disease, approximately one-third to two-thirds of heritability is captured by common SNPs2–5. It is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular if the causal variants are rare, or other reasons such as over-estimation of heritability from pedigree data. Here we show that pedigree heritability for height and body mass index (BMI) appears to be
fully recovered from whole-genome sequence (WGS) data on 21,620 unrelated individuals of European ancestry. We assigned
47.1 million genetic variants to groups based upon their minor allele frequencies (MAF) andlinkage disequilibrium (LD) with variants nearby, and estimated and partitioned variation
accordingly. The estimated heritability was 0.79 (SE 0.09) for height and 0.40 (SE 0.09) for BMI, consistent
with pedigreeestimates. Low-MAF variants in low LD with neighbouring variants were enriched for heritability, to a greater extent for protein altering variants, consistent with
negative selection thereon. Cumulatively variants in the MAF range of 0.0001 to 0.1 explained 0.54 (SE 0.05) and
0.51 (SE 0.11) of heritability for height and BMI, respectively. Our results imply that the still missing
heritability of complex traits and disease is accounted for by rare variants, in particular those in regions of low LD.
Bifactor and other hierarchical models [in factor analysis] have become central to representing and explaining
observations in psychopathology, health, and other areas of clinical science, as well as in the behavioral sciences more broadly. This prominence comes after a
relatively rapid period of rediscovery, however, and certain features remain poorly understood.
Here, hierarchical models are
compared and contrasted with other models of superordinate structure, with a focus on implications for model comparisons and interpretation. Issues pertaining to
the specification and estimation of bifactor and other hierarchical models are reviewed in exploratory as well as confirmatory modeling scenarios, as are emerging findings about model fit and selection.
Bifactor and other hierarchical models provide a powerful mechanism for parsing shared and unique components of variance,
but care is required in specifying and making inferences about them.
[Keywords: hierarchical model, higher order, bifactor, model equivalence, model complexity]
Figure 1: Hierarchical and related models. (a) Spearman’s (1904a, 1904b) 2-factor model, a precursor to hierarchical and bifactor models. The 2-factor model includes a general factor (G) as well as
systematic specific factors (S) and random error factors (e). As originally formulated, Spearman’s 2-factor model cannot be estimated, but it established the
idea of a superordinate general factor plus subordinate specific factors that account for systematic residual influences not accounted for by the general
factor. (b) The hierarchical or bifactor model, which includes superordinate general factors (G) as well as subordinate specific
factors (S); error factors are not shown. Bifactor models are a subtype of hierarchical model with one superordinate
factor and multiple subordinate factors. The 2-factor model and hierarchical model are examples of top-down models, in that subordinate factors
instantiate residual effects that are unexplained by the superordinate factor.
Although bifactor and other hierarchical models are now commonplace, this was not always so. Their current ubiquity follows a long period of relative neglect
(Reise 2012), having been derived in the early twentieth century (Holzinger & Harman 1938,
Holzinger & Swineford 1937) before being somewhat
overlooked for a number of decades and then being rediscovered more recently. Bifactor models were mistakenly dismissed as equivalent to and redundant with other
superordinate structural models (eg. Adcock 1964, Humphreys 1981, Wherry 1959, Reise 2012, Yung et al 1999); as differences between bifactor
models and other types of superordinate structural models became more recognized (Yung et al 1999), interest in bifactor models reemerged.
…Summary Points:
Bifactor and other hierarchical models represent superordinate structure in terms of orthogonal general and specific factors representing distinct,
non-nested components of shared variance among indicators. This contrasts with higher-order models, which represent
superordinate structure in terms of specific factors that are nested in general factors, and correlated-factors models, which represent superordinate structure
in terms of correlations among subordinate factors.
Higher-order models can be approached as a constrained form of hierarchical models, in which direct relationships between superordinate factors and observed
variables in the hierarchical model are constrained to equal the products of superordinate-subordinate paths and subordinate-observed variable paths.
Multiple exploratory factor analytic approaches to the delineation of hierarchical structure are available, including rank-deficient transformations,
analytic rotations, and targeted rotations. Among other things, these transformations and rotations differ in the number of factors being rotated, the nature of those factors, and how superordinate factor
structures are approximated.
Misspecification or under-specification of confirmatory bifactor and hierarchical models can occur for multiple reasons. Problems with model identification
may occur (1) with specific patterns of homogeneity in estimated or observed covariances, (2) if factors are allowed to correlate in inadmissible ways, or (3) if
covariate paths imply inadmissible correlations. Signs of model misspecification may be evident in anomalous estimates, such as loading estimates near
boundaries, or estimates that are suggestive of other types of models.
Common model fit statistics can overstate the fit of bifactor models due to the tendency of bifactor and other hierarchical
models to overfit to data in general, regardless of plausibility or population structure. Hierarchical models are similar to exploratory factor models in
their expansiveness of fit, and, in general, they are more expansive in fit than other confirmatory models.
Future Issues:
Research is needed to determine how to best account for the flexibility of hierarchical models when comparing models and evaluating model fit, given that the
relative flexibility of hierarchical models can only partly be accounted for by the number of parameters. Approaches based on minimum description length and
related paradigms, such as Bayesian inference with reference priors, are promising in this regard.
More research is needed to clarify the properties of hierarchical structures when they are embedded in longitudinal models and models with covariates. As
with challenges of multicollinearity in regression, parsing
unique general and specific factor components of explanatory paths may be inferentially challenging in the presence of strongly related predictors, covariates,
and outcomes.
More can be learned about the specification and identification of hierarchical models and the relationships between hierarchical models and other types of
models, such as exploratory factor models. Similarities in overfitting patterns between exploratory and hierarchical models, approaches to hierarchical structure
through bifactor rotations, and patterns of anomalous estimates that are sometimes obtained with hierarchical models,
point to important relationships between exploratory and hierarchical models. Further explication of model specification
principles with hierarchical models would also help clarify the appropriate structures to consider when evaluating
models.
Large-scale phylogenetic studies of animal cognition have revealed robust links between absolute brain volume and species differences in executive function.
However, past comparative samples have been composed largely of primates, which are characterized by evolutionarily derived neural scaling rules. Therefore, it is
currently unknown whether positive associations between brain volume and executive function reflect a broad-scale evolutionary phenomenon, or alternatively, a
unique consequence of primate brain evolution. Domestic dogs provide a powerful opportunity for investigating this question due to their close genetic relatedness,
but vast intraspecific variation. Using citizen science data on more than 7000 purebred dogs from 74 breeds, and controlling for genetic relatedness between
breeds, we identify strong relationships between estimated absolute brain weight and breed differences in cognition. Specifically, larger-brained breeds performed
statistically-significantly better on measures of short-term memory and self-control. However, the relationships between estimated brain weight and other cognitive
measures varied widely, supporting domain-specific accounts of cognitive evolution. Our results suggest that evolutionary increases in brain size are positively
associated with taxonomic differences in executive function, even in the absence of primate-like neuroanatomy. These findings also suggest that variation between
dog breeds may present a powerful model for investigating correlated changes in neuroanatomy and cognition among closely related taxa.
The neural substrates of intelligence represent a fundamental but largely uncharted topic in human developmental neuroscience. Prior neuroimaging studies have
identified modest but highly dynamic associations between intelligence and cortical thickness (CT) in childhood and adolescence. In a separate thread of research,
quantitative genetic studies have repeatedly demonstrated that most measures of intelligence are highly heritable, as are many brain regions associated with
intelligence. In the current study, we integrate these 2 streams of prior work by examining the genetic contributions to CT-intelligence relationships using a
genetically informative longitudinal sample of 813 typically developing youth, imaged with high-resolution MRI and
assessed with Wechsler Intelligence Scales (IQ). In addition to replicating the phenotypic association between multimodal association cortex and language
centers with IQ, we find that CT-IQ covariance is nearly entirely genetically mediated. Moreover, shared genetic factors drive the rapidly evolving landscape of
CT-IQ relationships in the developing brain.
How and when education improves cognitive capacity is an issue of profound societal importance. Education and later-life education-related factors, such as
occupational complexity and engagement in cognitive-intellectual activities, are frequently considered indices of cognitive reserve, but whether their effects are
truly causal remains unclear. In this study, after accounting for general cognitive ability (GCA) at an average age of 20
y, additional education, occupational complexity, or engagement in cognitive-intellectual activities accounted for little variance in late midlife cognitive
functioning in men age 56–66 (n= 1009). Age 20 GCA accounted for 40% of variance in the same measure in
late midlife and approximately 10% of variance in each of seven cognitive domains. The other factors each accounted for <1% of the variance in cognitive
outcomes. The impact of these other factors likely reflects reverse causation—namely, downstream effects of early adult GCA.Supporting that idea, age 20 GCA, but not education, was associated with late
midlife cortical surface area (n= 367). In our view, the most parsimonious explanation of our results, a meta-analysis of the impact of education, and
epidemiologic studies of the Flynn effect is that intellectual capacity gains due to education plateau in late adolescence/early adulthood. Longitudinal studies
with multiple cognitive assessments before completion of education would be needed to confirm this speculation. If cognitive gains reach an asymptote by early
adulthood, then strengthening cognitive reserve and reducing later-life cognitive decline and dementia risk may really begin with improving educational quality and
access in childhood and adolescence.
2019-genc.pdf: “The Neural
Architecture of General Knowledge”, Erhan Genç, Christoph Fraenz,
Caroline Schlüter, Patrick Friedrich, Manuel C. Voelkle, Rüdiger Hossiep, et al (2019-01-01):
Objective: This study examined the relation between polygenic scores (PGSs) for 5 major psychiatric
disorders and 2 cognitive traits with brain magnetic resonance imaging morphologic measurements in a large population-based sample of children. In addition,
this study tested for differences in brain morphology-mediated associations between PGSs for psychiatric disorders and
PGSs for related behavioral phenotypes.
Method: Participants included 1,139 children from the Generation R Study assessed at 10 years of age with genotype and neuroimaging data
available. PGSs were calculated forschizophrenia, bipolar disorder, major depression disorder, attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, intelligence, and educational attainment using results from the most recent genome-wide
association studies. Image processing was performed using FreeSurfer to extract cortical and subcortical brain volumes.
Results: Greater genetic susceptibility for ADHD was associated with smaller caudate
volume (strongest prior = 0.01: β = −0.07, p = 0.006). In boys, mediation analysis estimates showed that 11% of the association between the
PGS forADHDand the PGS
attention problems was mediated by differences in caudate volume (n = 535), whereas mediation was not statistically-significant in girls or the
entire sample. PGSs for educational attainment and intelligence showed positive associations with total brain
volume (strongest prior = 0.5: β = 0.14, p = 7.12 × 10−8; and β = 0.12, p = 6.87 × 10−7, respectively).
Conclusion: The present findings indicate that the neurobiological manifestation of polygenic susceptibility for ADHD, educational attainment, and intelligence involve early morphologic differences in caudate and total brain volumes
in childhood. Furthermore, the genetic risk for ADHD might influence attention problems through the caudate
nucleus in boys.
Using newly available polygenic scores for educational attainment and cognitive ability, this paper investigates the possible presence and causes of a negative
association between IQ and fertility in the Wisconsin Longitudinal Study sample, an issue that Retherford and Sewell first addressed 30 years ago. The effect of
the polygenic score on the sample’s reproductive characteristics was indirect: a latent cognitive ability measure, comprised of both educational attainment and IQ,
wholly mediated the relationship. Age at first birth mediated the negative effect of cognitive ability on sample fertility, which had a direct (positive) effect on
the number of grandchildren. statistically-significantly greater impacts of cognitive ability on the sample’s fertility characteristics were found among the female
subsample. This indicates that, in this sample, having a genetic disposition toward higher cognitive ability does not directly reduce number of offspring; instead,
higher cognitive ability is a risk factor for prolonging reproductive debut, which, especially for women, reduces the fertility window and, thus, the number of
children and grandchildren that can be produced. By estimating the effect of the sample’s reproductive characteristics on the strength of polygenic selection, it
was found that the genetic variance
component of IQ should be declining at a rate between −0.208 (95% CI [−0.020, −0.383]) and −0.424 (95% CI [−0.041, −0.766]) points per decade, depending
on whether GCTA-GREML or classical behavior genetic estimates of IQ heritability are used to correct for ‘missing’
heritability.
Human intelligence can be broadly subdivided into fluid (gf) and crystallized (gc) intelligence, each tapping into distinct cognitive
abilities. Although neuroanatomical correlates of intelligence have been previously studied, differential contribution of cortical morphologies to gf and
gc has not been fully delineated. Here, we tried to disentangle the contribution of cortical thickness, cortical surface area, and cortical gyrification
to gf and gc in a large sample of healthy young subjects (n = 740, Human Connectome Project) with high-resolution MRIs, followed by replication in a separate data set with distinct cognitive measures indexing gf and gc. We found
that while gyrification in distributed cortical regions had positive association with both gf and gc, surface area and thickness showed more
regional associations. Specifically, higher performance in gf was associated with cortical expansion in regions related to working memory, attention, and
visuo-spatial processing, while gc was associated with thinner cortex as well as higher cortical surface area in language-related networks. We discuss the
results in a framework where “horizontal” cortical expansion enables higher resource allocation, computational capacity, and functional specificity relevant to
gf and gc, while lower cortical thickness possibly reflects cortical pruning facilitating “vertical” intracolumnar efficiency in knowledge-based
tasks relevant mostly to gc.
MacCann et al 2014 explored various unidimensional, oblique, hierarchical and bifactor models to suggest that ability EI can represent a distinct set of cognitive abilities that can be placed within existing intelligence
frameworks.
The current study presents a conceptual replication of these analyses from data collected using alternative (non-proprietary) measures. Using a data set of 830
individuals, the current study provides further evidence to suggest ability EI best represents a hierarchical construct formed of emotion perception, understanding
and management factors, structured as a second stratum factor within broader models of cognitive ability.
A positive relationship between brain volume and intelligence has been suspected since the 19th century, and empirical studies seem to support this
hypothesis. However, this claim is controversial because of concerns about publication bias and the lack of systematic control for critical confounding factors (eg. height, population structure). We conducted a preregistered study of the
relationship between brain volume and cognitive performance using a new sample of adults from the United Kingdom that is about 70% larger than the combined samples
of all previous investigations on this subject (N = 13,608). Our analyses systematically controlled for sex, age, height, socioeconomic status, and
population structure, and our analyses were free of publication bias. We found a robust association between total brain volume and fluid intelligence (r =
0.19), which is consistent with previous findings in the literature after controlling for measurement quality of intelligence in our data. We also found a positive
relationship between total brain volume and educational attainment (r = 0.12). These relationships were mainly driven by gray matter (rather than white
matter or fluid volume), and effect sizes were similar for both sexes and across age groups.
[Keywords: intelligence, educational attainment, brain volume, preregistered analysis, UK Biobank, open
data, open materials, preregistered]
The relationship between general cognitive ability and reproduction is reviewed.
There is an inverse relation between cognitive ability and number of children.
The effect is stronger among females than males.
The effect appears to be increasing in strength over time.
Notable limitations of the current literature are reviewed.
The purpose of this study is to conduct a systematic review of the literature on the relationship between general cognitive ability and fertility among modern
humans. Our goals were to (a) evaluate the state of the extant literature, and (b) provide a quantitative summary of effect sizes to the extent possible (given the
limitations of the literature). A thorough search identified 17 unique datasets that passed the inclusion criteria. Using a Random Effects Model to
evaluate the data, the overall weighted effect was r = −0.11, although the data also indicated a sex effect (stronger correlations among females than
males), and a race effect (stronger correlations among Black and Hispanic populations compared to Whites). Importantly, the data suggest the correlation has been
increasing in strength throughout the 20th century (and early 21st). Finally, we discovered several notable limitations of the extant
literature; limitations that currently prohibit a psychometric meta-analysis. We discuss these issues with emphasis on improving future primary studies to allow
for more effective meta-analytic investigations.
In 19 (sub)samples from seven countries (United States, Austria, Germany, Costa Rica, Ecuador, Vietnam, Brazil), we analyzed the impact of parental
education compared with wealth on the cognitive ability of children (aged 4–22 years, total n = 15,297). The background of their families ranged from poor
indigenous remote villagers to academic families in developed countries, including parents of the gifted. Children’s cognitive ability was measured with mental
speed tests, Culture Fair Intelligence Test (CFT), the Raven’s, WienerEntwicklungstest (WET), Cognitive Abilities Test (CogAT), Piagetian tasks, Armed Forces Qualification Test
(AFQT), Progress in International Reading Literacy Study (PIRLS),
Trends in InternationalMathematics and Science Study (TIMSS), and Programme for InternationalStudent Assessment (PISA). Parental wealth was estimated by asking for income, indirectly by self-assessment of
relative wealth, and by evaluating assets. The mean direct effect of parental education was greater than wealth. In path analyses, parental education
(βEd) also showed a stronger impact on children’s intelligence than familial economic status (βIn, total effect averages:
βEd = .30–.45, βIn = .09–.12; N = 15,125, k = 18). The effects on mental speed were smaller than for
crystallized intelligence, but still larger for parental education than familial economic status (βEd → MS = .25,
βIn → MS = .00, βEd → CI = .36, βIn → CI = .09; N = 394,
k = 3). Additional factors affecting children’s cognitive ability are number of books, marital status, educational behavior of parents, and behavior of
children. If added, a general background (ethnicity, migration) factor shows strong effects (βBg = .30–.36). These findings are discussed in
terms of environmental versus hidden genetic effects.
[Keywords: cognitive competence, intelligence development, fluid and crystallized intelligence, SES,
number of books, marital status, smoking]
While deep reinforcement learning(DRL) has led to numerous successes in
recent years, reproducing these successes can be extremely challenging. One reproducibility challenge particularly relevant to DRL is nondeterminism in the training process, which can substantially affect the results. Motivated by this challenge, we study the
positive impacts of deterministic implementations in eliminating nondeterminism in training. To do so, we consider the particular case of the deep Q-learning
algorithm, for which we produce a deterministic implementation by identifying and controlling all sources of nondeterminism in the training process. One by one, we
then allow individual sources of nondeterminism to affect our otherwise deterministic implementation, and measure the impact of each source on the variance in
performance. We find that individual sources of nondeterminism can substantially impact the performance of agent, illustrating the benefits of deterministic
implementations. In addition, we also discuss the important role of deterministic implementations in achieving exact replicability of results.
Here we conducted a large-scale genetic association analysis of educational attainment in a sample of approximately 1.1 million individuals and identify 1,271
independent genome-wide-significant SNPs. For the SNPs taken together, we found
evidence of heterogeneouseffects across environments. The SNPs implicate genes involved in
brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent
genome-wide-significant SNPs and estimate aSNP heritability
of around 0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related
cognitive phenotypes generates polygenic scores that explain 11–13% of the variance in educational attainment and 7–10% of the variance in cognitive performance.
This prediction accuracy substantially increases the utility of polygenic scores as tools in research.
The study aim was to explore the relationship between a developmental assessment at preschool age and an intelligence quotient (IQ) assessment at school age.
One hundred sixty-two children were assessed at 2.5 years with the Bayley Scales of Infant and Toddler Development—Third Edition (Bayley-III) and then at 6.5 years with the Wechsler Intelligence Scale for Children—Fourth Edition (WISC-IV). The Bayley-III Cognitive Index score was the Bayley entitythat showed the
highest correlation with WISC-IV Full-Scale IQ (FSIQ; r = .41). There was a
statistically-significant difference between the individual WISC-IVFSIQ and the
Bayley-III Cognitive Index scores. Analyses showed an average difference of −4 units and 95% limits of agreement of
−18.5 to 26.4 units. A multivariate model identified the Bayley-III Cognitive Index score as the most important predictor
forFSIQ and General Ability Index (GAI), respectively, in comparison
withdemographic factors. The model explained 24% of the total FSIQvariation and 26% of the
GAI variation. It was concluded that theBayley-III measurement was an
insufficient predictor of later IQ.
Academically selective high schools are a polarizing topic in education policy, despite only having a small presence in some Australian states. They appear
successful. The schools regularly top annual school rankings of university entrance results, but this is perhaps unsurprising given that their students are
admitted based on their performances on an entrance exam.
This thesis asks whether selective high schools improve their students’ university entrance results beyond what they would have achieved otherwise. The main
chapter is a case study from an anonymized Australian state that follows high-achievement students through high school. The key challenge is finding a group of
non-selective students comparable to those who attend selective schools. For additional background, the thesis explored the following themes: the historical
development of selective high schools, the premise that the schools cater to gifted and talented students, and the high levels of demand for the schools within
current trends in educational policy.
The thesis provides the first estimates of the selective school effect (roughly contemporaneous with Zen 2016) from matching and
regression discontinuity approaches in the Australian context,
which are improved statistical methods compared with that of previous research (eg. regression analyses from Lu & Rickard 2014).
The estimates point to small positive effects at best on university entrance results from attending the selective schools.
Overall, the small selective school effect appears to reflect the high levels of educational aspiration of both selective students as well as applicants who
attended other schools. Both groups of students appear to be among the most driven and motivated, being disproportionately from immigrant and socio-economically
advantaged backgrounds and having implicitly signaled an aspirational intent by applying to the schools.
Lastly, the thesis expands on one aspect of the selective schools, whereby many of their students experience a decrease in within-school achievement ranks from
attending a school with high-achievement peers. In a more general context, the thesis assesses the effect from changes in local ranks on later achievement for
students who transitioned from primary to secondary school. The results indicate that perceived increases in local rank have a negative effect on standardized test
scores, suggesting that students reduced their allocation of effort in response to random increases in rank.
The new empirical evidence from the thesis supports the view that selective schools represent a positive achievement ideal for their students. Recent public
policy discourse on the selective schools has included calls for expansion of the system to the primary school level in one state, and criticisms of a
hyper-competitive culture at the schools, including suggestions of unfair entry due to excessive tutoring on the part of applicants. The research positively
contributes to the discourse by providing historical context, identifying the relevant issues and articulating the potential indirect consequences of these
policies.
Intelligence, or general cognitive function, is phenotypically and genetically correlated with many traits, including a wide range of physical, and mental
health variables. Education is strongly genetically correlated with intelligence (rg = 0.70). We used these findings as foundations for our use
of a novel approach—multi-trait analysis of genome-wide association studies (MTAG;Turley et al 2017)—to combine two large
genome-wide association studies (GWASs) of education and intelligence, increasing statistical power and resulting in the largest GWAS of intelligence yet reported. Our study
had four goals: first, to facilitate the discovery of new genetic loci associated with intelligence; second, to add to our understanding of the biology of
intelligence differences; third, to examine whether combining genetically correlated traits in this way produces results consistent with the primary phenotype of
intelligence; and, finally, to test how well this new meta-analytic data sample on intelligence predicts phenotypic intelligence in an independent sample.
By combining datasets using MTAG, our functional sample size increased from 199,242 participants to 248,482. We
found 187 independent loci associated with intelligence, implicating 538 genes, using both SNP-based and gene-based
GWAS. We found evidence that neurogenesis and myelination—as well as genes expressed in the synapse, and those involved
in the regulation of the nervous system—may explain some of the biological differences in intelligence.
The results of our combined analysis demonstrated the same pattern of genetic correlations as those from previous GWASs of intelligence, providing support for the meta-analysis of these genetically-related phenotypes.
People who score higher on intelligence tests tend to have larger brains. Twin studies suggest the same genetic factors influence both brain size and
intelligence. This has led to the hypothesis that genetics influence intelligence partly by contributing to the development of larger brains. We tested this
hypothesis using four large imaging genetics studies (combined n = 7965) with polygenic scores derived from a genome-wide association study
(GWAS) of educational attainment, a correlate of intelligence. We conducted meta-analysis to test associations among
participants’ genetics, total brain volume (ie. brain size), and cognitive test performance. Consistent with previous findings, participants with higher polygenic
scores achieved higher scores on cognitive tests, as did participants with larger brains. Participants with higher polygenic scores also had larger brains. We
found some evidence that brain size partly mediated associations between participants’ education polygenic scores and their cognitive test performance. Effect
sizes were larger in the population-based samples than in the convenience-based samples. Recruitment and retention of population-representative samples should be a
priority for neuroscience research. Findings suggest promise for studies integrating GWAS discoveries with brain imaging
to understand neurobiology linking genetics with cognitive performance.
University success, which includes enrolment in and achievement at university, as well as quality of the university, have all been linked to later earnings,
health and wellbeing. However, little is known about the causes and correlates of differences in university-level outcomes. Capitalizing on both quantitative and
molecular genetic data, we perform the first genetically sensitive investigation of university success with a UK-representative sample of 3,000 genotyped
individuals and 3,000 twin pairs. Twin analyses indicate substantial additive genetic influence on university entrance exam achievement (57%), university enrolment
(51%), university quality (57%) and university achievement (46%). We find that environmental effects tend to be non-shared, although the shared environment is
substantial for university enrolment. Furthermore, using multivariate twin analysis, we show moderate to high genetic
correlations between university success variables (0.27–0.76). Analyses using DNA alone also support
genetic influence on university success. Indeed, a genome-wide polygenic score, derived from a 2016 genome-wide association study of years of education, predicts
up to 5% of the variance in each university success variable. These findings suggest young adults select and modify their educational experiences in part based on
their genetic propensities and highlight the potential for DNA-based predictions of real-world outcomes, which
will continue to increase in predictive power.
Lewis Terman is widely seen as the “father of gifted education”, yet his work is
controversial. Terman’s “mixed legacy” includes the pioneering work in the creation of intelligence tests, the first large-scale longitudinal study, and the earliest discussions of gifted identification,
curriculum, ability grouping, acceleration, and more. However, since the 1950s, Terman has been viewed as a sloppy thinker at best and a racist, sexist, and/or
classist at worst.
This article explores the most common criticisms of Terman’s legacy: an overemphasis on IQ, support for the meritocracy, and emphasizing genetic explanations
for the origin of intelligence differences over environmental ones. Each of these criticisms is justified to some extent by the historical record, and each is
relevant today. Frequently overlooked, however, is Terman’s willingness to form a strong opinion based on weak data.
The article concludes with a discussion of the important lessons that Terman’s work has for modern educators and psychologists, including his contributions to
psychometrics and gifted education, his willingness to modify his opinions in the face of new evidence, and his inventiveness and inclination to experiment.
Terman’s legacy is complex, but one that provides insights that can enrich modern researchers and practitioners in these areas.
Finnish elite high school students enrol in university and so-called elite fields of study more often than Finnish high school students on average. However,
those who attend elite high schools are also higher-achieving in terms of baseline grade point average (GPA) from
comprehensive school. This selection bias must be taken into account in studying the causal effects of elite high schools.
This study focuses on 5 elite high schools in the Helsinki region and aims to solve the problem of selection bias by using a regression discontinuity
design (RDD). In our case RDD exploits the entrance thresholds of elite high schools
as a rule which assigns applicants near the threshold into treatment and control groups. By comparing the outcomes (eg. the probability of enrolment in a
university) of these groups we can estimate the causal effects of an elite high school offer on various educational outcomes, such as university enrolment.
We find that crossing the threshold of an elite high school leads to a higher-achieving peer group in terms of baseline GPA. However, the elite high school offer does not have a statistically-significant effect on the probability of enrolment in a
university or on the probability of enrolment in an elite field of study. The only exception is Etelä-Tapiola high school, which has a positive effect on the
probability of enrolment in a university.
[Keywords: education, regression discontinuity design, peer effects, school choice]
Intelligence—the ability to learn, reason and solve problems—is at the forefront of behavioural genetic research. Intelligence is highly heritable and predicts
important educational, occupational and health outcomes better than any other trait. Recent genome-wide association studies have successfully identified inherited
genome sequence differences that account for 20% of the 50% heritability of intelligence. These findings open new avenues for research into the causes and
consequences of intelligence using genome-wide polygenic scores that aggregate the effects of thousands of genetic variants.
It is well established that religiosity correlates inversely with intelligence. A prominent hypothesis states that this correlation reflects behavioral biases
toward intuitive problem solving, which causes errors when intuition conflicts with reasoning.
We tested predictions of this hypothesis by analyzing data from 2 large-scale Internet-cohort studies (combined n = 63,235).
We report that atheists surpass religious individuals in terms of reasoning but not working-memory performance. The
religiosity effect is robust across sociodemographic factors including age, education and country of origin. It varies statistically-significantly across religions
and this co-occurs with substantial cross-group differences in religious dogmatism. Critically, the religiosity effect is strongest for tasks that explicitly
manipulate conflict; more specifically, atheists outperform the most dogmatic religious group by a substantial margin (0.6 standard deviations) during a color-word
conflict task but not during a challenging matrix-reasoning task.
These results support the hypothesis that behavioral biases rather than impaired general intelligence underlie the religiosity effect.
When the fungus infects a carpenter ant, it grows through the insect’s body, draining it of nutrients and hijacking its mind. Over the course of a week, it
compels the ant to leave the safety of its nest and ascend a nearby plant stem. It stops the ant at a height of 25 centimeters—a zone with precisely the right
temperature and humidity for the fungus to grow. It forces the ant to permanently lock its mandibles around a leaf. Eventually, it sends a long stalk through the
ant’s head, growing into a bulbous capsule full of spores. And because the ant typically climbs a leaf that overhangs its colony’s foraging trails, the fungal
spores rain down onto its sisters below, zombifying them in turn.
…It’s also an obsession of one David Hughes, an entomologist at Pennsylvania State University, who has been studying it for years. He wants to know exactly how
this puppet master controls its puppets—and
his latest experiments suggest that it’s even more ghoulish than it first appears.
…When the fungus first enters its host, it exists as single cells that float around the ant’s bloodstream, budding off new copies of themselves. But at some
point, as Fredericksen’s images show, these single cells start working together. They connect to each other by building short tubes, of a kind that have only ever
been seen before in fungi that infects plants. Hooked up in this way, they can communicate and exchange nutrients. They can also start invading the ant’s muscles,
either by penetrating the muscle cells themselves or growing into the spaces between them. The result is what you can see in this video: a red muscle fiber,
encircled and drained by a network of interconnected yellow fungal cells. This is something unique to Ophiocordyceps. Hughes’s team found that another parasitic
fungus, which fatally infects ants but doesn’t manipulate their minds, also spreads into muscles but doesn’t form tubes between individual cells, and doesn’t wire
itself into large networks.
Whenever Hughes or anyone else discusses the zombie-ant fungus, they always talk about it as a single entity, which corrupts and subverts a host. But you could
also think of the fungus as a colony, much like the ants it targets. Individual microscopic cells begin life alone but eventually come to cooperate, fusing into a
superorganism. Together, these brainless cells can commandeer the brain of a much larger creature. But surprisingly, they can do that without ever physically
touching the brain itself. Hughes’s team found that fungal cells infiltrate the ant’s entire body, including its head, but they leave its brain untouched…“But
manipulation of ants by Ophiocordyceps is so exquisitely precise that it is perhaps surprising that the fungus doesn’t invade the brain of its host”,
Weinersmith says.
Analysis of Digit span and Corsi-block span data from
1754 independent samples (n = 139,677), covering a period of 43 years
Verbal and visuospatial short-term memory (STM) were positively correlated with year of publication.
Verbal and visuospatial working memory (WM) were negatively correlated with year of publication.
The Flynn effect has been investigated extensively for IQ, but few attempts have been made to study it in relation to working memory (WM). Based on the findings
from a cross-temporal meta-analysis using 1754 independent samples (n = 139,677), the Flynn effect was observed across a 43-year period, with changes here
expressed in terms of correlations (coefficients) between year of publication and mean memory test scores. Specifically, the Flynn effect was found for forward
digit span (r = 0.12, p < 0.01) and forward Corsi block span (r = 0.10, p < 0.01).
Moreover, an anti-Flynn effect was found for backward digit span (r = −0.06, p < 0.01) and for backward
Corsi block span (r = −0.17, p < 0.01). Overall, the results support co-occurrence theories that predict simultaneous secular gains in
specialized abilities and declines in g. The causes of the differential trajectories are further discussed.
[Keywords: Flynn effect, Short-term memory, Working memory, Forward and backward digit span, Forward and
backward Corsi block span, Cross-temporal meta-analysis]
Pedigree-based analyses of intelligence have reported that genetic differences account for 50–80% of the phenotypic variation. For personality traits these
effects are smaller, with 34–48% of the variance being explained by genetic differences. However, molecular genetic studies using unrelated individuals typically
report a heritability estimate of around 30% for intelligence and between 0% and 15% for personality variables. Pedigree-based estimates and molecular genetic estimates may differ because current genotyping platforms are poor at tagging causal
variants, variants with low minor allele frequency, copy number variants, and structural variants. Using ~20 000 individuals in the Generation Scotland family
cohort genotyped for ~700 000 single nucleotide polymorphisms (SNPs), we exploit the high levels of linkage disequilibrium (LD) found in members of the same family to quantify the total effect of
genetic variants that are not tagged in GWASs of unrelated individuals. In our models, genetic variants in low
LDwith genotyped SNPs explain over half of the genetic variance in
intelligence, education, and neuroticism. By capturing these additional genetic effects our models closely approximate the heritability estimates from twin studies
for intelligence and education, but not for neuroticism and extraversion. We then replicated our finding using imputed molecular genetic data from unrelated
individuals to show that ~50% of differences in intelligence, and ~40% of the differences in education, can be explained by genetic effects when a larger
number of rare SNPs are included. From an evolutionary genetic perspective, a substantial contribution of rare genetic
variants to individual differences in intelligence and education is consistent with mutation-selection balance.
2017-bo.pdf: “Who Becomes A
Politician?”, Ernesto Dal Bó, Frederico Finan, Olle Folke, Torsten Persson, Johanna Rickne (2017-06-01):
Can a democracy attract competent leaders, while attaining broad representation? Economic models suggest that free-riding incentives and lower opportunity costs
give the less competent a comparative advantage at entering political life. Moreover, if elites have more human capital, selecting on competence may lead to uneven
representation. This article examines patterns of political selection among the universe of municipal politicians and national legislators in Sweden, using
extraordinarily rich data on competence traits and social background for the entire population.
We document 4 new facts that together characterize an “inclusive meritocracy.” First, politicians are on average statistically-significantly smarter and better
leaders than the population they represent. Second, this positive selection is present even when conditioning on family (and hence social) background, suggesting
that individual competence is key for selection. Third, the representation of social background, whether measured by parental earnings or occupational social
class, is remarkably even. Fourth, there is at best a weak trade-off in selection between competence and social representation, mainly due to strong positive
selection of politicians of low (parental) socioeconomic status. A broad implication of these facts is that it is possible for democracy to generate competent and
socially representative leadership.
Intelligence is associated with important economic and health-related life outcomes1. Despite intelligence having substantial
heritability2 (0.54) and a confirmed polygenic nature, initial genetic studies were mostly underpowered3,4,5. Here we report a meta-analysis
for intelligence of 78,308 individuals. We identify 336 associated SNPs (METALp < 5 × 10−8) in 18 genomic loci, of which 15 are new. Around half of the SNPs are located inside
a gene, implicating 22 genes, of which 11 are new findings. Gene-based analyses identified an additional 30 genes (MAGMAp < 2.73 × 10−6), of which all but one had not been implicated previously. We show that the identified
genes are predominantly expressed in brain tissue, and pathway analysis indicates the involvement of genes regulating cell development (MAGMA competitivep = 3.5 × 10−6). Despite the well-known difference in twin-based heritability2 for
intelligence in childhood (0.45) and adulthood (0.80), we show substantial genetic correlation (rg =
0.89, LD score regression p = 5.4 × 10−29). These findings provide new insight into the genetic
architecture of intelligence.
The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide
association study (GWAS) methods. In an attempt toovercome these barriers, the current study utilized
GWAS meta-analysis to examine the association of common genetic variation (~8M single-nucleotide polymorphisms
(SNP) with minor allele frequency ⩾1%) to general cognitive function in a sample of 35 298 healthy
individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we
utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant
neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNPloci (top SNPs: rs76114856 inthe CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with
cognitive performance at the genome-wide statistical-significance level (p<5 × 10−8). Gene-based analysis identified an additional three
Bonferroni-corrected statistically-significant loci at chromosomes 17q21.31, 17p13.1 and 1p13.3. Altogether, common variation across the genome resulted in a
conservatively estimated SNP heritability of 21.5% (s.e. = 0.01%) for general cognitive function.
Integration with prior GWAS of cognitive performance and educational attainment yielded several additional
statistically-significant loci. Finally, we found robust polygenic correlations between cognitive performance and educational attainment, several psychiatric
disorders, birth length/weight and smoking behavior, as well as a novel genetic association to the personality trait of Openness. These data provide new insight
into the genetics of neurocognitive function with relevance to understanding the pathophysiology of neuropsychiatric illness.
Individually administered intelligence measures are commonly used in diagnostic work, but there is a continuing need for research investigating possible test
bias among these measures. One current intelligence measure, the Differential Ability Scales, Second Edition (DAS-II), is
a test with growing popularity. The issue of test bias,however, has not been thoroughly investigated with the DAS-II. Thecurrent study investigated whether the DAS-II demonstrates systematic
construct bias when used with children from three racial and ethnic groups—African American, Asian, and Hispanic—when compared to non-Hispanic Caucasian children.
Multi-group confirmatory factor analyses with data from the DAS-II standardization sample were used to assess
whether the constructs and measurement of constructs were invariant across groups. Results indicate cross-group internal structure validity in the
DAS-II, and thus a lack of construct bias. Minor differences were found, but these differences do not affect the
calculation of composite scores on the DAS-II and thus would not result in unfair scoring for the groups involved.
Results of this study support the appropriateness of the DAS-II for clinical use with these racial and ethnic
groups.
G-factor models such as the bifactor model and the hierarchical G-factor model are increasingly applied in psychology. Many applications of
these models have produced anomalous and unexpected results that are often not in line with the theoretical assumptions on which these applications are based.
Examples of such anomalous results are vanishing specific factors and irregular loading patterns.
In this article, the authors show that from the perspective of stochastic measurement theory anomalous results have to be expected when G-factor models
are applied to a single-level (rather than a 2-level) sampling process. The authors argue that the application of the bifactor model and related models require a
2-level sampling process that is usually not present in empirical studies.
We demonstrate how alternative models with a G-factor and specific factors can be derived that are more well-defined for the actual single-level
sampling design that underlies most empirical studies. It is shown in detail how 2 alternative models, the bifactor-(S − 1) model and the
bifactor-(S·I − 1) model, can be defined. The properties of these models are described and illustrated with an
empirical example.
Finally, further alternatives for analyzing multidimensional models are discussed.
Higher order cognition is related to baseline pupil size.
Baseline pupil size is uniquely related to fluid intelligence.
Implications for resting-state brain organization and locus coeruleus
function.
Pupil dilations of the eye are known to correspond to central cognitive processes. However, the relationship between pupil size and individual differences in
cognitive ability is not as well studied. A peculiar finding that has cropped up in this research is that those high on cognitive ability have a larger pupil size,
even during a passive baseline condition. Yet these findings were incidental and lacked a clear explanation. Therefore, in the present series of studies we
systematically investigated whether pupil size during a passive baseline is associated with individual differences in working memory capacity and fluid
intelligence.
Across 3 studies we consistently found that baseline pupil size is, in fact, related to cognitive ability. We showed that this relationship could not be
explained by differences in mental effort, and that the effect of working memory capacity and fluid intelligence on pupil size persisted even after 23 sessions and
taking into account the effect of novelty or familiarity with the environment. We also accounted for potential confounding
variables such as; age, ethnicity, and drug substances. Lastly, we found that it is fluid intelligence, more so than working memory capacity, which is related to
baseline pupil size.
In order to provide an explanation and suggestions for future research, we also consider our findings in the context of the underlying neural mechanisms
involved.
Selective high schools in the Australian state of New South Wales (NSW) provide an opportunity for students to attend
a public school with substantially higher-achieving peers—the average successful applicant scores more than 2 standard deviations higher on baseline
numeracy tests than the state average. Competition for entrance into these schools is fierce, with general public opinion attributing the superlative academic
success of selective school students at least in part to the selective school environment.
Much recent attention has been paid to credible evaluations of similar selective programs in other jurisdictions. Studies by Abdulkadiroğlu et al 2014 and Dobbie & Fryer 2014 in Boston, MA and New York City, NY find little-to-no
statistically-significant effect of attending selective high schools on student achievement.
In this paper, I employ fuzzy regression discontinuitydesigns on 18 NSW selective schools with varying gradations of selectivity to estimate causal effects of selective
school attendance on performance in high-stakes university entrance assessments and participation rates in advanced coursework. This is the first such study
of selective schools in NSW, which is home to the oldest and most extensive selective school system in Australia, using
a newly matched dataset encompassing the school careers of three state-wide cohorts of selective school applicants.
I find that receiving an offer to attend a selective school has only scattered and mostly insignificant impacts on overall student achievement and participation
in advanced coursework. I do find suggestive evidence that selective schools benefit low socioeconomic status students, but that such students are typically
underrepresented in selective schools, which has implications for Gifted and Talented education policy.
The concept of learning style is immensely popular despite the lack of evidence showing that learning style influences performance. This study tested the
hypothesis that the popularity of learning style is maintained because it is associated with subjective aspects of learning, such as judgements of learning
(JOLs). Preference for verbal and visual information was assessed using the revised Verbalizer-Visualizer
Questionnaire (VVQ). Then, participants studieda list of word pairs and a list of picture pairs, making
JOLs (immediate, delayed, and global) while studying each list. Learning was tested by cued recall. The results
showed that higher VVQverbalizer scores were associated with higher immediate JOLs forwords, and higher VVQ visualizer scores were associated with higherimmediate JOLs for pictures. There was no association between VVQscores
and recall or JOL accuracy. As predicted, learning style was associated with subjective aspects of learning but not
objective aspects of learning.
Neuroimaging has largely focused on 2 goals: mapping associations between neuroanatomical features and phenotypes and building individual-level prediction
models. This paper presents a complementary analytic strategy called morphometricity that aims to measure the neuroanatomical signatures of
different phenotypes.
Inspired by prior work on [genetic] heritability, we define morphometricity as the proportion of phenotypic variation that can be explained by brain morphology
(eg. as captured by structural brain MRI). In the dawning era of large-scale datasets comprising traits across a
broad phenotypic spectrum, morphometricity will be critical in prioritizing and characterizing behavioral, cognitive, and clinical phenotypes based on their
neuroanatomical signatures. Furthermore, the proposed framework will be important in dissecting the functional, morphological, and molecular underpinnings of
different traits.
…Complex physiological and behavioral traits, including neurological and psychiatric disorders, often associate with distributed anatomical variation. This
paper introduces a global metric, called morphometricity, as a measure of the anatomical signature of different traits. Morphometricity is defined as the
proportion of phenotypic variation that can be explained by macroscopic brain morphology.
We estimate morphometricity via a linear mixed-effects model that uses an anatomical similarity matrix computed based on measurements derived from
structural brain MRI scans. We examined over 3,800 unique MRI scans from 9
large-scale studies to estimate the morphometricity of a range of phenotypes, including clinical diagnoses such as Alzheimer’s disease, and nonclinical traits such
as measures of cognition.
Our results demonstrate that morphometricity can provide novel insights about the neuroanatomical correlates of a diverse set of traits, revealing associations
that might not be detectable through traditional statistical techniques.
IQs of children across 31 provinces of China are correlated with the percentage of Han in the population (r = 0.75).
And with the GDP per capita (r = 0.73)
And with years of education (r = 0.76)
This study reports the associations between the intelligence of children aged 8–10 years across 31 provinces and municipalities of the People’s Republic of
China and their economic and social correlates. It was found that regional IQs were statistically-significantly correlated at the p < 0.001
statistical-significance level with the percentage of Han in the population (r= 0.75), GDP per capita
(r = 0.73), and years of education (r = 0.76). Results of a multiple regression analysis showed that regional IQs were the only
statistically-significant predictor of regional differences in the GDP per capita accounting for 56% of the
variance.
[Keywords: intelligence, China, Chinese provinces and municipalities, per capita income, Han]
Utilizing a newly released cognitive Polygenic Score (PGS) from Wave IV of Add Health (n=
1,886), structural equation models (SEMs)examining the relationship between PGS and fertility (which is approximately 50% complete in the present sample), utilizing measures of verbal IQ and educational
attainment as potential mediators, were estimated. The results of indirect pathway models revealed that verbal IQ mediates the positive relationship between
PGS and educational attainment, and educational attainment in turn mediates the negative relationship between IQ and a
latent fertility measure. The direct path from PGS to fertility was non-significant. The model was robust to
controlling for age, sex and race, furthermore the results of a multi-group SEM revealed no statistically-significant
differences in the estimated path coefficients across sex. These results indicate that those predisposed towards higher IQ by virtue of higher
PGS values are also predisposed towards trading fertility against time spent in education, which contributes to
those with higher PGS values producing fewer offspring.
We documented that intelligence has negative effect on deforestation.
We found that intelligence moderates the effect of democracy on deforestation.
We documented that democracy has inverted u-shaped link with deforestation.
Intelligence offsets negative effect of democracy on deforestation in weak democracies.
This article examines the interconnection between national intelligence, political institutions, and the mismanagement of public resources (deforestation). The
paper examines the reasons for deforestation and investigates the factors accountable for it.
The analysis builds on authors-compiled cross-national dataset on 185 countries over the time period of twenty years, from 1990 to 2010. We find that, first,
nation’s intelligence reduces statistically-significantly the level of deforestation in a state. Moreover, the nations’ IQ seems to play an offsetting role in the
natural resource conservation (forest management) in the countries with weak democratic institutions. The analysis also discovered the presence of the U-shaped
relationship between democracy and deforestation. Intelligence sheds more light on this interconnection and explains the results. Our results are robust to various
sample selection strategies and model specifications.
The main implication from our study is that intelligence not only shapes formal rules and informal regulations such as social trust, norms and traditions but
also it has the ability to reverse the paradoxical process known as “resource curse.” The study contributes to better understanding of reasons of deforestation and
shed light on the debated impact of political regime on forest management.
Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the
variation across individuals1. Here we report the results
of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery
sample1,2 of 101,069 individuals to 293,723 individuals, and a
replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide
statistically-significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment
are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue,
especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural
phenotype that is mostly environmentally determined, a well-poweredGWAS
identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers
of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and
neuropsychiatric diseases.
Individual differences in the mere willingness to think analytically has been shown to predict religious disbelief. Recently, however, it has been argued that
analytic thinkers are not actually less religious; rather, the putative association may be a result of religiosity typically being measured after analytic thinking
(an order effect). In light of this possibility, we report four studies in which a negative correlation between religious belief and performance on analytic
thinking measures is found when religious belief is measured in a separate session. We also performed a meta-analysis on all previously published studies on the
topic along with our four new studies (n = 15,078, k = 31), focusing specifically on the association between performance on the Cognitive
Reflection Test (the most widely used individual difference measure of analytic thinking) and religious belief. This meta-analysis revealed an overall negative
correlation (r) of -.18, 95% CI [-.21, -.16]. Although this correlation is modest, self-identified atheists (n = 133) scored 18.7% higher than
religiously affiliated individuals (n = 597) on a composite measure of analytic thinking administered across our four new studies (d = 0.72). Our
results indicate that the association between analytic thinking and religious disbelief is not caused by a simple order effect. There is good evidence that
atheists and agnostics are more reflective than religious believers.
We identified the perceptual-cognitive skills and player history variables that differentiate players selected or not selected into an elite youth football
(ie. soccer) programme in Australia.
A sample of elite youth male football players (n = 127) completed an adapted participation history questionnaire and video-based assessments of
perceptual-cognitive skills. Following data collection, 22 of these players were offered a full-time scholarship for enrolment at an elite player residential
programme.
Participants selected for the scholarship programme recorded superior performance on the combined perceptual-cognitive skills tests compared to the non-selected
group. There were no statistically-significant between group differences on the player history variables. Stepwise discriminant function analysis identified 4 predictor variables that
resulted in the best categorization of selected and non-selected players (ie. recent match-play performance, region, number of other sports participated,
combined perceptual-cognitive performance). The effectiveness of the discriminant function is reflected by 93.7% of players being correctly classified, with the 4
variables accounting for 57.6% of the variance.
Our discriminating model for selection may provide a greater understanding of the factors that influence elite youth talent selection and identification.
Evolutionary forces that maintain genetic variance in traits can be inferred from their genetic architecture and fitness correlates.
A substantial amount of new data on the genomics and reproductive success associated with personality traits and intelligence has recently become
available.
Intelligence differences seem to have been selected for robustness against mutations.
Human tendencies to select, create and adapt to environments might support the maintenance of personality traits through balancing selection.
Like all human individual differences, personality traits and intelligence are substantially heritable. From an evolutionary perspective, this poses the
question what evolutionary forces maintain their genetic variation. Information about the genetic architecture and associations with evolutionary fitness permit
inferences about these evolutionary forces. As our understanding of the genomics of personality and its associations with reproductive success have grown
considerably in recent years, it is time to revisit this question. While mutations clearly affect the very low end of the intelligence continuum, individual
differences in the normal intelligence range seem to be surprisingly robust against mutations, suggesting that they might have been canalized to withstand such
perturbations. Most personality traits, by contrast, seem to be neither neutral to selection nor under consistent directional or stabilizing selection. Instead
evidence is in line with balancing selection acting on personality traits, probably supported by human tendencies to seek out, construct and adapt to fitting
environments.
Previous research finds that lower cognitive ability predicts greater prejudice. We test two unresolved questions about this association using a heterogeneous
set of target groups and data from a representative sample of the United States (n = 5,914). First, we test “who are the targets of prejudice?” We
replicate prior negative associations between cognitive ability and prejudice for groups who are perceived as liberal, unconventional, and having lower levels of
choice over group membership. We find the opposite (ie. positive associations), however, for groups perceived as conservative, conventional, and having higher
levels of choice over group membership. Second, we test “who shows intergroup bias?” and find that people with both relatively higher and lower levels of cognitive
ability show approximately equal levels of intergroup bias but toward different sets of groups.
Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the
variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational
attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349
individuals from the UK Biobank. We identify 74 genome-wide statistically-significant loci associated with the number of
years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating
gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for
biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a
well-poweredGWAS identifies replicable associated genetic variants that
suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy
phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.
Finding 7. Most measures of the “environment” show substantial genetic influence
Although it might seem a peculiar thing to do, measures of the environment widely used in psychological science—such as parenting, social support, and life
events—can be treated as dependent measures in genetic analyses. If they are truly measures of the environment, they should not show genetic influence. To the
contrary, in 1991, Plomin and Bergeman conducted a review of the first 18 studies in which environmental measures were used as dependent measures in genetically
sensitive designs and found evidence for genetic influence for these measures of the environment. Substantial genetic influence was found for objective measures
such as videotaped observations of parenting as well as self-report measures of parenting, social support, and life events. How can measures of the environment
show genetic influence? The reason appears to be that such measures do not assess the environment independent of the person. As noted earlier, humans select,
modify, and create environments correlated with their genetic behavioral propensities such as personality and psychopathology (McAdams, Gregory, & Eley, 2013). For
example, in studies of twin children, parenting has been found to reflect genetic differences in children’s characteristics such as personality and psychopathology
(Avinun & Knafo, 2014; Klahr & Burt, 2014; Plomin, 1994).
Since 1991, more than 150 articles have been published in which environmental measures were used in genetically sensitive designs; they have shown
consistently that there is substantial genetic influence on environmental measures, extending the findings from family environments to neighborhood, school, and
work environments. Kendler and Baker (2007) conducted a review of 55 independent genetic studies and found an average heritability of 0.27 across 35 diverse
environmental measures (confidence intervals not available). Meta-analyses of parenting, the most frequently studied domain, have shown genetic influence that is
driven by child characteristics (Avinun & Knafo, 2014) as well as by parent characteristics (Klahr & Burt, 2014). Some exceptions have emerged. Not surprisingly,
when life events are separated into uncontrollable events (eg. death of a spouse) and controllable life events (eg. financial problems), the former show
nonsignificant genetic influence. In an example of how all behavioral genetic results can differ in different cultures, Shikishima, Hiraishi, Yamagata,
Neiderhiser, and Ando (2012) compared parenting in Japan and Sweden and found that parenting in Japan showed more genetic influence than in Sweden, consistent with
the view that parenting is more child centered in Japan than in the West.
Researchers have begun to use GCTA to replicate these findings fromtwin studies. For example,
GCTA has been used to show substantial genetic influence on stressful life events (Power et al 2013) and
on variables often used as environmental measures in epidemiological studies such as years of schooling (C. A. Rietveld, Medland, et al 2013). Use of
GCTA can also circumvent a limitation of twin studies of children. Such twin studies are limited to investigating
within-family (twin-specific) experiences, whereas many important environmental factors such as socioeconomic status (SES) are the same for twochildren in a family. However, researchers can use GCTA to
assessgenetic influence on family environments such as SES that differbetween families, not within
families. GCTA has been used to showgenetic influence on family SES
(Trzaskowski et al 2014) and an index of social deprivation (Marioni et al 2014).
Spearman’s Other Hypothesis predicts that the common factor
amongst sensory discrimination measures corresponds to general intelligence (g). The co-occurrence model predicts that low-complexity physiological
information-processing indicators reliably measure g across cohorts, and should therefore decline with time due to genetic changes in the broader
population. As strong relations exist between general sensory discrimination and g, such measures should show evidence of secular declines.
This is tested using N-weighted temporal regression of square-root Total Error Scores (√TES), obtained from 4
Western normative samples published in the 1980s, 1990s and 2000s (combined n = 752) evaluated using the Farnsworth-Munsell 100-Hue colour acuity test (disattenuatedg loading = 0.78).
A statistically-significant temporal β value of 0.37 was found
(controlling for national IQ), suggesting a decline in colour acuity equating to a reduction in g of −3.15 points per decade. Analysis of the subset of
the cohorts aged 20–29 years, in which colour acuity is maximized, reveals a larger secular decline (β = 0.67, n = 199, −5.85 points per decade).
The small number of studies employed in these analyses makes these findings tentative however. Also consistent with a weaker variant of Spearman’s Other Hypothesis
is the finding that 100-Hue acuity-IQ correlations are associated with the Jensen effect. The aggregate vector correlation across 2 studies is 0.63 (n =
932.5, p < 0.05).
…After many decades of neglect, in the 1990s and 2000s a series of papers by Ian Deary revisited what came to be termed Spearman’s Other Hypothesis
(Deary 1994; Deary 2000a, 2000b). The first direct test of the Other Hypothesis was conducted in 2004, when Deary and co-workers collected data on
various sensory discrimination tasks amongst a sample of 62 Scottish secondary school students, along with various measures of IQ. Utilizing structural equations
modelling (SEM) to estimate the
common factor variance amongst the sensory discrimination and the cognitive ability measures, the latent general discrimination and g
factors were found to correlate at 0.92, making them virtually isomorphic—consistent with the prediction of the Other Hypothesis. In a second analysis, Deary,
Bell et al 2004 reanalysed a much larger dataset (899 individuals) for which measures of both cognitive and sensory discrimination ability had been
collected and analysed in a previous publication (Acton & Schroeder 2001). Using the same SEM-based method it was
found thatg correlated with the general discrimination factor at 0.676 for the male and 0.681 for the female cohort, which indicated some
divergence between the 2 common factors, but also demonstrated considerable shared variance, consistent with a weaker form
of the Other Hypothesis
Gender balance and turn-taking were unrelated to group performance.
Social sensitivity had no impact on latent group-IQ.
Individual IQ emerged as the cause of group-IQ.
Group-IQ almost exclusively reflects individual cognition.
What allows groups to behave intelligently? One suggestion is that groups exhibit a collective intelligence accounted for by number of women in the group,
turn-taking and emotional empathizing, with group-IQ being only weakly-linked to individual IQ (Woolley et al 2010).
Here we report tests of this model across 3 studies with 312 people.
Contrary to prediction, individual IQ accounted for around 80% of group-IQ differences. Hypotheses that group-IQ increases with number of women in the group and
with turn-taking were not supported. ‘Reading the mind in the eyes’ (RME) performance was associated with
individual IQ, and, in one study, with group-IQ factor scores. However, a well-fitting structural model combining data from studies 2 and 3 indicated that
RME exerted no influence on the group-IQ latent factor (instead having a modest impact on a single group test).
The experiments instead showed that higher individual IQ enhances group performance such that individual IQ determined 100% of latent group-IQ. Implications for
future work on group-based achievement are examined.
[Keywords: collective intelligence, group IQ, IQ, gender, communication, group psychology, administrative behavior]
Figure 1: Relationship of individual IQ to group-IQ in the combined data from studies 2 & 3.
The philosopher Ludwig Wittgenstein chose as his
prime exemplar of certainty the fact that the skulls of normal people are filled with neural tissue, not sawdust. In 1980 the British pediatrician John Lorber
reported that some normal adults, apparently cured of childhood hydrocephaly, had no more than 5% of the volume of normal brain tissue. While initially
disbelieved, Lorber’s observations have since been independently confirmed by clinicians in France and Brazil. Thus Wittgenstein’s certainty has become uncertain.
Furthermore, the paradox that the human brain’s information content (memory) appears to exceed the storage capacity of even normal-sized brains, requires
resolution. This article is one of a series on disparities between brain size and its assumed information content, as seen in cases of savant syndrome,
microcephaly, and hydrocephaly, and with special reference to the Victorian era views of Conan Doyle, Samuel Butler, and Darwin’s research associate, George
Romanes. The articles argue that, albeit unlikely, the scope of explanations must not exclude extracorporeal information storage.
[Keywords: Female brain, Head size, Information storage capacity, Long-term memory, John Lorber, Neuronal reductionism, Plasticity limits,
Redundancy, Supernatural explanations, Ventricle size]
Correlated vectors and multi-group CFA both confirmed Spearman’s hypothesis.
Bi-factor CFA models are a robust way to examine Spearman’s hypothesis.
Spearman’s hypothesis (SH) is a phrase coined by Arthur Jensen, which posits that
the size of Black-White mean differences across a group of diverse mental tests is a positive function of each test’s loading onto the general intelligence
(g) factor. Initially, a correlated vectors (CV) approach was used to examine SH, where the results typically confirmed that the magnitude of g
loadings were positively correlated with the size of mean group differences in the observed test scores. The CV approach has been heavily criticized by scholars
who have argued that a more precise method for examining SH can be better investigated using a multi-group confirmatory factor analysis (MG-CFA). Studies of SH using
MG-CFA have been much more equivocal, with results not clearly confirming nor disconfirming SH.
In the current study, we argue that a better method for extracting g in both the CV and MG-CFA approaches
is to use a bi-factor model. Because non-g factors extracted from a bi-factor approach are independent of g, the bi-factor model allows for a
robust examination of the influence of g and non-g factors on group differences on mental test scores.
Using co-normed standardization data from the Wechsler Adult Intelligence Scale-Fourth Edition and the Wechsler Memory Scale-Fourth Edition, we examined SH using both CV and
MG-CFA procedures.
We found support for the weak form of SH in both methods, which suggests that both g and non-g factors were involved in the observed mean
score differences between Black and White adults.
Research has shown that genes play an important role in educational achievement. A key question is the extent to which the same genes affect different academic
subjects before and after controlling for general intelligence.
The present study investigated genetic and environmental influences on, and links between, the various subjects of the age-16 UK-wide standardized
GCSE (General
Certificate of Secondary Education) examination results for 12,632 twins.
Using the twin method that compares identical and non-identical twins, we found that all GCSE subjects were
substantially heritable, and that various academic subjects correlated substantially both phenotypically and genetically, even after controlling for
intelligence. Further evidence for pleiotropy in academic achievement was found using a method [GCTA] based directly on DNA from unrelated
individuals.
We conclude that performance differences for all subjects are highly heritable at the end of compulsory education and that many of the same genes affect
different subjects independent of intelligence.
Recent reports of training-induced gains on fluid intelligence tests have fueled an explosion of interest in cognitive training-now a billion-dollar industry.
The interpretation of these results is questionable because score gains can be dominated by factors that play marginal roles in the scores themselves, and because
intelligence gain is not the only possible explanation for the observed control-adjusted far transfer across tasks. Here we present novel evidence that the test
score gains used to measure the efficacy of cognitive training may reflect strategy refinement instead of intelligence gains. A novel scanpath analysis of eye
movement data from 35 participants solving Raven’s Advanced Progressive Matrices on two separate sessions indicated that one-third of the variance of score gains
could be attributed to test-taking strategy alone, as revealed by characteristic changes in eye-fixation patterns. When the strategic
contaminant was partialled out, the residual score gains were no longer significant. These results are compatible with established theories of skill acquisition
suggesting that procedural knowledge tacitly acquired during training can later be utilized at posttest. Our novel method and result both underline a reason to be
wary of purported intelligence gains, but also provide a way forward for testing for them in the future.
Paroxetineis a selective serotonin reuptake inhibitor (SSRI) that is currently available on the market and is suspected of causing congenital malformations in babies born to mothers who
take the drug during the first trimester of pregnancy.
We utilized organismal performance assays(OPAs), a novel toxicity assessment method, to
assess the safety of paroxetine during pregnancy in a rodent model. OPAs utilize genetically diverse wild mice
(Mus musculus) to evaluate competitive performance between experimental and control animals as they compete amongst each other for limited
resources in semi-natural enclosures. Performance measures included reproductive success, male competitive ability and survivorship.
Paroxetine-exposed males weighed 13% less, had 44% fewer offspring, dominated 53% fewer territories and experienced a 2.5-fold increased trend in mortality,
when compared with controls. Paroxetine-exposed females had 65% fewer offspring early in the study, but rebounded at later time points. In cages,
paroxetine-exposed breeders took 2.3× longer to produce their first litter and pups of both sexes experienced reduced weight when compared with controls. Low-dose
paroxetine-induced health declines detected in this study were undetected in preclinical trials with dose 2.5-8× higher than human therapeutic doses.
These data indicate that OPAs detect phenotypic adversity and provide unique information that could useful
towards safety testing during pharmaceutical development.
Design principles and operational modes are explored that underlie the information processing capacity of the human brain.
The hypothesis is put forward that in higher organisms, especially in primates, the complexity of the neural circuitry of the cerebral cortex is the neural
correlate of the brain’s coherence and predictive power, and, thus, a measure of intelligence. It will be argued that with the evolution of the human brain we have
nearly reached the limits of biological intelligence.
[Keywords: biological intelligence, cognition, consciousness, cerebral cortex, primates, information processing, neural networks, cortical
design, human brain evolution]
In this commentary we answer 3 questions that are often posed when debating the usefulness and accuracy of correcting criterion-related validity coefficients
for unreliability: (a) Is 0.52 an inaccurate estimate? (b) Do corrections for criterion unreliability lead us to choose different selection tools? (c) Is too much
variance explained?
[1. Yes; 2. No, because rank-order of tools’ utility is preserved by the corrections; 3. No, because while everything is correlatedr = 0.30 on average, most of those variables are unknowable at hiring time and also
adding up variables ignores diminishing returns/intercorrelations between the predictors, so one will never predict perfectly.]
Conclusion: Based on our review of the evidence, the 0.52 estimate of the interrater reliability of supervisor ratings of job performance is an
appropriate estimate; corrections for unreliability do not appear to change our decisions regarding the choice of one selection tool over another; and most
variables may be more strongly correlated than people expect, making it difficult to demonstrate continued incremental validity in predicting job performance when
adding additional predictors. We agree with LeBreton et al that psychologists need to be careful when applying and interpreting corrections, and we are thankful
that they sponsored a discussion on the topic.
Corrections are critical for both basic science (ie., estimating population parameters) and practice (ie., recognizing artifacts attenuating estimates on which
our work may be evaluated by stakeholders, courts, and other third parties). Ultimately, the appropriate use of corrections depends on the purpose of the project.
If the goal is to explain variation among a sample of incumbents on observed criterion scores, then no corrections need to be made. If the goal is to explain
variation among incumbents on a true score for job performance, then a correction for unreliability is not only desirable but necessary. Finally, if the goal is to
estimate how much variation among applicants is explained by a predictor for a true score on job performance, then corrections for range restriction and unreliability are indispensable. This
goal represents the target validity inference that was included in Binning & Barrett 1989’s figure, but (rather interestingly) is omitted from LeBreton et
al’s reproduction of that figure. We believe that the target validity inference is the most important inference in personnel selection; it provides the critical
link from the observed predictor to the criterion construct (see also Putka & Sackett 2010).
To what extent do intellectually talented adolescents pursue educational and vocational careers that match their intellectual resources?
Career outcomes were compared between groups within different IQ ranges with a focus on comparing those with high IQ (top 10% IQ > 119) to those with average
IQ. Data were analyzed from the longitudinal Swedish IDA study (n = 1,326) with career outcomes measured
in midlife (age 43–47).
To obtain at least a master’s degree was almost 13× more common for those of high IQ than for those of average IQ. Still the proportion of high-IQ adolescents
who did this was not high (13% of females, 34% of males) and as much as 20% of them did not even graduate from 3-year high school. For men only, there was a graded
raise in income by IQ group. Within the high-IQ group there was no statistically-significant relationship between parents’ socioeconomic status and income. For
men, high IQ predicted a strongly increased income/vocational level in midlife beyond what was predicted from a linear model of the IQ-outcome relationship.
We evaluate the impact of Gifted and Talented (GT) programs on students through a regression discontinuity (RD) design, and by analyzing a randomized lottery
for elite magnet GT schools. We show that GT students in each analysis are exposed to higher achieving peers and, in the RD sample, a more advanced curriculum. We
find that achievement for marginal students neither improves nor worsens from GT services in the short run. We also find that lottery winners only perform better
in science. Using a bounding analysis we cannot rule out zero, though we do not find any significant negative effects.
Ericsson and colleagues argue that deliberate practice explains expert performance.
We tested this view in the two most studied domains in expertise research.
Deliberate practice is not sufficient to explain expert performance.
Other factors must be considered to advance the science of expertise.
Twenty years ago, Ericsson et al 1993 proposed that expert performance reflects a long
period of deliberate practice rather than innate ability, or “talent”. Ericsson et al 1993 found that elite musicians had accumulated thousands of
hours more deliberate practice than less accomplished musicians, and concluded that their theoretical framework could provide “a sufficient account of the major
facts about the nature and scarcity of exceptional performance” (p. 392). The deliberate practice view has since gained
popularity as a theoretical account of expert performance, but here we show that deliberate practice is not sufficient to
explain individual differences in performance in the two most widely studied domains in expertise research—chess and music. For researchers interested in advancing
the science of expert performance, the task now is to develop and rigorously test theories that take into account as many potentially relevant explanatory
constructs as possible.
This paper uses data from three prominent exam high schools in New York City to estimate the impact of attending a school with high-achieving peers on college
enrollment and graduation. Our identification strategy exploits sharp discontinuities in the admissions process. Applicants just eligible for an exam school have
peers that score 0.17 to 0.36 standard deviations higher on eighth grade state tests and that are 6.4 to 9.5 percentage points less likely to be black or Hispanic.
However, exposure to these higher-achieving and more homogeneous peers has little impact on college enrollment, college graduation, or college quality.
The material bases of information—paper, computer discs—usually scale with information quantity. Large quantities of information usually require large material
bases. Conventional wisdom has it that human long-term memory locates within brain tissue, and so might be expected to scale with brain size which, in turn,
depends on cranial capacity. Large memories, as in savants, should always require large heads. Small heads should always scale with small memories. While it was
previously concluded that neither of these predictions was invariably true, the evidence was weak. Brain size also depends on ventricle size, which can remain
large in some survivors of childhood hydrocephaly, occupying 95% of cranial volume. Yet some of these have normal or advanced intelligence, indicating little
impairment of long-term memory. This paradox challenges the scaling hypothesis. Perhaps we should be looking further afield?
The longitudinal rank-order stability of cognitive ability increases dramatically over the lifespan. Multiple theoretical perspectives have proposed that
genetic and/or environmental mechanisms underlie the longitudinal stability of cognition, and developmental trends therein. However, the patterns of stability of
genetic and environmental influences on cognition over the lifespan largely remain poorly understood.
We searched for longitudinal studies of cognition that reported raw genetically-informative longitudinal correlations or parameter estimates from longitudinal
behavior genetic models. We identified 150 combinations of time points and measures from 15 independent longitudinal samples. In total, longitudinal data came from
4,538 monozygotic twin pairs raised together, 7,777 dizygotic twin pairs raised together, 34 monozygotic twin pairs raised apart, 78 dizygotic twin pairs raised
apart, 141 adoptive sibling pairs, and 143 non-adoptive sibling pairs, ranging in age from infancy through late adulthood.
At all ages, cross-time genetic correlations and shared environmental correlations were substantially larger than
cross-time nonshared environmental correlations. Cross-time correlations for genetic and shared environmental components were low during early childhood, increased
sharply over child development, and remained relatively high from adolescence through late adulthood. Cross-time correlations for nonshared environmental
components were low across childhood and increased gradually to moderate magnitudes in adulthood. Increasing phenotypic stability over child development was almost
entirely mediated by genetic factors. Time-based decay of genetic and shared environmental stability was more pronounced earlier in child development.
Results: are interpreted in reference to theories of gene-environment interaction and correlation.
Figure 1: “Age curves of correlation coefficients between scores on selected initial tests and subsequent tests given at yearly
intervals.” The x-axis (bottom) indicates participant age, and the y-axis (left) indicates the longitudinal test-retest correlation. The labels at the right indicate the age at first measurement for each
corresponding connected line. From Bayley 1949, “Consistency and variability in the growth of intelligence from birth
to 18 years”, The Pedagogical Seminary and Journal of Genetic Psychology.
Figure 7: Temporal decay of phenotypic stability (top left panel), genetic stability (top right panel), shared environmental stability (bottom left panel), and nonshared environmental stability
(bottom right panel) in childhood. Each line represents a different starting age that is followed with increasing time
lags. The differential temporal decay of stability at different starting ages represents the age × time interaction.
For all of its versatility and sophistication, the extant toolkit of cognitive ability measures lacks a public domain method for large-scale, remote data collection. While the lack of copyright protection for such a measure poses a theoretical
threat to test validity, the effective magnitude of this threat is unknown and can be offset by the use of modern test-development techniques. To the extent that
validity can be maintained, the benefits of a public-domain resource are considerable for researchers, including: cost savings; greater control over test content;
and the potential for more nuanced understanding of the correlational structure between constructs.
The International Cognitive Ability Resource was developed to evaluate the prospects for such a
public-domain measure and the psychometric properties of the first 4 item types were evaluated based on administrations to both an offline university sample and a
large online sample. Concurrent and discriminative validity analyses suggest that the public-domain status of these item types did not compromise their validity
despite administration to 97,000 participants.
Further development and validation of extant and additional item types are recommended.
Generalized trust refers to trust in other members of society; it may be distinguished from particularized trust, which corresponds to trust in the family and
close friends. An extensive empirical literature has established that generalized trust is an important aspect of civic culture. It has been linked to a variety of
positive outcomes at the individual level, such as entrepreneurship, volunteering, self-rated health, and happiness. However, two recent studies have found that it
is highly correlated with intelligence, which raises the possibility that the other relationships in which it has been implicated may be spurious. Here we
replicate the association between intelligence and generalized trust in a large, nationally representative sample of U.S. adults. We also show that, after
adjusting for intelligence, generalized trust continues to be strongly associated with both self-rated health and happiness. In the context of substantial
variation across countries, these results bolster the view that generalized trust is a valuable social resource, not only for the individual but for the wider
society as well.
Parents gauge school quality in part by the level of student achievement and a school’s racial and socioeconomic mix. The importance of school characteristics
in the housing market can be seen in the jump in house prices at school district boundaries where peer characteristics change. The question of whether schools with
more attractive peers are really better in a value-added sense remains open, however. This paper uses a fuzzy regression-discontinuity design to evaluate the
causal effects of peer characteristics. Our design exploits admissions cutoffs at Boston and New York City’s heavily over-subscribed exam schools. Successful
applicants near admissions cutoffs for the least selective of these schools move from schools with scores near the bottom of the state SAT score distribution to schools with scores near the median. Successful applicants near admissions cutoffs for the most selective
of these schools move from above-average schools to schools with students whose scores fall in the extreme upper tail. Exam school students can also expect to
study with fewer nonwhite classmates than unsuccessful applicants. Our estimates suggest that the marked changes in peer characteristics at exam school admissions
cutoffs have little causal effect on test scores or college quality.
Concerning the correlational structure of intelligence, there is a broad consensus regarding hierarchical models with a general factor at the apex (g),
and less consensus regarding the number, content, and structure of more specific ability-factors hierarchically below g. Previous studies revealed very
high correlations of test-battery-specific g-factors, whereas the consistency of more specific ability-factors has been neglected.
In order to investigate this, current data stemming from n = 562 high school students who took 26 mental ability tests from independently developed
test-batteries were analyzed. Regarding the intelligence-structure, nested-factor models revealed a (relatively) better fit than higher-order models and
general-factor-models. The test-battery-specific g-factors of the nested-factor models were substantially correlated (r ≥ .91); the correlations
of the test-battery-specific verbal and numerical factors evidenced convergent and discriminant validity (convergent correlations: verbal—r = 0.83;
numerical—r = 0.46; figural—r = 0.22).
These results provided evidence that some group factors (besides the g-factors) of different test-batteries are largely similar.
The current study examined the Flynn Effect (ie. the increase in IQ scores over time) across all editions of the Wechsler Adult Intelligence Scale
(WAIS), Wechsler Intelligence Scale for Children(WISC), and Wechsler
Preschool and Primary Scale of Intelligence(WPPSI). By reverse engineering the correlation and scale score
transformations from each Wechsler edition’s technical manual, we made a mean and covariance matrix using the subtests and age groups that were in common for all
editions of a given instrument. The results indicated that when aggregated, there was a FE of 0.44 IQ points/year. This Wechsler instrument used, however,
moderates the FE, with the WISC showing the largest FE (0.73 IQ points/year) and the WAIS showing a smallest FE (0.30 IQ points/year). Moreover, this study found that the amount of invariant indicators across
instruments and age groups varied substantially, ranging from 51.53% in the WISC for the7-year-old group to
10.00% in the WPPSI for the 5- and 5.5-year-old age groups. Last, we discuss future direction for FE research based on
these results.
Because educational achievement at the end of compulsory schooling represents a major tipping point in life, understanding its causes and correlates is
important for individual children, their families, and society.
Here we identify the general ingredients of educational achievement using a multivariate design that goes beyond intelligence to consider a wide range of
predictors, such as self-efficacy, personality, and behavior problems, to assess their independent and joint contributions to educational achievement. We use a
genetically sensitive design to address the question of why educational achievement is so highly heritable. We focus on the results of a United Kingdom-wide
examination, the General Certificate of Secondary
Education(GCSE), which is administered at the end of compulsory education atage 16. GCSE scores were obtained for 13,306 twins at age 16, whom we also assessed contemporaneously on 83 scales that were condensed to 9
broad psychological domains, including intelligence, self-efficacy, personality, well-being, and behavior problems.
The mean of GCSE core subjects (English, mathematics, science) is more heritable (62%) than the 9 predictor
domains (35–58%). Each of the domains correlates statistically-significantly with GCSE results, and these
correlations are largely mediated genetically. The main finding is that, although intelligence accounts for more of the heritability of GCSE than any other single domain, the other domains collectivelyaccount for about as much GCSE heritability as intelligence. Together with intelligence, these domains account for 75% of the heritability of
GCSE.
We conclude that the high heritability of educational achievement reflects many genetically influenced traits, not just intelligence.
The relationships among intelligence, working memory, and creative thinking
Testing structural equation models of cognitive abilities and creative processes
Associative fluency predicted both divergent thinking and convergent thinking.
Intelligence and working memory also predicted three distinct creative processes.
Results support an executive interpretation of creative thinking.
The field of creativity has largely focused on individual differences in divergent thinking abilities. Recently, contemporary creativity researchers have shown
that intelligence and executive functions play an important role in divergent thought, opening new lines of research to examine how higher-order cognitive
mechanisms may uniquely contribute to creative thinking. The present study extends previous research on the intelligence and divergent thinking link by
systematically examining the relationships among intelligence, working memory, and three fundamental creative processes: associative fluency, divergent thinking,
and convergent thinking.
265 participants were recruited to complete a battery of tasks that assessed a range of elementary to higher-order cognitive processes related to intelligence
and creativity. Results provide evidence for an associative basis in two distinct creative processes: divergent thinking and convergent thinking. Findings also
supported recent work suggesting that intelligence statistically-significantly influences creative thinking. Finally, working memory played a
statistically-significant role in creative thinking processes.
Recasting creativity as a construct consisting of distinct higher-order cognitive processes has important implications for future approaches to studying
creativity within an individual differences framework.
Purpose: To examine the long-term functional outcomes and their predictors using a patient/family centered approach in a cohort of children
who had hemispherectomy. Functional outcome measures studied were the following: ambulation ability, visual symptoms, spoken language, reading skills, and
behavioral problems.
Methods: We reviewed 186 consecutive children who underwent hemispherectomy between 1997 and 2009 at our center. Preoperative clinical,
electroencephalography (EEG), imaging, and surgical data were collected. 125 families completed a structured
questionnaire to assess the functional status and seizure outcome. Prognostic predictors were examined using a multivariate regression analysis.
Key Findings: At a mean follow-up of 6.05 years after hemispherectomy, 70 patients (56%) were seizure-free and 45 (36%) had seizure recurrence;
10 patients (8%) were free of their preoperative seizures but had new-onset nonepileptic spells and were excluded from further analysis. Of 115, at follow-up
(mean age at follow-up 12.7 years, range 2–28 years), 96 patients (83%) walked independently, 10 (8.7%) walked with assistance, and 9 (7.8%) were unable to walk.
New visual symptoms that were not present preoperatively were reported only in 28 patients (24%). 80 patients (70%) had satisfactory spoken language skills but
only 44 (42%) of the 105 children older than 6 years had satisfactory reading skills. Substantial behavioral problems were reported in 30 patients (27%). Only 5
(6.2%) of the 81 children aged between 6 and 18 years attended mainstream school without assistance; 48 (59%) were in mainstream school with assistance and the
rest were in special school for disabled or home cared. Five (21%) of the 24 patients older than 18 years of age were gainfully employed.
Multivariate logistic regression analysis
identified the following factors as independently associated with poor functional outcome. (1) Seizure recurrence negatively affected all functional
domains—ambulation ability, spoken language and reading skills, and behavior (p < 0.05). (2) Abnormalities in the unoperated hemisphere on
magnetic resonance imaging (MRI) (p < 0.05) and preexisting quadriparesis (p < 0.01) correlated
with poor motor outcome. (3) Multilobar MRI abnormalities in the contralateral hemisphere (odds ratio [OR] = 13.9,
p = 0.001) and young age (indeterminate preoperative language status) at hemispherectomy (OR = 11.1, p = 0.01) also correlated with poor language
outcome. (4) Younger age at epilepsy onset correlated with poor reading skills (p = 0.01) but not with spoken language skills.
Significance: This study highlights the long-term functional status of patients after hemispherectomy. The majority of patients were ambulant
independently; however, impairments in reading and spoken language were frequent. Seizure recurrence after hemispherectomy and contralateral hemisphere
abnormalities on MRI were the major predictors of poor outcome in ambulation, spoken language, and reading abilities.
This study will assist in presurgical counseling using simple understandable functional outcome measures and may help in planning early interventions after
hemispherectomy to improve functional outcome.
A meta-analysis of 63 studies showed a significant negative association between intelligence and religiosity. The association was stronger for college students
and the general population than for participants younger than college age; it was also stronger for religious beliefs than religious behavior. For college students
and the general population, means of weighted and unweighted correlations between intelligence and the strength of religious beliefs ranged from −.20 to −.25 (mean
r = −.24). Three possible interpretations were discussed. First, intelligent people are less likely to conform and, thus, are more likely to resist religious
dogma. Second, intelligent people tend to adopt an analytic (as opposed to intuitive) thinking style, which has been shown to undermine religious beliefs. Third,
several functions of religiosity, including compensatory control, self-regulation, self-enhancement, and secure attachment, are also conferred by intelligence.
Intelligent people may therefore have less need for religious beliefs and practices.
A genome-wide association study (GWAS) of educational attainment was conducted in a discovery sample of 101,069
individuals and a replication sample of 25,490. Three independent single-nucleotide polymorphisms (SNPs) are genome-wide
statistically-significant (rs9320913, rs11584700, rs4851266), and all three replicate. Estimated effects sizes are small (coefficient of determination
R2 ≈ 0.02%), approximately 1 month of schooling per allele. A linear polygenic score from all measured SNPs
accounts for ≈2% of the variance in both educational attainment and cognitive function. Genes in the region of the loci have previously been associated with
health, cognitive, and central nervous system phenotypes, and bioinformatics analyses suggest the involvement of the anterior caudate nucleus. These findings
provide promising candidate SNPs for follow-up work, and our effect size estimates can anchor power analyses in social-science genetics.
[A landmark study in behavioral genetics and intelligence: the first well-powered GWAS to detect genetic variants for
intelligence and education which replicate out of sample and are proven to be causal in a between-sibling study.]
Recent research has indicated a negative relation between the propensity for analytic reasoning and religious beliefs and practices. Here, we propose conflict
detection as a mechanism underlying this relation, on the basis of the hypothesis that more-analytic people are less religious, in part, because they are more
sensitive to conflicts between immaterial religious beliefs and beliefs about the material world.
To examine cognitive conflict sensitivity, we presented problems containing stereotypes that conflicted with base-rate probabilities in a task with no religious content.
In 3 studies, we found evidence that religiosity is negatively related to conflict detection during reasoning. Independent measures of analytic cognitive style
also positively predicted conflict detection.
The present findings provide evidence for a mechanism potentially contributing to the negative association between analytic thinking and religiosity, and more
generally, they illustrate the insights to be gained from integrating individual-difference factors and contextual factors to investigate analytic reasoning.
Background: Genome-wide association studies (GWAS) have shown a polygenic component to the
risk of schizophrenia. The disorder is associated with impairments in general cognitive ability that also have a substantial
genetic contribution. No study has determined whether cognitive impairments can be attributed to schizophrenia’s polygenic architecture using data from
GWAS.
Methods: Members of the Lothian Birth Cohort 1936 (LBC1936,n = 937) were
assessed using the Moray House Test at age 11 and with the Moray House Test and a further cognitive battery at age 70. To create polygenic risk scores for
schizophrenia, we obtained data from the latest GWAS of the Psychiatric
GWAS Consortium onSchizophrenia. Schizophrenia polygenic risk profile scores
were calculated using information from the Psychiatric GWAS Consortium on SchizophreniaGWAS.
Results: In LBC1936, polygenic risk forschizophrenia
was negatively associated with IQ at age 70 but not at age 11. Greater polygenic risk for schizophrenia was associated with
more relative decline in IQ between these ages. These findings were maintained when the results of LBC1936 were combined
with that of the independent Lothian Birth Cohort 1921 (n = 517) in a meta-analysis.
Conclusions: Increased polygenic risk of schizophrenia is associated with lower cognitive ability at age
70 and greater relative decline in general cognitive ability between the ages of 11 and 70. Common genetic variants may underlie both cognitive aging and risk of
schizophrenia.
Intelligence in childhood, as measured by psychometric cognitive tests, is a strong predictor of many important life outcomes, including educational attainment,
income, health and lifespan. Results from twin, family and adoption studies are consistent with general intelligence being highly heritable and genetically stable
throughout the life course. No robustly associated genetic loci or variants for childhood intelligence have been reported.
Here, we report the first genome-wide association study (GWAS) on childhood intelligence (age range 6–18 years)
from 17 989 individuals in six discovery and three replication samples. Although no individual single-nucleotide polymorphisms (SNPs) were detected with genome-wide statistical-significance, we show that the aggregate effects of common SNPs explain 22–46% of phenotypic variation in childhood intelligence in the three largest cohorts (p =
3.9×10-15, 0.014 and 0.028). FNBP1L, previously reported to be the most statistically-significantly
associated gene for adult intelligence, was also statistically-significantly associated with childhood intelligence (p = 0.003). Polygenic prediction
analyses resulted in a statistically-significant correlation between predictor and outcome in all replication cohorts. The proportion of childhood intelligence
explained by the predictor reached 1.2% (p = 6×10-5), 3.5% (p = 10-3) and 0.5% (p = 6×10-5) in three
independent validation cohorts.
Given the sample sizes, these genetic prediction results are consistent with expectations if the genetic architecture of childhood intelligence is like that of
body mass index or height. Our study provides molecular support for the heritability and polygenic nature of childhood
intelligence. Larger sample sizes will be required to detect individual variants with genome-wide statistical-significance.
Intercepting a moving object requires prediction of its future location. This complex task has been solved by dragonflies, who intercept their prey in midair
with a 95% success rate.
In this study, we show that a group of 16 neurons, called target-selective descending neurons (TSDNs), code a
population vector that reflects the direction of the target with high accuracy and reliability across 360°. The TSDN spatial (receptive field) and temporal (latency) properties matched the area of the retina where the prey is focused and the
reaction time, respectively, during predatory flights. The directional tuning curves and morphological traits (3D tracings) for each TSDN type were consistent among animals, but spike rates were not.
Our results emphasize that a successful neural circuit for target tracking and interception can be achieved with few neurons and that in dragonflies this
information is relayed from the brain to the wing motor centers in population vector form.
Libertarians are an increasingly prominent ideological group in U.S. politics, yet they have been largely unstudied. Across 16 measures in a large
web-based sample that included 11,994 self-identified libertarians, we sought to understand the moral and psychological characteristics of self-described
libertarians. Based on an intuitionist view of moral judgment, we focused on the underlying affective and cognitive dispositions that accompany this unique
worldview. Compared to self-identified liberals and conservatives, libertarians showed (1) stronger endorsement of individual liberty as their foremost guiding
principle, and weaker endorsement of all other moral principles; (2) a relatively cerebral as opposed to emotional cognitive style; and (3) lower interdependence
and social relatedness. As predicted by intuitionist theories concerning the origins of moral reasoning, libertarian values showed convergent relationships with
libertarian emotional dispositions and social preferences. Our findings add to a growing recognition of the role of personality differences in the organization of
political attitudes.
[Herculano-Houzel 2009] Neuroscientists have become used to a number of “facts” about the
human brain: It has 100 billion neurons and 10- to 50-fold more glial cells; it is the largest-than-expected for its body among primates and mammals in general,
and therefore the most cognitively able; it consumes an outstanding 20% of the total body energy budget despite representing only 2% of body mass because of an
increased metabolic need of its neurons; and it is endowed with an overdeveloped cerebral cortex, the largest compared with brain size.
These facts led to the widespread notion that the human brain is literally extraordinary: an outlier among mammalian brains, defying evolutionary rules that
apply to other species, with a uniqueness seemingly necessary to justify the superior cognitive abilities of humans over mammals with even larger brains. These
facts, with deep implications for neurophysiology and evolutionary biology, are not grounded on solid evidence or sound assumptions, however.
Our recent development of a method that allows rapid and reliable quantification of the numbers of cells that compose the whole brain has provided a means to
verify these facts. Here, I review this recent evidence and argue that, with 86 billion neurons and just as many nonneuronal cells, the human brain is a scaled-up
primate brain in its cellular composition and metabolic cost, with a relatively enlarged cerebral cortex that does not have a relatively larger number of brain
neurons yet is remarkable in its cognitive abilities and metabolism simply because of its extremely large number of neurons.
While the importance of physical abilities and motor coordination is non-contested in sport, more focus has recently been turned toward cognitive processes
important for different sports. However, this line of studies has often investigated sport-specific cognitive traits, while few studies have focused on general
cognitive traits. We explored if measures of general executive functions can predict the success of a soccer player. The present study used standardized
neuropsychological assessment tools assessing players’ general executive functions including on-line multi-processing such as creativity, response inhibition, and
cognitive flexibility. In a first cross-sectional part of the study we compared the results between High Division players (HD), Lower Division players
(LD) and a standardized norm group. The result shows that both HD and LD players had
significantly better measures of executive functions in comparison to the norm group for both men and women. Moreover, the HD players outperformed the LD players in these tests. In the second prospective part of the study, a partial correlation test showed a statistically-significant
correlation between the result from the executive test and the numbers of goals and assists the players had scored two seasons later. The results from this study
strongly suggest that results in cognitive function tests predict the success of ball sport players.
Hydrocephalus is an entity which embraces a variety of diseases whose final result is the enlarged size of cerebral ventricular system, partially or completely.
The physiopathology of hydrocephalus lies in the
dynamics of circulation of cerebrospinal fluid (CSF). Theconsequent CSF
stasis inhydrocephalus interferes with cerebral and ventricular system development. Children and adults who sustain
congenital or acquired brain injury typically experience a diffuse insult that impacts many areas of the brain. Development and recovery after such injuries
reflects both restoration and reorganization of cognitive functions. Classic examples were already reported in literature. This suggests the presence of biological
mechanisms associated with resilient adaptation of brain networks. We will settle a link between the notable modifications to neurophysiology secondary to
hydrocephalus and the ability of neuronal tissue to reassume and reorganize its functions.
Human tail is a curiosity, a cosmetic stigma and presents as an appendage in the lumbosacral region. Six patients of tail in the lumbosacral region are
presented here to discuss the spectrum of presentation of human tails. The embryology, pathology and treatment of this entity are discussed along with a brief
review of the literature.
Fluid reasoning shares a large part of its variance with working memory capacity (WMC). The literature on working
memory (WM) suggests that the capacity of the focus of attention responsible for simultaneous maintenance and integration of information within WM, as well
as the effectiveness of executive control exerted over WM, determines individual variation in both WMC and
reasoning.
In 6 experiments, we used a modified n-back task to test the amount of
variance in reasoning that is accounted for by each of these 2 theoretical constructs. The capacity of the focus accounted for up to 62% of variance in fluid
reasoning, while the recognition of stimuli encoded outside of the focus was not related to reasoning ability. Executive control, measured as the ability to reject
distractors identical to targets but presented in improper contexts, accounted for up to 13% of reasoning variance.
Multiple analyses indicated that capacity and control predicted non-overlapping amounts of variance in reasoning.
Individual differences in human intelligence are of interest to a wide range of psychologists and to many people outside the discipline. This overview of
contributions to intelligence research covers the first decade of the twenty-first century. There is a survey of some of the major books that appeared since 2000,
at different levels of expertise and from different points of view.
Contributions to the phenotype of intelligence differences are discussed, as well as some contributions to causes and consequences of intelligence differences.
The major causal issues covered concern the environment and genetics, and how intelligence differences are being mapped to brain differences. The major outcomes
discussed are health, education, and socioeconomic status. Aging and intelligence are discussed, as are sex differences in intelligence and whether twins and
singletons differ in intelligence.
More generally, the degree to which intelligence has become a part of broader research in neuroscience, health, and social science is discussed.
General intelligence is an important human quantitative trait that accounts for much of the variation in diverse cognitive abilities. Individual differences in
intelligence are strongly associated with many important life outcomes, including educational and occupational attainments, income, health and lifespan. Data from
twin and family studies are consistent with a high heritability of intelligence, but this inference has been controversial. We conducted a genome-wide analysis of
3511 unrelated adults with data on 549,692 single nucleotide polymorphisms (SNPs) and detailed phenotypes on
cognitive traits. We estimate that 40% of the variation in crystallized-type intelligence and 51% of the variation in fluid-type intelligence between
individuals is accounted for by linkage disequilibrium between genotyped common SNP markers and unknown causal variants. These estimates provide lower bounds for the narrow-sense heritability of the
traits. We partitioned genetic variation on individual chromosomes and found that, on average, longer chromosomes explain more variation. Finally, using just
SNP data we predicted ~1% of the variance of crystallized and fluid cognitive phenotypes in an independent
sample (p = 0.009 and 0.028, respectively). Our results unequivocally confirm that a substantial proportion of individual differences in human
intelligence is due to genetic variation, and are consistent with many genes of small effects underlying the additive genetic influences on intelligence.
One of the most important findings that has emerged from human behavioral genetics involves the environment rather than heredity, providing the best available
evidence for the importance of environmental influences on personality, psychopathology, and cognition. The research also converges on the remarkable conclusion
that these environmental influences make two children in the same family as different from one another as are pairs of children selected randomly from the
population. The theme of the target article is that environmental differences between children in the same family (called “nonshared environment”) represent the
major source of environmental variance for personality, psychopathology, and cognitive abilities. One example of the evidence that supports this conclusion
involves correlations for pairs of adopted children reared in the same family from early in life. Because these children share family environment but not heredity,
their correlation directly estimates the importance of shared family environment. For most psychological characteristics, correlations for adoptive “siblings”
hover near zero, which implies that the relevant environmental influences are not shared by children in the same family. Although it has been thought that
cognitive abilities represent an exception to this rule, recent data suggest that environmental variance that affects IQ is also of the nonshared variety after
adolescence. The article has three goals: (1) To describe quantitative genetic methods and research that lead to the conclusion that nonshared environment is
responsible for most environmental variation relevant to psychological development, (2) to discuss specific nonshared environmental influences that have been
studied to date, and (3) to consider relationships between nonshared environmental influences and behavioral differences between children in the same family.
The reason for presenting this article in BBS is to draw attention to the far-reaching implications of finding that
psychologically relevant environmental influences make children in a family different from, not similar to, one another.
Standardized measures of intelligence, ability, or achievement are all measures of acquired knowledge and skill and have consistent relationships with multiple
facets of success in life, including academic and job performance.
Five persistent beliefs about ability tests have developed, including:
that there is no relationship with important outcomes like creativity or leadership,
that there is predictive bias,
that there is a lack of predictive independence from socioeconomic status,
that there are thresholds beyond which scores cease to matter, and
that other characteristics, like personality, matter as well.
We present the evidence and conclude that of these 5 beliefs, only the importance of personality is a fact; the other 4 are fiction.
Phenotypic variation in human intellectual functioning shows substantial heritability, as demonstrated by a long history of behavior genetic studies. Many
recent molecular genetic studies have attempted to uncover specific genetic variations responsible for this heritability, but identified effects capture little
variance and have proven difficult to replicate. The present study, motivated an interest in “mutation load” emerging from evolutionary perspectives, examined the
importance of the number of rare (or infrequent) copy number variations (CNVs), and the total number of base
pairs included in such deletions, for psychometric intelligence.
Genetic data was collected using the Illumina 1MDuoBeadChip Array from a sample of 202 adult individuals with alcohol dependence, and a subset of these
(n = 77) had been administered the Wechsler Abbreviated Scale of Intelligence (WASI). After removingCNV outliers, the impact of rare genetic deletions on psychometric intelligence was investigated in 74
individuals. The total length of the rare deletions statistically-significantly and negatively predicted intelligence (r = −0.30, p = 0.01).
As prior studies have indicated greater heritability in individuals with relatively higher parental socioeconomic status (SES), we also examined the impact of ethnicity (Anglo/White vs. Other), as a proxy measure of SES; these groups did not differ on any genetic variable. This categorical variable statistically-significantly moderated the effect
of length of deletions on intelligence, with larger effects being noted in the Anglo/White group.
Overall, these results suggest that rare deletions (between 5% and 1% population frequency or less) adversely affect intellectual functioning, and that
pleiotropic effects might partly account for the association of intelligence with health and mental health status. Substantial limitations of this research,
including issues of generalizability and CNV measurement, are discussed.
[See also Bates et al 2016’s failure to replicate.] Psychologists
have repeatedly shown that a single statistical factor—often called “general intelligence”—emerges from the correlations among people’s performance on a wide
variety of cognitive tasks. But no one has systematically examined whether a similar kind of “collective intelligence” exists for groups of people. In 2
studies with 699 people, working in groups of 2 to 5, we find converging evidence of a general collective intelligence factor that explains a group’s performance
on a wide variety of tasks. This “c factor” is not strongly correlated with the average or maximum individual intelligence of group members but is
correlated with the average social sensitivity of group members, the equality in distribution of conversational turn-taking, and the proportion of females in the
group.
Meeting of Minds: The performance of humans across a range of different kinds of cognitive tasks has been encapsulated as a common statistical
factor called g or general intelligence factor. What intelligence actually is, is unclear and hotly debated, yet there is a reproducible association of
g with performance outcomes, such as income and academic achievement. Woolley et al (p. 686, published online 30 September) report a
psychometric methodology for quantifying a factor termed “collective intelligence” (c), which reflects how well groups perform on a similarly diverse set
of group problem-solving tasks. The primary contributors to c appear to be the g factors of the group members, along with a propensity toward social
sensitivity—in essence, how well individuals work with others.
International Large-Scale Assessments (LSA) allow comparisons of education systems’ effectiveness in promoting
student learning in specific domains, such as reading, mathematics, and science. However, it has been argued that students’ scores in International
LSAs mostly reflect general cognitive ability (g).
This study examines the extent to which students’ scores in reading, mathematics, science, and a Raven’s Progressive Matrices test reflect general ability g
and domain-specific abilities with data from 3,472 Polish students who participated in the OECD’s 2009 Programme for International Student Assessment(PISA) and whowere retested with the same PISA instruments, but with a different item set, in 2010.
Variance in students’ responses to test items is explained better by with a bifactorItem Response Theory(IRT) model than by the multidimensional IRT modelroutinely used to scale PISA and other LSAs. The bifactor IRT model assumes that
non-g factors (reading, math, science, and Raven’s test) are uncorrelated with g and with each other. The bifactor model generates specific
ability factors with more theoretically credible relationships with criterion variables than the multidimensional standard model. Further analyses of the bifactor
model indicate that the domain-specific factors are not reliable enough to be interpreted meaningfully. They lie somewhere between unreliable measures of
domain-specific abilities and nuisance factors reflecting measurement error.
The finding that PISA achievement scores reflect mostlyg, which may arise because PISA aims to test broad abilities in a variety ofcontexts or may be a general characteristic of LSAs and national achievement tests.
This study analyzes Programme for International Student Assessment data from Poland to establish how much the achievement
of secondary school students in reading, mathematics, science and in a Raven’s Progressive Matrices test reflects general ability and how much it reflects
domain-specific abilities. Findings indicate that a scaling model that accounts for general ability, fit the data better than models typically employed in large
scale assessments that ignore the influence of general ability on student achievement. The finding that students’ responses to PISA test items reflect general ability rather than domain-specific abilities, if replicated to other countries, could have
important implications for the design of large-scale assessments and the interpretation of analyses of large-scale assessment data.
For more than a century the veracity of Spearman’s postulate that there is a nearly perfect correspondence between general intelligence and general sensory
discrimination has remained unresolved. Most studies have found significant albeit small correlations. However, this can be used neither to confirm nor dismiss
Spearman’s postulate, a major weakness of previous research being that only single discrimination capacities were considered rather than general discrimination.
The present study examines Spearman’s hypothesis with a sample of 1,330 5- to 10-year-old children, using structural equation modeling. The results support
Spearman’s hypothesis with a strong correlation (r = 0.78). Results are discussed in terms of the validity of the general sensory discrimination factor.
In addition, age-group-specific analyses explored the age differentiation hypothesis.
Military Personnel System · Indicators of Recruit Quality · Need for Military Selection · Short History of Military Personnel Testing (Pre-All Volunteer
Force) · Moving to an All-Volunteer Force · ASVAB Misnorming and Job Performance Measurement Project · Enlisted
Selection and Classification in Today’s Military · Enlistment Process · Recruit Quality Benchmarks and Enlistment Standards · Selection for Officer Commissioning
Programs · Officer Retention and Attrition · Officer Executive Development · Command Selection and Career Broadening Experiences · Defense Transformation in
Military Selection · Conclusions · References
Origins of Project A · Enabling of Project A · Specific Research Objectives · Overall Research Design · Research Instrument Development: Predictors · Job
Analyses and Criterion Development · Modeling the Latent Structure of Performance · Correlations of Past Performance With Future Performance · Criterion-Related
Validation · Some Broader Implications · Conclusions · References
This chapter 1 is about personnel selection and classification research on a scale never before attempted in terms of (a) the types and variety of information
collected, (b) the number of jobs that were considered simultaneously, (c) the size of the samples, and (d) the length of time that individuals were followed as
they progressed through the organization.
The effort, commonly known as Project A, was sponsored by the U.S. Army Research Institute for the Behavioral and Social Sciences (ARI). For contract management reasons the research program was conducted as two sequential projects: Project A (1982–1989) and
Career Force (1990–1994), which worked from a single overall design (described subsequently).
Collectively, these projects attempted to evaluate the selection validity and classification efficiency of systematically sampled domains of prediction
information for different selection and classification goals for the entire enlisted personnel system of the U.S. Army, using various alternative decision rules
(ie., “models”). Pursuing such ambitious objectives required the development of a comprehensive battery of new tests and inventories, the development of a wide
variety of training and job performance measures for each job in the sample, four major worldwide data collections involving thousands of Army enlisted job
incumbents for one to two days each, and the design and maintenance of the resulting database.
The truly difficult part was the never-ending need to develop a consensus among all of the project participants regarding literally hundreds of choices among
measurement procedures, analysis methods, and data collection design strategies. Although many such decisions were made in the original design stage, many more
occurred continuously as the projects moved forward, driven by the target dates for the major data collections, which absolutely could not be missed. The fact that
all major parts of the projects were completed within the prescribed time frames and according to the specified research design was a source of wonder for all who
participated.
[on the Wilson effect] Although common sense suggests that environmental influences increasingly account for individual differences in behavior as experiences
accumulate during the course of life, this hypothesis has not previously been tested, in part because of the large sample sizes needed for an adequately powered
analysis.
Here we show for general cognitive ability that, to the contrary, genetic influence increases with age. The heritability of general cognitive ability increases
substantially and linearly from 41% in childhood (9 years) to 55% in adolescence (12 years) and to 66% in young adulthood (17 years) in a sample of 11 000 pairs of
twins from 4 countries, a larger sample than all previous studies combined.
In addition to its far-reaching implications for neuroscience and molecular genetics, this finding suggests new ways of thinking about the interface between
nature and nurture during the school years. Why, despite life’s ‘slings and arrows of outrageous fortune’, do genetically driven differences increasingly account
for differences in general cognitive ability? We suggest that the answer lies with genotype-environment correlation: as children grow up, they increasingly select,
modify and even create their own experiences in part based on their genetic propensities.
Using a behavioral genetic approach, we examined the validity of the hypothesis concerning the singularity of human general intelligence, the g theory,
by analyzing data from 2 tests: the first consisted of 100 syllogism problems and the second a full-scale intelligence test.
The participants were 448 Japanese young adult twins (167 pairs of identical and 53 pairs of fraternal twins). Data were analyzed for their fit to 2 kinds of
multivariate genetic models: a common pathway model, in which a higher-order latent variable, g, was postulated as an entity; and an independent pathway
model, in which the higher-order latent variable was not posited. These analyses revealed that the common pathway model which included additive genetic and
nonshared environmental factors best accounted for the 3 distinct mental abilities: syllogistic logical deductive reasoning, verbal, and spatial.
Both the substantial g-loading for syllogism-solving, historically recognized as the symbol of human intelligence, and the emergence of g as
an entity at an etiological level, that is, at the genetic and environmental factor level, provide further support for the g theory.
[Keywords: g factor, syllogism, twin study, multivariate genetic analysis, common pathway model, independent pathway model]
Objective: Over the past three decades, there have been substantial changes in the diagnostic criteria for schizophrenia as well as changes in measurement of IQ. The last quantitative review of the literature on premorbid IQ in schizophrenia was published more than two decades ago. Since that time, there have been many published studies of data sets pertaining
to this issue. The purpose of the present review was to provide an updated meta-analysis of premorbid IQ in individuals who later develop schizophrenia.
Method: The authors performed a systematic literature search, which yielded 18 studies that met criteria for the meta-analysis. Inclusion
criteria were 1. premorbid psychometric measures of IQ in subjects who were later diagnosed with schizophrenia,
schizoaffective disorder, or schizophreniform disorder, 2. similar comparison data, and 3. sufficient data for calculation of an effect size. The analogue to the
analysis of variance method was used to model between-study variance due to key study-design features.
Results: Overall, schizophrenia samples demonstrated a reliable, medium-sized impairment in premorbid
IQ. The heterogeneity of effect sizes was minimal and almost exclusively the result of one study. Methodological differences, such as diagnostic criteria, type of
IQ measure, sample ascertainment, and age at premorbid testing, contributed minimally to the effect size variance. A cross-sectional analysis of all studies by age
and a descriptive review of studies that used repeated measures of IQ in a single sample did not support the presence of a relative decline in IQ during the
premorbid period in individuals with schizophrenia. However, all studies with pre-onset and post-onset testing within the
same sample suggested that a [substantial] decline in the IQ of individuals with schizophrenia, relative to comparison
subjects, was associated with the onset of frank psychosis.
Conclusions: Years before the onset of psychotic symptoms, individuals with schizophrenia, as a group,
demonstrate mean IQ scores approximately one-half of a standard deviation below that of healthy comparison subjects.
Students completed 4 psychometric tests soon after arriving at university: the NEO-PI-R measure of the Big Five
personality traits (Costa & McCrae 1992); the Study Process Questionnaire, which measures approaches to learning (Biggs 1978); and 2 measures of
cognitive ability: the Wonderlic IQ Test (Wonderlic, 1992) and the Baddeley Reasoning Test (Baddeley 1968) of fluid intelligence (gf). A
year later they completed comprehensive essay-based exams and received a mean score based on 6 examinations.
Academic performance (AP) correlated with ability, achieving and deep learning approaches, Openness and Conscientiousness. Together, these variables explained 40% of the variance in AP. Path analyses indicated that the effects of ability on
AP were mediated by personality and learning approaches.
Scores on cognitive tests have been very widely reported to have increased through the decades of the last century, a generational phenomenon termed the
‘Flynn Effect’ since it was most comprehensively documented by James Flynn in the
1980s. There has, however, been very little evidence concerning any continuity of the effect specifically into the present century.
We here report data from a population, namely young adult males in Denmark, showing that whereas there were modest increases between 1988 and 1998 in scores on
a battery of 4 cognitive tests—these constituting a diminishing continuation of a trend documented back to the late 1950s—scores on all 4 tests declined between
1998 and 2003–2004. For 2 of the tests, levels fell to below those of 1988. Across all tests, the decrease in the 5–6 year period corresponds to approximately
1.5 IQ points, very close to the net gain between 1988 and 1998. The declines between 1998 and 2003–4 appeared amongst both men pursuing higher academic education
and those not doing so.
We developed an analysis pipeline enabling population studies of HARDI data, and applied it to map genetic
influences on fiber architecture in 90 twin subjects. We applied tensor-driven 3D fluid registration to HARDI, resampling
the spherical fiber orientation distributionfunctions (ODFs) in appropriate Riemannian manifolds, after
ODF regularization and sharpening. Fitting structural equation models (SEM)
from quantitative genetics, we evaluated genetic influences onthe Jensen-Shannon divergence (JSD), a novel
measure of fiber spatialcoherence, and on the generalized fiber anisotropy (GFA) a measure of fiber
integrity. With random-effects regression, we mapped regions where diffusion profiles were highly correlated with subjects’ intelligence quotient (IQ). Fiber
complexity was predominantly under genetic control, and higher in more highly anisotropic regions; the proportion of genetic versus environmental control varied
spatially. Our methods show promise for discovering genes affecting fiber connectivity in the brain.
Recent psychological and neuropsychological research suggests that executive functions–the cognitive control processes that regulate thought and action–are
multifaceted and that different types of executive functions are correlated but separable. The present multivariate twin study of 3 executive functions (inhibiting
dominant responses, updating working memory representations, and shifting between task sets), measured as latent variables, examined why people vary in these
executive control abilities and why these abilities are correlated but separable from a behavioral genetic perspective. Results indicated that executive functions
are correlated because they are influenced by a highly heritable (99%) common factor that goes beyond general intelligence or perceptual speed, and they are
separable because of additional genetic influences unique to particular executive functions. This combination of general and specific genetic influences places
executive functions among the most heritable psychological traits. These results highlight the potential of genetic approaches for uncovering the biological
underpinnings of executive functions and suggest a need for examining multiple types of executive functions to distinguish different levels of genetic
influences.
This study revisits the relationship between interviews and cognitive ability tests, finding lower magnitudes of correlation than have previous meta-analyses; a
finding that has implications for both the construct and incremental validity of the interview. Our lower estimates of this relationship than previous
meta-analyses were mainly due to (a) an updated set of studies, (b) exclusion of samples in which interviewers potentially had access to applicants’ cognitive test
scores, and (c) attention to specific range restriction mechanisms that allowed us to identify a sizable subset of studies for which range restriction could be accurately accounted. Moderator analysis results were similar to previous meta-analyses, but magnitudes of
correlation were generally lower than in previous meta-analyses. Findings have implications for the construct and incremental validity of interviews, and
meta-analytic methodology in general.
In previous papers [Johnson & Bouchard Jr. 2005a] [Johnson & Bouchard Jr. 2005b] we have proposed the Verbal, perceptual, and
image rotation (VPR) modelof the structure of mental abilities. The VPR model
is hierarchical, with a g factor that contributes strongly to broad verbal, perceptual, and image rotation abilities, which in turn contribute to 8
more specialized abilities. The verbal and perceptual abilities, though separable, are highly correlated, as are the perceptual and mental rotation abilities. The
verbal and mental rotation abilities are much less correlated.
In this study we used the twin sample in the Minnesota
Study of Twins Reared Apart to estimate the genetic and environmental influences and the correlations among them at each order of the VPR model. Genetic influences accounted for 67–79% of the variance throughout the model, with the exception of the second-stratum
Content Memory factor, which showed 33% genetic influence. These influences could not be attributed to assessed similarity of rearing environment. Genetic
correlations closely mirrored the phenotypic correlations.
Together, these findings substantiate the theory that the entire structure of mental abilities is strongly influenced by genes.
[Keywords: genetic and environmental influences, genetic and environmental correlations, verbal and image rotation abilities,
intelligence, VPR model,g factor, twin study]
Humans have many cognitive skills not possessed by their nearest primate relatives. The cultural intelligence hypothesis argues that this is mainly due to a
species-specific set of social-cognitive skills, emerging early in ontogeny, for participating and exchanging knowledge in cultural groups.
We tested this hypothesis by giving a comprehensive battery of cognitive tests [the Primate Cognition Test Battery (PCTB)] to large numbers of 2 of humans’ closest primate relatives, chimpanzees and orangutans, as well as to 2.5-year-old human
children before literacy and schooling.
Supporting the cultural intelligence hypothesis and contradicting the hypothesis that humans simply have more “general intelligence”, we found that the children
and chimpanzees had very similar cognitive skills for dealing with the physical world but that the children had more sophisticated cognitive skills than either of
the ape species for dealing with the social world.
[Very brief case study.] On neuropsychological testing, he proved to have an intelligence quotient (IQ) of 75: his verbal IQ was 84, and his performance IQ 70.
CT showed severe dilatation of the lateral ventricles (figure); MRI revealed massive enlargement of the lateral,
third, and fourth ventricles, a very thin cortical mantle and a posterior fossa cyst. We diagnosed a non-communicating hydrocephalus…after a ventriculoperitoneal
shunt was inserted, the findings on neurological examination became normal within a few weeks. The findings on neuropsychological testing and CT did not
change.
“Is there a biology of intelligence which is characteristic of the normal human nervous system?” Here we review 37 modern neuroimaging studies in an attempt to
address this question posed by Halstead (1947) as he and other icons of the last century endeavored to understand how brain and behavior are linked through the
expression of intelligence and reason. Reviewing studies from functional (ie., functional magnetic resonance imaging, positron emission tomography) and structural
(ie., magnetic resonance spectroscopy, diffusion tensor imaging, voxel-based morphometry) neuroimaging paradigms, we report a striking consensus suggesting that
variations in a distributed network predict individual differences found on intelligence and reasoning tasks.
We describe this network as the Parieto-Frontal Integration Theory(P-FIT). The P-FIT model includes, by Brodmann areas (BAs): the dorsolateral prefrontal cortex (BAs 6, 9, 10, 45, 46, 47), the inferior (BAs 39,
40) and superior (BA 7) parietal lobule, the anterior cingulate (BA 32), and regions within the temporal (BAs 21, 37) and occipital (BAs 18, 19) lobes.
White matter regions (ie., arcuate fasciculus) are also implicated. The P-FIT is examined in light of findings
from human lesion studies, including missile wounds, frontal lobotomy/leukotomy, temporal lobectomy, and lesions resulting in damage to the language network (eg.
aphasia), as well as findings from imaging research identifying brain regions under substantial genetic control.
Overall, we conclude that modern neuroimaging techniques are beginning to articulate a biology of intelligence. We propose that the P-FIT provides a parsimonious account for many of the empirical observations, to date, which relate individual differences in
intelligence test scores to variations in brain structure and function. Moreover, the model provides a framework for testing new hypotheses in future experimental
designs.
Empirical data suggest that there is at most a very small sex difference in general mental ability, but men clearly perform better on visuospatial tasks while
women clearly perform better on tests of verbal usage and perceptual speed. In this study, we integrated these overall findings with predictions based on the
Verbal-Perceptual-Rotation (VPR) model ([Johnson, W., and Bouchard, T. J. (2005a). “Constructive replication of
the visual-perceptual-image rotation (VPR) model in Thurstone’s (1941) battery of 60 tests of mental ability”.
Intelligence, 33, 417–430.; Johnson, W., and Bouchard, T. J. (2005b). “The structure of human intelligence: It’s verbal, perceptual, and image
rotation (VPR), not fluid and crystallized”. Intelligence, 33. 393–416.]) of the structure of mental abilities.
We examined the structure of abilities after removing the effects of general intelligence, identifying three underlying dimensions termed rotation-verbal,
focus-diffusion, and memory. Substantial sex differences appeared to lie along all three dimensions, with men more likely to be positioned towards the rotation and
focus poles of those dimensions, and women displaying generally greater memory. At the level of specific ability tests, there were greater sex differences in
residual than full test scores, providing evidence that general intelligence serves as an all-purpose problem solving ability that masks sex differences in more
specialized abilities. The residual ability factors we identified showed strong genetic influences comparable to those for full abilities, indicating that the
residual abilities have some basis in brain structure and function.
[Keywords:, Sex differences, Residual mental abilities, Verbal and spatial abilities, General intelligence, VPR theory, Genetic and environmental influences]
The classic (“status attainment”) model of educational and occupational attainment suffers from 3 related shortcomings when used as a tool for comparative or
policy-oriented research on social mobility: (1) ambiguity of model parameters as measures of opportunity for achievement vs. ascription; (2) vulnerability to
incomplete specification of family background; and (3) confounding of environmental and genetic influences. These issues can
be addressed in part by using a (“behavior genetic”) model that distinguishes variance components associated with genetic endowment, shared (or common) family
environment, and unshared (or specific) environment. Size of the genetic component (heritability) measures opportunity for achievement; size of the shared
environment component (environmentality) measures social ascription.
A multivariate behavior genetic model of adolescent verbal IQ, grade point average and college plans is estimated using data for 6 types of adolescent sibling
pairs living in the same household: MZ twins, DZ twins, full siblings, half siblings, cousins and non-related siblings.
Results: show large genetic components, relatively small shared environmental components, and large unshared environmental components for all 3
outcomes. Parameters of the behavior genetic model can be used to compare mobility regimes across social contexts and the model therefore provides an important
tool for comparative social mobility research.
We recently evaluated the relative statistical performance of the Cattell-Horn fluid-crystallized model and the Vernon verbal-perceptual model of the structure
of human intelligence in a sample of 436 adults heterogeneous for age, place of origin, and educational background who completed 42 separate tests of mental
ability from 3 test batteries.
We concluded that the Vernon model’s performance was substantively superior but could be substantially improved. In so doing, we proposed a 4-stratum model with
a g factor at the top of the hierarchy and 3 factors at the third stratum. We termed this the Verbal-Perceptual-Image Rotation (VPR) model.
In this study, we constructively replicated the model comparisons and development of the VPR model using the data
matrix published by Thurstone and Thurstone (1941) [Thurstone & Thurstone 1941, Factorial studies of intelligence]. The data matrix was generated by scores of 710
Chicago 8th graders on 60 tests of mental ability.
[Keywords: g factor, fluid and crystallized intelligence, verbal and perceptual abilities, mental rotation, spatial
visualization, VPR theory]
In a heterogeneous sample of 436 adult individuals who completed 42 mental ability tests, we evaluated the relative statistical performance of 3 major
psychometric models of human intelligence—the Cattell-Horn fluid-crystallized model, Vernon’s verbal-perceptual model, and Carroll’s 3-strata model.
The verbal-perceptual model fit statistically-significantly better than the other 2. We improved it by adding memory and higher-order image rotation factors.
The results provide evidence for a 4-stratum model with a g factor and 3 third-stratum factors.
The model is consistent with the idea of coordination of function across brain regions and with the known importance of brain laterality in intellectual
performance. We argue that this model is theoretically superior to the fluid-crystallized model and highlight the importance of image rotation in human
intellectual function.
[Keywords: g factor, fluid and crystallized intelligence, verbal and perceptual abilities, mental rotation, spatial
visualization, VPR theory]
An important construct in Industrial, Work and Organizational (IWO) psychology, organizational behavior, and
human resources management (personnel selection, training, and performance evaluation) in general, and personnel selection in particular, is the construct of job
performance. Job performance is the most important dependent variable in IWO psychology. A general definition of the
construct of job performance reflects behaviors (both visually observable and non-observable) that can be evaluated. In other words, job performance refers
to scalable actions, behaviors, and outcomes that employees engage in or bring about that are linked with and contribute to organizational goals. To date, most
researchers focusing on the construct of job performance have confined themselves to particular situations and settings with no attempt to generalize their
findings. Also, there has been an emphasis on prediction and practical application rather than explanation and theory building. The consequence of these two trends
has been a proliferation of the various measures of job performance in the extant literature. Virtually every measurable individual differences dimension thought
to be relevant to the productivity, efficiency, or profitability of the unit or organization has been used as a measure of job performance. Absenteeism,
productivity ratings, violence on the job, and teamwork ratings are some examples of the variety of measures used to measure job performance.
Large epidemiological studies of almost an entire population in Scotland have found that intelligence (as measured by an IQ-type test) in childhood predicts
substantial differences in adult morbidity and mortality, including deaths from cancers and cardiovascular diseases. These relations remain
statistically-significant after controlling for socioeconomic variables.
One possible, partial explanation of these results is that intelligence enhances individuals’ care of their own health because it represents learning,
reasoning, and problem-solving skills useful in preventing chronic disease and accidental injury and in adhering to complex treatment regimens.
There is little evidence showing the relationship between the Scholastic Assessment Test (SAT) and g (general
intelligence). Thisresearch established the relationship between SAT and g, as well asthe
appropriateness of the SAT as a measure of g, and examined the SAT as a premorbid
measure of intelligence. In Study 1, we used the National Longitudinal Survey of Youth 1979. Measures of g were extracted from the Armed Services Vocational Aptitude Battery and correlated with SAT scores of 917 participants.
The resulting correlation was .82 (.86 corrected for nonlinearity). Study 2 investigated the correlation between revised and recentered
SAT scores and scores on the Raven’s Advanced Progressive Matrices among 104 undergraduates. The resulting correlation
was .483 (.72 corrected for restricted range). These studies indicate that the SAT is mainly atest of g. We
provide equations for converting SAT scores to estimated IQs; such conversion could be useful for estimating premorbid
IQ or conducting individual difference research with college students.
Past attempts to get computers to ride bicycles have required an inordinate amount of learning time (1700 practice rides for a reinforcement learning
approach1, while still failing to be able to ride in a straight line), or have required an algebraic analysis of the exact equations of motion for the
specific bicycle to be controlled [2, 3]. Mysteriously, humans do not need to do either of these when learning to ride a bicycle. Here we present a two-neuron
network1 that can ride a bicycle in a desired direction (for example, towards a desired goal or along a desired path), which may be chosen or changed at
run time. Just as when a person rides a bicycle, the network is very accurate for long range goals, but in the short run stability issues dominate the behavior.
This happens not by explicit design, but arises as a natural consequence of how the network controls the bicycle.
Associations between reaction times and mental ability test scores have been widely reported in the literature on the information processing theories of
psychometric intelligence. There have been varying estimates of the strength of these associations, which are typically reported in terms of correlation
coefficients.
In a previous article, we reported correlations between scores on Part 1 of the Alice Heim 4 and simple and 4-choice reaction time of −0.31 and −0.49,
respectively, derived from a population based sample of 900 residents of the West of Scotland aged 56. The use of the Pearson, or product moment, correlation
coefficient to summarise the association between reaction time and mental test ability assumes that they jointly have a bivariate normal distribution and that the relationship between them is
linear. The differentiation hypothesis can be construed as implying that the relationship should be nonlinear with a stronger relationship at lower levels of
mental ability.
We examined in detail the relationships underlying these correlations to assess whether they adequately represented the strength of the association and to test
for any departure from linearity. For 4-choice reaction time, the correlation is a good summary of the relation to AH4 score. However, the relation of AH4 and
simple reaction time is more complex and nonlinear
Hemispherectomy has been performed in the treatment of epilepsy in association with hemiplegia for over 50 years. However, the optimal timing of surgery with respect to age at presentation and the influence of underlying
pathology on outcome is only slowly emerging.
At follow-up, 52% were seizure free, 9% experienced rare seizures, 30% showed >75% reduction in seizures and 9% showed <75% seizure reduction or no
improvement. Seizure freedom was highest in those with acquired pathology (82%), followed by those with progressive pathology (50%) and those with developmental
pathology (31%). However, seizure freedom, rare seizures or >75% reduction in seizures occurred in 100% of those with progressive pathology, 91% of those with
acquired and 88% of those with developmental pathology, indicating a worthwhile seizure outcome in all groups. Hemiplegia remained unchanged following surgery in
22 out of 33 children, improved in 5 and was worse in 6. No large cognitive deterioration or loss of language occurred, and 4 children showed large cognitive
improvement. Behavioural improvement was reported in 92% of those who had behaviour problems pre-operatively.
…The cognitive category of the patients pre-operatively assessed according to IQ or DQ is shown in Figure 1.
Figure 1 shows that the majority of children (88%) with developmental pathology, including all 10 subjects with hemimegalencephaly, exhibited
severe cognitive/developmental delay. The majority of patients with acquired pathology (64%) also showed severe delay and a further 27% showed moderate delay.
Those with Rasmussen encephalitis were most likely to have normal levels of cognitive function (three out of 4) whilst the 2 children with Sturge-Weber syndrome
were in the severe and moderate impairment groups. 12 children (36%) had shown evidence of developmental regression prior to surgery.
Particular difficulty with expressive language was noted in 6 subjects and was anticipated in 2 subjects with Rasmussen encephalitis of the left hemisphere who
came to surgery at 3.8 and 4.2 years of age, respectively. One was developmentally normal and the other was only mildly developmentally delayed prior to surgery.
One showed very slurred speech, which was reduced in quantity during formal assessment, but developed clear speech immediately prior to surgery and the other
became aphasic 2 weeks prior to surgery. One further subject with left-sided pathology resulting from a congenital MCA infarction was 2.3 years at the time of surgery with severe developmental delay. The 3 remaining subjects showed abnormal
pathology of the right hemisphere and when assessed at age 1.5, 2.6 and 12 years, respectively, were thought to be severely developmentally delayed thereby making
language assessment difficult particularly in the 2 younger patients. In the opinion of experienced examiners, however, these children exhibited expressive
language difficulties beyond those which would have been predicted from cognitive performance and comprehension. The pathology was developmental in one, acquired
in one and the other child had Sturge-Weber syndrome.
Behaviour difficulties were present in 12 children (36%). The most common problem was difficulty with concentration (75%), followed by fluctuating mood with or
without socially intrusive behaviour (66%). 25% showed temper tantrums or aggression. The duration of seizures prior to surgery (median 7.38 years) and hence age
at surgery was statistically-significantly greater in those with behaviour problems compared with those without (median duration of seizures 2 years, Mann-Whitney U test p = 0.0033). The median duration of seizures prior to surgery
in those with acquired pathology was statistically-significantly longer at 7.75 years compared with 2.6 years and 1.9 years in the developmental and progressive
pathology groups, respectively (Kruskal-Wallis p = 0.0004). Behaviour problems were most common in the group with acquired pathology (73%), followed by
the group with progressive pathology (33%) and least common in those with developmental pathology (12.5%). There was no apparent association between the category
of cognitive performance and the presence or absence of behaviour problems.
Figure 1: Summary of pre-operative developmental categories of patients. The percentage of individuals in each developmental
category on the vertical axis is plotted against underlying pathology on the horizontal axis.
Creatine supplementation is in widespread use to enhance sports-fitness performance, and has been trialled successfully in the treatment of neurological,
neuromuscular and atherosclerotic disease. Creatine plays a pivotal role in brain energy homeostasis, being a temporal and spatial buffer for cytosolic and
mitochondrial pools of the cellular energy currency, adenosine triphosphate and its regulator, adenosine diphosphate. In this work, we tested the hypothesis that
oral creatine supplementation (5 g d(-1) for six weeks) would enhance intelligence test scores and working memory performance in 45 young adult, vegetarian
subjects in a double-blind, placebo-controlled, cross-over design. Creatine supplementation had a significant positive effect (p < 0.0001) on both
working memory (backward digit span) and intelligence (Raven’s Advanced Progressive Matrices), both tasks that require speed
of processing. These findings underline a dynamic and significant role of brain energy capacity in influencing brain performance.
In the 1920s and 1930s basic theories of intellectual ability were developed along with operational tests which proved effective in predicting job performance
(Spearman 1927; Thorndike 1936). In a series of studies and meta-analyses throughout the 1970s and 1980s, Schmidt and Hunter showed that cognitive
ability was the best overall predictor of job performance (Hunter & Hunter 1984; Hunter 1986; Schmidt & Hunter 1981). Partially in reaction to the
meta-analytic findings, research to expand on the definitions of competencies continued. The development of competencies by McClelland (1973) was followed by a
discussion of tacit knowledge (Wagner &
Sternberg 1985), practical intelligence (Sternberg & Wagner 1986), and multiple intelligence (Gardner 1999). In the 1990s, emotional intelligence
became the intelligence of interest (Feist & Barron 1996; Goleman 1995, 1998a, 1998b; Graves 1999; Mayer et al 1990).
All these new theories and proposed measurement instruments pose a challenge to traditional cognitive ability tests since it is claimed that these tests are
more valid and have lower adverse impact. It is our contention that many of these tests are nothing more than pop psychology. It is distressing to see such books
(ie. Goleman 1998b) quoted as if they had some merit. We will review the themes present throughout all of these “creative” concepts and examine whether they
have practical implications and can withhold legal scrutiny in the public and private sector.
Here we describe the associations between scores on a test of general mental ability (Alice Heim 4, AH4) and reaction times using a ‘Hick’-style device. The
sample is 900 people aged 56 years who are broadly representative of the Scottish population [West of Scotland 20–07 Study].
AH4 Part I total scores correlated −0.31 with simple reaction time, −0.49 with 4-choice reaction time, and −0.26 with intraindividual variability in both
reaction time procedures. The correlation between AH4 scores and the difference between simple and 4-choice reaction time was −0.15. Separate analyses were
conducted after partitioning the total group according to sex, educational level, social class grouping, and number of errors on the 4-choice reaction time task.
None of these factors statistically-significantly altered the effect-sizes.
This is the first report of reaction time and psychometric intelligence in a large, normal sample of the population. It provides a benchmark for other studies
and suggests larger effect sizes than the majority of present studies, which are dominated by young student samples.
[Keywords: intelligence, IQ, reaction time, information processing]
The military drawdown program of the early 1990’s provides an opportunity to obtain estimates of personal discount rates based on large numbers of people making
real choices involving large sums. The program offered over 65,000 separatees the choice between an annuity and a lump-sum payment. Despite break-even discount
rates exceeding 17%, most of the separatees selected the lump sum—saving taxpayers $2.87$1.702001 billion in separation costs. Estimates of discount rates range from 0 to over 30% and vary with education,
age, race, sex, number of dependents, ability test score, and the size of payment.
The American educational system has been frequently charged with discriminatory practices regarding the treatment of minority groups. Specifically, African
American students have been thought to achieve intellectual and academically below other ethnic groups. The misconception of underachievement led to and was
reinforced by systematic discriminatory practices such as ability grouping, tracking and overrepresentation in educable mentally handicapped special education
programs. One controversial issue has been the overrepresentation of African American students in the special education process. The roles that teachers, school
personnel and school psychologists play, from the referral through the assessment given, are crucial to the inquiry of why African Americans experience
differential educational outcomes in the public school environment.
To further investigate the trend of overrepresentation, we focused on the intellectual measures given and the presence of construct bias. Specifically,
the WISC-III was discussed because of it being the most frequently used IQ measure. One emergent technique to assess
measurement invariance has been multi-sample confirmatory factor analysis (MCFA). The purpose of this research study was
to conduct amulti-sample confirmatory factor analysis of the WISC-III to determine measurement invariance
between African American and Caucasian students.
Using MCFA, the WISC-III scores of 545 African American and Caucasian
students in the Hillsborough County Public School System were examined to test the presence of measurement invariance. Multi-sample confirmatory factor analysis
provided a more direct comparison in the investigation of factor structure equivalence across groups. A 4 step series of analyses was conducted during which all
possible parameters (factor loadings, the factor correlation, factor variances, and subtest unique and error variances) were constrained for both groups. From the
results obtained there were no statistically-significant differences in the 2 factor model of the [?] the sample of African American and Caucasian students. Within
each series of analysis there were no statistically-significant changes in chi square or decline in model fit for either group. Therefore, the proposed 2 factor
model as delineated in the WISC-III manual provided a relatively good fit to the sample data.
Infants with hydranencephaly are presumed to have a reduced life expectancy, with a survival of several weeks to months. Rarely, patients with prolonged
survival have been reported, but these infants may have had other neurologic conditions that mimicked hydranencephaly, such as massive hydrocephalus or holoprosencephaly. We report two infants with prenatally acquired hydranencephaly who survived for 66 and 24 months. We
reviewed published reports to ascertain the clinical and laboratory features associated with survival of more than 6 months. This review demonstrates that
prolonged survival up to 19 years can occur with hydranencephaly, even without rostral brain regions, with isoelectric electroencephalograms, and with
absent-evoked potentials. Finally, the ethical aspects of these findings, as they relate to anencephaly and organ transplantation, are discussed.
This article meta-analytically summarizes the literature on training motivation, its antecedents, and its relationships with training outcomes such as
declarative knowledge, skill acquisition, and transfer. statistically-significant predictors of training motivation and outcomes included individual
characteristics (eg. locus of control, conscientiousness, anxiety, age, cognitive ability, self-efficacy, valence, job involvement) and situational characteristics
(eg. climate). Moreover, training motivation explained incremental variance in training outcomes beyond the effects of cognitive ability. Meta-analytic path
analyses further showed that the effects of personality, climate, and age on training outcomes were only partially mediated by self-efficacy, valence, and job
involvement. These findings are discussed in terms of their practical importance and their implications for an integrative theory of training motivation.
The 1968 publication of the Rosenthal and Jacobson’s Pygmalion in the Classroom offered the optimistic message that raising teachers’ expectations
of their pupils’ potentials would raise their pupils’ intelligence. This claim was, and still is, endorsed by many psychologists and educators. The original study,
along with the scores of attempted replications and the acrimonious controversy that followed it, is reviewed, and its consequences discussed.
An analysis of information collected from historical archives reveals a wealth of data on 30 female researchers who worked in various capacities with
Dr. Lewis Terman in conducting his classic longitudinal study, Genetic Studies of Genius (1925), on 1,528 gifted children in California. The
published and unpublished papers, memoranda, and research field notes of these researchers, their respective correspondence With Terman and each other, and some
contacts with a living member of the research team and family members were used for this analysis. Although the information is incomplete on some of the women,
most of them appeared to have had satisfying personal lives in addition to productive professional careers. Not only did they each contribute greatly to the actual
work of carrying out Terman’s research conception, they also represent a continuum of life-long productivity. Personal responsibilities nay have had more to do
with their subsequent levels of productivity than societal expectations or conventions.
The results of 2 evaluation studies with respect to a programme for enhancing inductive reasoning ability of third grade students are presented. The programme
is a classroom version of the German programme Denktraining für Kinder 1 (“Cognitive training for children”; Klauer 1989).
In the first formative evaluation study, 2 experimental groups with 30 students in total and one control group with 9 students were involved. Observations
during the lessons, and teachers’ reports showed that teachers were able to implement the programme. Both experimental groups statistically-significantly
outperformed the control group on a posttest immediately after the programme and on a follow-up test 3 1⁄2 months later. Further analyses of the data revealed
tentative evidence of the superiority of a direct teaching method.
In the second summative evaluation study, the same programme was applied to a larger sample (experimental groups: n = 99 in total; and control groups:
n = 232 in total) of third grade students. On the basis of Study 1, the programme instructions were slightly changed. The experimental groups scored
statistically-significantly higher on a posttest 3 months after completion of the programme.
Structural and measurement invariance of the WISC-III was examined across White (n = 1542),
Black (n = 338), and Hispanic (n = 242) subgroups of the standardization sample. Data analyzed were separate subtest scaled score and raw score
variance-covariance matrices for each subgroup. Both sets of scores were analyzed as scaled scores may mask unique response patterns within each subgroup.
Within groups and simultaneous maximum
likelihood confirmatory factor analyses were performed to fit data to four competing correlated factor models: (a) model consisting of all 13 WISC-III subtests; (b) a verbal-performance factor model; (c) a Verbal Comprehension, Perceptual Organization, and Processing Speed
model; and (d) a Verbal Comprehension, Perceptual Organization, Freedom From Distractibility, and Processing Speed model. Freedom It was hypothesized that verbal
and performance factors would fit the data best for each group. It was further hypothesized that factor loading patterns would differ across groups and that
analyses of raw score data would reveal idiosyncratic response patterns across groups.
The chi-square/df ratio, Tucker-Lewis Index, and Adjusted Goodness of Fit Index indicated that the 4-factor model fit both sets of data best within each
racial-ethnic group. These indices and an incremental fit index demonstrated that the 4-factor model exhibited structural and measurement invariance across groups.
The same 4 factors explained the variance-covariance matrices of each group and WISC-III subtests are measured with
the same reliability. Differences in rank order of subtest factor loadings were observed when scaled score data were analyzed which was not expected.
Test development procedures safeguarding against bias and acculturation factors may account for the structural and measurement invariance of the 4-factor model.
Item content of the WISC-III was meant to appeal to a multicultural society. Geographic proximity and intermixing
between racial-ethnic groups may also account for the results. The 4-factor model may be used clinically in assessing children from White, Black, and Hispanic
groups. Since the groups studied were heterogeneous with respect to cultural practices and socioeconomic status, practitioners should not disregard racial-ethnic
group membership when assessing children from diverse backgrounds.
To show why the importance of intelligence is often misperceived, an analogy between single test items and single nontest actions in everyday life is drawn. 3
requirements of good test items are restated, and the analogy is employed to account for underrecognition of the importance of general intelligence in everyday
actions, which often fail to meet the requirements and thus fail as intelligence measures for reasons that have little to do with their dependence on intelligence.
A new perspective on the role of intelligence in nontest actions is introduced by considering its operation at 3 levels: that of the individual, that of the near
context of the individual, and that of entire populations. Social scientists have misunderstood the operation and impact of IQ in populations by confining
attention to the individual level. A population-IQ-outcome model is explained that tests for the pooled effects of intelligence at all 3 levels on differences
between 2 populations in prevalences of certain outcomes. When the model fits, the difference between 2 populations in the outcome measured is found commensurate
with the difference in their IQ or general intelligence distributions. The model is tested on and found to fit prevalences of juvenile delinquency, adult crime,
single parenthood, HIV infection, poverty, belief in conspiracy rumors, and key opinions from polls about the O.
J. Simpson trial and the earlier Tawana Brawley case. A deviance principle is extracted from empirical findings to indicate kinds of outcome the model will not
fit. Implications for theories of practical and multiple intelligences are discussed. To understand the full policy implications of intelligence, such a
fundamentally new perspective as that presented here will be needed.
We examined whether genetic and environmental effects on academic achievement changed as a function of the quality of the children’s environment.
The study included a variety of observed environmental measures such as parental cognitive stimulation and poverty level, longitudinal information about
previous environmental conditions, and a larger than average number of children who grew up in deprived environments. The sample consisted of 1664 pairs of full
siblings, 366 pairs of half siblings, and 752 pairs of cousins who were on average 9.58 years old.
Both a simple descriptive approach as well as statistical-significance tests performed with multilevel regression analyses showed little evidence for
genotype-environment interactions. There was only a slight trend consisting of a linear decrease of total variance or nonshared environmental effects from deprived
to good environments.
When asked whether he would discuss man in theOrigins of the Species, Darwin replied, ‘I think I shall avoid the subject, as so surrounded with
prejudices, though I fully admit it is the highest and most interesting problem for the naturalist’. Galton on the other hand replied to the same question, ‘I
shall treat man and see what the theory of heredity of variations and the principles of natural selection mean when applied to man’ (Pearson, 1914–30, Vol. II, p.
86).
Correlation matrices were computed on academic achievement and family environment measures using longitudinal data on siblings. The 8 × 8 correlation matrices
were computed on Hispanics, blacks, and whites separately. When compared employing a LISREL method, the matrices
were equal across these ethnic-racial groups. Hence, developmental processes influencing academic achievement may be similar in Hispanics, blacks, and
whites. A structural equation model with 4 free parameters was fitted successfully to a correlation matrix pooled across groups. As a single structural equation
model fitted all groups, the existence of minority-specific developmental processes was not supported.
The human brain is a product of Darwinian evolution and as such it has evolved from a set of underlying structures that constrain its ultimate potential. A
combination of the physical size of the dendrites, axons and the associated blood vessels, and therefore their related signal space, limit the amount of
information the brain can effectively store and process. By analysing the inter-relationship of the key constraints we have shown that:
The maximum effective diameter of the human brain is around 10–20cm.
The interconnectivity of neurons is dictated by thermal, volumetric, signal processing and transmission constraints, and is not, a priori, a key system
parameter for intelligence.
Intelligent signal processing inflicts an order of magnitude time constraint on an optimised structure.
Thus we contend that the human brain is at, or near, the capability limits that a neuron-based system allows. This implies that our future evolutionary
potential is limited and that, as a species, Homo Sapiens may be near the pinnacle of achievable intelligence using current cellular carbon technology.
The reviewer notes that this book (see record 1994-98748-000) has a simple but powerful thesis: There are substantial individual and group differences in
intelligence; these differences profoundly influence the social structure and organization of work in modern industrial societies, and they defy easy remediation.
In the current political milieu this book’s message is not merely controversial, it is incendiary. Commentators from across the political spectrum have documented
the profound social changes that all industrialized societies are undergoing at the end of the 20th century—erosion of the middle class, loss of
well-paying manufacturing jobs, and an emerging information age in which individual success will depend on brains not brawn. This book differs from other works by
focusing on intelligence, rather than education or social class, as a causal variable. The authors argue that general cognitive ability is a major determiner of
social status and that variance in general mental ability is largely attributable to genetic factors—propositions that are certainly endorsed by many experts in
the field. The book explicitly disclaims, however, that general mental ability is the only determinant of social status.
Comments that after considering the responses of R. E. Boyatzis (see record 1994-27864-001) and D. C. McClelland (see record 1994-27871-001) and reviewing
additional reports by these authors, the conclusions drawn by G. V. Barrett and R. L. Depinet’s (see record 1992-03797-001) article on competence testing are
reinforced. If McClelland’s concept of competencies is to make a contribution to psychology, he must present empirical data to support his contention. Three sets
of data are presented to illustrate this point.
[Barrett points out that according to McClelland’s own analyses, his proposed screening methods barely predict job performance, are usually not even
statistically-significant, would violate employment/discrimination law, and that McClelland’s claim that his methods don’t work because of the “knowledge-testing-educational complex” is an excuse.]
Responds to the criticisms of G. V. Barrett and R. L. Depinet (see record 1992-03797-001) regarding the author’s
(1973) article on competence testing. D. C. McClelland agrees with Barrett and Depinet’s dismissal of competency testing as a poor alternative to ability testing.
McClelland holds that well-designed competency-based tests could make an important contribution to selecting people who are better suited for certain jobs, but
that these tests will not be developed until there is a strong commitment by psychologists to develop them and the necessary financial support is available.
Restriction of range is a frequently acknowledged issue in estimating the validity of predictors of academic performance in graduate school. Data obtained from
a doctoral program in a psychology department where graduate students were admitted without regard to Graduate Record Examination (GRE) scores yielded essentially identical standard deviations on this test for the 204 applicants and 138 enrolled students.
The GRE-Total validity coefficients obtained on subjects in the enrolled sample ranged from .55 through .70; these
values are considerably higher than those typically reported. The data are congruent with the argument that uncorrected GRE validity coefficients yield biased estimates of the unknown validity in unrestricted applicant pools.
The data on a group of 22 rats, each measured for their speed of reasoning, accuracy of reasoning, response flexibility, and attention for novelty, were
subjected to two different methods of factor analysis. By both methods, the correlation matrix of their performance was consistent with a single-factor model. In a
second cohort of rats, where brain size was known, the score for this ‘general factor’ was computed. The regression for brain weight and the general factor was
statistically-significant.
[Keywords: intelligence, reasoning, rat, methylazoxymethanol, brain, mental retardation]
In light of the outdatedness of empirical research on IQ constancy among gifted children, and with the aim of examining possible cross cultural differences, the
present study investigated the issue within the Israeli context.
Specifically, we analyzed the constancy of IQ scores on the WISC-R test for 161 kindergartners through
4th graders identified as gifted by the Jerusalem Psychological Service in 1981/82–1983/84. Assessment of IQ constancy was based on a retest
administered to subjects 1–4 years after the first test.
Results showed that 86% of the children in the sample were defined as gifted also on retest. Mean absolute differences between testings ranged from 1⁄3 to 1⁄2
SD (5–8 IQ points) for Verbal, Performance and Full-scale IQ scores, and from 1⁄2 to 3⁄4 SD for subtest scores. On the whole, Performance scores remained constant,
while Verbal scores tended to decline. There were no consistent differences attributable to age of identification or measurement interval.
David C. McClelland’s 1973 article has deeply influenced both professional and public opinion. In it, he presented 5 major themes: (1) Grades in school did not
predict occupational success, (2) intelligence tests and aptitude tests did not predict occupational success or other important life outcomes, (3) tests and
academic performance only predicted job performance because of an underlying relationship with social status, (4) such tests were unfair to minorities, and (5)
“competencies” would be better able to predict important behaviors than would more traditional tests. Despite the pervasive influence of these assertions, this
review of the literature showed only limited support for these claims.
Although numerous studies have examined the relationship between communication apprehension (CA) and cognitive performance (eg. IQ grade point averages, course
grades, assignment grades, and test scores), the findings are equivocal.
One area of findings suggests that students in the traditional educational environment experiencing high CA are at a distinct disadvantage when compared to
their low or moderate counterparts. A second area of findings suggests that no statistically-significant relationship exists. A third area indicates that the
nature of the instructional environment is a statistically-significant mediating variable that moderates the effects of CA on cognitive performance.
In the present study, a meta-analysis was conducted of 23 manuscripts containing information on 30 experiments that examined CA and cognitive performance.
Results confirmed a statistically-significant negative correlation between CA and cognitive performance.
Implications for future research and classroom instruction are discussed.
Previous attempts to summarize the vehicular accident involvement literature have been non-quantitative. Outcomes of these reviews have also reflected the
equivocalness of research in this area. In an attempt to synthesize the diverse research findings into a collective result, a meta-analysis procedure that
controlled for sampling error was used.
4 classes of variables were identified as predictors of vehicular accident involvement. These were information-processing, cognitive ability, personality, and
demographic/biographical variables. Moderate-to-marginally favorable overall meta-analysis results were obtained for selective attention, regard for authority,
locus of control, and cognitive ability as predictors of vehicular accident involvement.
Suggestions and directions for future research are discussed.
The purpose of this review was to integrate validity evidence relevant to the primary use of the Armed Services Vocational Aptitude Battery (ASVAB) as a selection and classification tool for military manpower, personnel, and training systems. The review covers
the period from the first use of ASVABForm 1 in 1966 in the DODStudent Testing Program to the latest reports of the validity for ASVAB Forms 11, 12, 13, and 14. The review presents the evidence for the construct, content, and criterion-related
validity of the ASVAB. 172 studies from the military and civilian sectors and from the professional
literature were reviewed and summarized to show averaged validity for military occupations. Reviewed studies established the validity of the ASVAB as a predictor of success in military technical training schools, and its validity for other criteria such as
first-term attrition and job performance. Implications of the review for the military selection and classification systems are discussed.
…This review discusses the validity of the ASVAB for a number of different types of criteria. Among them
are final technical school training grade, time-to-completion for self-paced technical training courses, attrition from technical training, first-term attrition,
and experimental job performance measures.
The primary conclusion from the review of the literature is that the ASVAB aptitude composites andArmed Forces Qualification Test (AFQT) are valid predictors of final school
grades, self-paced technical school completion times, first-term attrition, and job performance measures. The consistent finding from empirical, criterion-related
studies shows that the five composites examined in this review (Mechanical-M, Administrative-A, General-G, Electronics-E and the AFQT) all predict final technical school grades with an order of magnitude between 0.55 and 0.60 (corrected for restriction in
range). The validity coefficients of these five ASVAB composites against other criteria are lower, but still
appreciable.
An important question in studies of mental ability concerns the effect of parental socio-economic status (SES) on the
IQ of their offspring. Only a full cross-fostering study, including children born to biological parents from the most highly contrasting SES and adopted byparents with equally contrasting SES, can answer this
question.
Previous adoption studies using incomplete cross-fostering designs1–3 have indicated an effect of postnatal environment on the IQ of children
born to low-SES backgrounds and adopted by high-SESparents. They have not
shown whether a low SES reduces the IQ ofchildren born to high-SES parents or
whether the SES of biologicalparents has an effect on IQ, or whether the effect of the SES ofadoptive parents is independent of the SES of biological parents.
We present a full cross-fostering study dealing with IQ, and find that children adopted by high-SES parents score
higher than childrenadopted by low-SES parents; children born to high-SES
parents scorehigher than children born to low-SES parents; and that there is no evidence for an
interaction between these 2 factors on children’s IQ.
The Model of School Learning, first published 25 years ago, has taken its place as a useful guide in research on teaching and learning in schools. The model
accounts for variations in school learning with five classes of variables, three, of which can be expressed in terms of time, the other two in terms of
achievement. Most aspects of the model have been confirmed, although details remain to be filled out by further research. Ways that the model might be used to
address current problems in education are considered. The model’s emphasis on aptitude as a determinant of time needed for learning suggests that increased efforts
be placed on predicting student potentialities and designing instruction appropriate to those potentialities, if ideals of equal opportunity to learn are to be
achieved within a diversity of educational objectives.
The cognitive correlates literature suggests that a general ability, probably Spearman’s g, underlies most information processing/intelligence relationships.
In the present paper we suggest that the nature of g is clarified by the following patterns: (a) response consistency has better predictive and
convergent validity than does response speed, and (b) tasks which demand dynamic memory processing predict intelligence better than do tasks which require only
stimulus encoding and simple stimulus/response translations. Accordingly, g appears related to the ability to flexibly and consistently reconfigure the
contents of working memory.
A possible physiological basis of this ability is the recruitment of the transient neural assemblies which underlie thought (after Hebb 1949).
Race and ethnic differences in measures of achievement, information, and award of educational credentials are reviewed starting with 1960 Project Talent data. Data are more consistently available for blacks and whites than for
other minorities, while accurate identification of the latter groups is made difficult by variability in terminology.
Nevertheless, blacks, Mexican Americans, Puerto Ricans, and American Indians today still have substantial deficits in basic academic skills and information
although small gains have been made. Asian Americans have small deficits in verbal skills and small advantages in quantitative skills in comparison to the white
majority.
Several kinds of evidence converge to support a description of the deficits as the inadequate learning syndrome (ILS).
The ILS socialepidemic is as serious in its way as the AIDS epidemic.
Targetedsupport of at least the same magnitude as with AIDS is required forresearch and development
with respect to ILS. Remedies that are typically discussed are superficial and ineffective.
[Literature review of Simonton & other’s research into life history predictors of great accomplishment in the arts/sciences/politics/etc, particularly
childhood: what variables seem to correlate with later eminence? Simonton discusses as predictors: 1. intelligence; 2. birth order (first-born); 3. extreme
motivation/drive; 3. parental loss/orphanhood (!); 4. a previous generation of role models to imitate; 5. formal education (or lack thereof); 6. global
circumstances/‘zeitgeist’.
On nature-nurture, Simonton deprecates the role of genetics, arguing that genius counts fluctuate too much and are too sporadic over time to reflect primarily
genetics, but see Lykken et al on ‘emergenesis’, dysgenics, and tail effects in order statistics (especially the Lotka curve/log-normal distribution‘leaky pipeline’ Simonton is so familiar
with) for why this argument is weak.]
The study shows that although many features of copulation in decorticate male rats are normal, copulatory success is importantly dependent upon the control of
approaches exerted by the normal female rat. Copulation by neonatally decorticated adult rats and normal adult rats was studied in cohabitation and videotaped
tests. Seven of 10 decorticate rats and 6 of 6 normal rats sired pups in the cohabitation test. When initially paired with ovariectomized and primed female rats,
in the videotaped tests, all normal rats, but only one decorticated rat, copulated. All decorticate rats made movements indicative of sexual interest including:
treading on the female’s back, passing over the female, and sniffing the female’s genitals. After activating stimulation, 5 of 6 remaining decorticated males
copulated. After one successful mount the remaining copulatory patterns proceeded relatively normally. Numbers of mounts, intromissions, ejaculations,
postejaculatory songs, and the intromission and ejaculatory patterns were like those of control rats, although the decorticate rats had fewer mount bouts and
showed abnormalities in the execution of movements. Precopulatory movements were notated, using the Eshkol-Wachmann system, and compared with copulatory movements.
Non-copulatory and copulatory approaches were similar, except that clasping appeared to be the key movement involved in the transition of an approach movement into
a copulatory movement. The analysis also showed that the females’ movements of hopping, turning, and kicking were important for regulating the males’ approaches,
and were instrumental in the success achieved by the decorticated males. The study shows that although the cortex, insofar as it facilitates the appearance of
certain movements and contributes to their efficiency, is involved in male sexual activity, in its absence well organized sexual activity is possible, although
this is dependent, in part, upon the behaviour of the female.
1985-johnson.pdf: “Galton's data a century later”, Ronald C. Johnson, Gerald E. McClearn, Sylvia Yuen, Craig
T. Nagoshi, Frank M. Ahern, Robert E. Cole (1985-01-01)
This article is a synopsis of a triarchic theory of human intelligence. The theory comprises three subtheories: a contextual subtheory, which relates
intelligence to the external world of the individual; a componential subtheory, which relates intelligence to the individual’s internal world; and a two-facet
subtheory, which relates intelligence to both the external and internal worlds. The contextual subtheory defines intelligent behavior in terms of purposive
adaptation to, shaping of, and selection of real-world environments relevant to one’s life. The normal course of intelligent functioning in the everyday world
entails adaptation to the environment; when the environment does not fit one’s values, aptitudes, or interests, one may attempt to shape the environment so as to
achieve a better person-en
![Table 3: Decomposition of variance [95% CI] for each measure and subtest of cognitive ability. Note: 95% CIs are computed from each parameter’s 200 bootstrap iterations (Efron & Tibshirani 1993) for each scale. Non-shared environment is computed by subtracting the heritability, parental environment, sibling environment, and gene-environment (G-E) covariance from 1. For full parameter estimates, see SI Table S12. Column values add up to 1, total phenotypic variance.](/images/iq/2021-willoughby-table3-acegeneticmodelestimatesofcognitivescores.png)
