Nootropics

Notes on nootropics I tried, and my experiments
nootropics, psychology, experiments, predictions, statistics, DNB, shell, Haskell, R, power-analysis, survey, Bayes, reviews
2010-01-022018-12-20 in progress certainty: likely importance: 7


A record of I have tried, with thoughts about which ones worked and did not work for me. These anec­dotes should be con­sid­ered only as anec­dotes, and one’s efforts with nootrop­ics a hobby to put only lim­ited amounts of time into due to the inher­ent lim­its of drugs as a force-mul­ti­plier com­pared to other things like pro­gram­ming1; for an ironic coun­ter­point, I sug­gest the reader lis­ten to a video of “I Feel Fan­tas­tic” while read­ing.

Background

Your mileage will vary. There are so many para­me­ters and inter­ac­tions in the brain that any of them could be or respon­si­ble path­way, and one could fall prey to the com­mon U-shaped (eg. ; see also & ) which may imply that the smartest are those who ben­e­fit least23 but ulti­mately they all cash out in a very few sub­jec­tive assess­ments like ‘ener­getic’ or ‘moti­vated’, with even appar­ently pre­cise descrip­tions like ‘work­ing mem­ory’ or ‘ver­bal flu­ency’ not telling you much about what the nootropic actu­ally did. It’s tempt­ing to list the nootrop­ics that worked for you and tell every­one to go use them, but that is merely (and the more nootrop­ics - or med­i­ta­tion styles, or self­-help books, or “get­ting things done” sys­tems - you try, the stronger the temp­ta­tion is to evan­ge­lize). The best you can do is read all the tes­ti­mo­ni­als and stud­ies and use that to pri­or­i­tize your list of nootrop­ics to try. You don’t know in advance which ones will pay off and which will be wast­ed. You can’t know in advance. And wasted some must be; to coin a Umeshism: if all your exper­i­ments work, you’re just fool­ing your­self. (And the corol­lary - if some­one else’s exper­i­ments always work, they’re not .)

The above are all rea­sons to expect that even if I do excel­lent self­-ex­per­i­ments, there will still be the old prob­lem of “” ver­sus “”: an exper­i­ment may be wrong or erro­neous or unlucky in some way (lack of inter­nal valid­i­ty) or be right but not mat­ter to any­one else (lack of exter­nal valid­i­ty). For exam­ple, alco­hol makes me sad & depressed; I could run the per­fect blind ran­dom­ized exper­i­ment for hun­dreds of tri­als and be extremely sure that alco­hol makes me less hap­py, but would that prove that alco­hol makes every­one sad or unhap­py? Of course not, and as far as I know, for a lot of peo­ple alco­hol has the oppo­site effect. So my hypo­thet­i­cal alco­hol exper­i­ment might have tremen­dous inter­nal valid­ity (it does prove that I am sad­der after ine­bri­at­ing), and zero exter­nal valid­ity (some­one who has never tried alco­hol learns noth­ing about whether they will be depressed after imbib­ing). Keep this in mind if you are minded to take the exper­i­ments too seri­ous­ly.

Some­what iron­i­cally given the stereo­types, while I was in col­lege I dab­bled very lit­tle in nootrop­ics, stick­ing to mela­tonin and tea. Since then I have come to find nootrop­ics use­ful, and intel­lec­tu­ally inter­est­ing: they shed light on in phi­los­o­phy of biol­ogy & evo­lu­tion, argue against naive psy­cho­log­i­cal dual­ism and for mate­ri­al­ism, offer cases in point on the his­tory of tech­nol­ogy & civ­i­liza­tion or recent psy­chol­ogy the­o­ries about addic­tion & willpow­er, chal­lenge our under­stand­ing of the of sta­tis­tics and psy­chol­ogy - where they don’t offer nifty lit­tle prob­lems in sta­tis­tics and eco­nom­ics them­selves, and are excel­lent fod­der for the young move­ment4; modafinil itself demon­strates the lit­tle-known fact that has no accepted evo­lu­tion­ary expla­na­tion. (The hard drugs also have more ram­i­fi­ca­tions than one might expect: how can one under­stand the his­tory of South­east Asia and the Viet­namese War with­out , or more con­tem­po­ra­ne­ous­ly, how can one under­stand the last­ing appeal of the Tal­iban in Afghanistan and the unpop­u­lar­ity & cor­rup­tion of the cen­tral gov­ern­ment with­out ref­er­ence to the Tal­iban’s fre­quent anti-drug cam­paigns or the drug-funded war­lords of the ?)

Golden age

Nootrop­ics have been around a long time, but they’ve never been so promi­nent, eas­ily accessed, cheap, or avail­able in such a vari­ety. I think there is no sin­gle fac­tor respon­si­ble but rather exist­ing trends pro­gress­ing to the point where it’s pos­si­ble to obtain much more obscurer things than before.

(In par­tic­u­lar, I don’t think it’s because there’s a sud­den new surge of drugs. FDA drug approval has been decreas­ing over the past few decades, so this is unlikely a pri­ori. More specifi­cal­ly, many of the major or hot drugs go back a long time. Bacopa goes back mil­len­nia, mela­tonin I don’t even know, pirac­etam was the ’60s, modafinil was ’70s or ’80s, ALCAR was ’80s AFAIK, Noopept & colu­rac­etam were ’90s, and so on.)

What I see as being the rel­e­vant trends are a com­bi­na­tion of these trends:

  1. the rise of IP scofflaw coun­tries which enable the man­u­fac­ture of known drugs: India does not respect the modafinil patents, enabling the cheap gener­ics we all use, and Chi­nese pirac­etam man­u­fac­tur­ers don’t give a damn about the FDA’s chill­ing-effect moves in the US. If there were no Indian or Chi­nese man­u­fac­tur­ers, where would we get our modafinil? Buy them from phar­ma­cies at $10 a pill or worse? It might be worth­while, but think of the chill­ing effect on new users.
  2. along with the pre­vi­ous bit of glob­al­iza­tion is an impor­tant fac­tor: ship­ping is ridicu­lously cheap. The most expen­sive S&H in my modafinil price table is ~$15 (and most are inter­na­tion­al). To put this in per­spec­tive, I remem­ber in the ‘90s you could eas­ily pay $15 for domes­tic S&H when you ordered online - but it’s 2013, and the dol­lar has lost at least half its val­ue, so in real terms, order­ing from abroad may be like a quar­ter of what it used to cost, which makes a big differ­ence to peo­ple dip­ping their toes in and con­tem­plat­ing a small order to try out this ’nootrop­ics’ thing they’ve heard about.
  3. as sci­en­tific papers become much more acces­si­ble online due to Open Access, dig­i­ti­za­tion by pub­lish­ers, and cheap host­ing for pirates, the avail­able knowl­edge about nootrop­ics increases dras­ti­cal­ly. This reduces the per­ceived risk by users, and enables them to edu­cate them­selves and make much more sophis­ti­cated esti­mates of risk and side-effects and ben­e­fits. (Take my modafinil page: in 1997, how could an aver­age per­son get their hands on any of the papers avail­able up to that point? Or get detailed info like the FDA’s pre­scrib­ing guide? Even assum­ing they had a com­puter & Inter­net?)
  4. the larger size of the com­mu­nity enables economies of scale and increases the peak sophis­ti­ca­tion pos­si­ble. In a small nootrop­ics com­mu­ni­ty, there is likely to be no one knowl­edge­able about statistics/experimentation/biochemistry/neuroscience/whatever-you-need-for-a-particular-discussion, and the avail­able funds increase: con­sider /r/Nootropics’s test­ing pro­gram, which is doable only because it’s a large lucra­tive com­mu­nity to sell to so the sell­ers are will­ing to donate funds for inde­pen­dent lab tests/Certificates of Analy­sis (COAs) to be done. If there were 1000 read­ers rather than 23,295, how could this ever hap­pen short of one of those 1000 read­ers being very altru­is­tic?
  5. Nootrop­ics users tend to ‘stick’. If modafinil works well for you, you’re prob­a­bly going to keep using it on and off. So sim­ply as time pass­es, one would expect the user­base to grow. Sim­i­larly for press cov­er­age and forum com­ments and blog posts: as time pass­es, the total mass increases and the more likely a ran­dom per­son is to learn of this stuff.

Defaults

I do rec­om­mend a few things, like or , to many adults, albeit with mis­giv­ings about any attempt to gen­er­al­ize like that. (It’s also often a good idea to get pow­ders, see the appen­dix.) Some of those peo­ple are helped; some have told me that they tried and the sug­ges­tion did lit­tle or noth­ing. I view nootrop­ics as akin to a bio­log­i­cal lot­tery; one good dis­cov­ery pays for all. I forge on in the hopes of fur­ther strik­ing gold in my par­tic­u­lar biol­o­gy. Your mileage will vary. All you have to do, all you can do is to just try it. Most of my expe­ri­ences were in my 20s as a right-handed 5’11 white male weigh­ing 190-220lbs, fit­ness vary­ing over time from not-so-fit to fairly fit. In rough order of per­sonal effec­tive­ness weighted by cost­s+side-effects, I rank them as fol­lows:

  1. Modafinil/armodafinil (less than weekly for overnight; skip­ping days for day use)
  2. Mela­tonin (dai­ly)
  3. Caffeine+thea­nine (dai­ly)
  4. Nico­tine (week­ly)
  5. Pirac­etam+choline (dai­ly)
  6. Vit­a­min D (dai­ly)
  7. Sul­bu­ti­amine (dai­ly)

(Peo­ple aged <=18 should­n’t be using any of this except harm­less stuff - where one may have nutri­tional deficits - like fish oil & vit­a­min D; mela­tonin may be espe­cially use­ful, thanks to the effects of screwed-up school sched­ules & elec­tron­ics use on teenagers’ sleep. Changes in effects with age are real - amphet­a­mi­nes’ stim­u­lant effects and modafinil’s his­t­a­mine-like side-effects come to mind as exam­ples.)

Prospects for Nootropics

I’ve become increas­ingly skep­ti­cal of nootrop­ics in gen­eral which aren’t either stim­u­lants or address­ing spe­cial cases (like vegetarians/creatine). This is par­tially due to mod­ern genomics con­vinc­ing me that intel­li­gence and most other indi­vid­ual differ­ences are dri­ven by muta­tion load: just a ton of small bits of sand in the gears of every­thing, with intel­li­gence as par­tic­u­larly acutely affected by prob­lems upstream (eg in mito­chon­dri­a). For that sort of con­cep­tion, it is extremely improb­a­ble to find any par­tic­u­lar sil­ver bul­let. We also have yet to find any genetic muta­tions which boost intel­li­gence by more than a triv­ial amount. On the other hand, personality/motivation seem some­what more sus­cep­ti­ble to mod­i­fi­ca­tion because per­son­al­ity is in selec­tion bal­ance: unlike intel­li­gence, where more is bet­ter, for every envi­ron­ment like the mod­ern envi­ron­ment there is a cer­tain amount of Extra­ver­sion which is opti­mal which is not being max­i­mally Extravert­ed, say, there is a cer­tain Con­sci­en­tious­ness level which is opti­mum to pre­vent slack­ing (but too much leads to behav­ioral inflex­i­bil­ity and sunk cost­s), and so on, and so there’s plenty of poten­tial lee­way for there to be some­thing to mod­ify moti­va­tion sub­stan­tial­ly, because evo­lu­tion does­n’t ever want to mod­ify motivation/personality too far from the pop­u­la­tion mean.

So, I don’t have any mas­ter list of par­tic­u­larly promis­ing can­di­dates. There’s noth­ing I think could be a sil­ver bul­let if only some­one would run a proper study.

Acetyl-l-carnitine (ALCAR)

No effects, alone or mixed with choline+pirac­etam. This is pretty much as expected from reports about (Exam­ine.­com), but I had still been hop­ing for energy boosts or some­thing. (Bought from Smart Pow­der­s.)

Adderall

is a mix of 4 salts (FDA adverse events), and not much bet­ter than the oth­ers (but per­haps less addic­tive); as such, like caffeine or metham­phet­a­mine, it is not strictly a nootropic but a cog­ni­tive enhancer and can be tricky to use right (for how one should use stim­u­lants, see “How To Take Ritalin Cor­rectly”). I ordered 10x10mg Adder­all IR off (). On the 4th day after con­fir­ma­tion from sell­er, the pack­age arrived. It was a harm­less look­ing lit­tle padded mail­er. Adder­all as promised: 10 blue pills with mark­ings, in a dou­ble ziplock baggy (rea­son­able, it’s not cocaine or any­thing). They matched pretty much exactly the descrip­tions of the generic I had found online. (Sur­pris­ing­ly, appar­ently both the brand name and the generic are man­u­fac­tured by the same phar­ma­cor­p.)

I took the first pill at 12:48 pm. 1:18, still noth­ing really - head is a lit­tle foggy if any­thing. later noticed a steady sort of men­tal energy last­ing for hours (got a good deal of read­ing and pro­gram­ming done) until my mid­night walk, when I still felt alert, and had trou­ble sleep­ing. (Zeo reported a ZQ of 100, but a full 18 min­utes awake, 2 or 3 times the usual amoun­t.)

At this point, I began think­ing about what I was doing. Black­-mar­ket Adder­all is fairly expen­sive; $4-10 a pill vs pre­scrip­tion prices which run more like $60 for 120 20mg pills. It would be a bad idea to become a fan with­out being quite sure that it is deliv­er­ing bang for the buck. Now, why the pirac­etam mix as the placebo as opposed to my other avail­able pow­der, cre­a­tine pow­der, which has much smaller men­tal effects? Because the ques­tion for me is not whether the Adder­all works (I am quite sure that the amphet­a­mines have effect­s!) but whether it works bet­ter for me than my cheap legal stand­bys (pirac­etam & caffeine)? (Does Adder­all have mar­ginal advan­tage for me?) Hence, I want to know whether Adder­all is bet­ter than my pirac­etam mix. Peo­ple fre­quently under­es­ti­mate the power of placebo effects, so it’s worth test­ing. (Un­for­tu­nate­ly, it seems that there is exper­i­men­tal evi­dence that peo­ple on Adder­all know they are on Adder­all and also believe they have improved per­for­mance, when they do not5. So the blind test­ing does not buy me as much as it could.)

Adderall blind testing

Blinding yourself

But how to blind myself? I used my pill maker to make 9 OO pills of pirac­etam mix, and then 9 OO pills of pirac­etam mix+the Adder­all, then I put them in a bag­gy. The idea is that I can blind myself as to what pill I am tak­ing that day since at the end of the day, I can just look in the baggy and see whether a placebo or Adder­all pill is miss­ing: the big cap­sules are trans­par­ent so I can see whether there is a crushed-up blue Adder­all in the end or not. If there are fewer Adder­all than place­bo, I took an Adder­all, and vice-ver­sa. Now, since I am check­ing at the end of each day, I also need to remove or add the oppo­site pill to main­tain the ratio and make it easy to check the next day; more impor­tantly I need to replace or remove a pill, because oth­er­wise the odds will be skewed and I will know how they are skewed. (Imag­ine I started with 4 Adder­alls and 4 place­bos, and then 3 days in a row I draw place­bos but I don’t add or remove any pills; the next day, because most of the place­bos have been used up, there’s only a small chance I will get a place­bo…)

This is only one of many ways to blind myself; for exam­ple, instead of using one bag, one could use two bags and instead blindly pick a bag to take a pill out of, bal­anc­ing con­tents as before. (See also my Vit­a­min D and day modafinil tri­al­s.)

Results

  1. Began dou­ble-blind tri­al. Today I took one pill blindly at 1:53 PM. at the end of the day when I have writ­ten down my impres­sions and guess whether it was one of the Adder­all pills, then I can look in the baggy and count and see whether it was. there are many other pro­ce­dures one can take to blind one­self (have an accom­plice mix up a sequence of pills and record what the sequence was; don’t count & see but blindly take a pho­to­graph of the pill each day, etc.) Around 3, I begin to won­der whether it was Adder­all because I am argu­ing more than usual on IRC and my heart rate seems a bit high just sit­ting down. 6 PM: I’ve started to think it was a place­bo. My heart rate is back to nor­mal, I am hav­ing diffi­culty con­cen­trat­ing on long text, and my appetite has shown up for din­ner (although I did­n’t have lunch, I don’t think I had lunch yes­ter­day and yes­ter­day the hunger did­n’t show up until past 7). Pro­duc­tiv­ity wise, it has been a nor­mal day. All in all, I’m not too sure, but I think I’d guess it was Adder­all with 40% con­fi­dence (an­other way of say­ing ‘placebo with 60% con­fi­dence’). When I go to exam­ine the bag­gie at 8:20 PM, I find out… it was an Adder­all pill after all. Oh dear. One lit­tle strike against Adder­all that I guessed wrong. It may be that the prob­lem is that I am intrin­si­cally a lit­tle worse today (nor­mal vari­a­tion? come down from Adder­al­l?).

    So, a change to the pro­to­col. I will take a pill every other day - a day to washout and reac­cli­mate to ‘base­line’, and then an exper­i­men­tal day. In sub­se­quent entries, assume there was either a at least one inter­ven­ing break or placebo day.

  2. Took ran­dom pill at 2:02 PM. Went to lunch half an hour after­wards, talked until 4 - more out­go­ing than my usual self. I con­tin­ued to be pretty ener­getic despite not tak­ing my caffeine+pirac­etam pills, and though it’s now 12:30 AM and I lis­tened to TAM YouTube videos all day while read­ing, I feel pretty ener­getic and am review­ing Mnemosyne cards. I am pretty con­fi­dent the pill today was Adder­all. Hard to believe placebo effect could do this much for this long or that nor­mal vari­a­tion would account for this. I’d say 90% con­fi­dence it was Adder­all. I do some more Mnemosyne, typ­ing prac­tice, and read­ing in a Mon­taigne book, and finally get tired and go to bed around 1:30 AM or so. I check the bag­gie when I wake up the next morn­ing, and sure enough, it had been an Adder­all pill. That makes me 1 for 2.

  3. Took pill 1:27 PM. At 2 my hunger gets the best of me (de­spite my usual tea drink­ing and caffeine+pirac­etam pills) and I eat a large lunch. This makes me sus­pi­cious it was placebo - on the pre­vi­ous days I had noted a con­sid­er­able appetite-sup­pres­sant effect. 5:25 PM: I don’t feel unusu­ally tired, but noth­ing spe­cial about my pro­duc­tiv­i­ty. 8 PM; no longer so sure. Read and excerpted a fair bit of research I had been putting off since the morn­ing. After putting away all the laun­dry at 10, still feel­ing active, I check. It was Adder­all. I can’t claim this one either way. By 9 or 10 I had begun to won­der whether it was really Adder­all, but I did­n’t feel con­fi­dent say­ing it was; my feel­ing could be fairly described as 50%.

  4. Break; this day/night was for try­ing armodafinil, pill #1

  5. Took pill around 6 PM; I had a very long drive to and from an air­port ahead of me, ideal for Adder­all. In case it was Adder­all, I chewed up the pill - by mak­ing it absorb faster, more of the effect would be there when I needed it, dur­ing dri­ving, and not lin­ger­ing in my sys­tem past mid­night. Was it? I did­n’t notice any change in my pulse, I yawned sev­eral times on the way back, my con­ver­sa­tion was not more volu­mi­nous than usu­al. I did stay up later than usu­al, but that’s fully explained by walk­ing to get ice cream. All in all, my best guess was that the pill was place­bo, and I feel fairly con­fi­dent but not hugely con­fi­dent that it was place­bo. I’d give it ~70%. And check­ing the next morn­ing… I was right! Final­ly.

  6. Took pill 12:11 PM. I am not cer­tain. While I do get some things accom­plished (a fair amount of work on the Silk Road arti­cle and its sub­mis­sion to places), I also have some diffi­culty read­ing through a fic­tion book (Sum) and I seem kind of twitchy and con­stantly shift­ing win­dows. I am weakly inclined to think this is Adder­all (say, 60%). It’s not my nor­mal feel­ing. Next morn­ing - it was Adder­all.

  7. Week-long break - armodafinil #2 exper­i­ment, vol­un­teer work

  8. Took pill #6 at 12:35 PM. Hard to be sure. I ulti­mately decided that it was Adder­all because I did­n’t have as much trou­ble as I nor­mally would in focus­ing on read­ing and then fin­ish­ing my novel (Sur­face Detail) despite my fam­ily watch­ing a movie, though I did­n’t notice any lack of appetite. Call this one 60-70% Adder­all. I check the next evening and it was Adder­all.

  9. Took pill at 10:50 AM. At 12:30 I watch the new Cap­tain Amer­ica6, and come out as ener­getic as I went in and was not hun­gry for snacks at all dur­ing it; at this point, I’m pretty con­fi­dent (70%) that it was Adder­all. At 5 I check, and it was. Over­all, pretty nor­mal day, save for lead­ing up to the third armodafinil tri­al.

  10. Just 3 Adder­all left; took ran­dom pill at 12:30. Hope­fully I can get a lot of for­mat­ting done on . I do man­age to do a lot of work on it and my appetite seems minor up until 8 PM, although if not for those two obser­va­tions; per­haps 60% that it was Adder­all. I check the next morn­ing, and it was not.

  11. Skip­ping break day since it was placebo yes­ter­day and I’d like to wind up the Adder­all tri­als. Pill at 12:24 PM. I get very hun­gry around 3 PM, and it’s an unpro­duc­tive day even con­sid­er­ing how much stress and aggra­va­tion and the 3 hours a failed Debian unsta­ble upgrade cost me. I feel quite sure (75%) it was place­bo. It was.

  12. Took pill at 11:27 AM. Mod­er­ately pro­duc­tive. Not entirely sure. 50% either way. (It’s place­bo.)

  13. Pill at 12:40 PM. I spend entirely too much time argu­ing mat­ters related to a LW post and on IRC, but I man­age to chan­nel it into writ­ing a new mini-es­say on my past intel­lec­tual sins. This sort of thing seems like Adder­all behav­ior, and I don’t get hun­gry until much lat­er. All in all, I feel eas­ily 75% sure it’s Adder­all; and it was.

  14. 12:18 PM. (There are/were just 2 Adder­all left now.) I man­age to spend almost the entire after­noon sin­gle-mind­edly con­cen­trat­ing on tran­scrib­ing two parts of a 1996 Toshio Okada inter­view (it was very long, and the for­mat­ting more chal­leng­ing than expect­ed), which is strong evi­dence for Adder­all, although I did feel fairly hun­gry while doing it. I don’t go to bed until mid­night and & sleep very poorly - despite tak­ing triple my usual mela­ton­in! Inas­much as I’m already fairly sure that Adder­all dam­ages my sleep, this makes me even more con­fi­dent (>80%). When I grumpily crawl out of bed and check: it’s Adder­all. (One Adder­all left.)

  15. 10:50 AM. Nor­mal appetite; I try to read through The Grand Strat­egy of the Byzan­tine Empire, slow going. Over­all, I guess it was placebo with 70% - I notice noth­ing I asso­ciate with Adder­all. I check it at mid­night, and it was place­bo.

  16. 11:30 AM. By 2:30 PM, my hunger is quite strong and I don’t feel espe­cially focused - it’s diffi­cult to get through the tab-ex­plo­sion of the morn­ing, although one par­tic­u­larly stu­pid poster on the DNB ML makes me feel irri­tated like I might on Adder­all. I ini­tially fig­ure the prob­a­bil­ity at per­haps 60% for Adder­all, but when I wake up at 2 AM and am com­pletely unable to get back to sleep, even­tu­ally rack­ing up a Zeo score of 73 (com­pared to the usual 100s), there’s no doubt in my mind (95%) that the pill was Adder­all. And it was the last Adder­all pill indeed.

My pre­dic­tions were sub­stan­tially bet­ter than ran­dom chance7, so my default belief - that Adder­all does affect me and (most­ly) for the bet­ter - is borne out. I usu­ally sleep very well and 3 sep­a­rate inci­dents of hor­ri­ble sleep in a few weeks seems rather unlikely (though I did­n’t keep track of dates care­fully enough to link the Zeo data with the Adder­all data). Between the price and the sleep dis­tur­bances, I don’t think Adder­all is per­son­ally worth­while.

Value of Information (VoI)

See also the dis­cus­sion as applied to order­ing modafinil & eval­u­at­ing sleep exper­i­ments.

The amphet­a­mine mix branded “Adder­all” is ter­ri­bly expen­sive to obtain even com­pared to modafinil, due to its tight reg­u­la­tion (a lower sched­ule than modafinil), pop­u­lar­ity in col­lege as a study drug, and report­edly moves by its man­u­fac­ture to exploit its priv­i­leged posi­tion as a licensed amphet­a­mine maker to extract more con­sumer sur­plus. I paid roughly $4 a pill but could have paid up to $10. Good stim­u­lant hygiene involves recov­ery peri­ods to avoid one’s body adapt­ing to elim­i­nate the stim­u­lat­ing effects, so even if Adder­all was the answer to all my woes, I would not be using it more than 2 or 3 times a week. Assum­ing 50 uses a year (for spe­cific pro­jects, let’s say, and not ordi­nary aim­less usage), that’s a cool $200 a year. My gen­eral belief was that Adder­all would be too much of a stim­u­lant for me, as I am amphet­a­mine-naive and Adder­all has a bad rep­u­ta­tion for let­ting one waste time on unim­por­tant things. We could say my pre­dic­tion was 50% that Adder­all would be use­ful and worth inves­ti­gat­ing fur­ther. The exper­i­ment was pretty sim­ple: blind ran­dom­ized pills, 10 placebo & 10 active. I took notes on how pro­duc­tive I was and the next day guessed whether it was placebo or Adder­all before break­ing the seal and find­ing out. I did­n’t do any for­mal sta­tis­tics for it, much less a power cal­cu­la­tion, so let’s try to be con­ser­v­a­tive by penal­iz­ing the infor­ma­tion qual­ity heav­ily and assume it had 25%. So ! The exper­i­ment prob­a­bly used up no more than an hour or two total.

Vaniver argues that since I start off not intend­ing to con­tinue Adder­all, the analy­sis actu­ally needs to be differ­ent:

In 3, you’re con­sid­er­ing adding a new sup­ple­ment, not stop­ping a sup­ple­ment you already use. The “I don’t try Adder­all” case has value $0, the “Adder­all fails” case is worth -$40 (as­sum­ing you only bought 10 pills, and this num­ber should be increased by your analy­sis time and a weighted cost for poten­tial per­ma­nent side effect­s), and the “Adder­all suc­ceeds” case is worth $X-40-4099, where $X is the dis­counted life­time value of the increased pro­duc­tiv­ity due to Adder­all, minus any dis­counted long-term side effect costs. If you esti­mate Adder­all will work with p = 0.5, then you should try out Adder­all if you esti­mate that → $X>4179$. (Ad­der­all work­ing or not isn’t bina­ry, and so you might be more com­fort­able break­ing down the var­i­ous “how effec­tive Adder­all is” cases when elic­it­ing X, by com­ing up with differ­ent lev­els it could work at, their val­ues, and then using a weighted sum to get X. This can also give you a bet­ter tar­get with your exper­i­ment- “this needs to show a ben­e­fit of at least Y from Adder­all for it to be worth the cost, and I’ve designed it so it has a rea­son­able chance of show­ing that.”)

One thing to notice is that the default case mat­ters a lot. This asym­me­try is because you switch deci­sions in differ­ent pos­si­ble worlds - when you would take Adder­all but stop you’re in the world where Adder­all does­n’t work, and when you would­n’t take Adder­all but do you’re in the world where Adder­all does work (in the per­fect infor­ma­tion case, at least). One of the ways you can visu­al­ize this is that you don’t penal­ize tests for giv­ing you true neg­a­tive infor­ma­tion, and you reward them for giv­ing you true pos­i­tive infor­ma­tion. (This might be worth a post by itself, and is very Litany of Gendlin.)

Either way, this exam­ple demon­strates that any­thing you are doing expen­sively is worth test­ing exten­sively.

Adrafinil

The /Olmifon (bought simul­ta­ne­ously with the hydergine from Anti-Ag­ing Sys­tems, now Anti­ag­ing Cen­tral) was a dis­ap­point­ment. Almost as expen­sive as actual modafinil, with the risk of liver prob­lems, but did noth­ing what­so­ever that I noticed. It is sup­posed to be sub­tler than modafinil, but that’s a lit­tle ridicu­lous.

The advan­tage of adrafinil is that it is legal & over-the-counter in the USA, so one removes the small legal risk of order­ing & pos­sess­ing modafinil with­out a pre­scrip­tion, and the retail­ers may be more reli­able because they are not oper­at­ing in a niche of dubi­ous legal­i­ty. Based on com­ments from oth­ers, the liver prob­lem may have been overblown, and modafinil ven­dors post-2012 seem to have become more unsta­ble, so I may give adrafinil (from another source than Anti­ag­ing Cen­tral) a shot when my modafinil/armodafinil run out.

Aniracetam

Very expen­sive; I noticed min­i­mal improve­ments when com­bined with sul­bu­ti­amine & pirac­etam+­choline. Defi­nitely not worth­while for me.

Bacopa monnieri

Bacopa is a sup­ple­ment herb often used for mem­ory or stress adap­ta­tion. Its chronic effects report­edly take many weeks to man­i­fest, with no impor­tant acute effects. Out of curios­i­ty, I bought 2 bot­tles of Bac­og­nize Bacopa pills and ran a non-ran­dom­ized non-blinded ABABA qua­si­-self-ex­per­i­ment from June 2014 to Sep­tem­ber 2015, mea­sur­ing effects on my mem­ory per­for­mance, sleep, and daily self­-rat­ings of mood/productivity. Because of the very slow onset, small effec­tive sam­ple size, defi­nite tem­po­ral trends prob­a­bly unre­lated to Baco­pa, and noise in the vari­ables, the results were as expect­ed, ambigu­ous, and do not strongly sup­port any cor­re­la­tion between Bacopa and memory/sleep/self-rating (+/-/- respec­tive­ly).

Main arti­cle: .

Beta-phenylethylamine (PEA)

Based on this H+ article/advertisement, I gave a sup­ple­ment a try. Noticed noth­ing. Crit­i­cal com­men­ta­tors pointed out that PEA was noto­ri­ously degraded by the diges­tive sys­tem and has essen­tially no effect on its own8, though Neur­vana’s ‘pro’ sup­ple­ment claimed to avoid that. I guess it does­n’t.

Dis­cus­sions of PEA men­tion that it’s almost use­less with­out a to ; hence, when I decided to get deprenyl and noticed that deprenyl is a MAOI, I decided to also give PEA a sec­ond chance in con­junc­tion with deprenyl. Unfor­tu­nate­ly, in part due to my own shenani­gans, Nubrain can­celed the deprenyl order and so I have 20g of PEA sit­ting around. Well, it’ll keep until such time as I do get a MAOI.

Caffeine

(Exam­ine.­com; FDA adverse events) is of course the most famous stim­u­lant around. But con­sum­ing 200mg or more a day, I have dis­cov­ered the down­side: it is addic­tive and has a nasty with­drawal - headaches, decreased moti­va­tion, apa­thy, and gen­eral unhap­pi­ness. (It’s a lit­tle amus­ing to read aca­d­e­mic descrip­tions of caffeine addic­tion9; if caffeine were a new drug, I won­der what Sched­ule it would be in and if peo­ple might be even more leery of it than modafinil.) Fur­ther, in some ways, aside from the ubiq­ui­tous placebo effect, caffeine com­bines a mix of weak per­for­mance ben­e­fits (Lorist & Snel 2008, Nehlig 2010) with some pos­si­ble decre­ments, anec­do­tally and sci­en­tifi­cally:

  1. slows mem­ory retrieval for unprimed mem­o­ries (although it speeds retrieval for related/primed mem­o­ries)
  2. the usual U-curve applies to caffeine dos­es: eg while a small dose of caffeine in energy drinks sub­stan­tially improves reac­tion-time in the cued go/no-go task, higher doses improve reac­tion-time less and are much closer to base­line (their opti­mal tested dose is, for my weight of 93kg, ~100mg)
  3. caffeine dam­ages sleep (nec­es­sary for mem­ory and alert­ness), even 6 hours before sleep
  4. very low doses (9mg) of caffeine can still have neg­a­tive effects
  5. did I men­tion that it cor­re­lates with changed estro­gen lev­els in women?
  6. in rats, it inhibits mem­ory for­ma­tion in the and in mice, although other mice saw men­tal ben­e­fits with improve­ment to “long-term mem­ory when tested with object recog­ni­tion”

Final­ly, it’s not clear that caffeine results in per­for­mance gains after long-term use; homeostasis/tolerance is a con­cern for all stim­u­lants, but espe­cially for caffeine. It is plau­si­ble that all caffeine con­sump­tion does for the long-term chronic user is restore per­for­mance to base­line. (Imag­ine some­one wak­ing up and drink­ing coffee, and their per­for­mance improves - well, so would the per­for­mance of a non-ad­dict who is also slowly wak­ing up!) See for exam­ple, James & Rogers 2005, , and Rogers et al 2010. A in the Cam­bridge brain-train­ing study found “caffeine intake showed neg­li­gi­ble effect sizes for mean and com­po­nent scores” (par­tic­i­pants were not told to use caffeine, but the train­ing was recre­ational & diffi­cult, so one expects some differ­ence).

This research is in con­trast to the other sub­stances I like, such as pirac­etam or fish oil. I knew about with­drawal of course, but it was not so bad when I was drink­ing only tea. And the side-effects like jit­ter­i­ness are worse on caffeine with­out tea; I chalk this up to the lack of thea­nine. (My later expe­ri­ences with thea­nine seems to con­firm this.) These neg­a­tive effects mean that caffeine does­n’t sat­isfy the strictest defi­n­i­tion of ‘nootropic’ (hav­ing no neg­a­tive effect­s), but is merely a ‘cog­ni­tive enhancer’ (with both ben­e­fits & cost­s). One might won­der why I use caffeine any­way if I am so con­cerned with men­tal abil­i­ty.

My answer is that this is not a lot of research or very good research (not nearly as good as the research on nico­tine, eg.), and assum­ing it’s true, I don’t value that much because LTM is some­thing that is eas­ily assisted or replaced (per­sonal archives, and ). For me, my prob­lems tend to be more about akra­sia and energy and not get­ting things done, so even if a stim­u­lant comes with a lit­tle cost to long-term mem­o­ry, it’s still use­ful for me. I’m going con­tinue to use the caffeine. It’s not so bad in con­junc­tion with tea, is very cheap, and I’m already addict­ed, so why not? Caffeine is extremely cheap, addic­tive, has min­i­mal effects on health (and may be ben­e­fi­cial, from the var­i­ous epi­demi­o­log­i­cal asso­ci­a­tions with tea/coffee/chocolate & longevi­ty), and costs extra to remove from drinks pop­u­lar regard­less of their caffeine con­tent (coffee and tea again). What would be the point of care­fully inves­ti­gat­ing it? Sup­pose there was con­clu­sive evi­dence on the top­ic, the value of this evi­dence to me would be roughly $0 or since igno­rance is bliss, neg­a­tive money - because unless the neg­a­tive effects were dras­tic (which cur­rent stud­ies rule out, although tea has other issues like flu­o­ride or ), I would not change any­thing about my life. Why? I enjoy my too much. My usual tea seller does­n’t even have decaffeinated oolong in gen­er­al, much less var­i­ous vari­eties I might want to drink, appar­ently because de-caffeinat­ing is so expen­sive it’s not worth­while. What am I sup­posed to do, give up my tea and caffeine just to save on the cost of caffeine? Buy de-caffeinat­ing machines (which I could­n’t even find any prices for, googling)? This also holds true for peo­ple who drink coffee or caffeinated soda. (As opposed to a drug like modafinil which is expen­sive, and so the value of a defin­i­tive answer is sub­stan­tial and would jus­tify some more exten­sive cal­cu­lat­ing of cost-ben­e­fit.)

I ordered 400g of ‘anhy­drous caffeine’ from Smart Pow­ders. Appar­ently my does­n’t con­tain very much caffeine, so adding a frac­tion of a gram wakes me up a bit. Sur­pris­ingly for some­thing with ‘anhy­drous’ in its name, it does­n’t seem to dis­solve very well.

I ulti­mately mixed it in with the 3kg of pirac­etam and included it in that batch of pills. I mixed it very thor­ough­ly, one ingre­di­ent at a time, so I’m not very wor­ried about ‘hot spots’. But if you are, one clever way to get accu­rate caffeine mea­sure­ments is to mea­sure out a large quan­tity & dis­solve it since it’s eas­ier to mea­sure water than pow­der, and dis­solv­ing guar­an­tees even dis­tri­b­u­tion. This can be impor­tant because caffeine is, like nicotine, an poi­son which - “the dose makes the poi­son” - can kill in high dos­es, and con­cen­trated pow­der makes it easy to take too much, as one inept Eng­lish­man dis­cov­ered the hard way. (This dis­solv­ing trick is applic­a­ble to any­thing else that dis­solves nice­ly.)

Choline/DMAE

Does lit­tle alone, but absolutely nec­es­sary in con­junc­tion with pirac­etam. (Bought from Smart Pow­der­s.) When turn­ing my 3kg of pirac­etam into pills, I decided to avoid the fishy-s­melling choline and go with 500g of (Exam­ine.­com); it seemed to work well when I used it before with oxirac­etam & pirac­etam, since I had no ‘pirac­etam headaches’, and be con­sid­er­ably less bulky.

In the future, I might try Alpha-GPC instead of the reg­u­lar choli­nes; that sup­pos­edly has bet­ter bio-avail­abil­i­ty.

Cocoa

or cocoa pow­der (Exam­ine.­com), con­tains the stim­u­lants caffeine and the caffeine metabo­lite , so it’s not nec­es­sar­ily sur­pris­ing if cocoa pow­der was a weak stim­u­lant. It’s also a witch’s brew of chem­i­cals such as and some of which have been fin­gered as help­ful10, which all adds up to an (once you con­trol for eat­ing a lot of sug­ar).

Googling, you some­times see cor­re­la­tional stud­ies like “Intake of Flavonoid-Rich Wine, Tea, and Choco­late by Elderly Men and Women Is Asso­ci­ated with Bet­ter Cog­ni­tive Test Per­for­mance”; in this one, the cor­re­lated per­for­mance increase from eat­ing choco­late was gen­er­ally fairly mod­est (say, <10%), and the max­i­mum effects were at 10g/day of what was prob­a­bly milk choco­late, which gen­er­ally has 10-40% choco­late liquor in it, sug­gest­ing any exper­i­ment use 1-4g. More inter­est­ing is the blind RCT exper­i­ment “Con­sump­tion of cocoa fla­vanols results in acute improve­ments in mood and cog­ni­tive per­for­mance dur­ing sus­tained men­tal effort”11, which found improve­ments at ~1g; the most dra­matic improve­ment of the 4 tasks (on the “Threes cor­rect”) saw a differ­ence of 2 to 6 at the end of the hour of test­ing, while sev­eral of the other tests con­verged by the end or saw the con­trols win­ning (“Sev­ens cor­rect”). Crews et al 2008 found no cog­ni­tive ben­e­fit, and an fMRI exper­i­ment found the change in brain oxy­gen lev­els it wanted but no improve­ment to reac­tion times.

It’s not clear that there is much of an effect at all. This makes it hard to design a self­-ex­per­i­ment - how big an effect on, say, dual n-back should I be expect­ing? Do I need an ardu­ous long trial or an easy short one? This would prin­ci­pally deter­mine the “value of infor­ma­tion” too; choco­late seems like a net ben­e­fit even if it does not affect the mind, but it’s also fairly cost­ly, espe­cially if one likes (as I do) dark choco­late. Given the mixed research, I don’t think cocoa pow­der is worth inves­ti­gat­ing fur­ther as a nootrop­ic.

Coconut oil

was rec­om­mended by Pon­tus Granström on the Dual N-Back mail­ing list for boost­ing energy & men­tal clar­i­ty. It is fairly cheap (~$13 for 30 ounces) and tastes sur­pris­ingly good; it has a very bad rep­u­ta­tion in some parts, but seems to be in the mid­dle of a reha­bil­i­ta­tion. Seth Robert’s But­ter­mind exper­i­ment found no men­tal ben­e­fits to coconut oil (and ben­e­fits to eat­ing but­ter), but I won­der.

The first night I was eat­ing some coconut oil, I did my n-back­ing past 11 PM; nor­mally that dam­ages my scores, but instead I got 66/66/75/88/77% (▁▁▂▇▃) on D4B and did not feel men­tally exhausted by the end. The next day, I per­formed well on the Cam­bridge men­tal rota­tions test. An anec­dote, of course, and it may be due to the vit­a­min D I simul­ta­ne­ously start­ed. Or another day, I was slumped under apa­thy after a promis­ing start to the day; a dose of fish & coconut oil, and 1 last vit­a­min D, and I was back to feel­ing chip­per and opti­mist. Unfor­tu­nately I haven’t been test­ing out coconut oil & vit­a­min D sep­a­rate­ly, so who knows which is to thank. But still inter­est­ing.

After sev­eral weeks of reg­u­larly con­sum­ing coconut oil and using up the first jar of 15oz, I’m no longer par­tic­u­larly con­vinced it was doing any­thing. (I’ve found it’s good for fry­ing eggs, though.) Sev­eral days after using up the sec­ond jar, I notice no real differ­ence in mood or energy or DNB scores.

Coluracetam

One of the most obscure -rac­etams around, (Smarter Nootrop­ics, Ceretropic, Isochroma) acts in a differ­ent way from pirac­etam - pirac­etam appar­ently attacks the break­down of acetyl­choline while colu­rac­etam instead increases how much choline can be turned into use­ful acetyl­choline. This appar­ently is a unique mech­a­nism. A crazy Longecity user, Sci­enceGuy ponied up $16,000 (!) for a cus­tom syn­the­sis of 500g; he was exper­i­ment­ing with 10-80mg sub­lin­gual doses (the ranges in the orig­i­nal anti-de­pres­sive tri­als) and reported a laun­dry list of effects (as does Isochro­ma): pri­mar­ily that it was anx­i­olytic and increased work sta­mi­na. Unfor­tu­nately for my stack, he claims it com­bines poorly with pirac­etam. He offered free 2g sam­ples for reg­u­lars to test his claims. I asked & received some.

Exper­i­ment design is com­pli­cated by his lack of use of any kind of objec­tive tests, but 3 met­rics seem worth­while:

  1. dual n-back: test­ing his claims about con­cen­tra­tion, increased energy & sta­mi­na, and increased alert­ness & lucid­i­ty.

  2. daily Mnemosyne flash­card scores: test­ing his claim about short & medi­um-term mem­o­ry, viz.

    I have per­son­ally found that with respect to the NOOTROPIC effec­t(s) of all the RACETAMS, whilst I have expe­ri­enced improve­ments in con­cen­tra­tion and work­ing capac­ity / pro­duc­tiv­i­ty, I have never expe­ri­enced a notice­able ongo­ing improve­ment in mem­o­ry. COLURACETAM is the only RACETAM that I have taken wherein I noticed an improve­ment in MEMORY, both with regards to SHORT-TERM and MEDIUM-TERM MEMORY. To put mat­ters into per­spec­tive, the mem­ory improve­ment has been mild, yet still sig­nifi­cant; whereas I have expe­ri­enced no such improve­ment at all with the other RACETAMS.

  3. daily mood/productivity log (1-5): for the anx­i­olytic and work­ing claims.

(In all 3, higher = bet­ter, so a mul­ti­vari­ate result is eas­ily inter­pret­ed..)

He rec­om­mends a 10mg dose, but sub­lin­gual­ly. He men­tions “COLURACETAM’s taste is more akin to that of PRAMIRACETAM than OXIRACETAM, in that it tastes absolutely vile” (not a sur­prise), so it is impos­si­ble to dou­ble-blind a sub­lin­gual admin­is­tra­tion - even if I knew of an inac­tive equal­ly-vile-tast­ing sub­sti­tute, I’m not sure I would sub­ject myself to it. To com­pen­sate for ingest­ing the colu­rac­etam, it would make sense to dou­ble the dose to 20mg (turn­ing the 2g into <100 dos­es). Whether the effects per­sist over mul­ti­ple days is not clear; I’ll assume it does not until some­one says it does, since this makes things much eas­i­er.

Creatine

(Exam­ine.­com) mono­hy­drate was another early essay of mine - cheap (be­cause it’s so pop­u­lar with the body­builder type­s), and with a very good safety record. I bought some from Bulk Pow­ders and com­bined it with my then-cur­rent reg­i­men (pirac­etam+­choline).

I’m not a body­builder, but my inter­est was sparked by , some show­ing ben­e­fits and oth­ers not - usu­ally in sub­pop­u­la­tions like veg­e­tar­i­ans or old peo­ple.

As I am not any of the lat­ter, I did­n’t really expect a men­tal ben­e­fit. As it hap­pens, I observed noth­ing. What sur­prised me was some­thing I had for­got­ten about: its phys­i­cal ben­e­fits. My per­for­mance in classes sud­denly improved - specifi­cal­ly, my endurance increased sub­stan­tial­ly. Before, classes had left me nearly pros­trate at the end, but after, I was weary yet fairly alert and hap­py. (I have done Taek­wondo since I was 7, and I have a pretty good sense of what is and is not nor­mal per­for­mance for my body. This was not any­thing as sim­ple as fail­ing to notice increas­ing fit­ness or some­thing.) This was dri­ven home to me one day when in a flurry before class, I pre­pared my cus­tom­ary tea with pirac­etam, choline & cre­atine; by the mid­dle of the class, I was feel­ing faint & tired, had to take a break, and sud­den­ly, thun­der­struck, real­ized that I had absent­mind­edly for­got to actu­ally drink it! This made me a believ­er.

After I ran out of cre­atine, I noticed the increased diffi­cul­ty, and resolved to buy it again at some point; many months lat­er, there was a Smart Pow­ders sale so bought it in my batch order, $12 for 1000g. As before, it made Taek­wondo classes a bit eas­i­er. I paid closer atten­tion this sec­ond time around and noticed that as one would expect, it only helped with mus­cu­lar fatigue and did noth­ing for my aer­o­bic issues. (I hate aer­o­bic exer­cise, so it’s always been a weak point.) I even­tu­ally capped it as part of a sulbutiamine-DMAE-creatine-theanine mix. This ran out 2013-05-01. In March 2014, I spent $19 for 1kg of micronized cre­a­tine mono­hy­drate to resume cre­a­tine use and also to use it as a placebo in a hon­ey-sleep exper­i­ment test­ing Seth Robert­s’s claim that a few grams of honey before bed­time would improve sleep qual­i­ty: my usual flour placebo being unus­able because the mech­a­nism might be through sim­ple sug­ars, which flour would digest into. (I did not do the exper­i­ment: it was going to be a fair amount of messy work cap­ping the honey and cre­atine, and I did­n’t believe Robert­s’s claims for a sec­ond - my only rea­son to do it would be to prove the claim wrong but he’d just ignore me and no one else cares.) I did­n’t try mea­sur­ing out exact doses but just put a spoon­ful in my tea each morn­ing (cre­a­tine is taste­less). The 1kg lasted from 25 March to 18 Sep­tem­ber or 178 days, so ~5.6g & $0.11 per day.

Ryan Carey tracked cre­a­tine con­sump­tion vs some tests with ambigu­ous results.

Cytisine

is an obscure drug known, if at all, for use in anti-smok­ing treat­ment.

Cyti­sine is not known as a stim­u­lant and I’m not addicted to nicotine, so why give it a try? Nico­tine is one of the more effec­tive stim­u­lants avail­able, and it’s odd how few nico­tine ana­logues or nico­tinic ago­nists there are avail­able; nico­tine has a few flaws like short half-life and increas­ing blood pres­sure, so I would be inter­ested in a replace­ment. The nico­tine metabo­lite , in the human stud­ies avail­able, looks intrigu­ing and poten­tially bet­ter, but I have been unable to find a source for it. One of the few rel­e­vant drugs which I can obtain is cytisine, from Ceretropic, at 2x1.5mg dos­es. There are not many anec­do­tal reports on cytisine, but at least a few sug­gest some­what com­pa­ra­ble effects with nicotine, so I gave it a try.

My first dose on 2017-03-01, at the rec­om­mended 0.5ml/1.5mg was mis­er­able, as I felt like I had the flu and had to nap for sev­eral hours before I felt well again, requir­ing 6h to return to nor­mal; after wait­ing a mon­th, I tried again, but after a week of daily dos­ing in May, I noticed no ben­e­fits; I tried increas­ing to 3x1.5mg but this imme­di­ately caused another after­noon crash/nap on 18 May. So I scrapped my cyti­sine. Oh well.

Fish oil

(Exam­ine.­com, buy­er’s guide) pro­vides ben­e­fits relat­ing to gen­eral mood (eg. inflam­ma­tion & anx­i­ety; see later on anx­i­ety) and anti-schiz­o­phre­nia; it is one of the bet­ter sup­ple­ments one can take. (The known risks are a higher rate of prostate can­cer and inter­nal bleed­ing, but are out­weighed by the car­diac ben­e­fits - assum­ing those ben­e­fits exist, any­way, which may not be true.) The ben­e­fits of omega acids are well-re­searched.

It is at the top of the sup­ple­ment snake oil list thanks to tons of cor­re­la­tions; for a review, see Lucht­man & Song 2013 but some specifics include “Teenage Boys Who Eat Fish At Least Once A Week Achieve Higher Intel­li­gence Scores”, anti-in­flam­ma­tory prop­er­ties (see on arthri­tis), and oth­ers - “Fish oil can head off first psy­chotic episodes” (study; Seth Roberts com­men­tary), “Fish Oil May Fight Breast Can­cer”, “Fatty Fish May Cut Prostate Can­cer Risk” & “Wal­nuts slow prostate can­cer”, “Ben­e­fits of omega-3 fatty acids tally up”, “Serum Phos­pho­lipid Docosa­hexaenonic Acid Is Asso­ci­ated with Cog­ni­tive Func­tion­ing dur­ing Mid­dle Adult­hood” end­less anec­dotes.

But like any other sup­ple­ment, there are some safety con­cerns neg­a­tive stud­ies like “Fish oil fails to hold off heart arrhyth­mia” or “other reports cast doubt on a pro­tec­tive effect against demen­tia” or “Fish Oil Use in Preg­nancy Did­n’t Make Babies Smart” (WSJ) (an early promise but one that faded a bit later) or “…Sup­ple­men­ta­tion with DHA com­pared with placebo did not slow the rate of cog­ni­tive and func­tional decline in patients with mild to mod­er­ate Alzheimer dis­ease.”.

As far as anx­i­ety goes, psy­chi­a­trist Emily Deans has an overview of why the Kiecolt-Glaser et al 2011 study is nice; she also dis­cusses why fish oil seems like a good idea from an evo­lu­tion­ary per­spec­tive. There was also a weaker ear­lier 2005 study also using healthy young peo­ple, which showed reduced anger/anxiety/depression plus slightly faster reac­tions. The anti-stress/anxiolytic may be related to the pos­si­ble car­dio­vas­cu­lar ben­e­fits (Carter et al 2013).

Experiment?

I can test fish oil for mood, since the other claimed ben­e­fits like anti-schiz­o­phre­nia are too hard to test. The med­ical stu­dent trial (Kiecolt-Glaser et al 2011) did not see changes until visit 3, after 3 weeks of sup­ple­men­ta­tion. (Visit 1, 3 weeks, visit 2, sup­ple­men­ta­tion started for 3 weeks, visit 3, sup­ple­men­ta­tion con­tin­ued 3 weeks, visit 4 etc.) There were no tests in between the test start­ing week 1 and start­ing week 3, so I can’t pin it down any fur­ther. This sug­gests ran­dom­iz­ing in 2 or 3 week . (For an expla­na­tion of block­ing, see the foot­note in the page.)

The place­bos can be the usual pills filled with olive oil. The Nature’s Answer fish oil is lemon-fla­vored; it may be worth mix­ing in some lemon juice. In Kiecolt-Glaser et al 2011, ‘anx­i­ety’ was mea­sured via the Beck Anx­i­ety scale; the placebo mean was 1.2 on a stan­dard devi­a­tion of 0.075, and the exper­i­men­tal mean was 0.93 on a stan­dard devi­a­tion of 0.076. (These are all log-trans­formed covari­ates or some­thing; I don’t know what that means, but if I naively plug those num­bers into Cohen’s d, I get a very large effect: =3.55.)

Quasi-experiment

I noticed what may have been an effect on my dual n-back scores; the differ­ence is not large (▃▆▃▃▂▂▂▂▄▅▂▄▂▃▅▃▄ vs ▃▄▂▂▃▅▂▂▄▁▄▃▅▂▃▂▄▂▁▇▃▂▂▄▄▃▃▂▃▂▂▂▃▄▄▃▆▄▄▂▃▄▃▁▂▂▂▃▂▄▂▁▁▂▄▁▃▂▄) and appears mostly in the aver­ages - Toomim’s quick two-sam­ple gave p = 0.23, although a another analy­sis gives p = 0.138112. One issue with this before-after qua­si­-ex­per­i­ment is that one would expect my scores to slowly rise over time and hence a fish oil after would yield a score increase - the 3.2 point differ­ence could be attrib­ut­able to that, placebo effect, or ran­dom vari­a­tion etc. But an acci­den­tally noticed effect (d = 0.28) is a promis­ing start. An exper­i­ment may be worth doing given that fish oil does cost a fair bit each year: ran­dom­ized blocks per­mit­ting an fish-oil-then-placebo com­par­i­son would take care of the first issue, and then blind­ing (olive oil cap­sules ver­sus fish oil cap­sules?) would take care of the placebo wor­ry.

Power calculation

We have clear hypothe­ses here, so we can be a lit­tle opti­mistic: the fish oil will either improve mood or scores or it will do noth­ing; it will not worsen either. First, the large anx­i­ety effect:

pwr.t.test(d=3.55,type="paired",power=0.75,alternative="greater",sig.level=0.05)
#      Paired t test power calculation
#
#               n = 2.269155
#
#               NOTE: n is number of *pairs*

Sus­pi­ciously easy. 2.25 pairs or 6 blocks? Let’s be pes­simistic and use the smaller effect size esti­mate from my qua­si­-tri­al:

# pwr.t.test(d=0.28,type="paired",power=0.75,alternative="greater",sig.level=0.05)
#
#      Paired t test power calculation
#
#               n = 69.98612

70 pairs is 140 blocks; we can drop to 36 pairs or 72 blocks if we accept a power of 0.5/50% chance of reach­ing sig­nifi­cance. (Or we could econ­o­mize by hop­ing that the effect size is not 3.5 but maybe twice the pes­simistic guess; a d = 0.5 at 50% power requires only 12 pairs of 24 block­s.) 70 pairs of blocks of 2 weeks, with 2 pills a day requires pills. I don’t even have that many empty pills! I have <500; 500 would sup­ply 250 days, which would yield 18 2-week blocks which could give 9 pairs. 9 pairs would give me a power of:

pwr.t.test(d=0.28,type="paired",alternative="greater",sig.level=0.05,n=9)
# ...          power = 0.1908962
pwr.t.test(d=0.5,type="paired",alternative="greater",sig.level=0.05,n=9)
# ...          power = 0.3927739

A 20-40% chance of detect­ing the effect.

VoI

For back­ground on “value of infor­ma­tion” cal­cu­la­tions, see the Adder­all cal­cu­la­tion.

  1. Cost of fish oil:

    The price is not as good as mul­ti­vi­t­a­mins or mela­tonin. The stud­ies show­ing effects gen­er­ally use pretty high dosages, 1-4g dai­ly. I took 4 cap­sules a day for roughly 4g of omega acids. The jar of 400 is 100 days’ worth, and costs ~$17, or around 17¢ a day. The gen­eral health ben­e­fits push me over the edge of favor­ing its indefi­nite use, but look­ing to econ­o­mize. Usu­al­ly, small amounts of pack­aged sub­stances are more expen­sive than bulk unprocessed, so I looked at fish oil fluid prod­ucts; and unsur­pris­ing­ly, liq­uid is more cost-effec­tive than pills (but like with the pow­ders, straight fish oil isn’t very appe­tiz­ing) in lieu of mem­ber­ship some­where or some other price-break. I bought 4 bot­tles (16 fluid ounces each) for $53.31 total (thanks to coupons & sales), and each bot­tle lasts around a month and a half for per­haps half a year, or ~$100 for a year’s sup­ply. (As it turned out, the 4 bot­tles lasted from 2010-12-04 to 2011-06-17, or 195 days.) My next batch lasted 2011-08–19-2012-02-20, and cost $58.27. Since I needed to buy empty 00 cap­sules (for my lithium exper­i­ment) and a book (Stanovich 2010, for SIAI work) from Ama­zon, I bought 4 more bot­tles of 16fl oz Nature’s Answer (le­mon-lime) at $48.44, which I began using 2012-02-27. So call it ~$70 a year.

    Most of the most solid fish oil results seem to melio­rate the effects of age; in my 20s, I’m not sure they are worth the cost. But I would prob­a­bly resume fish oil in my 30s or 40s when aging really becomes a con­cern. So the exper­i­ment at most will result in dis­con­tin­u­ing for a decade. At $X a year, that’s a of sum $ map (\n -> 70 / (1 + 0.05)^n) [1..10] = $540.5.

  2. Cost of exper­i­men­ta­tion:

    The fish oil can be con­sid­ered a free sunk cost: I would take it in the absence of an exper­i­ment. The empty pill cap­sules could be used for some­thing else, so we’ll put the 500 at $5. Fill­ing 500 cap­sules with fish and olive oil will be messy and take an hour. Tak­ing them reg­u­larly can be added to my habit­ual morn­ing rou­tine for vit­a­min D and the lithium exper­i­ment, so that is close to free but we’ll call it an hour over the 250 days. Record­ing mood/productivity is also free a sunk cost as it’s nec­es­sary for the other exper­i­ments; but record­ing dual n-back scores is more expen­sive: each round is ~2 min­utes and one wants >=5, so each block will cost >10 min­utes, so 18 tests will be >180 min­utes or >3 hours. So >5 hours. Total: .

  3. Pri­ors:

    The power cal­cu­la­tion indi­cates a 20% chance of get­ting use­ful infor­ma­tion. My qua­si­-ex­per­i­ment has <70% chance of being right, and I pre­serve a gen­eral skep­ti­cism about any exper­i­ment, even one as well done as the med­ical stu­dent one seems to be, and give that one a <80% chance of being right; so let’s call it 70% the effect exists, or 30% it does­n’t exist (which is the case in which I save money by drop­ping fish oil for 10 years).

  4. Value of Infor­ma­tion

    Power times prior times ben­e­fit minus cost of exper­i­men­ta­tion: . So the VoI is neg­a­tive: because my default is that fish oil works and I am tak­ing it, weak infor­ma­tion that it does­n’t work isn’t enough. If the power cal­cu­la­tion were giv­ing us 40% reli­able infor­ma­tion, then the chance of learn­ing I should drop fish oil is improved enough to make the exper­i­ment worth­while (go­ing from 20% to 40% switches the value from -$9 to +$23.8).

Flaxseed

The gen­eral cost of fish oil made me inter­ested in pos­si­ble sub­sti­tutes. Seth Roberts uses exclu­sively flaxseed oil or flaxseed meal, and this seems to work well for him with sub­jec­tive effects (eg. notic­ing his Chi­nese brands seemed to not work, pos­si­bly because they were unre­frig­er­ated and slightly ran­cid). It’s been stud­ied much less than fish oil, but omega acids are con­fus­ing enough in gen­eral (is there a right ratio? McCluskey’s roundup gives the impres­sion claims about ratios may have been over­stat­ed) that I’m not con­vinced ALA is a much infe­rior replace­ment for fish oil’s mixes of EPA & DHA.

Flaxseed oil is, ounce for ounce, about as expen­sive as fish oil, and also must be refrig­er­ated and goes bad within months any­way. Flax seeds on the other hand, do not go bad within months, and cost dol­lars per pound. Var­i­ous resources I found online esti­mated that the ALA com­po­nent of human-ed­i­ble flaxseed to be around 20% So Ama­zon’s 6lbs for $14 is ~1.2lbs of ALA, com­pared to 16fl-oz of fish oil weigh­ing ~1lb and cost­ing ~$17, while also keep­ing bet­ter and being a calor­i­cally use­ful part of my diet. The flaxseeds can be ground in an ordi­nary food proces­sor or coffee grinder. It’s not a hugely impres­sive cost-sav­ings, but I think it’s worth try­ing when I run out of fish oil.

After try­ing out 2 6lb packs between 12 Sep­tem­ber & 2012-11-25, and 20 March & 2013-08-20, I have given up on flaxseed meal. They did not seem to go bad in the refrig­er­a­tor or freez­er, and tasted OK, but I had diffi­culty work­ing them into my usual recipes: it does­n’t com­bine well with hot or cold oat­meal, and when I tried using flaxseed meal in soups I learned flaxseed is a thick­ener which can give soup the con­sis­tency of snot. It’s eas­ier to use fish oil on a daily basis.

Huperzine-A

The chem­i­cal (Exam­ine.­com) is extracted from a moss. It is an acetyl­cholinesterase inhibitor (in­stead of forc­ing out more acetyl­choline like the -rac­etams, it pre­vents acetyl­choline from break­ing down). My expe­ri­ence report: One for the ‘null hypoth­e­sis’ files - Huperzine-A did noth­ing for me. Unlike pirac­etam or fish oil, after a full bot­tle (Source Nat­u­rals, 120 pills at 200μg each), I noticed no side-effects, no men­tal improve­ments of any kind, and no changes in DNB scores from straight Huperzine-A.

Pos­si­ble con­found­ing fac­tors:

  • youth: I am con­sid­er­ably younger than the other poster who uses HA
  • I only tested a few days with choline+H-A (but I did­n’t notice any­thing beyond the choline there).
  • coun­ter­feit­ing? Source Nat­u­rals is sup­posed to be trust­wor­thy, but rare herbal prod­ucts are most sus­cep­ti­ble to fake goods.

It’s really too bad. H-A is cheap, com­pact, does­n’t taste at all, and in gen­eral is much eas­ier to take than fish oil (and much eas­ier to swal­low than pirac­etam or choline!). But if it does­n’t deliv­er, it does­n’t deliv­er.

Hydergine

(FDA adverse events) was another dis­ap­point­ment (like the adrafinil, pur­chased from Anti-Ag­ing Systems/Anti­ag­ing Cen­tral). I noticed lit­tle to noth­ing that could­n’t be nor­mal daily vari­a­tion.

Iodine

As dis­cussed in my (FDA adverse events), iodine is a pow­er­ful health inter­ven­tion as it elim­i­nates cre­tinism and improves aver­age IQ by a shock­ing mag­ni­tude. If this effect were pos­si­ble for non-fe­tuses in gen­er­al, it would be the best nootropic ever dis­cov­ered, and so I looked at it very close­ly. Unfor­tu­nate­ly, after going through ~20 exper­i­ments look­ing for ones which inter­vened with iodine post-birth and took mea­sures of cog­ni­tive func­tion, my meta-analy­sis con­cludes that: the effect is small and dri­ven mostly by one out­lier study. Once you are born, it’s too late. But the results could be wrong, and iodine might be cheap enough to take any­way, or take for non-IQ rea­sons. (This pos­si­bil­ity was fur­ther weak­ened for me by an August 2013 blood test of which put me at 3.71 uIU/ml, com­fort­ably within the ref­er­ence range of 0.27-4.20.)

Power analysis

Start­ing from the stud­ies in my meta-analy­sis, we can try to esti­mate an upper bound on how big any effect would be, if it actu­ally exist­ed. One of the most promis­ing null results, Southon et al 1994, turns out to be not very infor­ma­tive: if we punch in the num­ber of kids, we find that they needed a large effect size (d = 0.81) before they could see any­thing:

library(pwr)
pwr.t.test(power=0.75, sig.level=0.05, n=22)
#      Two-sample t test power calculation
#
#               n = 22
#               d = 0.8130347

Fitzger­ald 2012 is bet­ter, and gives a num­ber of use­ful details on her adult exper­i­ment:

Par­tic­i­pants (n = 205) [young adults aged 18-30 years] were recruited between July 2010 and Jan­u­ary 2011, and were ran­dom­ized to receive either a daily 150 µg (0.15mg) iodine sup­ple­ment or daily placebo sup­ple­ment for 32 week­s…After adjust­ing for base­line cog­ni­tive test score, exam­in­er, age, sex, income, and eth­nic­i­ty, iodine sup­ple­men­ta­tion did not sig­nifi­cantly pre­dict 32 week cog­ni­tive test scores for Block Design (p = 0.385), Digit Span Back­ward (p = 0.474), Matrix Rea­son­ing (p = 0.885), Sym­bol Search (p = 0.844), Visual Puz­zles (p = 0.675), Cod­ing (p = 0.858), and Let­ter-Num­ber Sequenc­ing (p = 0.408).

Full text isn’t avail­able although some of the p-val­ues sug­gest that there might be differ­ences which did­n’t reach sig­nifi­cance, so to esti­mate an upper bound on what sort of effec­t-size we’re deal­ing with:

pwr.t.test(type="two.sample",power=0.75,alternative="greater",n=102)
#      Two-sample t test power calculation
#
#               n = 102
#               d = 0.325867

This is a much tighter upper bound than Southon et al 1994 gave us, and also kind of dis­cour­ag­ing: remem­ber, the smaller the effect size, the more data you will need to see it, and data is always expen­sive. If I were to try to do any exper­i­ment, how many pairs would I need if we opti­misti­cally assume that d = 0.32?

pwr.t.test(type="paired",d=0.325867,power=0.75,alternative="greater")
#      Paired t test power calculation
#
#               n = 52.03677

We’d want 53 pairs, but Fitzger­ald 2012’s exper­i­men­tal design called for 32 weeks of sup­ple­men­ta­tion for a sin­gle pair of before-after tests - so that’d be 1664 weeks or ~54 months or ~4.5 years! We can try to adjust it down­wards with shorter blocks allow­ing more fre­quent test­ing; but prob­lem­at­i­cal­ly, iodine is stored in the thy­roid and can appar­ently linger else­where - many of the cited stud­ies used intra­mus­cu­lar injec­tions of iodized oil (as opposed to iodized salt or kelp sup­ple­ments) because this ensured an ade­quate sup­ply for months or years with no fur­ther com­pli­ance by the sub­jects. If the effects are that long-last­ing, it may be worth­less to try shorter blocks than ~32 weeks.

We’ve looked at esti­mat­ing based on indi­vid­ual stud­ies. But we aggre­gated them into a meta-analy­sis more pow­er­ful than any of them, and it gave us a final esti­mate of d=~0.1. What does that imply?

pwr.t.test(type="paired",d=0.1,power=0.75,alternative="greater")
#      Paired t test power calculation
#
#               n = 539.2906

540 pairs of tests or 1080 blocks… This game is not worth the can­dle!

VoI

For back­ground on “value of infor­ma­tion” cal­cu­la­tions, see the Adder­all cal­cu­la­tion.

  1. Cost:

    This would be a very time-con­sum­ing exper­i­ment. Any attempt to com­bine this with other exper­i­ments by ANOVA would prob­a­bly push the end-date out by months, and one would start to be seri­ously con­cerned that changes caused by aging or envi­ron­men­tal fac­tors would con­t­a­m­i­nate the results. A 5-year exper­i­ment with 7-month inter­vals will prob­a­bly eat up 5+ hours to pre­pare <12,000 pills (ac­tive & place­bo); each switch and test of men­tal func­tion­ing will prob­a­bly eat up another hour for 32 hours. (And what test main­tains valid­ity with no prac­tice effects over 5 years? Dual n-back would be unus­able because of improve­ments to WM over that peri­od.) Add in an hour for analy­sis & write­up, that sug­gests >38 hours of work, and . 12,000 pills is roughly $12.80 per thou­sand or $154; 120 potas­sium iodide pills is ~$9, so .

    The time plus the gel cap­sules plus the potas­sium iodide is $567.

  2. Ben­e­fit:

    Some work has been done on esti­mat­ing the value of IQ, both as net ben­e­fits to the pos­ses­sor (in­clud­ing all zero-sum or neg­a­tive-sum aspects) and as net pos­i­tive exter­nal­i­ties to the rest of soci­ety. The esti­mates are sub­stan­tial: in the thou­sands of dol­lars per IQ point. But since increas­ing IQ post-child­hood is almost impos­si­ble bar­ring dis­ease or sim­i­lar deficits, and even increas­ing child­hood IQs is very chal­leng­ing, much of these esti­mates are merely cor­re­la­tions or regres­sions, and the exper­i­men­tal child­hood esti­mates must be weak­ened con­sid­er­ably for any adult - since so much time and so many oppor­tu­ni­ties have been lost. A wild guess: $1000 net present value per IQ point. The range for severely defi­cient chil­dren was 10-15 points, so any nor­mal (some­what defi­cient) adult gain must be much smaller and con­sis­tent with Fitzger­ald 2012’s ceil­ing on pos­si­ble effect sizes (smal­l).

    Let’s make another wild guess at 2 IQ points, for $2000.

  3. Expec­ta­tion:

    What is my prior expec­ta­tion that iodine will do any­thing? A good way to break this ques­tion down is the fol­low­ing series of nec­es­sary steps:

    • how much do I believe I am iodine defi­cient?

      (If I am not defi­cient, then sup­ple­men­ta­tion ought to have no effec­t.) The pre­vi­ous mate­r­ial on mod­ern trends sug­gests a prior >25%, and higher than that if I were female. How­ev­er, I was raised on a low-salt diet because my father has high blood pres­sure, and while I like seafood, I doubt I eat it more often than week­ly. I sus­pect I am some­what iodine-d­e­fi­cient, although I don’t believe as con­fi­dently as I did that I had a vit­a­min D defi­cien­cy. Let’s call this one 75%.

    • If defi­cient, how likely would it help at my age?

      (The effect may exist only at lim­ited age ranges - like height, once you’re done grow­ing, few inter­ven­tions short of bone surgery will make one taller or short­er.) So this is one of the key assump­tions: can we extend the ben­e­fits in defi­cient chil­dren to some­what defi­cient adults?

      Fitzger­ald 2012 and the gen­eral absence of suc­cess­ful exper­i­ments sug­gests not, as does the gen­eral his­toric fail­ure of scores of IQ-re­lated inter­ven­tions in healthy young adults. Of the 10 stud­ies listed in the orig­i­nal sec­tion deal­ing with iodine in chil­dren or adults, only 2 show any ben­e­fit; in lieu of a meta-analy­sis, a rule of thumb would be 20%, but both those stud­ies used a pack­age of dozens of nutri­ents - and not just iodine - so if the respon­si­ble sub­stance were ran­domly picked, that sug­gests we ought to give it a chance of of being iodine! I may be unduly opti­mistic if I give this as much as 10%.

    • If it would help at my age, how likely do I think my sup­ple­men­ta­tion would hit the sweet spot and not under or over­shoot?

      (We already saw that too much iodine could poi­son both adults and chil­dren, and of course too lit­tle does not help much - iodine would seem to fol­low a U-curve like most sup­ple­ments.) The listed doses at iherb.com often are ridicu­lously large: 10-50mg! These are doses that seems to actu­ally be dan­ger­ous for long-term con­sump­tion, and I believe these are doses that are designed to com­pletely suffo­cate the thy­roid gland and pre­vent it from absorb­ing any more iodine - which is use­ful as a , but quite use­less from a sup­ple­men­ta­tion stand­point. For­tu­nate­ly, there are avail­able doses at Fitzger­ald 2012’s exact dose, which is roughly the daily RDA: 0.15mg. Even the con­trar­ian mate­ri­als seem to focus on a mod­est dou­bling or tripling of the exist­ing RDA, so the range seems rel­a­tively nar­row. I’m fairly con­fi­dent I won’t over­shoot if I go with 0.15-1mg, so let’s call this 90%.

    Con­clu­sion: 75% times 10% times 90% is 6.3%.

  4. EV of tak­ing iodine

    Now, what is the expected value (EV) of sim­ply tak­ing iodine, with­out the addi­tional work of the exper­i­ment? 4 cans of 0.15mg x 200 is $20 for 2.1 years’ worth or ~$10 a year or a NPV cost of $205 () ver­sus a 20% chance of $2000 or $400. So the expected value is greater than the NPV cost of tak­ing it, so I should start tak­ing iodine.

  5. Value of Infor­ma­tion

    Final­ly, what is the value of infor­ma­tion of con­duct­ing the exper­i­ment?

    With an esti­mated power of 75%, and my own skep­ti­cal prior of 20% that there’s any effect worth car­ing about, and a poten­tial ben­e­fit of $2000, that’s . We must weigh $95 against the esti­mated exper­i­men­ta­tion cost of $567. Since the infor­ma­tion is worth less than the exper­i­ment costs, I should not do it.

    But notice that most of the cost imbal­ance is com­ing from the esti­mate of the ben­e­fit of IQ - if it quadru­pled to a defen­si­ble $8000, that would be close to the exper­i­ment cost! So in a way, what this VoI cal­cu­la­tion tells us is that what is most valu­able right now is not that iodine might pos­si­bly increase IQ, but get­ting a bet­ter grip on how much any IQ inter­ven­tion is worth.

So the over­all pic­ture is that I should:

  1. start tak­ing a mod­er­ate dose of iodine at some point

  2. look into cheap tests for iodine defi­ciency

    • One self­-test sug­gested online involves drip­ping iodine onto one’s skin and see­ing how long it takes to be absorbed. This does­n’t seem ter­ri­ble, but accord­ing to Derry and Abra­ham, it is unre­li­able.
    • Home urine test kits of unknown accu­racy are avail­able online (Google “iodine urine test kit”) but run $70-$100+ eg. Hakala Research.
  3. try to think of cheaper exper­i­ments I could run for ben­e­fits from iodine

Iodine eye color changes?

A poster or two on Longecity claimed that iodine sup­ple­men­ta­tion had changed their eye col­or, sug­gest­ing a con­nec­tion to the yel­low-red­dish ele­ment - bro­mides being dis­placed by their chem­i­cal cous­in, iodine. I was skep­ti­cal this was a real effect since I don’t know why vis­i­ble amounts of either iodine or bromine would be in the eye, and the pho­tographs pro­duced were less than con­vinc­ing. But it’s an easy thing to test, so why not?

For 2 weeks, upon awak­en­ing I took close-up pho­tographs of my right eye. Then I ordered two jars of Life-Ex­ten­sion Sea-Io­dine (60x1mg) (1mg being an appar­ently safe dose), and when it arrived on 2012-09-10, I stopped the pho­tog­ra­phy and began tak­ing 1 iodine pill every other day. I noticed no ill effects (or ben­e­fits) after a few weeks and upped the dose to 1 pill dai­ly. After the first jar of 60 pills was used up, I switched to the sec­ond jar, and began pho­tog­ra­phy as before for 2 weeks. The pho­tographs were upload­ed, cropped by hand in Gimp, and shrunk to more rea­son­able dimen­sions; both sets are avail­able in a Zip file.

Upon exam­in­ing the pho­tographs, I noticed no differ­ence in eye col­or, but it seems that my move had changed the ambi­ent light­ing in the morn­ing and so there was a clear differ­ence between the two sets of pho­tographs! The ‘before’ pho­tographs had brighter light­ing than the ‘after’ pho­tographs. Regard­less, I decided to run a small sur­vey on QuickSurveys/Toluna to con­firm my diag­no­sis of no-change; the sur­vey was 11 forced-choice pairs of pho­tographs (be­fore-after), with the instruc­tions as fol­lows:

Esti­mated time: <1 min.

Below is 11 pairs of close-up eye pho­tograph­s,. In half the pho­tos, the eye color of the iris may or may not have been arti­fi­cially light­ened; as a chal­lenge, the pho­tos are taken under vary­ing light con­di­tions!

In each pair, try to pick the photo with a light­ened iris eye color if any. (Do not judge sim­ply on over­all light­ing.)

(I rea­soned that this descrip­tion is not actu­ally decep­tive: tak­ing pills is indeed “arti­fi­cial”, as I would not ‘nat­u­rally’ con­sume so much iodine or sea­weed extract, and I did­n’t know for sure that my eyes had­n’t changed color so the cor­rect descrip­tion is indeed “may or may not have”.)

I posted a link to the sur­vey on my Google+ account, and inserted the link at the top of all Gwern.net pages; 51 peo­ple com­pleted all 11 binary choices (most of them com­ing from North Amer­ica & Europe), which seems ade­quate since the 11 ques­tions are all ask­ing the same ques­tion, and 561 responses to one ques­tion is quite a few. A few differ­ent sta­tis­ti­cal tests seem applic­a­ble: a chi-squared test whether there’s a differ­ence between all the answers, a two-sam­ple test on the aver­ages, and most mean­ing­ful­ly, sum­ming up the responses as a sin­gle pair of num­bers and doing a bino­mial test:

before <- c(27,31,18,26,22,29,20,13,18,31,27) # I split the 11 questions into how many picked,
after  <- c(24,20,33,25,29,22,31,38,33,20,24) # for it, before vs after
summary(before); summary(after)
#    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.
#    13.0    19.0    26.0    23.8    28.0    31.0
#    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.
#    20.0    23.0    25.0    27.2    32.0    38.0
chisq.test(before, after, simulate.p.value=TRUE)
#     Pearson`s Chi-squared test with simulated p-value
#
# data:  before and after
# X-squared = 77, df = NA, p-value = 0.000135
wilcox.test(before, after)
#     Wilcoxon rank sum test with continuity correction
#
# data:  before and after
# W = 43, p-value = 0.2624
# alternative hypothesis: true location shift is not equal to 0
binom.test(c(sum(before), sum(after)))
#     Exact binomial test
#
# data:  c(sum(before), sum(after))
# number of successes = 262, number of trials = 561, p-value = 0.1285
# alternative hypothesis: true probability of success is not equal to 0.5
# 95% confidence interval:
#  0.4251 0.5093
# sample estimates:
# probability of success
#                  0.467

So the chi-squared believes there is a sta­tis­ti­cal­ly-sig­nifi­cant differ­ence, the two-sam­ple test dis­agrees, and the bino­mial also dis­agrees. Since I regarded it as a dubi­ous the­o­ry, can’t see a differ­ence, and the bino­mial seems like the most appro­pri­ate test, I con­clude that sev­eral months of 1mg iodine did not change my eye col­or. (As a final test, when I posted the results on the Longecity forum where peo­ple were claim­ing the eye color change, I swapped the labels on the pho­tos to see if any­one would claim some­thing along the lines “when I look at the pho­tos, I can see a differ­ence!”. I thought some­one might do that, which would be a damn­ing demon­stra­tion of their biases & wish­ful think­ing, but no one did.)

Kratom

(Erowid, Red­dit) is a tree leaf from South­east Asia; it’s addic­tive to some degree (like caffeine and nico­tine), and so it is regulated/banned in Thai­land, Malaysia, Myan­mar, and Bhutan - but not the USA. (One might think that kratom’s com­mon use there indi­cates how very addic­tive it must be, except it lit­er­ally grows on trees so it can’t be too hard to get.) Kratom is not par­tic­u­larly well-s­tud­ied (and what has been stud­ied is not nec­es­sar­ily rel­e­vant - I’m not addicted to any opi­ates!), and it suffers the usual herbal prob­lem of being an end­lessly vari­able food prod­uct and not a spe­cific chem­i­cal with the fun risks of per­haps being poi­so­nous, but in my read­ing it does­n’t seem to be par­tic­u­larly dan­ger­ous or have seri­ous side-effects.

A Less­Wronger found that it worked well for him as far as moti­va­tion and get­ting things done went, as did another Less­Wronger who sells it online (terming it “a rea­son­able pro­duc­tiv­ity enhancer”) as did one of his cus­tomers, a pickup artist oddly enough. The for­mer was curi­ous whether it would work for me too and sent me Spe­ciosa Pro’s “Starter Pack: Test Drive” (a sam­pler of 14 pack­ets of pow­der and a cute lit­tle wooden spoon). In SE Asia, kratom’s appar­ently chewed, but the pow­ders are brewed as a tea.

  1. I started with the 10g of ‘Vital­ity Enhanced Blend’, a sort of tan dust. Used 2 lit­tle-spoon­fuls (dust tastes a fair bit like green/oolong tea dust) into the tea mug and then some boil­ing water. A minute of steep­ing and… bleh. Tastes sort of musty and sour. (I see why peo­ple rec­om­mended sweet­en­ing it with hon­ey.) The effects? While I might’ve been more moti­vated - I had­n’t had caffeine that day and was a tad under the weath­er, a feel­ing which seemed to go away per­haps half an hour after start­ing - I can’t say I expe­ri­enced any nau­sea or very notice­able effects. (At least the fla­vor is no longer quite so offen­sive.)
  2. 3 days lat­er, I’m fairly mis­er­able (slept poor­ly, had a hair-rais­ing inci­dent, and a big project was not received as well as I had hope­d), so well before din­ner (and after a nap) I brew up 2 wood­en-spoons of ‘Malaysia Green’ (olive-color dust). I drank it down; tasted slightly bet­ter than the first. I was feel­ing bet­ter after the nap, and the kratom did­n’t seem to change that.
  3. The next day was some­what sim­i­lar, so at 2:40 I tried out 3 spoon­fuls of ‘sm00th’ (?), a straight tan pow­der. Like the Malaysia Green, not so bad tast­ing. By the sec­ond cup, my stom­ach is growl­ing a lit­tle. No par­tic­u­lar moti­va­tion.
  4. A week lat­er: ‘Golden Suma­tran’, 3 spoon­fuls, a more yel­low­ish pow­der. (I com­bined it with some tea dregs to hope­fully cut the fla­vor a bit.) Had a paper to review that night. No (sub­jec­tively notice­able) effect on energy or pro­duc­tiv­i­ty. I tried 4 spoon­fuls at noon the next day; noth­ing except a lit­tle men­tal ten­sion, for lack of a bet­ter word. I think that was just the har­bin­ger of what my runny nose that day and the day before was, a head cold that laid me low dur­ing the evening.
  5. 4 spoons of ‘Thai Red Vein’ at 1:30 PM; cold has­n’t gone away but the aceta­minophen was mak­ing it bear­able.
  6. 4 spoons of ‘Enriched Thai’ (brown) at 8PM. Steeped 15 min­utes, drank; no effect - I have to take a break to watch 3 Mobile Suit Gun­dam episodes before I even feel like work­ing.
  7. 5 spoons of ‘Enriched Suma­tran’ (tan­nish-brown) at 3:10 PM; espe­cially sludgy this time, the Suma­tran pow­der must be finer than the oth­er.
  8. 4 spoons ‘Syn­ergy’ (a “Pre­mium Whole Leaf Blend”) at 11:20 AM; by 12:30 PM I feel quite tired and like I need to take a nap (pre­vi­ous night’s sleep was slightly above aver­age, 96 ZQ).
  9. 5 spoons ‘Essen­tial Indo’ (olive green) at 1:50 PM; no appar­ent effect except per­haps some energy for writ­ing (but then a vague headache).

At dose #9, I’ve decided to give up on kratom. It is pos­si­ble that it is help­ing me in some way that care­ful test­ing (eg. dual n-back over weeks) would reveal, but I don’t have a strong belief that kratom would help me (I seem to ben­e­fit more from stim­u­lants, and I’m not clear on how an opi­ate-bearer like kratom could stim­u­late me). So I have no rea­son to do care­ful test­ing. Oh well.

Lion’s Mane mushroom

(Exam­ine.­com) was rec­om­mended strongly by sev­eral on the ImmInst.org forums for its long-term ben­e­fits to learn­ing, appar­ently linked to . Highly spec­u­la­tive stuff, and it’s unclear whether the mush­room pow­der I bought was the right form to take (Im­mInst.org dis­cus­sions seem to uni­ver­sally assume one is tak­ing an alco­hol or hot­wa­ter extrac­t). It tasted nice, though, and I mixed it into my sleep­ing pills (which con­tain mela­tonin & tryp­to­phan). I’ll prob­a­bly never know whether the $30 for 0.5lb was well-spent or not.

(I was more than a lit­tle non­plussed when the mush­room seller included a lit­tle pam­phlet edu­cat­ing one about how papaya leaves can cure can­cer, and how I’m short­en­ing my life by decades by not eat­ing many raw fruits & veg­eta­bles. There were some stud­ies cit­ed, but usu­ally for points dis­con­nected from any actual cur­ing or longevi­ty-in­duc­ing result­s.)

Lithium

Lithium is a well-known mood sta­bi­lizer & sui­cide pre­ven­ta­tive; some research sug­gests lithium may be a cog­ni­tive­ly-pro­tec­tive nutri­ent and on pop­u­la­tion lev­els chronic lithium con­sump­tion (through drink­ing water) pre­dicts lower lev­els of men­tal ill­ness, vio­lence, & sui­cide. Main arti­cle: .

is sold com­mer­cially in low-dos­es; I pur­chased 200 pills with 5mg of lithium each. (To put this dosage in com­par­ison, the psy­chi­atric doses of lithium are around 500mg and roughly 100x larg­er.) The pills are small and taste­less, and not at all hard to take.

Lithium experiment

I exper­i­ment with a blind ran­dom trial of 5mg lithium oro­tate look­ing for effects on mood and var­i­ous mea­sures of pro­duc­tiv­i­ty. There is no detectable effect, good or bad.

Some sug­gested that the lithium would turn me into a ‘zom­bie’, recall­ing the com­plaints of psy­chi­atric patients. But at 5mg ele­men­tal lithium x 200 pills, I’d have to eat 20 to get up to a sin­gle clin­i­cal dose (a psy­chi­atric dose might be 500mg of , which trans­lates to ~100mg ele­men­tal), so I’m not wor­ried about over­dos­ing. To test this, I took on day 1 & 2 no less than 4 pills/20mg as an attack dose; I did­n’t notice any large change in emo­tional affect or energy lev­els. And it may’ve helped my moti­va­tion (though I am also try­ing out the tyrosine).

The effect? 3 or 4 weeks lat­er, I’m not sure. When I began putting all of my nootropic pow­ders into pil­l-form, I put half a lithium pill in each, and nev­er­the­less ran out of lithium fairly quickly (3kg of pirac­etam makes for >4000 OO-size pill­s); those cap­sules were buried at the bot­tom of the bucket under lithi­um-less pills. So I sud­denly went cold-turkey on lithi­um. Reflect­ing on the past 2 weeks, I seem to have been less opti­mistic and pro­duc­tive, with items now lin­ger­ing on my To-Do list which I did­n’t expect to. An effect? Pos­si­bly.

A real exper­i­ment is called for.

Design

Most of the reported ben­e­fits of lithium are impos­si­ble for me to test: rates of sui­cide and Parkin­son’s are right out, but so is crime and neu­ro­ge­n­e­sis (the for­mer is too rare & unusu­al, the lat­ter too sub­tle & hard to mea­sure), and like­wise poten­tial neg­a­tives. So we could mea­sure:

  1. mood, via daily self­-re­port; should increase

    The prin­ci­pal met­ric would be ‘mood’, how­ever defined. Zeo’s web inter­face & data export includes a field for ‘Day Feel’, which is a rat­ing 1-5 of gen­eral mood & qual­ity of day. I can record a sim­i­lar met­ric at the end of each day. 1-5 might be a lit­tle crude even with a year of data, so a more sophis­ti­cated mea­sure might be in order. The first mood study is pay­walled so I’m not sure what they used, but Shiot­suki 2008 used (STAI) and Test (POMS). The full POMS sounds too long to use dai­ly, but the Brief POMS might work. In the orig­i­nal 1987 paper “A brief POMS mea­sure of dis­tress for can­cer patients”, patients answer­ing this ques­tion­naire had a mean total mean of 10.43 (stan­dard devi­a­tion 8.87). Is this the best way to mea­sure mood? I’ve asked Seth Roberts; he sug­gested using a 0-100 scale, but per­son­al­ly, there’s no way I can assess my mood on 0-100. My mood is suffi­ciently sta­ble (to me) that 0-5 is ask­ing a bit much, even.

    I ulti­mately decided to just go with the sim­ple 0-5 scale, although it seems to have turned out to be more of a 2-4 scale! Appar­ently I’m not very good at intro­spec­tion.

  2. long-term mem­ory (Mnemosyne 2.0’s sta­tis­tic­s); could increase (neu­ro­ge­n­e­sis), do noth­ing (null result), or decrease (metal poi­son­ing)

  3. work­ing mem­ory (dual n-back scores via Brain Work­shop13); like long-term mem­ory

  4. sleep (Zeo); should increase (via mood improve­ment)

  5. time pro­cras­ti­nat­ing on com­puter (arbtt dae­mon every 10-40 sec­onds records open & active win­dows; these sta­tis­tics can be parsed into cat­e­gories like work or play. Total time on lat­ter cat­e­gories could be a use­ful met­ric. A sec­ond met­ric would be num­ber of com­mits to the Gwern.net source repos­i­to­ry.)

Lithium is some­what per­sis­tent in the body, and its effects are not acute espe­cially in low dos­es; this calls for long blocked tri­als.

The blood half-life is 12-36 hours; hence two or three days ought to be enough to build up and wash out. A week-long block is rea­son­able since that gives 5 days for effects to man­i­fest, although mon­th-long blocks would not be a bad choice either. (I pre­fer blocks which fit in round peri­ods because it makes self­-ex­per­i­ments eas­ier to run if the blocks fit in nor­mal time-cy­cles like day/week/month. The most use­less self­-ex­per­i­ment is the one aban­doned halfway.)

With sub­tle effects, we need a lot of data, so we want at least half a year (6 blocks) or bet­ter yet, a year (12 block­s); this requires 180 actives and 180 place­bos. This is eas­ily cov­ered by $11 for “Doc­tor’s Best Best Lithium Oro­tate (5mg), 200-Count” (more pre­cise­ly, “Lithium 5mg (from 125mg of lithium oro­tate)”) and $14 for 1000x1g empty cap­sules (pur­chased Feb­ru­ary 2012). For con­ve­nience I set­tled on 168 lithium & 168 place­bos (7 pil­l-ma­chine batch­es, 14 batches total); I can use them in 24 paired blocks of 7-days/1-week each (48 total blocks/48 week­s). The lithium expi­ra­tion date is Octo­ber 2014, so that is not a prob­lem

The method­ol­ogy would be essen­tially the same as the vit­a­min D in the morn­ing exper­i­ment: put a mul­ti­ple of 7 place­bos in one con­tain­er, the same num­ber of actives in another iden­ti­cal con­tain­er, hide & ran­domly pick one of them, use con­tainer for 7 days then the other for 7 days, look inside them for the label to deter­mine which period was active and which was place­bo, refill them, and start again.

VoI

For back­ground on “value of infor­ma­tion” cal­cu­la­tions, see the Adder­all cal­cu­la­tion.

Low-dose lithium oro­tate is extremely cheap, ~$10 a year. There is some research lit­er­a­ture on it improv­ing mood and impulse con­trol in reg­u­lar peo­ple, but some of it is epi­demi­o­log­i­cal (which implies con­sid­er­able unre­li­a­bil­i­ty); my cur­rent belief is that there is prob­a­bly some effect size, but at just 5mg, it may be too tiny to mat­ter. I have ~40% belief that there will be a large effect size, but I’m doing a long exper­i­ment and I should be able to detect a large effect size with >75% chance. So, the for­mula is NPV of the differ­ence between tak­ing and not tak­ing, times qual­ity of infor­ma­tion, times expec­ta­tion: , which jus­ti­fies a time invest­ment of less than 9 hours. As it hap­pens, it took less than an hour to make the pills & place­bos, and tak­ing them is a mat­ter of sec­onds per week, so the analy­sis will be the time-con­sum­ing part. This one may actu­ally turn a profit.

Data

  1. first pair

    1. first block started and pill tak­en: 2012-05-11 - 19 May: 1
    2. 20 May - 27: 0
  2. sec­ond pair

    1. first block started and pill tak­en: 29 May - 4 June: 1
    2. sec­ond block: 5 June - 11 June: 0
  3. third pair

    1. first block: 12 June - 18 June: 1
    2. sec­ond block: 19 June - 25 June: 0
  4. fourth pair

    1. first block: 26 June - 2 July: 1
    2. sec­ond block: 3 July - 8 July: 0
  5. fifth pair

    1. first block: 13 July - 20 July: 1
    2. sec­ond block: 21 July - 27 July: 0
  6. sixth pair

    1. first block: 28 July - 3 August: 0
    2. sec­ond block: 4 August - 10 August: 1
  7. sev­enth pair

    1. first block: 11 August - 17 August: 1
    2. sec­ond block: 18 August - 24 August: 0
  8. eighth pair

    1. first block: 25 August - 31 August: 1
    2. sec­ond block: 1 Sep­tem­ber - 4 Sep­tem­ber, stopped until 24 Sep­tem­ber, fin­ished 25 Sep­tem­ber: 0
  9. I inter­rupted the lithium self­-ex­per­i­ment until March 2013 in order to run the LSD micro­dos­ing self­-ex­per­i­ment with­out a poten­tial con­found; ninth block pair:

    1. 2013-03-12 - 18 March: 1
    2. 19 March - 25 March: 0
  10. tenth pair:

    1. 26 March - 1 April: 0
    2. 2 April - 8 April: 1
  11. eleventh pair:

    1. 9 April - 15 April: 0
    2. 16 April - 21 April: 1
  12. twelfth pair:

    1. 22 April - 28 April: 1
    2. 29 April - 5 May: 0
  13. thir­teenth pair:

    1. 6 May - 12 May: 0
    2. 13 May - 19 May: 1
  14. four­teenth pair:

    1. 20 May - 26 May: 1
    2. 27 May - 2 June: 0
  15. fifteen­th:

    1. 5 June - 11 June: 0
    2. 12 June - 18 June: 1
  16. six­teen­th:

    1. 19 June - 25 June: 0
    2. 26 June - 2 July: 1
  17. sev­en­teen­th:

    1. 3 July - 9 July: 0
    2. 10 July - 16 July: 1
  18. eigh­teen­th:

    1. 17 July - 23 July: 0
    2. 24 July - 28 July, 8 August - 9 August: 1
  19. nine­teen­th:

    1. 10 August - 16 August: 0
    2. 17 August - 23 August: 1
  20. twen­ti­eth:

    1. 24 August - 30 August: 0
    2. 3 Sep­tem­ber - 6 Sep­tem­ber: 1
  21. twen­ty-first:

    1. 7 Sep­tem­ber - 13 Sep­tem­ber: 1
    2. 14 Sep­tem­ber - 20 Sep­tem­ber: 0
  22. twen­ty-sec­ond:

    1. 21 Sep­tem­ber - 27 Sep­tem­ber: 0
    2. 28 Sep­tem­ber - 4 Octo­ber: 1
  23. twen­ty-third:

    1. 5 Octo­ber - 11 Octo­ber: 0
    2. 12 Octo­ber - 18 Octo­ber: 1
  24. twen­ty-fourth:

    1. 20 - 26 Octo­ber: 0
    2. 27 Octo­ber - 2 Novem­ber: 1

Analysis

Preprocessing

  1. lithi­um: hand-gen­er­ated

  2. MP: hand-edited into mp.csv

  3. Mnemosyne daily recall scores: extracted from the data­base:

    sqlite3 -batch ~/.local/share/mnemosyne/default.db \
              "SELECT timestamp,easiness,grade FROM log WHERE event_type==9;" | \
      tr "|" "," \
      > gwern-mnemosyne.csv
  4. DNB scores: omit­ted because I wound up get­ting tired of DNB around Nov 2012 and so have no scores for most of the exper­i­ment

  5. Zeo sleep: loaded from exist­ing export; I don’t expect any changes so I will test just the ZQ

  6. arbtt: sup­ports the nec­es­sary script­ing:

    arbtt-stats --logfile=/home/gwern/doc/arbtt/2012-2013.log \
      --output-format="csv" --for-each="day" --min-percentage=0 > 2012-2013-arbtt.csv
    arbtt-stats --logfile=/home/gwern/doc/arbtt/2013-2014.log \
     --output-format="csv" --for-each="day" --min-percentage=0 > 2013-2014-arbtt.csv

    arbtt gen­er­ates cumu­la­tive time-usage for roughly a dozen over­lap­ping tags/categories of activ­ity of vary­ing val­ue. For the spe­cific analy­sis, I plan to run to extract one or two fac­tors which seem to cor­re­late with use­ful activity/work, and regress on those, instead of try­ing to regress on a dozen differ­ent time vari­ables.

  7. num­ber of com­mits to the Gwern.net source repos­i­tory

    cd ~/wiki/
    echo "Gwern.net.patches,Date" > ~/patchlog.txt
    git log --after=2012-05-11 --before=2013-11-02 --format="%ad" --date=short master | \
     sort | uniq --count | tr --squeeze-repeats ' ' ',' | cut -d ',' -f 2,3 >> ~/patchlog.txt

Prep work (read in, extract rel­e­vant date range, com­bine into a sin­gle dataset, run fac­tor analy­sis to extract some poten­tially use­ful vari­ables):

lithium <- read.csv("lithium.csv")
lithium$Date <- as.Date(lithium$Date)
rm(lithium$X)

mp <- read.csv("mp.csv")
mp$Date <- as.Date(mp$Date)

mnemosyne <- read.csv("gwern-mnemosyne.csv", header=FALSE,
                      col.names =c("Timestamp", "Easiness", "Grade"),
                      colClasses=c("integer",   "numeric",  "integer"))
mnemosyne$Date <- as.Date(as.POSIXct(mnemosyne$Timestamp, origin = "1970-01-01", tz = "EST"))
mnemosyne <- mnemosyne[mnemosyne$Date>as.Date("2012-05-11") & mnemosyne$Date<as.Date("2013-11-02"),]
mnemosyne <- aggregate(mnemosyne$Grade, by=list(mnemosyne$Date), FUN=function (x) { mean(as.vector(x));})
colnames(mnemosyne) <- c("Date", "Mnemosyne.grade")

zeo <- read.csv("https://www.gwern.net/docs/zeo/gwern-zeodata.csv")
zeo$Sleep.Date <- as.Date(zeo$Sleep.Date, format="%m/%d/%Y")
colnames(zeo)[1]  <- "Date"
zeo <- zeo[zeo$Date>as.Date("2012-05-11") & zeo$Date<as.Date("2013-11-02"),]
zeo <- zeo[,c(1:10, 23)]

zeo$Start.of.Night <- sapply(strsplit(as.character(zeo$Start.of.Night), " "), function(x) { x[[2]] })
## convert "06:45" to 24300
interval <- function(x) { if (!is.na(x)) { if (grepl(" s",x)) as.integer(sub(" s","",x))
                                           else { y <- unlist(strsplit(x, ":"));
                                                  as.integer(y[[1]])*60 + as.integer(y[[2]]); }
                                                  }
                          else NA
                          }
zeo$Start.of.Night <- sapply(zeo$Start.of.Night, interval)
## the night 'wraps around' at ~800, so let's take 0-400 and add +800 to reconstruct 'late at night'
zeo[zeo$Start.of.Night<400,]$Start.of.Night <- (zeo[zeo$Start.of.Night<400,]$Start.of.Night + 800)

arbtt1 <- read.csv("2012-2013-arbtt.csv")
arbtt2 <- read.csv("2013-2014-arbtt.csv")
arbtt <- rbind(arbtt1, arbtt2)
arbtt <- arbtt[as.Date(arbtt$Day)>=as.Date("2012-05-11") & as.Date(arbtt$Day)<=as.Date("2013-11-02"),]
## rename Day -> Date, delete Percentage
arbtt <- with(arbtt, data.frame(Date=Day, Tag=Tag, Time=Time))
## Convert time-lengths to second-counts: "0:16:40" to 1000 (seconds); "7:57:30" to 28650 (seconds) etc.
## We prefer units of seconds since arbtt has sub-minute resolution and not all categories
## will have a lot of time each day.
interval <- function(x) { if (!is.na(x)) { if (grepl(" s",x)) as.integer(sub(" s","",x))
                                           else { y <- unlist(strsplit(x, ":"));
                                                  as.integer(y[[1]])*3600 +
                                                   as.integer(y[[2]])*60 +
                                                   as.integer(y[[3]]);
                                                 }
                                          }
                          else NA
                          }
arbtt$Time <- sapply(as.character(arbtt$Time), interval)
library(reshape)
arbtt <- reshape(arbtt, v.names="Time", timevar="Tag", idvar="Date", direction="wide")
arbtt[is.na(arbtt)] <- 0
arbtt$Date <- as.Date(arbtt$Date)

patches <- read.csv("patchlog.txt")
patches$Date <- as.Date(patches$Date)

## merge all the previous data into a single data-frame:
lithiumExperiment <- merge(merge(merge(merge(merge(lithium, mp), mnemosyne, all=TRUE),
                            patches, all=TRUE), arbtt, all=TRUE), zeo, all=TRUE)
## no patches recorded for a day == 0 patches that day
lithiumExperiment[is.na(lithiumExperiment$Gwern.net.patches),]$Gwern.net.patches  <- 0
## NA=I didn't do SRS that day; but that is bad and should be penalized!
lithiumExperiment[is.na(lithiumExperiment$Mnemosyne.grade),]$Mnemosyne.grade  <- 0

productivity <- lithiumExperiment[,c(3,5:22)]
library(psych) ## for factor analysis
nfactors(productivity)
# VSS complexity 1 achieves a maximum of 0.58  with  14  factors
# VSS complexity 2 achieves a maximum of 0.67  with  14  factors
# The Velicer MAP achieves a minimum of 0.02  with  1  factors
# Empirical BIC achieves a minimum of  -304.3  with  4  factors
# Sample Size adjusted BIC achieves a minimum of  -97.84  with  7  factors
#
# Statistics by number of factors
#    vss1 vss2   map dof   chisq     prob sqresid  fit RMSEA    BIC SABIC complex  eChisq    eRMS
# 1  0.16 0.00 0.016 152 1.3e+03 2.6e-190    20.4 0.16 0.122  389.4 871.9     1.0 2.1e+03 1.1e-01
# 2  0.27 0.31 0.022 134 7.8e+02  1.9e-91    16.7 0.31 0.095  -65.2 360.1     1.3 1.1e+03 7.9e-02
# 3  0.30 0.40 0.021 117 4.9e+02  5.2e-47    14.3 0.41 0.078 -247.2 124.2     1.6 7.0e+02 6.2e-02
# 4  0.39 0.47 0.024 101 2.5e+02  4.1e-14    12.1 0.50 0.052 -389.8 -69.2     1.7 3.4e+02 4.3e-02
# 5  0.39 0.51 0.028  86 1.9e+02  2.5e-10    11.2 0.54 0.049 -347.4 -74.4     1.7 2.4e+02 3.6e-02
# 6  0.41 0.53 0.034  72 1.4e+02  7.9e-06    10.3 0.57 0.041 -317.3 -88.8     1.6 1.7e+02 3.1e-02
# 7  0.44 0.54 0.041  59 8.6e+01  1.2e-02     9.6 0.60 0.030 -285.1 -97.8     1.8 1.1e+02 2.5e-02
# 8  0.40 0.52 0.050  47 1.1e+02  1.4e-07     9.9 0.59 0.053 -181.2 -32.0     2.0 2.0e+02 3.3e-02
# 9  0.48 0.57 0.063  36 4.6e+01  1.1e-01     8.3 0.66 0.024 -180.2 -65.9     1.7 6.0e+01 1.8e-02
# 10 0.51 0.62 0.079  26 1.9e+01  8.3e-01     7.2 0.70 0.000 -144.6 -62.1     1.6 1.9e+01 1.0e-02
# 11 0.52 0.62 0.098  17 1.4e+01  6.8e-01     6.7 0.72 0.000  -93.2 -39.3     1.7 1.5e+01 9.0e-03
# 12 0.52 0.61 0.124   9 1.1e+01  3.1e-01     6.7 0.72 0.020  -46.1 -17.5     1.6 1.3e+01 8.3e-03
# 13 0.48 0.61 0.163   2 4.9e+00  8.6e-02     6.3 0.74 0.053   -7.7  -1.3     1.8 6.2e+00 5.8e-03
# 14 0.58 0.67 0.210  -4 7.5e-03       NA     4.9 0.80    NA     NA    NA     1.8 9.0e-03 2.2e-04
# 15 0.56 0.64 0.293  -9 4.6e-06       NA     5.3 0.78    NA     NA    NA     2.0 6.1e-06 5.7e-06
# 16 0.53 0.62 0.465 -13 8.7e-07       NA     5.5 0.77    NA     NA    NA     2.1 8.6e-07 2.2e-06
# 17 0.51 0.61 0.540 -16 9.3e-12       NA     5.6 0.77    NA     NA    NA     2.1 1.1e-11 7.8e-09
# 18 0.51 0.61 1.000 -18 7.0e-10       NA     5.6 0.77    NA     NA    NA     2.1 7.8e-10 6.5e-08
# 19 0.51 0.61    NA -19 0.0e+00       NA     5.6 0.77    NA     NA    NA     2.1 6.2e-25 1.8e-15
#    eCRMS   eBIC
# 1  0.112 1107.9
# 2  0.089  303.3
# 3  0.075  -31.6
# 4  0.055 -300.5
# 5  0.050 -304.3
# 6  0.047 -280.3
# 7  0.042 -257.4
# 8  0.062  -97.2
# 9  0.039 -167.1
# 10 0.026 -144.7
# 11 0.028  -92.1
# 12 0.036  -44.0
# 13 0.054   -6.4
# 14    NA     NA
# 15    NA     NA
# 16    NA     NA
# 17    NA     NA
# 18    NA     NA
# 19    NA     NA

factorization <- fa(productivity, nfactors=4); factorization
# Standardized loadings (pattern matrix) based upon correlation matrix
#                     MR3   MR1   MR2   MR4     h2    u2 com
# MP                 0.05  0.01 -0.02  0.34 0.1241 0.876 1.1
# Gwern.net.patches -0.04  0.01  0.01  0.48 0.2241 0.776 1.0
# Time.WWW           0.98 -0.04 -0.10  0.02 0.9778 0.022 1.0
# Time.X             0.49  0.29  0.47 -0.03 0.5801 0.420 2.6
# Time.IRC           0.35 -0.06 -0.14  0.16 0.1918 0.808 1.8
# Time.Writing       0.04 -0.01  0.04  0.69 0.4752 0.525 1.0
# Time.Stats         0.42 -0.10  0.30  0.01 0.2504 0.750 1.9
# Time.PDF          -0.09 -0.05  0.98  0.00 0.9791 0.021 1.0
# Time.Music         0.10 -0.10  0.02  0.03 0.0196 0.980 2.2
# Time.Rec           0.03  0.99 -0.03 -0.02 0.9950 0.005 1.0
# Time.SRS           0.06 -0.06  0.07  0.10 0.0209 0.979 3.4
# Time.Sysadmin      0.22  0.13 -0.04  0.13 0.0953 0.905 2.4
# Time.DNB          -0.04 -0.05 -0.06  0.07 0.0149 0.985 3.3
# Time.Bitcoin       0.15 -0.07 -0.07 -0.04 0.0306 0.969 2.1
# Time.Blackmarkets  0.18 -0.09 -0.08  0.02 0.0470 0.953 1.9
# Time.Programming  -0.04  0.05 -0.04  0.43 0.1850 0.815 1.1
# Time.Backups      -0.09  0.06 -0.01  0.04 0.0114 0.989 2.4
# Time.Umineko      -0.16  0.71 -0.03  0.06 0.5000 0.500 1.1
# Time.Typing       -0.03 -0.04  0.02 -0.01 0.0034 0.997 2.4
#
#                        MR3  MR1  MR2  MR4
# SS loadings           1.67 1.64 1.33 1.08
# Proportion Var        0.09 0.09 0.07 0.06
# Cumulative Var        0.09 0.17 0.24 0.30
# Proportion Explained  0.29 0.29 0.23 0.19
# Cumulative Proportion 0.29 0.58 0.81 1.00
#
#  With factor correlations of
#       MR3   MR1   MR2   MR4
# MR3  1.00  0.12 -0.05  0.10
# MR1  0.12  1.00  0.07 -0.08
# MR2 -0.05  0.07  1.00 -0.08
# MR4  0.10 -0.08 -0.08  1.00
#
# Mean item complexity =  1.8
# Test of the hypothesis that 4 factors are sufficient.
#
# The degrees of freedom for the null model are 171
# and the objective function was 3.08 with Chi Square of 1645
# The degrees of freedom for the model are 101  and the objective function was  0.46
#
# The root mean square of the residuals (RMSR) is  0.04
# The df corrected root mean square of the residuals is  0.06
#
# The harmonic number of observations is  538 with the empirical chi square  332.7  with prob <  1.6e-26
# The total number of observations was  542  with MLE Chi Square =  246  with prob <  4.1e-14
#
# Tucker Lewis Index of factoring reliability =  0.832
# RMSEA index =  0.052  and the 90 % confidence intervals are  0.043 0.06
# BIC =  -389.8
# Fit based upon off diagonal values = 0.88
# Measures of factor score adequacy
#                                                 MR3  MR1  MR2  MR4
# Correlation of scores with factors             0.99 1.00 0.99 0.79
# Multiple R square of scores with factors       0.98 0.99 0.98 0.63
# Minimum correlation of possible factor scores  0.95 0.99 0.96 0.25

## I interpret MR3=Internet+Stats usage; MR1=goofing off; MR2=reading/stats; MR4=writing
## I don't care about MR1, so we'll look for effects on 3/2/4:
lithiumExperiment$MR3 <- predict(factorization, data=productivity)[,1]
lithiumExperiment$MR2 <- predict(factorization, data=productivity)[,3]
lithiumExperiment$MR4 <- predict(factorization, data=productivity)[,4]
write.csv(lithiumExperiment, file="2012-lithium-experiment.csv", row.names=FALSE)

Test

lithiumExperiment <- read.csv("https://www.gwern.net/docs/lithium/2012-lithium-experiment.csv")
l1 <- lm(cbind(MP, Mnemosyne.grade, Gwern.net.patches, ZQ, MR3, MR2, MR4) ~ Lithium, data=lithiumExperiment)
summary(l1)
# Response MP :
#
# Coefficients:
#             Estimate Std. Error t value Pr(>|t|)
# (Intercept)   3.0613     0.0591    51.8   <2e-16
# Lithium      -0.0425     0.0841    -0.5     0.61
#
# Residual standard error: 0.755 on 320 degrees of freedom
#   (220 observations deleted due to missingness)
# Multiple R-squared:  0.000796,    Adjusted R-squared:  -0.00233
# F-statistic: 0.255 on 1 and 320 DF,  p-value: 0.614
#
#
# Response Mnemosyne.grade :
#
# Coefficients:
#             Estimate Std. Error t value Pr(>|t|)
# (Intercept)    3.158      0.120   26.41   <2e-16
# Lithium       -0.141      0.170   -0.83     0.41
#
# Residual standard error: 1.53 on 320 degrees of freedom
#   (220 observations deleted due to missingness)
# Multiple R-squared:  0.00214, Adjusted R-squared:  -0.000975
# F-statistic: 0.687 on 1 and 320 DF,  p-value: 0.408
#
#
# Response Gwern.net.patches :
#
# Coefficients:
#             Estimate Std. Error t value Pr(>|t|)
# (Intercept)   3.8712     0.3271   11.83   <2e-16
# Lithium       0.0345     0.4655    0.07     0.94
#
# Residual standard error: 4.18 on 320 degrees of freedom
#   (220 observations deleted due to missingness)
# Multiple R-squared:  1.72e-05,    Adjusted R-squared:  -0.00311
# F-statistic: 0.00549 on 1 and 320 DF,  p-value: 0.941
#
#
# Response ZQ :
#
# Coefficients:
#             Estimate Std. Error t value Pr(>|t|)
# (Intercept)   91.773      1.024   89.66   <2e-16
# Lithium        0.523      1.457    0.36     0.72
#
# Residual standard error: 13.1 on 320 degrees of freedom
#   (220 observations deleted due to missingness)
# Multiple R-squared:  0.000402,    Adjusted R-squared:  -0.00272
# F-statistic: 0.129 on 1 and 320 DF,  p-value: 0.72
#
#
# Response MR3 :
#
# Coefficients:
#             Estimate Std. Error t value Pr(>|t|)
# (Intercept)  -0.0258     0.0691   -0.37     0.71
# Lithium       0.0657     0.0983    0.67     0.50
#
# Residual standard error: 0.882 on 320 degrees of freedom
#   (220 observations deleted due to missingness)
# Multiple R-squared:  0.00139, Adjusted R-squared:  -0.00173
# F-statistic: 0.447 on 1 and 320 DF,  p-value: 0.504
#
#
# Response MR2 :
#
# Coefficients:
#             Estimate Std. Error t value Pr(>|t|)
# (Intercept)   0.0187     0.0788    0.24     0.81
# Lithium       0.0435     0.1121    0.39     0.70
#
# Residual standard error: 1.01 on 320 degrees of freedom
#   (220 observations deleted due to missingness)
# Multiple R-squared:  0.00047, Adjusted R-squared:  -0.00265
# F-statistic: 0.15 on 1 and 320 DF,  p-value: 0.698
#
#
# Response MR4 :
#
# Coefficients:
#              Estimate Std. Error t value Pr(>|t|)
# (Intercept)  0.000209   0.052772    0.00     1.00
# Lithium     -0.073464   0.075099   -0.98     0.33
#
# Residual standard error: 0.674 on 320 degrees of freedom
#   (220 observations deleted due to missingness)
# Multiple R-squared:  0.00298, Adjusted R-squared:  -0.000134
# F-statistic: 0.957 on 1 and 320 DF,  p-value: 0.329

summary(manova(l1))
#            Df      Pillai  approx F num Df den Df  Pr(>F)
# Lithium     1 0.009477169 0.4291862      7    314 0.88373
# Residuals 320

No vari­able reaches sta­tis­ti­cal-sig­nifi­cance, the coeffi­cient signs are incon­sis­tent, and the MANOVA indi­cates no over­all improve­ment by using the lithium vari­able.

Conclusion

There were no observ­able effects, either pos­i­tive or ben­e­fi­cial, to the lithium oro­tate dos­es. This is con­sis­tent with my sub­jec­tive expe­ri­ence. So I will not be using lithium oro­tate any­more.

LLLT

An unusual inter­ven­tion is infrared/near-infrared light of par­tic­u­lar wave­lengths (LLLT), the­o­rized to assist mito­chon­dr­ial res­pi­ra­tion and yield­ing a vari­ety of ther­a­peu­tic ben­e­fits. Some have sug­gested it may have cog­ni­tive ben­e­fits. LLLT sounds strange but it’s sim­ple, easy, cheap, and just plau­si­ble enough it might work. I tried out LLLT treat­ment on a spo­radic basis 2013-2014, and sta­tis­ti­cal­ly, usage cor­re­lated strongly & sta­tis­ti­cal­ly-sig­nifi­cantly with increases in my daily self­-rat­ings, and not with any sleep dis­tur­bances. Excited by that result, I did a ran­dom­ized self­-ex­per­i­ment 2014-2015 with the same pro­ce­dure, only to find that the causal effect was weak or non-ex­is­tent. I have stopped using LLLT as likely not worth the incon­ve­nience.

(LLLT) is a curi­ous treat­ment based on the appli­ca­tion of a few min­utes of weak light in spe­cific near-in­frared wave­lengths (the name is a bit of a mis­nomer as LEDs seem to be employed more these days, due to the laser aspect being unnec­es­sary and LEDs much cheap­er). Unlike most kinds of , it does­n’t seem to have any­thing to do with cir­ca­dian rhythms or zeit­ge­bers. Pro­po­nents claim effi­cacy in treat­ing phys­i­cal injuries, back pain, and numer­ous other ail­ments, recently extend­ing it to case stud­ies of men­tal issues like brain fog. (It’s applied to injured parts; for the brain, it’s typ­i­cally applied to points on the skull like F3 or F4.) And LLLT is, nat­u­ral­ly, com­pletely safe with­out any side effects or risk of injury.

To say that this all sounds dubi­ous would be an under­state­ment. (My first reac­tion was that LLLT and lost­fal­co’s other pro­pos­als were prob­a­bly the stu­pid­est thing I’d seen all month.)

The research lit­er­a­ture, while copi­ous, is messy and var­ied: method­olo­gies and devices vary sub­stan­tial­ly, sam­ple sizes are tiny, the study designs vary from paper to paper, met­rics are some­times com­i­cally lim­ited (one study mea­sured speed of fin­ish­ing a RAPM IQ test but not scores), blind­ing is rare and unclear how suc­cess­ful, etc. Rel­e­vant papers include , , & Gon­za­lez-Lima & Bar­rett 2014. Another Longecity user ran a self­-ex­per­i­ment, with some design advice from me, where he per­formed a few cog­ni­tive tests over sev­eral peri­ods of LLLT usage (the blocks turned out to be ABBA), using his father and tow­els to try to blind him­self as to con­di­tion. , and his scores did seem to improve, but his scores improved so much in the last part of the self­-ex­per­i­ment I found myself dubi­ous as to what was going on - pos­si­bly a fail­ure of ran­dom­ness given too few blocks and an tem­po­ral exoge­nous fac­tor in the last quar­ter which was respon­si­ble for the improve­ment.

While the mech­a­nism is largely unknown, one com­monly mech­a­nism pos­si­bil­ity is that light of the rel­e­vant wave­lengths is pref­er­en­tially absorbed by the pro­tein , which is a key pro­tein in mito­chon­dr­ial metab­o­lism and pro­duc­tion of , sub­stan­tially increas­ing out­put, and this extra out­put pre­sum­ably can be use­ful for cel­lu­lar activ­i­ties like heal­ing or higher per­for­mance.

I was con­tacted by the Longecity user lost­falco, and read through some of his writ­ings on the topic. I had never heard of LLLT before, but the mito­chon­dria mech­a­nism did­n’t sound impos­si­ble (although I won­dered whether it made sense at a quan­tity level14151617), and there was at least some research back­ing it; more impor­tant­ly, lost­falco had dis­cov­ered that devices for LLLT could be obtained as cheap as $15. (Clearly no one will be get­ting rich off LLLT or affil­i­ate rev­enue any time soon.) Nor could I think of any way the LLLT could be eas­ily harm­ful: there were no drugs involved, phys­i­cal con­tact was unnec­es­sary, power out­put was too low to directly dam­age through heat­ing, and if it had no LLLT-style effect but some sort of cir­ca­dian effect through hit­ting pho­tore­cep­tors, using it in the morn­ing would­n’t seem to inter­fere with sleep.

Since LLLT was so cheap, seemed safe, was inter­est­ing, just try­ing it would involve min­i­mal effort, and it would be a favor to lost­fal­co, I decided to try it. I pur­chased off eBay a $13 “48 LED illu­mi­na­tor light IR Infrared Night Vision+Power Sup­ply For CCTV. Auto Pow­er-On Sen­sor, only turn-on when the sur­round­ing is dark. IR LED wave­length: 850nm. Pow­ered by DC 12V 500mA adap­tor.” It arrived in 4 days, on 2013-09-07. It fits hand­ily in my palm. My cell­phone cam­era ver­i­fied it worked and emit­ted infrared - impor­tant because there’s no vis­i­ble light at all (ex­cept in com­plete dark­ness I can make out a faint red light), no noise, no appar­ent heat (it took about 30 min­utes before the lens or body warmed up notice­ably when I left it on a table). This was good since I wor­ried that there would be heat or noise which made blind­ing impos­si­ble; all I had to do was fig­ure out how to ran­domly turn the power on and I could run blinded self­-ex­per­i­ments with it.

My first time was rel­a­tively short: 10 min­utes around the F3/F4 points, with another 5 min­utes to the fore­head. Awk­ward hold­ing it up against one’s head, and I see why peo­ple talk of “LED hel­mets”, it’s bor­ing wait­ing. No ini­tial impres­sions except maybe feel­ing a bit men­tally cloudy, but that goes away within 20 min­utes of fin­ish­ing when I took a nap out­side in the sun­light. Lost­falco says “Expec­ta­tions: You will be tired after the first time for 2 to 24 hours. It’s per­fectly nor­mal.”, but I’m not sure - my dog woke me up very early and dis­turbed my sleep, so maybe that’s why I felt sud­denly tired. On the sec­ond day, I esca­lated to 30 min­utes on the fore­head, and tried an hour on my fin­ger joints. No par­tic­u­lar obser­va­tions except less tired­ness than before and per­haps less joint ache. Third day: skipped fore­head stim­u­la­tion, exclu­sively knee & ankle. Fourth day: fore­head at var­i­ous spots for 30 min­utes; tired­ness 5/6/7/8th day (11/12/13/4): skipped. Ninth: fore­head, 20 min­utes. No notice­able effects.

Pilot

At this point I began to get bored with it and the lack of appar­ent effects, so I began a pilot tri­al: I’d use the LED set for 10 min­utes every few days before 2PM, record, and in a few months look for a cor­re­la­tion with my daily self­-rat­ings of mood/productivity (for 2.5 years I’ve asked myself at the end of each day whether I did more, the usu­al, or less work done that day than aver­age, so 2=be­low-av­er­age, 3=av­er­age, 4=above-av­er­age; it’s ad hoc, but in some fac­tor analy­ses I’ve been play­ing with, it seems to load on a lot of other vari­ables I’ve mea­sured, so I think it’s mean­ing­ful).

On 2014-03-15, I dis­abled light sen­sor: the com­plete absence of sub­jec­tive effects since the first ses­sions made me won­der if the LED device was even turn­ing on - a lit­tle bit of ambi­ent light seems to dis­able it thanks to the light sen­sor. So I stuffed the sen­sor full of put­ty, ver­i­fied it was now always-on with the cell­phone cam­era, and began again; this time it seemed to warm up much faster, mak­ing me won­der if all the pre­vi­ous ses­sions’ sense of warmth was sim­ply heat from my hand hold­ing the LEDs

In late July 2014, I was clean­ing up my rooms and was tired of LLLT, so I decided to chuck the LED device. But before I did that, I might as well ana­lyze the data.

That left me with 329 days of data. The results are that (cor­rect­ing for the mag­ne­sium cit­rate self­-ex­per­i­ment I was run­ning dur­ing the time period which did not turn out too great) days on which I hap­pened to use my LED device for LLLT were much bet­ter than reg­u­lar days. Below is a graph show­ing the entire MP dataseries with LOESS-smoothed lines show­ing LLLT vs non-LLLT days:

Daily pro­duc­tiv­ity self­-rat­ing (high­er=­bet­ter) over time, split by LLLT usage that day (2013–2014)

LLLT pilot analysis

The cor­re­la­tion of LLLT usage with higher MP self­-rat­ing is fairly large (r = 0.19 / d = 0.455) and sta­tis­ti­cal­ly-sig­nifi­cant (p = 0.0006).

I have no par­tic­u­larly com­pelling story for why this might be a cor­re­la­tion and not cau­sa­tion. It could be place­bo, but I was­n’t expect­ing that. It could be selec­tion effect (days on which I both­ered to use the annoy­ing LED set are bet­ter days) but then I’d expect the off-days to be below-av­er­age and com­pared to the 2 years of trend­line before, there does­n’t seem like much of a fall.

The R code:

lllt <- read.csv("https://www.gwern.net/docs/nootropics/2014-08-03-lllt-correlation.csv")
l <- lm(MP ~ LLLT + as.logical(Magnesium.citrate) + as.integer(Date) +
              as.logical(Magnesium.citrate):as.integer(Date),
           data=lllt); summary(l)
# ...Coefficients:
#                                                        Estimate   Std. Error  t value   Pr(>|t|)
# (Intercept)                                         4.037702597  0.616058589  6.55409 5.0282e-10
# LLLTTRUE                                            0.330923350  0.095939634  3.44929 0.00069087
# as.logical(Magnesium.citrate)TRUE                   0.963379487  0.842463568  1.14353 0.25424378
# as.integer(Date)                                   -0.001269089  0.000880949 -1.44059 0.15132856
# as.logical(Magnesium.citrate)TRUE:as.integer(Date) -0.001765953  0.001213804 -1.45489 0.14733212

0.330923350 / sd(lllt$MP, na.rm=TRUE)
# [1] 0.455278787

cor.test(lllt$MP, as.integer(lllt$LLLT))
#
#   Pearson`s product-moment correlation
#
# data:  lllt$MP and as.integer(lllt$LLLT)
# t = 3.4043, df = 327, p-value = 0.0007458
# alternative hypothesis: true correlation is not equal to 0
# 95% confidence interval:
#  0.0784517682 0.2873891665
# sample estimates:
#         cor
# 0.185010342

## check whether there's odd about non-LLLT days by expanding to include baseline
llltImputed <- lllt
llltImputed[is.na(llltImputed)] <- 0
llltImputed[llltImputed$MP == 0,]$MP <- 3 # clean up an outlier using median

summary(lm(MP ~ LLLT + as.logical(Magnesium.citrate) + as.integer(Date) +
                as.logical(Magnesium.citrate):as.integer(Date),
           data=llltImputed))
# ...Coefficients:
#                                                        Estimate   Std. Error  t value   Pr(>|t|)
# (Intercept)                                         2.959172295  0.049016571 60.37085 < 2.22e-16
# LLLT                                                0.336886970  0.083731179  4.02344 6.2212e-05
# as.logical(Magnesium.citrate)TRUE                   2.155586397  0.619675529  3.47857 0.00052845
# as.integer(Date)                                    0.000181441  0.000103582  1.75166 0.08017565
# as.logical(Magnesium.citrate)TRUE:as.integer(Date) -0.003373682  0.000904342 -3.73054 0.00020314

power.t.test(power=0.8,
             delta=(0.336886970 / sd(lllt$MP, na.rm=TRUE)),
             type="paired",
             alternative="one.sided")
#
#      Paired t test power calculation
#
#               n = 30.1804294
#           delta = 0.463483435
#              sd = 1
#       sig.level = 0.05
#           power = 0.8
#     alternative = one.sided
#
# NOTE: n is number of *pairs*, sd is std.dev. of *differences* within pairs

library(ggplot2)
llltImputed$Date <- as.Date(llltImputed$Date)
ggplot(data = llltImputed, aes(x=Date, y=MP, col=as.logical(llltImputed$LLLT))) +
 geom_point(size=I(3)) +
 stat_smooth() +
 scale_colour_manual(values=c("gray49", "green"),
                     name = "LLLT")

So, I have started a ran­dom­ized exper­i­ment; should take 2 months, given the size of the cor­re­la­tion. If that turns out to be suc­cess­ful too, I’ll have to look into meth­ods of blind­ing - for exam­ple, some sort of elec­tronic doohickey which turns on ran­domly half the time and which records whether it’s on some­where one can’t see. (Then for the exper­i­ment, one hooks up the LED, turns the doohickey ‘on’, and applies directly to fore­head, check­ing the next morn­ing to see whether it was really on or off).

Sleep

One reader notes that for her, the first weeks of LLLT usage seemed to be accom­pa­nied by sleep­ing longer than usu­al. Did I expe­ri­ence any­thing sim­i­lar? There does­n’t appear to be any par­tic­u­lar effect on total sleep or other sleep vari­ables:

lllt <- read.csv("https://www.gwern.net/docs/nootropics/2014-08-03-lllt-correlation.csv")
zeo <- read.csv("https://www.gwern.net/docs/zeo/gwern-zeodata.csv")
lllt$Date <- as.Date(lllt$Date)
zeo$Date <- as.Date(zeo$Sleep.Date, format="%m/%d/%Y")

sleepLLLT <- merge(lllt, zeo, all=TRUE)
l <- lm(cbind(Start.of.Night, Time.to.Z, Time.in.Wake, Awakenings, Time.in.REM, Time.in.Light, Time.in.Deep, Total.Z, ZQ, Morning.Feel) ~ LLLT, data=sleepLLLT)
summary(manova(l))
##            Df     Pillai approx F num Df den Df  Pr(>F)
## LLLT        1 0.04853568 1.617066     10    317 0.10051
## Residuals 326
library(ggplot2)
qplot( sleepLLLT$Date, sleepLLLT$Total.Z, color=sleepLLLT$LLLT)

LLLT pilot factor analysis

Fac­tor-an­a­lyz­ing sev­eral other per­sonal datasets into 8 fac­tors while omit­ting the pre­vi­ous MP vari­able, I find LLLT cor­re­lates with per­son­al-pro­duc­tiv­i­ty-re­lated fac­tors, but less con­vinc­ingly than MP, sug­gest­ing the pre­vi­ous result is not quite as good as it seems.

My worry about the MP vari­able is that, plau­si­ble or not, it does seem rel­a­tively weak against manip­u­la­tion; other vari­ables I could look at, like arbtt win­dow-track­ing of how I spend my com­puter time, # or size of edits to my files, or spaced rep­e­ti­tion per­for­mance, would be harder to manip­u­late. If it’s all due to MP, then if I remove the MP and LLLT vari­ables, and sum­ma­rize all the other vari­ables with fac­tor analy­sis into 2 or 3 vari­ables, then I should see no increases in them when I put LLLT back in and look for a cor­re­la­tion between the fac­tors & LLLT with a mul­ti­vari­ate regres­sion.

Prepa­ra­tion of data:

lllt <- read.csv("~/wiki/docs/nootropics/2014-08-03-lllt-correlation.csv",
                 colClasses=c("Date",rep("integer", 4), "logical"))
lllt <- data.frame(Date=lllt$Date, LLLT=lllt$LLLT)
mp <- read.csv("~/selfexperiment/mp.csv", colClasses=c("Date", "integer"))
creativity <- read.csv("~/selfexperiment/dailytodo-marchjunecreativity.csv",
                       colClasses=c("Date", "integer"))
mnemosyne <- read.csv("~/selfexperiment/mnemosyne.csv", header=FALSE,
                      col.names =c("Timestamp", "Easiness", "Grade"),
                      colClasses=c("integer",   "numeric",  "integer"))
mnemosyne$Timestamp <- as.POSIXct(mnemosyne$Timestamp, origin = "1970-01-01", tz = "EST")
mnemosyne$Date    <- as.Date(mnemosyne$Timestamp)
mnemosyne <- aggregate(Grade ~ Date, mnemosyne, mean)
mnemosyne$Average.Spaced.repetition.score <- mnemosyne$Grade
rm(mnemosyne$Grade)

dnb <- read.csv("~/doc/brainworkshop/data/stats.txt", header=FALSE)
dnb$V1 <- as.POSIXct(dnb$V1, format="%F %R:%S")
dnb <- dnb[!is.na(dnb$V1),]
dnb <- with(dnb, data.frame(Timestamp=V1, Nback.type=V2, Percentage=V3))
dnb$Date <- as.Date(dnb$Timestamp)
dnbDaily <- aggregate(Percentage ~ Date + Nback.type, dnb, mean)

arbtt1 <- read.csv("~/selfexperiment/2012-2013-arbtt.txt")
arbtt2 <- read.csv("~/selfexperiment/2013-2014-arbtt.txt")
arbtt <- rbind(arbtt1, arbtt2)
rm(arbtt$Percentage)
interval <- function(x) { if (!is.na(x)) { if (grepl(" s",x)) as.integer(sub(" s","",x))
                                          else { y <- unlist(strsplit(x, ":"));
                                                 as.integer(y[[1]])*3600 +
                                                  as.integer(y[[2]])*60 +
                                                  as.integer(y[[3]]);
                                                }
                                          }
                         else NA
                         }
arbtt$Time <- sapply(as.character(arbtt$Time), interval)
library(reshape)
arbtt <- reshape(arbtt, v.names="Time", timevar="Tag", idvar="Day", direction="wide")
arbtt$Date <- as.Date(arbtt$Day)
rm(arbtt$Day)
arbtt[is.na(arbtt)] <- 0

patches <- read.csv("~/selfexperiment/patchlog-gwern.net.txt", colClasses=c("integer", "Date"))
patches$Gwern.net.patches.log <- log1p(patches$Gwern.net.patches)

# modified lines per day is much harder: state machine to sum lines until it hits the next date
patchCount <- scan(file="~/selfexperiment/patchlog-linecount-gwern.net.txt", character(), sep = "\n")
patchLines <- new.env()
for (i in 1:length(patchCount)) {
 if (grepl("\t", patchCount[i])) { patchLines[[date]] <- patchLines[[date]] +
                                                          sum(sapply(strsplit(patchCount[i], "\t"), as.integer))
                                  }
  else { date <- patchCount[i]
   patchLines[[date]] <- 0 }
   }
patchLines <- as.list(patchLines)
patchLines <- data.frame(
         Date = rep(names(patchLines), lapply(patchLines, length)),
         Gwern.net.linecount= unlist(patchLines))
rm(row.names(patchLines))
patchLines$Date <- as.Date(patchLines$Date)
patchLines$Gwern.net.linecount.log <- log1p(patchLines$Gwern.net.linecount)

firstDay <- patches$Date[1]; lastDay <- patches$Date[nrow(patches)]
patches <- merge(merge(patchLines, patches, all=TRUE), data.frame(Date=seq(firstDay, lastDay, by="day")), all=TRUE)

# if entries are missing, they == 0
patches[is.na(patches)] <- 0

# combine all the data:
llltData <- merge(merge(merge(merge(merge(lllt, mp, all=TRUE), creativity, all=TRUE), dnbDaily, all=TRUE), arbtt, all=TRUE), patches, all=TRUE)
write.csv(llltData, file="2014-08-08-lllt-correlation-factoranalysis.csv", row.names=FALSE)

Fac­tor analy­sis. The strat­e­gy: read in the data, drop unnec­es­sary data, impute miss­ing vari­ables (data is too het­ero­ge­neous and col­lected start­ing at vary­ing inter­vals to be clean), esti­mate how many fac­tors would fit best, fac­tor ana­lyze, pick the ones which look like they match best my ideas of what ‘pro­duc­tive’ is, extract per-day esti­mates, and finally regress LLLT usage on the selected fac­tors to look for increas­es.

lllt <- read.csv("https://www.gwern.net/docs/nootropics/2014-08-08-lllt-correlation-factoranalysis.csv")
## the log transforms are more useful:
rm(lllt$Date, lllt$Nback.type, lllt$Gwern.net.linecount, lllt$Gwern.net.patches)

## https://stats.stackexchange.com/questions/28576/filling-nas-in-a-dataset-with-column-medians-in-r
imputeColumnAsMedian <- function(x){
   x[is.na(x)] <- median(x, na.rm=TRUE) #convert the item with NA to median value from the column
   x #display the column
}
llltI  <- data.frame(apply(lllt, 2, imputeColumnAsMedian))

library(psych)
nfactors(llltI[-c(1,2)])
# VSS complexity 1 achieves a maximum of 0.56  with  16  factors
# VSS complexity 2 achieves a maximum of 0.66  with  16  factors
# The Velicer MAP achieves a minimum of 0.01  with  1  factors
# Empirical BIC achieves a minimum of  -280.23  with  8  factors
# Sample Size adjusted BIC achieves a minimum of  -135.77  with  9  factors

fa.parallel(llltI[-c(1,2)], n.iter=2000)
# Parallel analysis suggests that the number of factors =  7  and the number of components =  7
## split the difference between sample-size adjusted BIC and parallel analysis with 8:
factorization <- fa(llltI[-c(1,2)], nfactors=8); factorization
# Standardized loadings (pattern matrix) based upon correlation matrix
#                           MR6   MR1   MR2   MR4   MR3   MR5   MR7   MR8     h2    u2 com
# Creativity.self.rating   0.22  0.06 -0.04  0.08 -0.04  0.02 -0.05 -0.14 0.0658 0.934 2.5
# Percentage              -0.05 -0.02  0.01  0.01  0.00 -0.42  0.02  0.02 0.1684 0.832 1.0
# Time.X                  -0.04  0.11  0.04  0.88 -0.02  0.01  0.01  0.02 0.8282 0.172 1.0
# Time.PDF                 0.02  0.99 -0.02  0.04  0.02  0.00 -0.01 -0.01 0.9950 0.005 1.0
# Time.Stats              -0.10  0.21  0.12  0.16 -0.04  0.04  0.12  0.25 0.2310 0.769 4.3
# Time.IRC                 0.01 -0.02  0.99  0.02  0.02  0.01  0.00 -0.01 0.9950 0.005 1.0
# Time.Writing             0.01 -0.02  0.01  0.04 -0.01 -0.03  0.68  0.04 0.4720 0.528 1.0
# Time.Rec                 0.20 -0.12 -0.06  0.42  0.62 -0.02 -0.07 -0.01 0.8501 0.150 2.2
# Time.Music              -0.05  0.05  0.02  0.02 -0.04  0.22  0.02  0.13 0.0909 0.909 2.0
# Time.SRS                -0.07  0.09  0.08  0.00  0.00  0.08  0.06  0.16 0.0702 0.930 3.6
# Time.Sysadmin            0.05 -0.09 -0.04  0.15  0.07  0.01  0.14  0.42 0.2542 0.746 1.7
# Time.Bitcoin             0.45  0.02  0.25 -0.07 -0.03 -0.09 -0.04  0.11 0.3581 0.642 1.9
# Time.Backups             0.22  0.10 -0.08 -0.19  0.12  0.13  0.02  0.27 0.1809 0.819 4.3
# Time.Blackmarkets        0.62 -0.01  0.06 -0.02 -0.09 -0.01 -0.04  0.15 0.4442 0.556 1.2
# Time.Programming         0.06 -0.01 -0.01 -0.04  0.07  0.08  0.41 -0.07 0.1790 0.821 1.3
# Time.DNB                -0.01 -0.01  0.02  0.01 -0.01  0.76 -0.01  0.00 0.5800 0.420 1.0
# Time.Typing             -0.04  0.05  0.02  0.01 -0.02 -0.01  0.00 -0.01 0.0054 0.995 2.9
# Time.Umineko            -0.10  0.08  0.06 -0.15  0.77 -0.01  0.03  0.02 0.5082 0.492 1.2
# Gwern.net.linecount.log  0.65  0.03  0.00 -0.03  0.04  0.00  0.10 -0.13 0.4223 0.578 1.1
# Gwern.net.patches.log    0.11  0.02 -0.01  0.02  0.00  0.06  0.29 -0.06 0.1001 0.900 1.5
#
#                        MR6  MR1  MR2  MR4  MR3  MR5  MR7  MR8
# SS loadings           1.24 1.12 1.13 1.13 1.05 0.86 0.80 0.48
# Proportion Var        0.06 0.06 0.06 0.06 0.05 0.04 0.04 0.02
# Cumulative Var        0.06 0.12 0.17 0.23 0.28 0.33 0.37 0.39
# Proportion Explained  0.16 0.14 0.14 0.14 0.13 0.11 0.10 0.06
# Cumulative Proportion 0.16 0.30 0.45 0.59 0.73 0.84 0.94 1.00
#
#  With factor correlations of
#       MR6   MR1   MR2   MR4   MR3   MR5   MR7  MR8
# MR6  1.00 -0.13  0.26  0.15  0.22 -0.09  0.03 0.16
# MR1 -0.13  1.00 -0.12  0.25 -0.05  0.06  0.12 0.11
# MR2  0.26 -0.12  1.00  0.04 -0.04  0.10  0.20 0.19
# MR4  0.15  0.25  0.04  1.00  0.32  0.01 -0.05 0.10
# MR3  0.22 -0.05 -0.04  0.32  1.00 -0.04 -0.07 0.00
# MR5 -0.09  0.06  0.10  0.01 -0.04  1.00  0.11 0.11
# MR7  0.03  0.12  0.20 -0.05 -0.07  0.11  1.00 0.20
# MR8  0.16  0.11  0.19  0.10  0.00  0.11  0.20 1.00
#
# Mean item complexity =  1.9
# Test of the hypothesis that 8 factors are sufficient.
#
# The degrees of freedom for the null model are  190
# and the objective function was  2.46 with Chi Square of  5344.68
# The degrees of freedom for the model are 58  and the objective function was  0.07
#
# The root mean square of the residuals (RMSR) is  0.02
# The df corrected root mean square of the residuals is  0.03
#
# The harmonic number of observations is  2178 with the empirical chi square  190.08  with prob <  5.9e-16
# The total number of observations was  2178  with MLE Chi Square =  149.65  with prob <  4.9e-10
#
# Tucker Lewis Index of factoring reliability =  0.942
# RMSEA index =  0.027  and the 90 % confidence intervals are  0.022 0.032
# BIC =  -296.15
# Fit based upon off diagonal values = 0.98
# Measures of factor score adequacy
#                                                 MR6  MR1  MR2  MR4  MR3  MR5  MR7   MR8
# Correlation of scores with factors             0.84 1.00 1.00 0.93 0.89 0.80 0.76  0.64
# Multiple R square of scores with factors       0.70 0.99 0.99 0.86 0.79 0.63 0.58  0.41
# Minimum correlation of possible factor scores  0.40 0.99 0.99 0.71 0.58 0.27 0.16 -0.19

The impor­tant fac­tors seem to be: #1/MR6 (Creativity.self.rating, Time.Bitcoin, Time.Backups, Time.Blackmarkets, Gwern.net.linecount.log), #2/MR1 (Time.PDF, Time.Stats), #7/MR7 (Time.Writing, Time.Sysadmin, Time.Programming, Gwern.net.patches.log), and #8/MR8 (Time.States, Time.SRS, Time.Sysadmin, Time.Backups, Time.Blackmarkets). The rest seem to be time-wast­ing or reflect dual n-back/DNB usage (which is not rel­e­vant in the LLLT time peri­od).

So we want to extract and look at fac­tors #1/2/7/8 (MR6/1/7/8):

lllt$MR6 <- predict(factorization, data=llltI[-c(1,2)])[,1]
lllt$MR1 <- predict(factorization, data=llltI[-c(1,2)])[,2]
lllt$MR7 <- predict(factorization, data=llltI[-c(1,2)])[,7]
lllt$MR8 <- predict(factorization, data=llltI[-c(1,2)])[,8]
l <- lm(cbind(MR6, MR1, MR7, MR8) ~ LLLT, data=lllt); summary(l)
# Response MR6 :
# Coefficients:
#              Estimate Std. Error  t value Pr(>|t|)
# (Intercept) 1.5307773  0.0736275 20.79085  < 2e-16
# LLLTTRUE    0.1319675  0.1349040  0.97823  0.32868
#
# Response MR1 :
# Coefficients:
#               Estimate Std. Error  t value  Pr(>|t|)
# (Intercept) -0.1675241  0.0609841 -2.74701 0.0063473
# LLLTTRUE     0.0317851  0.1117381  0.28446 0.7762378
#
# Response MR7 :
# Coefficients:
#               Estimate Std. Error  t value Pr(>|t|)
# (Intercept) -0.0924052  0.0709438 -1.30251 0.193658
# LLLTTRUE     0.2556655  0.1299869  1.96686 0.050045
#
# Response MR8 :
# Coefficients:
#              Estimate Std. Error t value Pr(>|t|)
# (Intercept) 0.0741850  0.0687618 1.07887  0.28144
# LLLTTRUE    0.1380131  0.1259889 1.09544  0.27413
0.2556655 / sd(lllt$MR7)
# [1] 0.335510445
summary(manova(l))
#            Df     Pillai approx F num Df den Df  Pr(>F)
# LLLT        1 0.01372527 1.127218      4    324 0.34355
# Residuals 327

All of the coeffi­cients are pos­i­tive, as one would hope, and one spe­cific fac­tor (MR7) squeaks in at d = 0.34 (p = 0.05). The graph is much less impres­sive than the graph for just MP, sug­gest­ing that the cor­re­la­tion may be spread out over a lot of fac­tors, the cur­rent dataset isn’t doing a good job of cap­tur­ing the effect com­pared to the MP self­-rat­ing, or it really was a placebo effect:

Daily MR7 activ­ity (writing/programming) fac­tor cor­re­lated with LLLT usage (2013-2014)
library(ggplot2)
llltRecent$index <- 1:nrow(llltRecent)
qplot(index, MR7, color=LLLT, data=llltRecent) +
 geom_point(size=I(3)) +
 stat_smooth() +
 scale_colour_manual(values=c("gray49", "green"),
                     name = "LLLT")

The con­cen­tra­tion in one fac­tor leaves me a bit dubi­ous. We’ll see what the exper­i­ment turns up.

Experiment

A ran­dom­ized non-blind self­-ex­per­i­ment of LLLT 2014-2015 yields a causal effect which is sev­eral times smaller than a cor­rel­a­tive analy­sis and non-statistically-significant/very weak Bayesian evi­dence for a pos­i­tive effect. This sug­gests that the ear­lier result had been dri­ven pri­mar­ily by reverse cau­sa­tion, and that my LLLT usage has lit­tle or no ben­e­fits.

Fol­low­ing up on the promis­ing but unran­dom­ized pilot, I began ran­dom­iz­ing my LLLT usage since I wor­ried that more pro­duc­tive days were caus­ing use rather than vice-ver­sa. I began on 2014-08-02, and the last day was 2015-03-03 (n = 167); this was twice the sam­ple size I thought I need­ed, and I stopped, as before, as part of clean­ing up (I wanted to know whether to get rid of it or not). The pro­ce­dure was sim­ple: by noon, I flipped a bit and either did or did not use my LED device; if I was dis­tracted or did­n’t get around to ran­dom­iza­tion by noon, I skipped the day. This was an unblinded exper­i­ment because find­ing a ran­dom­ized on/off switch is tricky/expensive and it was eas­ier to just start the exper­i­ment already. The ques­tion is sim­ple too: con­trol­ling for the simul­ta­ne­ous blind mag­ne­sium exper­i­ment & my rare nico­tine use (I did not use modafinil dur­ing this period or any­thing else I expect to have major influ­ence), is the pilot cor­re­la­tion of d = 0.455 on my daily self­-rat­ings borne out by the exper­i­ment?

Daily pro­duc­tiv­ity self­-rat­ing (high­er=­bet­ter) over time, split by LLLT usage that day (2014-2015)
llltRandom <- read.csv("https://www.gwern.net/docs/nootropics/2015-lllt-random.csv",
                        colClasses=c("Date", "logical", "integer", "logical", "logical"))
# impute magnesium data: that randomized experiment started a month later
llltRandom[is.na(llltRandom$Magnesium.random),]$Magnesium.random <- 0
l <- lm(MP ~ LLLT.random + Nicotine + Magnesium.random, data=llltRandom); summary(l); confint(l)
# ...Coefficients:
#                    Estimate Std. Error  t value Pr(>|t|)
# (Intercept)      3.28148626 0.06856553 47.85912  < 2e-16
# LLLT.randomTRUE  0.04099628 0.09108322  0.45010  0.65324
# NicotineTRUE     0.21152245 0.26673557  0.79300  0.42893
# Magnesium.random 0.10299190 0.09312616  1.10594  0.27038
#
# Residual standard error: 0.5809214 on 163 degrees of freedom
#   (47 observations deleted due to missingness)
# Multiple R-squared:  0.01519483,  Adjusted R-squared:  -0.002930415
# F-statistic: 0.8383241 on 3 and 163 DF,  p-value: 0.474678
#
#                           2.5 %       97.5 %
# (Intercept)       3.14609507948 3.4168774481
# LLLT.randomTRUE  -0.13885889747 0.2208514560
# NicotineTRUE     -0.31518017129 0.7382250752
# Magnesium.random -0.08089731164 0.2868811034
0.04099628 / sd(llltRandom$MP)
# [1] 0.0701653002

library(ggplot2)
ggplot(data = llltRandom, aes(x=Date, y=MP, col=as.logical(llltRandom$LLLT.random))) +
 geom_point(size=I(3)) +
 stat_smooth() +
 scale_colour_manual(values=c("gray49", "blue"),
                     name = "LLLT")

The esti­mate of the causal effect of LLLT+placebo is not sta­tis­ti­cal­ly-sig­nifi­cant, and the effect size of +0.04 / d = 0.07 is much smaller than d = 0.455 (15%) and the orig­i­nal pilot’s point esti­mate of +0.33 is excluded by the new con­fi­dence inter­val (95% CI: -0.13 - +0.22).

I have strong pri­ors about the pos­si­ble effects of LLLT, nico­tine & mag­ne­sium (specifi­cal­ly, I know from expe­ri­ence that they tend to be smal­l), so a Bayesian lin­ear model using JAGS is use­ful for let­ting me take that into account and also pro­duc­ing more mean­ing­ful results (prob­a­bil­i­ties, rather than p-val­ues):

## JAGS won't automatically drop rows with missing variables like `lm` does by default
llltClean <- llltRandom[!is.na(llltRandom$LLLT.random),]
library(rjags)
library(R2jags)
model1<-"
model {
    for (i in 1:n) {
        MP[i] ~ dnorm(MP.hat[i], tau)
        MP.hat[i] <- a + b1*LLLT.random[i] + b2*Nicotine[i] + b3*Magnesium.random[i]
    }

    # intercept
    a  ~ dnorm(3, 4) # precision 4 ~= 0.5^-2 ~= SD 0.5, the historical SD of my MPs

    # coefficients
    ## informative prior: effects should be <0.5 usually, and >0.3 is unusual
    b1 ~ dnorm(0, 13) # precision 13 ~= SD 0.3
    b2 ~ dnorm(0, 13)
    b3 ~ dnorm(0, 13)

    # informative prior: 2-5 doesn't allow for much variance
    sigma ~ dunif(0, 1)
    # convert SD to 'precision' unit that JAGS's distributions use instead
    tau <- pow(sigma, -2)
}
"
j1 <- with(llltClean, jags(data=list(n=nrow(llltClean), MP=MP, LLLT.random=LLLT.random,
                                       Nicotine=Nicotine, Magnesium.random=Magnesium.random),
                         parameters.to.save=c("b1", "b2", "b3"),
                         model.file=textConnection(model1),
                         n.chains=getOption("mc.cores"), n.iter=1000000))
print(j1, intervals=c(0.0001, 0.5, 0.9999))
# Inference for Bugs model at "4", fit using jags,
#  4 chains, each with 1e+06 iterations (first 5e+05 discarded), n.thin = 500
#  n.sims = 4000 iterations saved
#          mu.vect sd.vect   0.01%     50%  99.99%  Rhat n.eff
# b1         0.042   0.087  -0.276   0.041   0.326 1.002  2100
# b2         0.114   0.194  -0.533   0.114   0.745 1.001  4000
# b3         0.100   0.088  -0.266   0.100   0.412 1.001  4000
# deviance 293.023   2.864 288.567 292.420 314.947 1.001  4000
#
# For each parameter, n.eff is a crude measure of effective sample size,
# and Rhat is the potential scale reduction factor (at convergence, Rhat=1).
#
# DIC info (using the rule, pD = var(deviance)/2)
# pD = 4.1 and DIC = 297.1
# DIC is an estimate of expected predictive error (lower deviance is better).

This analy­sis sug­gests that there’s a 95% prob­a­bil­ity the effect is some­where between -0.129 & 0.208 (d=-0.22 - d = 0.35), sim­i­lar to the orig­i­nal lin­ear mod­el’s CI. More rel­e­vant­ly: there is only a 70% prob­a­bil­ity that the effect is >0 (al­beit prob­a­bly tiny), and >99.99% prob­a­bil­ity it’s not as big as the pilot data had claimed.

At small effects like d = 0.07, a non­triv­ial chance of neg­a­tive effects, and an unknown level of placebo effects (this was non-blind­ed, which could account for any resid­ual effect­s), this strongly implies that LLLT is not doing any­thing for me worth both­er­ing with. I was pretty skep­ti­cal of LLLT in the first place, and if 167 days can’t turn up any­thing notice­able, I don’t think I’ll be con­tin­u­ing with LLLT usage and will be giv­ing away my LED set. (Should any exper­i­men­tal stud­ies of LLLT for cog­ni­tive enhance­ment in healthy peo­ple sur­face with large quan­ti­ta­tive effects - as opposed to a hand­ful of qual­i­ta­tive case stud­ies about brain-dam­aged peo­ple - and I decide to give LLLT another try, I can always just buy another set of LEDs: it’s only ~$15, after all.)

LSD microdosing

For the full writeup of back­ground, method­ol­o­gy, data, and sta­tis­ti­cal analy­sis, please see the page.

Intrigued by old sci­en­tific results & many pos­i­tive anec­dotes since, I exper­i­mented with “micro­dos­ing” - tak­ing doses ~10μg, far below the level at which it causes its famous effects. At this lev­el, the anec­dotes claim the usual broad spec­trum of pos­i­tive effects on mood, depres­sion, abil­ity to do work, etc. After research­ing the mat­ter a bit, I dis­cov­ered that as far as I could tell, since the orig­i­nal exper­i­ment in the 1960s, no one had ever done a blind or even a ran­dom­ized self­-ex­per­i­ment on it.

The self­-ex­per­i­ment was sim­ple: I ordered two tabs off Silk Road, dis­solved one in dis­tilled water, put the solu­tion in one jar & tap water in the oth­er, and took them in pairs of 3-day blocks.

The results of my pre-spec­i­fied analy­sis on a well-pow­ered ran­dom­ized blind self­-ex­per­i­ment:

  1. Sleep:

    • laten­cy: none (p = 0.42)

    • total sleep: none (p = 0.14)

    • num­ber of awak­en­ings: none (p = 0.36)

    • morn­ing feel: increased (p = 0.02)

      There is an increase in “Morn­ing Feel” from 2.6 to 2.9, d = 0.42 & p = 0.023; cor­rect­ing for per­form­ing 7 differ­ent tests, this result is not sta­tis­ti­cal­ly-sig­nifi­cant (it does not sur­vive a (since ) nor the q-value approach to fam­i­ly-wise cor­rec­tion).

  2. Mnemosyne flash­card scores: none (p = 0.52)

  3. Mood/productivity: none (d=-0.18; p = 0.86)

  4. Cre­ativ­i­ty: none (d=-0.19; p = 0.87)

I con­cluded that if any­thing, the LSD micro­dos­ing may done the oppo­site of what I want­ed.

Magnesium

Main arti­cle:

TODO

Melatonin

See for infor­ma­tion on effects & cost; I reg­u­larly use mela­tonin to sleep (more to induce sleep than pro­long or deepen it), and inves­ti­gat­ing with my Zeo, it does seem to improve & shorten my sleep. Some research sug­gests that higher doses are not nec­es­sar­ily bet­ter and may be overkill, so each time I’ve run out, I’ve been steadily decreas­ing the dose from 3mg to 1.5mg to 1mg, with­out appar­ently com­pro­mis­ing the use­ful­ness.

Modafinil

See for back­ground on per­for­mance improve­ments and side-effects; the fol­low­ing sec­tions are about my usage.

SpierX

Here are the notes I jot­ted down while try­ing out modafinil back in Novem­ber 2009. I did­n’t make any effort to write sen­si­bly, so this makes my lucid­ity seem much worse than it actu­ally was:

Thurs­day: 3g piracetam/4g choline bitar­trate at 1; 1 200mg modafinil at 2:20; noticed a ‘lev­el­ing’ of fatigue by 3:30; dry eyes? no bad after taste or any­thing. a lit­tle light-headed by 4:30, but men­tally clear and focused. won­der if light-head­ed­ness is due sim­ply to miss­ing lunch and not modafinil. 5:43: noticed my foot jig­gling - does­n’t usu­ally jig­gle while in piracetam/choline. 7:30: start­ing feel­ing a bit jit­tery & manic - not much or to a prob­lem­atic level but defi­nitely notice­able; but then, that often hap­pens when I miss lunch & din­ner. 12:30: bed­time. Can’t sleep even with 3mg of mela­ton­in! Sub­jec­tive­ly, I toss & turn (in part thanks to my cat) until 4:30, when I really wake up. I hang around bed for another hour & then give up & get up. After a show­er, I feel fairly nor­mal, strange­ly, though not as good as if I had truly slept 8 hours. The les­son here is to pay atten­tion to wikipedia when it says the half-life is 12-15 hours! About 6AM I take 200mg; all the way up to 2pm I feel increas­ingly less ener­getic and unfo­cused, though when I do apply myself I think as well as ever. Not fixed by food or tea or piracetam/choline. I want to be up until mid­night, so I take half a pill of 100mg and chew it (since I’m not plan­ning on stay­ing up all night and I want it to work rel­a­tively soon). From 4-12PM, I notice that today as well my heart rate is ele­vat­ed; I mea­sure it a few times and it seems to aver­age to ~70BPM, which is higher than nor­mal, but not high enough to con­cern me. I stay up to mid­night fine, take 3mg of mela­tonin at 12:30, and have no trou­ble sleep­ing; I think I fall asleep around 1. Alarm goes off at 6, I get up at 7:15 and take the other 100mg. Only 100mg/half-a-pill because I don’t want to leave the half lay­ing around in the open, and I’m curi­ous whether 100mg + ~5 hours of sleep will be enough after the last 2 days. Maybe next week­end I’ll just go with­out sleep entirely to see what my lim­its are.

In gen­er­al, I feel a lit­tle bit less alert, but still close to nor­mal. By 6PM, I have a mild headache, but I try out 30 rounds of gbrainy (haven’t played it in months) and am sur­prised to find that I reach an all-time high; no idea whether this is due to DNB or not, since Gbrainy is very heav­ily ‘crys­tal­lized’ (half the chal­lenge dis­ap­pears as you learn how the prob­lems work), but it does indi­cate I’m not delud­ing myself about men­tal abil­i­ty. (To give a fig­ure: my last score well before I did any DNB was 64, and I was doing well that day; on modafinil, I had a 77.) I fig­ure the headache might be food relat­ed, eat, and by 7:30 the headache is pretty much gone and I’m fine up to mid­night.

I took 1.5mg of mela­ton­in, and went to bed at ~1:30AM; I woke up around 6:30, took a modafinil pill/200mg, and felt pretty rea­son­able. By noon my mind started to feel a bit fuzzy, and lunch did­n’t make much of it go away. I’ve been look­ing at stud­ies, and users seem to degrade after 30 hours; I started on mid-Thurs­day, so call that 10 hours, then 24 (Fri­day), 24 (Sat­ur­day), and 14 (Sun­day), total­ing 72hrs with <20hrs sleep; this might be equiv­a­lent to 52hrs with no sleep, and writes:

One study of heli­copter pilots sug­gested that 600 mg of modafinil given in three doses can be used to keep pilots alert and main­tain their accu­racy at pre-de­pri­va­tion lev­els for 40 hours with­out sleep­.[60] How­ev­er, sig­nifi­cant lev­els of nau­sea and ver­tigo were observed. Another study of fighter pilots showed that modafinil given in three divided 100 mg doses sus­tained the flight con­trol accu­racy of sleep­-de­prived F-117 pilots to within about 27% of base­line lev­els for 37 hours, with­out any con­sid­er­able side effect­s.[61] In an 88-hour sleep loss study of sim­u­lated mil­i­tary grounds oper­a­tions, 400 mg/day doses were mildly help­ful at main­tain­ing alert­ness and per­for­mance of sub­jects com­pared to place­bo, but the researchers con­cluded that this dose was not high enough to com­pen­sate for most of the effects of com­plete sleep loss.

If I stop tonight and do noth­ing Mon­day (and I sleep the nor­mal eight hours and do not pay any penal­ty), then that’ll be 4 out of 5 days on modafinil, each sav­ing 3 or 4 hours. Each day took one pill which cost me $1.20, but each pill saved let’s call it 3.5 hours; if I value my time at min­i­mum wage, or 7.25/hr (fed­eral min­i­mum wage), then that 3.5 hours is worth $25.37, which is much more than $1.20, ~21x more.

My men­tal per­for­mance con­tin­ues as before; curi­ous­ly, I get an even higher score on Gbrainy, despite being sure I was less sharp than yes­ter­day. Either I’m wrong about that, or Gbrainy is even more train­able than I thought. I go to bed Sun­day around 1AM, and get up around 8AM (so call it 6 or 7 hours).

Mon­day: It’s a long day ahead of me, so I take 200mg. Rea­son­able per­for­mance.

Tues­day: I went to bed at 1am, and first woke up at 6am, and I wrote down a dream; the lucid dream­ing book I was read­ing advised that wak­ing up in the morn­ing and then going back for a short nap often causes lucid dreams, so I tried that - and wound up wak­ing up at 10am with no dreams at all. Oops. I take a pill, but the whole day I don’t feel so hot, although my con­ver­sa­tion and argu­ments seem as cogent as ever. I’m also hav­ing a ter­ri­ble time focus­ing on any actual work. At 8 I take anoth­er; I’m behind on too many things, and it looks like I need an all-nighter to catch up. The dose is no good; at 11, I still feel like at 8, pos­si­bly worse, and I take another along with the choline+pirac­etam (which makes a total of 600mg for the day). Come 12:30, and I dis­con­so­lately note that I don’t seem any bet­ter, although I still seem to under­stand the IQ essays I am read­ing. I won­der if this is tol­er­ance to modafinil, or per­haps sleep catch­ing up to me? Pos­si­bly it’s just that I don’t remem­ber what the qua­si­-light-head­ed­ness of modafinil felt like. I feel this sort of zom­bie-like state with­out change to 4am, so it must be doing some­thing, when I give up and go to bed, get­ting up at 7:30 with­out too much trou­ble. Some N-back­ing at 9am gives me some low scores but also some pretty high scores (38/43/66/40/24/67/60/71/54 or ▂▂▆▂▁▆▅▇▄), which sug­gests I can per­form nor­mally if I con­cen­trate. I take another pill and am fine the rest of the day, going to bed at 1am as usu­al.

Thurs­day: this is an impor­tant day where I really need to be awake. I’m up around 8, take a pill, and save one for lat­er; I’ll take half a pill at noon and the other half at 2. This works very well, and I don’t feel tired well up to mid­night, even though I spent an hour walk­ing.

Fri­day: alarm clock woke me at 7:40, but I some­how man­aged to go back to sleep until 9:40. Per­haps sleep iner­tia is build­ing up despite the modafinil. Another pill. I am in gen­eral notic­ing less effect, but I’ll not take any this week­end to see whether I have sim­ply got­ten used to it.

Sat/Sun: bed at 1/2AM, awake at 10/11 respec­tive­ly. Gen­er­ally unmo­ti­vat­ed.

Mon: went to bed at 11:30 Sun, woke at 7:30 and dozed to 8. 200mg at 8:30. No par­tic­u­lar effect. Past this, I stop keep­ing notes. The main thing I notice is that my throat seems to be a lit­tle rough and my voice hoarser than usu­al.

(On a side note, I think I under­stand now why modafinil does­n’t lead to a sce­nar­io; BiS includes mas­sive IQ and moti­va­tion boosts as part of the Sleep­less mod­i­fi­ca­tion. Just adding 8 hours a day does­n’t do the world-chang­ing trick, no more than some researchers liv­ing to 90 and oth­ers to 60 has lead to the for­mer tak­ing over. If every­one were sud­denly granted the abil­ity to never need sleep, many of them would have no idea what to do with the extra 8 or 9 hours and might well be destroyed by the gift; it takes a lot of moti­va­tion to make good use of the time, and if one can­not, then it is a curse akin to the sto­ries of immor­tals who yearn for death - they yearn because life is not a bless­ing to them, though that is a fact more about them than life.)

Modalert

In 2011, as part of the Silk Road research, I ordered 10x100mg Modalert (5btc) from a sell­er. I also asked him about his sourcing, since if it was bad, it’d be valu­able to me to know whether it was sourced from one of the ven­dors listed in my table. He replied, more or less, “I get them from a large Far East­ern phar­ma­ceu­ti­cals whole­saler. I think they’re prob­a­bly the sup­plier for a num­ber of the online phar­ma­cies.” 100mg seems likely to be too low, so I treated this ship­ment as 5 dos­es:

  1. I split the 2 pills into 4 doses for each hour from mid­night to 4 AM. 3D dri­ver issues in Debian unsta­ble pre­vented me from using Brain Work­shop, so I don’t have any DNB scores to com­pare with the armodafinil DNB scores. I had the sub­jec­tive impres­sion that I was worse off with the Modalert, although I still man­aged to get a fair bit done so the deficits could­n’t’ve been too bad. The apa­thy dur­ing the morn­ing felt worse than armodafinil, but that could have been caused by or exac­er­bated by an unex­pected and very stress­ful 2 hour drive through rush hour and mul­ti­ple acci­dents; the quick hour-long nap at 10 AM was half-wak­ing half-light-sleep accord­ing to the Zeo, but seemed to help a bit. As before, I began to feel bet­ter in the after­noon and by evening felt nor­mal, doing my usual read­ing. That night, the Zeo recorded my sleep as last­ing ~9:40, when it was usu­ally more like 8:40-9:00 (although I am not sure that this was due to the modafinil inas­much as once a week or so I tend to sleep in that long, as I did a few days later with­out any influ­ence from the modafinil); assum­ing the worse, the nap and extra sleep cost me 2 hours for a net profit of ~7 hours. While it’s not clear how modafinil affects recov­ery sleep (see the foot­note in the essay), it’s still inter­est­ing to pon­der the ben­e­fits of merely being able to delay sleep18.
  2. I tried tak­ing whole pills at 1 and 3 AM. I felt kind of bushed at 9 AM after all the read­ing, and the 50 minute nap did­n’t help much - I was sleep only around 10 min­utes and spent most of it think­ing or med­i­ta­tion. Just as well the 3D dri­ver is still bro­ken; I doubt the scores would be rea­son­able. Began to perk up again past 10 AM, then felt more bushed at 1 PM, and so on through­out the day; kind of gave up and began watch­ing & fin­ish­ing anime ( and ) for the rest of the day with occa­sional read­ing breaks (eg. to start See­ing Like A State, which is as described so far). As expected from the low qual­ity of the day, the recov­ery sleep was big­ger than before: a full 10 hours rather than 9:40; the next day, I slept a nor­mal 8:50, and the fol­low­ing day ~8:20 (woken up ear­ly); 10:20 (slept in); 8:44; 8:18 (▁▇▁▁). It will be inter­est­ing to see whether my excess sleep remains in the hour range for ‘good’ modafinil nights and two hours for ‘bad’ modafinil nights.
  3. I decided to try out day-time usage on 2 con­sec­u­tive days, tak­ing the 100mg at noon or 1 PM. On both days, I thought I did feel more ener­getic but noth­ing extra­or­di­nary (maybe not even as strong as the nicotine), and I had trou­ble falling asleep on Hal­loween, think­ing about the meta-ethics essay I had been writ­ing dili­gently on both days. Not a good use com­pared to stay­ing up a night.

Modalert blind day trial

Most peo­ple I talk to about modafinil seem to use it for day­time usage; for me that has not ever worked out well, but I had noth­ing in par­tic­u­lar to show against it. So, as I was cap­ping the last of my pirac­etam-caffeine mix and clear­ing off my desk, I put the 4 remain­ing Modalerts pills into cap­sules with the last of my cre­a­tine pow­der and then mixed them with 4 of the thea­nine-cre­a­tine pills. Like the pre­vi­ous Adder­all trial, I will pick one pill blindly each day and guess at the end which it was. If it was active (modafinil-cre­atine), take a break the next day; if placebo (thea­nine-cre­atine), replace the placebo and try again the next day. We’ll see if I notice any­thing on DNB or pos­si­bly Gwern.net edits.

  1. Take at 10 AM; seem a bit more active but that could just be the pres­sure of the hol­i­day sea­son com­bined with my nice clean desk. I do the chores with­out too much issue and make progress on other things, but noth­ing major; I sur­vive going to The Sit­ter with­out too much tired­ness, so ulti­mately I decide to give the palm to it being active, but only with 60% con­fi­dence. I check the next day, and it was place­bo. Oops.
  2. Take at 11 AM; dis­trac­tions ensue and the Christ­mas tree-cut­ting also takes up much of the day. By 7 PM, I am exhausted and in a bad mood. While I don’t expect day-time modafinil to buoy me up, I do expect it to at least buffer me against being tired, and so I con­clude placebo this time, and with more con­fi­dence than yes­ter­day (65%). I check before bed, and it was place­bo.
  3. 10:30 AM; no major effect that I notice through­out the day - it’s nei­ther good nor bad. This smells like placebo (and part of my mind is going ‘how unlikely is it to get placebo 3 times in a row!’, which is just the talk­ing inas­much as this is sam­pling with replace­men­t). I give it 60% place­bo; I check the next day right before tak­ing, and it is. Man!
  4. 1 PM; over­all this was a pretty pro­duc­tive day, but I can’t say it was very pro­duc­tive. I would almost say even odds, but for some rea­son I feel a lit­tle more inclined towards modafinil. Say 55%. That night’s sleep was vile: the Zeo says it took me 40 min­utes to fall asleep, I only slept 7:37 total, and I woke up 7 times. I’m com­fort­able tak­ing this as evi­dence of modafinil (half-life 10 hours, 1 PM to mid­night is only 1 full halv­ing), bump­ing my pre­dic­tion to 75%. I check, and sure enough - modafinil.
  5. 10:40 AM; again no major effects, although I got two jQuery exten­sions work­ing and some addi­tional writ­ing so one could argue the day went well. I don’t know; 50%. Place­bo.
  6. 11 AM; a rather pro­duc­tive day. I give it 65%. To my sur­prise, it was place­bo.
  7. 10 AM; this was an espe­cially pro­duc­tive day, but this was also the day my nico­tine gum finally arrived and I just had to try it (I had been wait­ing so long); it’s defi­nitely a stim­u­lant, alright. But this trashes my own sub­jec­tive esti­mates; I hoped it was just place­bo, but no, it was modafinil.
  8. 9:50 AM; noth­ing noticed by noon. Man­aged to fin­ish “Rea­sons of State: Why Did­n’t Den­mark Sell Green­land?” which was a sur­pris­ing amount of work, espe­cially after I man­aged to delete a third of the first draft - but noth­ing I would chalk up to modafinil. I decide to give it 60% place­bo, and I turn out to be wrong: it was my last modafinil.

So with these 8 results in hand, what do I think? Rough­ly, I was right 5 of the days and wrong 3 of them. If not for the sleep effect on #4, which is - in a way - cheat­ing (one hopes to detect modafinil due to good effect­s), the ratio would be 5:4 which is awfully close to a coin-flip. Indeed, a scor­ing rule ranks my per­for­mance at almost iden­ti­cal to a coin flip: -5.49 vs -5.5419. (The bright side is that I did­n’t do worse than a coin flip: I was at least .)

I can’t call this much of a suc­cess; there may be an effect on my pro­duc­tiv­ity but it’s cer­tainly not very clear sub­jec­tive­ly. I’ll chalk this up as a fail­ure for modafinil and evi­dence for what I believed - day-time modafinil use does not work for me (even if it works for oth­er­s).

VoI

For back­ground on “value of infor­ma­tion” cal­cu­la­tions, see the Adder­all cal­cu­la­tion.

I had tried 8 ran­dom­ized days like the Adder­all exper­i­ment to see whether I was one of the peo­ple whom modafinil ener­gizes dur­ing the day. (The other way to use it is to skip sleep, which is my pre­ferred use.) I rarely use it dur­ing the day since my ini­tial uses did not impress me sub­jec­tive­ly. The exper­i­ment was not my best - while it was dou­ble-blind ran­dom­ized, the mea­sure­ments were sub­jec­tive, and not a good mea­sure of men­tal func­tion­ing like dual n-back (DNB) scores which I could sta­tis­ti­cally com­pare from day to day or against my many pre­vi­ous days of dual n-back scores. Between my high expec­ta­tion of find­ing the null result, the poor exper­i­ment qual­i­ty, and the min­i­mal effect it had (elim­i­nat­ing an already rare use), the value of this infor­ma­tion was very small.

I mostly did it so I could tell peo­ple that “no, day usage isn’t par­tic­u­larly great for me; why don’t you run an exper­i­ment on your­self and see whether it was just a placebo effect (or whether you gen­uinely are sleep­-de­prived and it is indeed com­pen­sat­ing)?”

Armodafinil

is sort of a puri­fied modafinil which Cephalon sells under the brand-name ‘Nuvigil’ (and Sun under ‘Wak­lert’20). Armodafinil acts much the same way (see the ADS Drug Pro­file) but the modafinil vari­ant fil­tered out are the faster-act­ing mol­e­cules21. Hence, it is sup­posed to last longer. as stud­ies like “Phar­ma­co­dy­namic effects on alert­ness of sin­gle doses of armodafinil in healthy sub­jects dur­ing a noc­tur­nal period of acute sleep loss” seem to bear out; anec­do­tal­ly, it’s also more pow­er­ful, with Cephalon offer­ing pills with doses as low as 50mg. (To be tech­ni­cal, modafinil is : it comes in two which are rota­tions, mir­ror-im­ages of each oth­er. The rota­tion usu­ally does­n’t mat­ter, but it mat­ters tremen­dously - for exam­ple, one form of stops , and the other rota­tion causes .)

Besides Adder­all, I also pur­chased on 5x250mg pills of armodafinil. The price was extremely rea­son­able, 1.5btc or roughly $23 at that day’s exchange rate; I attribute the low price to the seller being new and need­ing feed­back, and offer­ing a dis­count to induce buy­ers to take a risk on him. (Buy­ers bear a large risk on Silk Road since sell­ers can eas­ily phys­i­cally anonymize them­selves from their ship­ment, but a buyer can be found just by fol­low­ing the pack­age.) Because of the longer active-time, I resolved to test the armodafinil not dur­ing the day, but with an all-nighter.

Nuvigil

  1. First use

    Took full pill at 10:21 PM when I started feel­ing a bit tired. Around 11:30, I noticed my head feel­ing fuzzy but my read­ing seemed to still be up to snuff. I would even­tu­ally fin­ish the sci­ence book around 9 AM the next day, tak­ing some very long breaks to walk the dog, write some poems, write a pro­gram, do Mnemosyne review (mem­ory per­for­mance: sub­jec­tively below aver­age, but not as bad as I would have expected from stay­ing up all night), and some other things. Around 4 AM, I reflected that I felt much as I had dur­ing my night­watch job at the same hour of the day - except I had switched sleep sched­ules for the job. The tired­ness con­tin­ued to build and my willpower weak­ened so the morn­ing was­n’t as pro­duc­tive as it could have been - but my actual per­for­mance when I could be both­ered was still pretty nor­mal. That struck me as kind of inter­est­ing that I can feel very tired and not act tired, in line with the anec­dotes.

    Past noon, I began to feel bet­ter, but since I would be dri­ving to errands around 4 PM, I decided to not risk it and take an hour-long nap, which went well, as did the dri­ving. The evening was nor­mal enough that I for­got I had stayed up the pre­vi­ous night, and indeed, I did­n’t much feel like going to bed until past mid­night. I then slept well, the giv­ing me a 108 ZQ (not an all-time record, but still unusu­al).

  2. I had intended to run another Adder­all trial this day but then I learned we would be going to the mid­night show­ing of the last movie. A per­fect oppor­tu­ni­ty: going to bed at 3 AM after a stim­u­lat­ing bat­tle movie would mean crappy sleep, so why not just do another armodafinil trial and kill 2 birds with one stone?

    I took the pill at 11 PM the evening of (tech­ni­cal­ly, the day before); that day was a lit­tle low on sleep than usu­al, since I had woken up an hour or half-hour ear­ly. I did­n’t yawn at all dur­ing the movie (merely mediocre to my eyes with some ques­tion­able parts)22. It worked much the same as it did the pre­vi­ous time - as I walked around at 5 AM or so, I felt per­fectly alert. I made good use of the hours and wrote up some stuff.

    (As I was doing this, I reflected how modafinil is such a pure exam­ple of the mon­ey-time trade­off. It’s not that you pay some­one else to do some­thing for you, which nec­es­sar­ily they will do in a way differ­ent from you; nor is it that you have exchanged money to free your­self of a bur­den of some future time-in­vest­ment; nor have you paid money for a spec­u­la­tive return of time later in life like with many med­ical expenses or sup­ple­ments. Rather, you have paid for 8 hours today of your own time.)

    And as before, around 9 AM I began to feel the pecu­liar feel­ing that I was men­tally able and apa­thetic (in a sort of way); so I decided to try what helped last time, a short nap. But this time, though I took a full hour, I slept not a wink and my Zeo recorded only 2 tran­sient episodes of light sleep! A back­-handed sort of proof of alert­ness, I sup­pose. I did­n’t bother try­ing again. The rest of the day was medioc­re, and I wound up spend­ing much of it on chores and what­not out of my con­trol. Men­tal­ly, I felt bet­ter past 3 PM.

    This con­tin­ued up to 1 AM, at which point I decided not to take a sec­ond armodafinil (why spend a sec­ond pill to gain what would likely be an unpro­duc­tive set of 8 hours?) and fin­ish up the exper­i­ment with some n-back­ing. My 5 rounds: 60/38/62/44/5023. This was sur­pris­ing. Com­pare those scores with scores from sev­eral pre­vi­ous days: 39/42/44/40/20/28/36. I had esti­mated before the n-back­ing that my scores would be in the low-end of my usual per­for­mance (20-30%) since I had not slept for the past 41 hours, and instead, the low­est score was 38%. If one did not know the con­text, one might think I had dis­cov­ered a good nootrop­ic! Inter­est­ing evi­dence that armodafinil pre­serves at least one kind of men­tal per­for­mance.

  3. I stayed up late writ­ing some and about how , and decided to make a night of it. I took the armodafinil at 1 AM; the inter­est­ing bit is that this was the morning/evening after what turned out to be an Adder­all (as opposed to place­bo) tri­al, so per­haps I will see how well or ill they go togeth­er. A set of nor­mal scores from a pre­vi­ous day was 32%/43%/51%/48%. At 11 PM, I scored 39% on DNB; at 1 AM, I scored 50%/43%; 5:15 AM, 39%/37%; 4:10 PM, 42%/40%; 11 PM, 55%/21%/38%. (▂▄▆▅ vs ▃▅▄▃▃▄▃▇▁▃)

    The pecu­liar tired-sharp feel­ing was there as usu­al, and the DNB scores con­tinue to sug­gest this is not an illu­sion, as they remain in the same 30-50% band as my nor­mal per­for­mance. I did not notice the pre­vi­ous ‘abou­lia’ feel­ing; instead, around noon, I was filled with a ner­vous energy and a dis­turbingly rapid pulse which med­i­ta­tion & deep breath­ing did lit­tle to help with, and which did­n’t go away for an hour or so. For­tu­nate­ly, this was pri­mar­ily at church, so while I felt irri­ta­ble, I did­n’t actu­ally inter­act with any­one or snap at them, and was able to keep a lid on it. I have no idea what that was about. I won­dered if it might’ve been a since amphet­a­mines are some of the drugs that can trig­ger storms but the Adder­all had been at 10:50 AM the pre­vi­ous day, or >25 hours (the half-lives of the ingre­di­ents being around 13 hours). An hour or two pre­vi­ously I had taken my usual caffeine-pirac­etam pill with my morn­ing tea - could that have inter­acted with the armodafinil and the resid­ual Adder­all? Or was it caffeine+­modafinil? Spec­u­la­tion, per­haps. A house­-mate was ill for a few hours the pre­vi­ous day, so maybe the truth is as pro­saic as me catch­ing what­ever he had.

  4. Stayed up with the pur­pose of fin­ish­ing my work for a con­test. This time, instead of tak­ing the pill as a sin­gle large dose (I feel that after 3 times, I under­stand what it’s like), I will take 4 doses over the new day. I took the first quar­ter at 1 AM, when I was start­ing to feel a lit­tle foggy but not majorly impaired. Sec­ond dose, 5:30 AM; feel­ing a lit­tle impaired. 8:20 AM, third dose; as usu­al, I feel phys­i­cally a bit off and men­tally tired - but still men­tally sharp when I actu­ally do some­thing. Early on, my heart rate seemed a bit high and my limbs trem­bling, but it’s pretty clear now that that was the caffeine or pirac­etam. It may be that the other day, it was the caffeine’s fault as I sus­pect­ed. The final dose was around noon. The after­noon ‘crash’ was­n’t so pro­nounced this time, although moti­va­tion remains a prob­lem. I put every­thing into fin­ish­ing up the spaced rep­e­ti­tion lit­er­a­ture review, and did­n’t do any n-back­ing until 11:30 PM: 32/34/31/54/40%.

  5. With the last pill, I wound up try­ing split-doses on non-full nights; that is, if one full pill keeps me awake one full night, what does 1/4th the pill do?

    1. Between mid­night and 1:36 AM, I do four rounds of n-back: 50/39/30/55%. I then take 1/4th of the pill and have some tea. At roughly 1:30 AM, Angry­Pars­ley linked a SF anthology/novel, Fine Struc­ture, which sucked me in for the next 3-4 hours until I finally fin­ished the whole thing. At 5:20 AM, cir­cum­stances forced me to go to bed, still hav­ing only taken 1/4th of the pill and that deter­mines this par­tic­u­lar exper­i­ment of sleep; I quickly do some n-back: 29/20/20/54/42. I fall asleep in 13 min­utes and sleep for 2:48, for a ZQ of 28 (a full night being ~100). I did not notice any­thing from that pos­si­ble modafinil+­caffeine inter­ac­tion. Sub­jec­tively upon awak­en­ing: I don’t feel great, but I don’t feel like 2-3 hours of sleep either. N-back at 10 AM after break­fast: 25/54/44/38/33. These are not very impres­sive, but seem nor­mal despite tak­ing the last armodafinil ~9 hours ago; per­haps the 3 hours were enough. Later that day, at 11:30 PM (just before bed): 26/56/47.
    2. 2 break days lat­er, I took the quar­ter-pill at 11:22 PM. I had dis­cov­ered I had for years phys­i­cally pos­sessed a very long inter­view not avail­able online, and tran­scrib­ing that seemed like a good way to use up a few hours. I did some read­ing, some Mnemosyne, and started it around mid­night, fin­ish­ing around 2:30 AM. There seemed a men­tal dip around 30 min­utes after the armodafinil, but then things really picked up and I made very good progress tran­scrib­ing the final draft of 9000 words in that peri­od. (In com­par­ison, “The Con­science of the Otak­ing” parts 2 & 4 were much eas­ier to read than the tiny font of the RahX­ephon book­let, took per­haps 3 hours, and totaled only 6500 words. The nico­tine is prob­a­bly also to thank.) By 3:40 AM, my writ­ing seems to be clum­sier and my mind fogged. Began DNB at 3:50: 61/53/44. Went to bed at 4:05, fell asleep in 16 min­utes, slept for 3:56. Wak­ing up was eas­ier and I felt bet­ter, so the extra hour seemed to help.
    3. With this exper­i­ment, I broke from the pre­vi­ous method­ol­o­gy, tak­ing the remain­ing and final half Nuvigil at mid­night. I am behind on work and could use a full night to catch up. By 8 AM, I am as usual impressed by the Nuvigil - with Modalert or some­thing, I gen­er­ally start to feel down by mid-morn­ing, but with Nuvig­il, I feel pretty much as I did at 1 AM. Sleep: 9:51/9:15/8:27

Waklert

I noticed on SR some­thing I had never seen before, an offer for 150mgx10 of “Wak­lert” for ₿13.47 (then, ₿1 = $3.14). I searched and it seemed Sun was some­how man­u­fac­tur­ing armodafinil! Inter­est­ing. Maybe not cost-effec­tive, but I tried out of curios­i­ty. They look and are pack­aged the same as the Modalert, but at a higher price-point: 150 rather than 81 rupees. Not entirely sure how to use them: assum­ing qual­ity is the same, 150mg Wak­lert is still 100mg less armodafinil than the 250mg Nuvigil pills.

  1. Take quar­ter at mid­night, another quar­ter at 2 AM. Night runs rea­son­ably well once I remem­ber to eat a lot of food (I fin­ish a big edit­ing task I had put off for week­s), but the apa­thy kicks in early around 4 AM so I gave up and watched , fin­ish­ing around 6 AM. I then read until it’s time to go to a big shot­gun club func­tion, which occu­pies the rest of the morn­ing and after­noon; I had noth­ing to do much of the time and napped very poorly on occa­sion. By the time we got back at 4 PM, the apa­thy was com­pletely gone and I started some modafinil research with gusto (in­ter­rupted by going to see Puss in Boots). That night: Zeo recorded 8:30 of sleep, gap of about 1:50 in the record­ing, fig­ure 10:10 total sleep; fol­low­ing night, 8:33; third night, 8:47; fourth, 8:20 (▇▁▁▁).
  2. First quar­ter at 1:20 AM. Sec­ond quar­ter at 4 AM. 20 minute nap at 7:30 AM; took show and last 2 doses at 11 AM. (If I feel bad past 3 PM, I’ll try one of the Modalerts or maybe another quar­ter of a Wak­lert - 150mg may just be too lit­tle.) Over­all, pretty good day. Nights: 9:43; 9:51; 7:57; 8:25; 8:08; 9:02; 8:07 (▇█▁▂▁▄▁).
  3. First half at 6 AM; sec­ond half at noon. Wrote a short essay I’d been putting off and napped for 1:40 from 9 AM to 10:40. This approach seems to work a lit­tle bet­ter as far as the abou­lia goes. (I also bother to smell my urine this time around - there’s a defi­nite off smell to it.) Nights: 10:02; 8:50; 10:40; 7:38 (2 bad nights of nasal infec­tion­s); 8:28; 8:20; 8:43 (▆▃█▁▂▂▃).
  4. Whole pill at 5:42 AM. (Some­what pro­duc­tive night/morning before­hand.) DNB at 2 PM: 52/36/54 (▇▁█); slept for 49 min­utes; DNB at 8 PM: 50/44/38/40 (▆▄▁▂). Nights: 10:02; 8:02; no data; 9:21; 8:20 (█▁ ▅▂).
  5. Whole pill at 3 AM. I spend the entire morn­ing and after­noon typ­ing up a tran­script of . I tried tak­ing a nap around 10 AM, but dur­ing the hour I was down, I had <5m of light sleep, the Zeo said. After I fin­ished the tran­script (~16,600 words with for­mat­ting), I was com­pletely pooped and watched a bunch of Mobile Suit Gun­dam episodes, then I did . The rest of the night was noth­ing to write home about either - some read­ing, movie watch­ing, etc. Next time I will go back to split-doses and avoid typ­ing up 110kB of text. On the pos­i­tive side, this is the first trial I had avail­able the ‘aver­age daily grade’ Mnemosyne 2.0 plu­g­in. The daily aver­ages all are 3-point-some­thing (peak­ing at 3.89 and floor­ing at 3.59), so just graph­ing the past 2 weeks, the modafinil day, and recov­ery days: ▅█▅▆▄▆▄▃▅▄▁▄▄ ▁ ▂▄▄█. Not an impres­sive per­for­mance but there was a pre­vi­ous non-modafinil day just as bad, and I’m not too sure how impor­tant a met­ric this is; I must see whether future tri­als show sim­i­lar under­per­for­mance. Nights: 11:29; 9:22; 8:25; 8:41.
  6. Spaced rep­e­ti­tion at mid­night: 3.68. (Graph­ing pre­ced­ing and fol­low­ing days: ▅▄▆▆▁▅▆▃▆▄█ ▄ ▂▄▄▅) DNB start­ing 12:55 AM: 30/34/41. Tran­scribed , then took a walk. DNB start­ing 6:45 AM: 45/44/33. Decided to take a nap and then take half the armodafinil on awak­en­ing, before break­fast. I wound up over­sleep­ing until noon (4:28); since it was so late, I took only half the armodafinil sub­lin­gual­ly. I spent the after­noon learn­ing how to do “value of infor­ma­tion” cal­cu­la­tions, and then care­fully work­ing through 8 or 9 exam­ples for my var­i­ous pages, which I pub­lished on Less­wrong. That was a use­ful lit­tle pro­ject. DNB start­ing 12:09 AM: 30/38/48. (To graph the pre­ced­ing day and this night: ▇▂█▆▅▃▃▇▇▇▁▂▄ ▅▅▁▁▃▆) Nights: 9:13; 7:24; 9:13; 8:20; 8:31.
  7. Feel­ing behind, I resolved to take some armodafinil the next morn­ing, which I did - but in my hurry I failed to recall that 200mg armodafinil was prob­a­bly too much to take dur­ing the day, with its long half life. As a result, I felt irri­tated and not that great dur­ing the day (pos­si­bly aggra­vated by some caffeine - I wish some stud­ies would be done on the pos­si­ble inter­ac­tion of modafinil and caffeine so I knew if I was imag­in­ing it or not). Cer­tainly not what I had been hop­ing for. I went to bed after mid­night (half an hour later than usu­al), and suffered severe insom­nia. The time was­n’t entirely wasted as I wrote a short story and fig­ured out how to make nico­tine gum place­bos dur­ing the hours in the dark, but I could have done with­out the expe­ri­ence. All met­rics omit­ted because it was a day usage.

NGF

is a pro­tein involved in exactly what its name sug­gests. Admin­is­tra­tion may have effects on neu­rode­gen­er­a­tion, plas­tic­i­ty, and learn­ing. Its co-dis­cov­er­er, Nobelist , report­edly took NGF eye­drops daily.

NGF may sound intrigu­ing, but the price is a deal­break­er: at sug­gested doses of 1-100μg (NGF dos­ing in humans for ben­e­fits is, shall we say, not an exact sci­ence), and a cost from sketchy sup­pli­ers of $1210/100μg/$470/500μg/$750/1000μg/$1000/1000μg/$1030/1000μg/$235/20μg. (Le­vi-Mon­tal­cini was pre­sum­ably able to divert some of her lab’s pro­duc­tion.) A year’s sup­ply then would be com­i­cally expen­sive: at the low­est doses of 1-10μg using the cheap­est sell­ers (for some­thing one is dump­ing into one’s eye­s?), it could cost any­where up to $10,000.

As well, the pos­si­ble effects seem like they would be long-term and diffi­cult to mea­sure or exper­i­ment on; so if one could some­how afford NGF eye­drops, one would­n’t be able to know they were work­ing.

So unless the price of NGF comes down by at least two orders of mag­ni­tude, it’s not a viable nootrop­ic.

Nicotine

One of the most pop­u­lar legal stim­u­lants in the world, is often con­flated with the harm­ful effects of tobac­co; con­sid­ered on its own, . Nico­tine is widely avail­able at mod­er­ate prices as long-act­ing nico­tine patch­es, gums, lozenges, and sus­pended in water for . While intended for smok­ing ces­sa­tion, there is no rea­son one can­not use a nico­tine patch or nico­tine gum for its stim­u­lant effects.

Nicotine’s stim­u­lant effects are gen­eral and do not come with the same tweak­i­ness and aggres­sion asso­ci­ated with the amphet­a­mi­nes, and sub­jec­tively are much ‘cleaner’ with less of a crash. I would say that its stim­u­lant effects are fairly strong, around that of modafinil. Another advan­tage is that nico­tine oper­ates through nico­tinic recep­tors and so does­n’t cross-tol­er­ate with dopamin­er­gic stim­u­lants (hence one could hypo­thet­i­cally cycle through nicotine, modafinil, amphet­a­mi­nes, and caffeine, hit­ting differ­ent recep­tors each time).

Like caffeine, nico­tine tol­er­ates rapidly and addic­tion can devel­op, after which the appar­ent per­for­mance boosts may only rep­re­sent a return to base­line after with­drawal; so nico­tine as a stim­u­lant should be used judi­cious­ly, per­haps roughly as fre­quent as modafinil. Another prob­lem is that nico­tine has a half-life of merely 1-2 hours, mak­ing reg­u­lar dos­ing a require­ment. There is also some ele­vated heart-rate/blood-pressure often asso­ci­ated with nicotine, which may be a con­cern. (Pos­si­ble alter­na­tives to nico­tine include , 2’-methyl­ni­cotine, , , , WAY-317,538, EVP-6124, and , but none have emerged as clearly supe­ri­or.)

I decided to try it out myself since it would be both bor­ing and hyp­o­crit­i­cal not to. The stim­u­lant prop­er­ties are well-estab­lished, and after read­ing up, I did­n’t think there was a >3% chance it might lead me to any short or long-term future cig­a­rette use.

So I ordered the most cost-effec­tive batch of chew­ing gum I could find on Ama­zon (100 Nicorette 4mg) - and the seller can­celed on me! Poor show, “Direct Super cen­ter”, very poor show.

In August 2011, after win­ning the spaced rep­e­ti­tion con­test and fin­ish­ing up the Adder­all dou­ble-blind test­ing, I decided the time was right to try nico­tine again. I had since learned that e-ci­g­a­rettes use nico­tine dis­solved in water, and that nicotine-wa­ter was a vastly cheaper source of nico­tine than either gum or patch­es. So I ordered 250ml of water at 12mg/ml (to­tal cost: $18.20). A cig­a­rette appar­ently deliv­ers around 1mg of nicotine, so half a ml would be a solid dose of nicotine, mak­ing that ~500 dos­es. Plenty to exper­i­ment with. The ques­tion is, besides the stim­u­lant effect, nico­tine also causes ‘habit for­ma­tion’; what habits should I rein­force with nicotine? Exer­cise, and spaced rep­e­ti­tion seem like 2 good tar­gets.

Nicotine water

It arrived as described, a lit­tle bot­tle around the vol­ume of a soda can. I had handy a plas­tic syringe with mil­li­liter units which I used to mea­sure out the nicotine-wa­ter into my tea. I began with half a ml the first day, 1ml the sec­ond day, and 2ml the third day. (My sleep scores were 85/103/86 (▁▇▁), and the lat­ter had a feline expla­na­tion; these val­ues are within nor­mal vari­a­tion for me, so if nico­tine affects my sleep, it does so to a lesser extent than Adder­al­l.) Sub­jec­tive­ly, it’s hard to describe. At half a ml, I did­n’t really notice any­thing; at 1 and 2ml, I thought I began to notice it - sort of a cleaner caffeine. It’s nice so far. It’s not as strong as I expect­ed. I looked into whether the boil­ing water might be break­ing it down, but the answer seems to be no - boil­ing tobacco is a stan­dard way to extract nicotine, actu­al­ly, and nicotine’s own boil­ing point is much higher than water; nor do I notice a dras­tic differ­ence when I take it in ordi­nary water. And accord­ing to var­i­ous e-ci­g­a­rette sources, the liq­uid should be good for at least a year.

2ml is sup­posed to trans­late to 24mg, which is a big dose. I do not believe any of the com­mer­cial patches go much past that. I asked Wedri­fid, whose notes inspired my ini­tial inter­est, and he was tak­ing per­haps 2-4mg, and expressed aston­ish­ment that I might be tak­ing 24mg. (2mg is in line with what I am told by another per­son - that 2mg was so much that they actu­ally felt a lit­tle sick. On the other hand, in one study, the sub­jects could not reli­ably dis­tin­guish between 1mg and placebo24.) 24mg is par­tic­u­larly trou­bling in that I weigh ~68kg, and and the nico­tine LD50 start, for me, at around 68mg of nico­tine. (I reflected that the entire jar could be a use­ful mur­der weapon, although nico­tine pre­sum­ably would be caught in an autop­sy’s tox­i­col­ogy screen; I later learned nico­tine was an infa­mous weapon in the 1800s before any test was devel­oped. It does­n’t seem used any­more, but there are still fatal acci­dents due to dis­solved nico­tine.) The upper end of the range, 10mg/kg or 680mg for me, is cal­cu­lated based on expe­ri­enced smok­ers. Some­thing is wrong here - I can’t see why I would have nico­tine tol­er­ance com­pa­ra­ble to a hard­ened smok­er, inas­much as my max­i­mum prior expo­sure was sec­ond-hand smoke once in a blue moon. More likely is that either the syringe is mis­lead­ing me or the seller Nic­Vape sold me some­thing more dilute than 12mg/ml. (I am sure that it’s not sim­ply plain water; when I mix the drops with reg­u­lar water, I can feel the burn­ing as it goes down.) I would rather not accuse an estab­lished and appar­ently well-liked sup­plier of fraud, nor would I like to sim­ply shrug and say I have a mys­te­ri­ous tol­er­ance and must exper­i­ment with doses closer to the LD50, so the most likely prob­lem is a prob­lem with the syringe. The next day I altered the pro­ce­dure to suck­ing up 8ml, squirt­ing out enough fluid to move the menis­cus down to 7ml, and then eject­ing the rest back into the con­tain­er. The result was another mild clean stim­u­la­tion com­pa­ra­ble to the pre­vi­ous 1ml days. The next step is to try a com­pletely differ­ent mea­sur­ing device, which does­n’t change either.

One item always of inter­est to me is sleep; a stim­u­lant is no good if it dam­ages my sleep (un­less that’s what it is sup­posed to do, like modafinil) - anec­dotes and research sug­gest that it does. Over the past few days, my Zeo sleep scores con­tin­ued to look nor­mal. But that was while not tak­ing nico­tine much later than 5 PM. In lieu of a differ­ent ml mea­surer to test my the­ory that my syringe is mis­lead­ing me, I decide to more directly test nicotine’s effect on sleep by tak­ing 2ml at 10:30 PM, and go to bed at 12:20; I get a decent ZQ of 94 and I fall asleep in 16 min­utes, a bit below my weekly aver­age of 19 min­utes. The next day, I take 1ml directly before going to sleep at 12:20; the ZQ is 95 and time to sleep is 14 min­utes.

The next cheap propo­si­tion to test is that the 2ml dose is so large that the sedation/depressive effect of nico­tine has begun to kick in. This is easy to test: take much less, like half a ml. I do so two or three times over the next day, and sub­jec­tively the feel­ing seems to be the same - which seems to sup­port that propo­si­tion (although per­haps I’ve been placebo effect­ing myself this whole time, in which case the exact amount does­n’t mat­ter). If this the­ory is true, my pre­vi­ous sleep results don’t show any­thing; one would expect nicotine-as-seda­tive to not hurt sleep or improve it. I skip the day (no crav­ings or addic­tion noticed), and take half a ml right before bed at 11:30; I fall asleep in 12 min­utes and have a ZQ of ~105. The next few days I try putting one or two drops into the tea ket­tle, which seems to work as well (or poor­ly) as before. At that point, I was warned that there were some results that nico­tine with­drawal can kick in with delays as long as a week, so I should­n’t be con­fi­dent that a few days off proved an absence of addic­tion; I imme­di­ately quit to see what the week would bring. 4 or 7 days in, I did­n’t notice any­thing. I’m still using it, but I’m defi­nitely a lit­tle non­plussed and dis­grun­tled - I need some inde­pen­dent source of nico­tine to com­pare with!

After try­ing the nico­tine gum (see below) and expe­ri­enc­ing effects, I decided the liq­uid was busted some­how and to request a refund. To its cred­it, Nic­Vape imme­di­ately agreed to a refund.

Poor absorption?

2 com­menters point out that my pos­si­ble lack of result is due to my mis­taken assump­tion that if nico­tine is absorbable through skin, mouth, and lungs it ought to be per­fectly fine to absorb it through my stom­ach by drink­ing it (rather than vapor­iz­ing it and breath­ing it with an e-ci­g­a­rette machine) - it’s appar­ently known that absorp­tion differs in the stom­ach.

  • the online book The Cig­a­rette Papers describes early ani­mal exper­i­ments (with­out spe­cific bioavail­abil­ity per­cent­ages):

    The Fate of Nico­tine in the Body also describes Bat­telle’s ani­mal work on nico­tine absorp­tion. Using C14-la­beled nico­tine in rab­bits, the Bat­telle sci­en­tists com­pared gas­tric absorp­tion with pul­monary absorp­tion. Gas­tric absorp­tion was slow, and first pass removal of nico­tine by the liver (which trans­forms nico­tine into inac­tive metabo­lites) was demon­strated fol­low­ing gas­tric admin­is­tra­tion, with con­se­quently low sys­temic nico­tine lev­els. In con­trast, absorp­tion from the lungs was rapid and led to wide­spread dis­tri­b­u­tion. These results show that nico­tine absorbed from the stom­ach is largely metab­o­lized by the liver before it has a chance to get to the brain. That is why tobacco prod­ucts have to be puffed, smoked or sucked on, or absorbed directly into the blood­stream (i.e., via a nico­tine patch). A nico­tine pill would not work because the nico­tine would be inac­ti­vated before it reached the brain.

  • “Metab­o­lism and Dis­po­si­tion Kinet­ics of Nico­tine”:

    Absorp­tion of nico­tine across bio­log­i­cal mem­branes depends on pH. Nico­tine is a weak base with a pKa of 8.0 (Fowler, 1954). In its ion­ized state, such as in acidic envi­ron­ments, nico­tine does not rapidly cross mem­branes…About 80 to 90% of inhaled nico­tine is absorbed dur­ing smok­ing as assessed using C14-ni­co­tine (Ar­mitage et al., 1975). The effi­cacy of absorp­tion of nico­tine from envi­ron­men­tal smoke in non­smok­ing women has been mea­sured to be 60 to 80% (Iwase et al., 1991)…The var­i­ous for­mu­la­tions of nico­tine replace­ment ther­apy (NRT), such as nico­tine gum, trans­der­mal patch, nasal spray, inhaler, sub­lin­gual tablets, and lozenges, are buffered to alka­line pH to facil­i­tate the absorp­tion of nico­tine through cell mem­branes. Absorp­tion of nico­tine from all NRTs is slower and the increase in nico­tine blood lev­els more grad­ual than from smok­ing (Table 1). This slow increase in blood and espe­cially brain lev­els results in low abuse lia­bil­ity of NRTs (Hen­ning­field and Keenan, 1993; West et al., 2000). Only nasal spray pro­vides a rapid deliv­ery of nico­tine that is closer to the rate of nico­tine deliv­ery achieved with smok­ing (Suther­land et al., 1992; Gourlay and Benow­itz, 1997; Guthrie et al., 1999). The absolute dose of nico­tine absorbed sys­tem­i­cally from nico­tine gum is much less than the nico­tine con­tent of the gum, in part, because con­sid­er­able nico­tine is swal­lowed with sub­se­quent first-pass metab­o­lism (Benowitz et al., 1987). Some nico­tine is also retained in chewed gum. A por­tion of the nico­tine dose is swal­lowed and sub­jected to first-pass metab­o­lism when using other NRTs, inhaler, sub­lin­gual tablets, nasal spray, and lozenges (Jo­hans­son et al., 1991; Bergstrom et al., 1995; Lunell et al., 1996; Molan­der and Lunell, 2001; Choi et al., 2003). Bioavail­abil­ity for these prod­ucts with absorp­tion mainly through the mucosa of the oral cav­ity and a con­sid­er­able swal­lowed por­tion is about 50 to 80% (Table 1)…Ni­co­tine is poorly absorbed from the stom­ach because it is pro­to­nated (ion­ized) in the acidic gas­tric flu­id, but is well absorbed in the small intestine, which has a more alka­line pH and a large sur­face area. Fol­low­ing the admin­is­tra­tion of nico­tine cap­sules or nico­tine in solu­tion, peak con­cen­tra­tions are reached in about 1 h (Benowitz et al., 1991; Zins et al., 1997; Dempsey et al., 2004). The oral bioavail­abil­ity of nico­tine is about 20 to 45% (Benowitz et al., 1991; Comp­ton et al., 1997; Zins et al., 1997). Oral bioavail­abil­ity is incom­plete because of the hepatic first-pass metab­o­lism. Also the bioavail­abil­ity after colonic (en­e­ma) admin­is­tra­tion of nico­tine (ex­am­ined as a poten­tial ther­apy for ulcer­a­tive col­i­tis) is low, around 15 to 25%, pre­sum­ably due to hepatic first-pass metab­o­lism (Zins et al., 1997). Coti­nine is much more polar than nicotine, is metab­o­lized more slow­ly, and under­goes lit­tle, if any, first-pass metab­o­lism after oral dos­ing (Benowitz et al., 1983b; De Schep­per et al., 1987; Zevin et al., 1997).

    Par­tic­u­larly ger­mane is the table of absorp­tion by admin­is­tra­tion meth­ods, which gives bioavail­abil­ity for oral cap­sule (44%) and oral solu­tion (20%)

  • does not break out bioavail­abil­ity for their ene­ma, but they seem to have mea­sured lev­els con­sis­tent with 10-20%.

  • “Absorp­tion of nico­tine by the human stom­ach and its effect on gas­tric ion fluxes and poten­tial differ­ence”’s abstract con­firms the vari­a­tion from acid­i­ty:

    Nico­tine was well absorbed, mean 18.6±3.4% in 15 min, on intra­gas­tric instil­la­tion at pH 9.8. Absorp­tion was accom­pa­nied by side effects of nau­sea and vom­it­ing, and delay in gas­tric emp­ty­ing. Gas­tric absorp­tion of nico­tine at pH 7.4 was less marked (mean 8.2±2.9%), but was neg­li­gi­ble at pH 1 (mean 3.3±1.4%).

  • “Facts About Nico­tine Tox­i­c­ity”:

    Nico­tine is poorly absorbed from the stom­ach due to the acid­ity of the gas­tric flu­id, but is well absorbed in the small intestine, which has a more alka­line pH and a large sur­face area [“Nicotine, its metab­o­lism and an overview of its bio­log­i­cal effects”].

  • Tobacco and Shaman­ism in South Amer­ica (Wilbert 1993), pg 139:

    Nico­tine absorp­tion through the stom­ach is vari­able and rel­a­tively reduced in com­par­i­son with absorp­tion via the buc­cal cav­ity and the small intes­tine. ‘Drink­ing’, ‘eat­ing’, and swal­low­ing of tobacco smoke by South Amer­i­can Indi­ans have fre­quently been report­ed. Tenete­hara shamans reach a state of tobacco nar­co­sis through large swal­lows of smoke, and Tapi­rape shams are said to “eat smoke” by forc­ing down large gulps of smoke only to expel it again in a rapid sequence of belch­es. In gen­er­al, swal­low­ing of tobacco smoke is quite fre­quently likened to ‘drink­ing’. How­ev­er, although the amounts of nico­tine swal­lowed in this way - or in the form of sat­u­rated saliva or pipe juice - may be large enough to be behav­iorally sig­nifi­cant at nor­mal lev­els of gas­tric pH, nicotine, like other weak bases, is not sig­nifi­cantly absorbed.

    From the stand­point of absorp­tion, the drink­ing of tobacco juice and the inter­ac­tion of the infu­sion or con­coc­tion with the small intes­tine is a highly effec­tive method of gas­troin­testi­nal nico­tine admin­is­tra­tion. The epithe­lial area of the intestines is incom­pa­ra­bly larger than the mucosa of the upper tract includ­ing the stom­ach, and “the small intes­tine rep­re­sents the area with the great­est capac­ity for absorp­tion” (Levine 1983:81-83). As prac­ticed by most of the six­ty-four tribes doc­u­mented here, intox­i­cated states are achieved by drink­ing tobacco juice through the mouth and/or nose…The large intestine, although func­tion­ally lit­tle equipped for absorp­tion, nev­er­the­less absorbs nico­tine that may have passed through the small intes­tine.

  • “Stom­ach absorp­tion of intu­bated insec­ti­cides in fasted mice”’s abstract reports 10% stom­ach bioavail­abil­ity in rats.

It looks like the over­all pic­ture is that nico­tine is absorbed well in the intestines and the colon, but not so well in the stom­ach; this might be the expla­na­tion for the lack of effect, except on the other hand, the spe­cific esti­mates I see are that 10-20% of the nico­tine will be bioavail­able in the stom­ach (as com­pared to 50%+ for mouth or lungs)… so any of my doses of >5ml should have over­come the poorer bioavail­abil­i­ty! But on the grip­ping hand, these papers are men­tion­ing some­thing about the liver metab­o­liz­ing nico­tine when absorbed through the stom­ach, so…

Nicotine gum

So I even­tu­ally got around to order­ing another thing of nico­tine gum, “Habi­trol Nico­tine Gum, 4mg MINT fla­vor COATED gum. 96 pieces per box”. Gum should be eas­ier to dou­ble-blind myself with than nico­tine patches - just buy some mint gum. If 4mg is too much, cut the gum in half or what­ev­er. When it arrived, my hopes were borne out: the gum was rec­tan­gu­lar and soft, which made it easy to cut into fourths.

Remem­ber­ing what Wedri­fid told me, I decided to start with a quar­ter of a piece (~1mg). The gum was pretty taste­less, which ought to make blind­ing eas­i­er. The effects were notice­able around 10 min­utes - greater energy verg­ing on jit­ter­i­ness, much faster typ­ing, and appar­ent gen­eral quick­en­ing of thought. Like a more pleas­ant caffeine. While test­ing my typ­ing speed in Amphetype, my speed seemed to go up >=5 WPM, even after the time penal­ties for cor­rect­ing the increased mis­takes; I also did twice the usual num­ber with­out feel­ing espe­cially tired. A sec­ond dose was sim­i­lar, and the third dose was at 10 PM before play­ing seemed to stop the usual exhaus­tion I feel after play­ing through a level or so. (It’s a tough game, which I have yet to mas­ter like .) Return­ing to the pre­vi­ous con­cern about sleep prob­lems, though I went to bed at 11:45 PM, it still took 28 min­utes to fall sleep (com­pared to my more usual 10-20 minute range); the next day I use 2mg from 7-8PM while dri­ving, going to bed at mid­night, where my sleep latency is a more rea­son­able 14 min­utes. I then skipped for 3 days to see whether any crav­ings would pop up (they did­n’t). I sub­se­quently used 1mg every few days for dri­ving or Ninja Gaiden II, and while there were no crav­ings or other side-effects, the stim­u­la­tion defi­nitely seemed to get weaker - ben­e­fits seemed to still exist, but I could no longer describe any con­sid­er­able energy or jit­ter­i­ness.

The eas­i­est way to use 2mg was to use half a gum; I tried not chew­ing it but just hold­ing it in my cheek. The first night I tried, this seemed to work well for moti­va­tion; I knocked off a few long-s­tand­ing to-do items. Sub­se­quent­ly, I began using it for writ­ing, where it has been sim­i­larly use­ful. One diffi­cult night, I wound up using the other half (for a total of 4mg over ~5 hours), and it worked but gave me a fairly mild headache and a faint sen­sa­tion of nau­sea; these may have been due to for­get­ting to eat din­ner, but this still indi­cates 3mg should prob­a­bly be my per­sonal ceil­ing until and unless tol­er­ance to lower doses sets in.

Experiment

Design

Blind­ing stymied me for a few months since the nasty taste was unmis­tak­able and I could­n’t think of any gums with a sim­i­lar fla­vor to serve as place­bo. (The nasty taste does not seem to be due to the nico­tine despite what one might expect; Vaniver plau­si­bly sug­gested the bad taste might be intended to pre­vent over-con­sump­tion, but noth­ing in the Habi­trol ingre­di­ent list seemed to be noted for its bad taste, and a num­ber of ingre­di­ents were sweet­en­ing sug­ars of var­i­ous sorts. So I could­n’t sim­ply fla­vor some gum.)

I almost resigned myself to buy­ing patches to cut (and let the nico­tine evap­o­rate) and hope they would still stick on well enough after­wards to be indis­tin­guish­able from a fresh patch, when late one sleep­less night I real­ized that a piece of nico­tine gum hang­ing around on my desk­top for a week proved use­less when I tried it, and that was the answer: if nico­tine evap­o­rates from patch­es, then it must evap­o­rate from gum as well, and if gum does evap­o­rate, then to make a per­fect placebo all I had to do was cut some gum into proper sizes and let the pieces sit out for a while. (A while lat­er, I lost a piece of gum overnight and con­sumed the full 4mg to no sub­jec­tive effec­t.) Google searches led to noth­ing indi­cat­ing I might be fool­ing myself, and sug­gested that evap­o­ra­tion started within min­utes in patches and a patch was use­less within a day. Just a day is push­ing it (who knows how much is left in a use­less patch?), so I decided to build in a very large safety fac­tor and let the gum sit for around a month rather than a sin­gle day.

The exper­i­ment then is straight­for­ward: cut up a fresh piece of gum, ran­domly select from it and an equiv­a­lent ‘dry’ piece of gum, and do 5 rounds of dual n-back to test attention/energy & WM. (If it turns out to be place­bo, I’ll imme­di­ately use the remain­ing active dose: no sense in wast­ing gum, and this will test whether nigh-daily use ren­ders nico­tine gum use­less, sim­i­lar to how caffeine may be use­less if taken dai­ly. If there’s 3 pieces of active gum left, then I wrap it very tightly in Saran wrap which is sticky and air-tight.) The dose will be 1mg or 1/4 a gum. I cut up a dozen pieces into 4 pieces for 48 doses and set them out to dry. Per the pre­vi­ous power analy­ses, 48 groups of DNB rounds likely will be enough for detect­ing smal­l­-medium effects (partly since we will be only look­ing at one met­ric - aver­age % right per 5 rounds - with no need for mul­ti­ple cor­rec­tion). Analy­sis will be one-tailed, since we’re look­ing for whether there is a clear per­for­mance improve­ment and hence a rea­son to keep using nico­tine gum (rather than whether nico­tine gum might be harm­ful).

Cost-wise, the gum itself (~$5) is an irrel­e­vant sunk cost and the DNB some­thing I ought to be doing any­way. If the results are neg­a­tive (which I’ll define as d < 0.2), I may well drop nico­tine entirely since I have no rea­son to expect other forms (patch­es) or higher doses (2mg+) to cre­ate new ben­e­fits. This would save me an annual expense of ~$40 with a net present value of <$); even if we count the time-value of the 20 min­utes for the 5 DNB rounds over 48 days (), it’s still a clear profit to run a con­vinc­ing exper­i­ment.

Data

Analysis

First, we’ll check the pre­dic­tion score (ver­sus a ran­dom guesser scor­ing 0; higher is bet­ter):

logBinaryScore = sum . map (\(result,p) -> if result then 1 + logBase 2 p else 1 + logBase 2 (1-p))
logBinaryScore [(True,0.35),(False,0.40),(False,0.40),(True,0.60),(True,0.35),(False,0.45),(False,0.50),
                (True,0.60),(False,0.30),(True,0.50),(False,0.40),(False,0.30),(False,0.25),(False,0.75),
                (False,0.40),(False,0.40),(False,0.65),(False,0.45),(True,0.50),(False,0.65),(True,0.40),
                (True,0.55),(True,0.40),(False,0.50),(False,0.60),(True,0.40),(False,0.50),(False,0.50),
                (False,0.55),(True,0.55),(False,0.50),(False,0.55),(False,0.45),(True,0.55),(True,0.50),
                (True,0.50),(False,0.55),(True,0.50)]
-- -0.58

Ouch, so my guesses were actu­ally worse than ran­dom; this isn’t encour­ag­ing (if nico­tine was help­ful, why did­n’t I notice? Has 1mg tol­er­at­ed?) but it does indi­cate the blind­ing was suc­cess­ful.

Now we will exam­ine the actual per­for­mance. Extract­ing the indi­vid­ual rounds scores from my Brain Work­shop log file, we can aver­age them in groups of 5 to get a daily aver­age; then feed them into BEST (Bayesian equiv­a­lent of t-test; see Kruschke 2012):

## individual rounds; the imbalance is unfortunate but the experiment design means nothing can be done
on <- c(36,36,25,27,38,50,34,62,33,22,40,28,37,50,25,42,44,58,47,55,38,35,43,60,47,44,40,33,44,
        19,58,38,41,52,41,33,47,45,45,55,45,27,35,45,30,30,52,36,28,43,50,27,29,55,45,31,15,47,
        64,35,33,60,38,28,60,45,64,50,44,38,35,61,56,30,44,41,37,41,43,38)
off <- c(25,34,30,40,57,34,41,51,36,26,37,42,40,45,31,24,38,40,47,35,31,27,66,25,17,43,46,50,36,
         38,58,50,23,50,31,38,33,66,30,68,42,40,29,69,45,60,37,22,28,40,41,45,37,18,50,20,41,42,
         47,44,60,31,46,46,55,47,42,35,40,29,47,56,37,50,20,31,42,53,27,45,50,65,33,33,33,40,47,
         41,25,55,40,31,30,45,50,20,25,30,70,47,47,42,40,35,45,60,37,22,38,36,54,64,25,28,50,42,
         31,50,30,30)
on2 <- rowMeans(as.data.frame(matrix(on,ncol=5,byrow=TRUE)))
off2 <- rowMeans(as.data.frame(matrix(off,ncol=5,byrow=TRUE)))
on2
#  [1] 32.4 40.2 36.0 49.2 44.6 36.0 46.0 45.0 36.4 37.8 41.2 38.4 43.8 48.2 45.2
# [16] 40.0
off2
#  [1] 37.2 37.6 39.0 36.8 33.2 42.6 42.4 47.0 45.0 37.4 38.2 38.8 47.6 38.6 42.0
# [16] 39.6 42.8 41.6 39.2 38.4 41.8 38.6 44.2 36.6

source("BEST.R")
mcmc = BESTmcmc(on2, off2); postInfo
#            SUMMARY.INFO
# PARAMETER         mean     median       mode     HDIlow   HDIhigh pcgtZero
#   mu1       41.2808129 41.2819208 41.2272636 38.5078129 44.032699       NA
#   mu2       40.1981087 40.1955543 40.1777039 38.6810806 41.706469       NA
#   muDiff     1.0827042  1.0837831  1.1279921 -2.0292432  4.244909 75.87121
#   sigma1     5.2563674  5.0898354  4.7768681  3.3307493  7.511054       NA
#   sigma2     3.5513796  3.4850902  3.3453379  2.4655024  4.782887       NA
#   sigmaDiff  1.7049879  1.5917839  1.3816030 -0.6523817  4.300692 93.36015
#   nu        37.7948193 29.3217989 13.0664336  2.2755711 98.116623       NA
#   nuLog10    1.4472479  1.4671906  1.5204474  0.7604963  2.101837       NA
#   effSz      0.2460061  0.2450074  0.2361248 -0.4399959  0.936570 75.87121

The results graphed:

Daily data means, differ­ences of inferred stan­dard devi­a­tions & effect sizes: BESTplot(on2, off2, mcmcChain=mcmc, ROPEeff=c(0.1,1.5))

We can read off the results from the table or graph: the nico­tine days aver­age 1.1% high­er, for an effect size of 0.24; how­ev­er, the 95% (equiv­a­lent of con­fi­dence inter­val) goes all the way from 0.93 to -0.44, so we can­not exclude 0 effect and cer­tainly not claim con­fi­dence the effect size must be >0.1. Specifi­cal­ly, the analy­sis gives a 66% chance that the effect size is >0.1. (One might won­der if any increase is due purely to a “train­ing effect” - get­ting bet­ter at DNB. Prob­a­bly not25.)

This is dis­ap­point­ing.

One curi­ous thing that leaps out look­ing at the graphs is that the esti­mated under­ly­ing stan­dard devi­a­tions differ: the nico­tine days have a strik­ingly large stan­dard devi­a­tion, indi­cat­ing greater vari­abil­ity in scores - both higher and low­er, since the means weren’t very differ­ent. The differ­ence in stan­dard devi­a­tions is just 6.6% below 0, so the differ­ence almost reaches our usual fre­quen­tist lev­els of con­fi­dence too, which we can ver­ify by test­ing:

var.test(on2, off2, alternative="greater")
#     F test to compare two variances
#
# data:  on2 and off2
# F = 1.9823, num df = 15, denom df = 23, p-value = 0.06775
# alternative hypothesis: true ratio of variances is greater than 1
# 95% confidence interval:
#  0.9314525       Inf
# sample estimates:
# ratio of variances
#           1.982333

We can dou­ble-check this by see­ing what the vari­ance is for the unaver­aged scores: we know the means are only 1.1% differ­ent, so the addi­tional stan­dard devi­a­tion must be com­ing from how indi­vid­ual days are good or bad, and if that is so, then unaver­ag­ing them out to elim­i­nate most of the observed differ­ence. We re-run BEST:

mcmc = BESTmcmc(on,off); postInfo
#            SUMMARY.INFO
# PARAMETER          mean      median        mode     HDIlow     HDIhigh pcgtZero
#   mu1       41.22703657 41.22582276 41.11576792 38.7591670  43.7209215       NA
#   mu2       40.12386083 40.12235449 40.04585340 37.9655703  42.3037602       NA
#   muDiff     1.10317574  1.10302023  1.13446641 -2.1520680   4.4246013 74.52276
#   sigma1    10.91966242 10.86603052 10.74158135  9.1335897  12.7962565       NA
#   sigma2    11.69484205 11.66111990 11.57560017 10.1050885  13.3605913       NA
#   sigmaDiff -0.77517964 -0.79214849 -0.85774274 -3.1789680   1.6252535 25.70744
#   nu        46.86258782 38.65278685 22.91066668  5.8159908 109.9850644       NA
#   nuLog10    1.57972151  1.58718081  1.60810992  1.0214182   2.1234248       NA
#   effSz      0.09778545  0.09763823  0.09931263 -0.1895882   0.3907156 74.52276
Means, differ­ences of inferred stan­dard devi­a­tions & effect sizes: BESTplot(on, off, mcmcChain=mcmc, ROPEeff=c(0.1,1.5))

We see the stan­dard devi­a­tion differ­ence go away - now the differ­ence esti­mate is almost cen­tered on zero with a just 75% esti­mate the stan­dard devi­a­tion differs in the observed direc­tion. And to repeat the fre­quen­tist test:

var.test(on, off, alternative="greater")
#     F test to compare two variances
#
# data:  on and off
# F = 0.8564, num df = 79, denom df = 119, p-value = 0.7689
# alternative hypothesis: true ratio of variances is greater than 1
# 95% confidence interval:
#  0.6140736       Inf
# sample estimates:
# ratio of variances
#           0.856387

(So our p-value there went from 0.06 to 0.769 when we dis­ag­gre­gated the days, con­sis­tent with the Bayesian result­s.)

Good days and bad days?

The greatly increased vari­ance, but only some­what increased mean, is con­sis­tent with nico­tine oper­at­ing on me with an inverted U-curve for dosage/performance (or the Yerkes-Dod­son law): on good days, 1mg nico­tine is too much and degrades per­for­mance (per­haps I am over­stim­u­lated and find it hard to focus on some­thing as bor­ing as n-back) while on bad days, nico­tine is just right and improves n-back per­for­mance.

This would be easy to test if I had done some­thing before tak­ing the nico­tine gum; then I would sim­ply see if pre-gum scores were higher than post-gum scores on nico­tine days, but equal on placebo days. Unfor­tu­nate­ly, I did­n’t.

The clos­est data I have is my daily log of productivity/mood (1-5). If nico­tine scores are higher than placebo scores on bad days (1-2) and lower on good days (3-4), then I think that would be con­sis­tent with an inverted U-curve.

nicotine <- read.table(stdin(),header=TRUE)
day      active mp score
20120824 1      3  35.2
20120827 0      5  37.2
20120828 0      3  37.6
20120830 1      3  37.75
20120831 1      2  37.75
20120902 0      2  36.0
20120905 0      5  36.0
20120906 1      5  37.25
20120910 0      5  49.2
20120911 1      3  36.8
20120912 0      3  44.6
20120913 0      5  38.4
20120915 0      5  43.8
20120916 0      2  39.6
20120918 0      3  49.6
20120919 0      4  38.4
20120923 0      5  36.2
20120924 0      5  45.4
20120925 1      3  43.8
20120926 0      4  36.4
20120929 1      3  43.8
20120930 1      3  36.0
20121001 1      3  46.0
20121002 0      4  45.0
20121008 0      2  34.6
20121009 1      3  45.2
20121012 0      5  37.8
20121013 0      4  37.2
20121016 0      4  40.2
20121020 1      3  39.0
20121021 0      3  41.2
20121022 0      3  42.2
20121024 0      5  40.4
20121029 1      2  41.4
20121031 1      3  38.4
20121101 1      5  43.8
20121102 0      3  48.2
20121103 1      5  40.6
summary(nicotine)
#       day               active             mp            score
#  Min.   :20120824   Min.   :0.0000   Min.   :2.000   Min.   :34.60
#  1st Qu.:20120911   1st Qu.:0.0000   1st Qu.:3.000   1st Qu.:37.21
#  Median :20120926   Median :0.0000   Median :3.000   Median :39.30
#  Mean   :20120954   Mean   :0.3947   Mean   :3.632   Mean   :40.47
#  3rd Qu.:20121015   3rd Qu.:1.0000   3rd Qu.:5.000   3rd Qu.:43.80
#  Max.   :20121103   Max.   :1.0000   Max.   :5.000   Max.   :49.60
cor(nicotine)
#               day      active          mp       score
# day                0.05331968  0.07437166  0.32021554
# active                        -0.27754064 -0.05727501
# mp                                         0.05238032
Plot scores for each mood/productivity lev­el, split between placebo & nicotine: boxplot(nicotine$score ~ (nicotine$active + nicotine$mp)^2)

Inter­est­ing. On days ranked ‘2’ (be­low-av­er­age mood/productivity), nico­tine seems to have boosted scores; on days ranked ‘3’, nico­tine hurts scores; there aren’t enough ‘4’s to tell, but even ’5’ days seem to see a boost from nicotine, which is not pre­dicted by the the­o­ry. But I don’t think much of a con­clu­sion can be drawn: not enough data to make out any sim­ple rela­tion­ship. Some mod­el­ing sug­gests no rela­tion­ship in this data either (although also no differ­ence in stan­dard devi­a­tions, lead­ing me to won­der if I screwed up the data record­ing - not all of the DNB scores seem to match the input data in the pre­vi­ous analy­sis). So although the ‘2’ days in the graph are strik­ing, the the­ory may not be right.

Conclusion

What should I make of all these results?

  • The poor pre­dic­tion per­for­mance, while con­firm­ing my belief that my novel strat­egy for blind­ing nico­tine gum worked well, under­mines con­fi­dence in the value of nico­tine.

  • I spec­i­fied at the begin­ning that I wanted an effect size of >0.2; I got it, but with it came a very wide cred­i­ble inter­val, under­min­ing con­fi­dence in the effect size.

  • The differ­ence in stan­dard devi­a­tions is not, from a the­o­ret­i­cal per­spec­tive, all that strange a phe­nom­e­non: at the very begin­ning of this page, I cov­ered some basic prin­ci­ples of nootrop­ics and men­tioned how many stim­u­lants or sup­ple­ments fol­low a inverted U-curve where too much or too lit­tle lead to poorer per­for­mance (iron­i­cal­ly, one of the exam­ples in Kruschke 2012 was a smart drug which did not affect means but increased stan­dard devi­a­tion­s).

    If this is the case, this sug­gests some thought­ful­ness about my use of nicotine: there are times when use of nico­tine will not be help­ful, but times where it will be help­ful. I don’t know what makes the differ­ence, but I can guess it relates to over-s­tim­u­la­tion: on some nights dur­ing the exper­i­ment, I had diffi­cult con­cen­trat­ing on n-back­ing because it was bor­ing and I was think­ing about the other things I was inter­ested in or work­ing on - in ret­ro­spect, I won­der if those instances were nico­tine nights.

In ret­ro­spect, there were 2 parts of the exper­i­ment design I prob­a­bly should have changed:

  1. I used 1mg gum, rather than 2mg

    1mg may have too small effects to eas­ily detect, and I may have devel­oped tol­er­ance to 1mg even though I’ve been care­ful to space out all my gum use. 2mg would have reduced this con­cern.

  2. I used 1mg each day regard­less of the ran­dom­iza­tion

    This was to make each day more con­sis­tent and avoid wast­ing a sliced piece of gum (due to evap­o­ra­tion, it’s use-it-or-lose-it). But this plau­si­bly is a source of tol­er­ance, and even #1 was not an issue when the self­-ex­per­i­ment began, this could have become an issue.

All things con­sid­ered, I will prob­a­bly con­tinue using nico­tine gum spar­ing­ly.

Nicotine patches

Run­ning low on gum (even using it weekly or less, it still runs out), I decided to try patch­es. Read­ing through var­i­ous dis­cus­sions, I could­n’t find any clear ver­dict on what patch brands might be safer (in terms of nico­tine evap­o­ra­tion through a cut or edge) than oth­ers, so I went with the cheap­est Habi­trol I could find as a first try of patches (“Nico­tine Trans­der­mal Sys­tem Patch, Stop Smok­ing Aid, 21 mg, Step 1, 14 patches”) in May 2013. I am curi­ous to what extent nico­tine might improve a long time period like sev­eral hours or a whole day, com­pared to the short­er-act­ing nico­tine gum which feels like it helps for an hour at most and then tapers off (which is very use­ful in its own right for kick­ing me into start­ing some­thing I have been pro­cras­ti­nat­ing on). I have not decided whether to try another self­-ex­per­i­ment.

Using the 21mg patch­es, I cut them into quar­ters. What I would do is I would cut out 1 quar­ter, and then seal the two edges with scotch tape, and put the Pac-Man back into its sleeve. Then the next time I would cut another quar­ter, seal the new edge, and so on. I thought that 5.25mg might be too much since I ini­tially found 4mg gum to be too much, but it’s deliv­ered over a long time and it wound up feel­ing much more like 1mg gum used reg­u­lar­ly. I don’t know if the tape worked, but I did not notice any loss of poten­cy. I did­n’t like them as much as the gum because I would some­times for­get to take off a patch at the end of the day and it would inter­fere with sleep, and because the onset is much slower and I find I need stim­u­lants more for get­ting started than for ongo­ing stim­u­la­tion so it is bet­ter to have gum which can be taken pre­cisely when needed and start act­ing quick­ly. (One case where the patches were defi­nitely bet­ter than the gum was long car trips where slow onset is fine, since you’re most alert at the start.) When I finally ran out of patches in June 2016 (us­ing them spar­ing­ly), I ordered gum instead.

Noopept

Related to the famous -rac­etams but report­edly bet­ter (and much less bulky), is one of the many obscure Russ­ian nootrop­ics. (Fur­ther read­ing: Google Scholar, Exam­ine.­com, Red­dit, Longecity, Blue­light.ru.) Its advan­tages seem to be that it’s far more com­pact than pirac­etam and does­n’t taste awful so it’s eas­ier to store and con­sume; does­n’t have the cloud hang­ing over it that pirac­etam does due to the FDA let­ters, so it’s easy to pur­chase through nor­mal chan­nels; is cheap on a per-dose basis; and it has fans claim­ing it is bet­ter than pirac­etam.

A Red­di­tor ordered some Russ­ian brand Noopept, but find­ing it was unpleas­ant & not work­ing for him, gave the left­-over half to me:

Russ­ian Noopept box, front & back
Russ­ian Noopept blis­ter-pack, front & back

It appeared in rea­son­ably good shape, and closely matched the pho­tographs in the Wikipedia arti­cle. I took 2 of the 25 10mg pills on suc­ces­sive days on top of my usual caffeine+pirac­etam stack, and did­n’t notice any­thing; in par­tic­u­lar, I did­n’t find it unpleas­ant like he did.

Pilot experiment

So, I thought I might as well exper­i­ment since I have it. I put the 23 remain­ing pills into gel cap­sules with brown rice as fill­ing, made ~30 placebo cap­sules, and will use the one-bag blinding/randomization method. I don’t want to spend the time it would take to n-back every day, so I will sim­ply look for an effect on my daily mood/productivity self­-rat­ing; hope­fully Noopept will add a lit­tle on aver­age above and beyond my exist­ing prac­tices like caffeine+pirac­etam (yes, Noopept may be as good as pirac­etam, but since I still have a ton of pirac­etam from my 3kg order, I am pri­mar­ily inter­ested in whether Noopept adds onto pirac­etam rather than replaces). 10mg doses seem to be on the low side for Noopept users, weak­en­ing the effect, but on the other hand, if I were to take 2 cap­sules at a time, then I’d halve the sam­ple size; it’s not clear what is the opti­mal trade­off between dose and n for sta­tis­ti­cal pow­er.

Nor am I sure how impor­tant the results are - part­way through, I haven’t noticed any­thing bad, at least, from tak­ing Noopept. And any effect is going to be sub­tle: peo­ple seem to think that 10mg is too small for an ingested rather than sub­lin­gual dose and I should be tak­ing twice as much, and Noopep­t’s claimed to be a chronic grad­ual sort of thing, with less of an acute effect. If the effect size is pos­i­tive, regard­less of sta­tis­ti­cal-sig­nifi­cance, I’ll prob­a­bly think about doing a big­ger real self­-ex­per­i­ment (more days blocked into weeks or months & 20mg dose)

Power

I don’t expect to find an effect, though; a quick t-test power analy­sis of a one-sided paired design with 23 pairs sug­gests that a rea­son­able power of 80% would still only be able to detect an increase of d>=0.5:

pwr.t.test(n=23, type="paired", alternative="greater", sig.level=0.05, power=0.8)
#      Paired t test power calculation
#
#               n = 23
#               d = 0.5352

Or in other words, since the stan­dard devi­a­tion of my pre­vi­ous self­-rat­ings is 0.75 (see the data), a mean rat­ing increase of >0.39 on the self­-rat­ing. This is, unfor­tu­nate­ly, imply­ing an extreme shift in my self­-assess­ments (for exam­ple, 3s are ~50% of the self­-rat­ings and 4s ~25%; to cause an increase of 0.25 while leav­ing 2s alone in a sam­ple of 23 days, one would have to push 3s down to ~25% and 4s up to ~47%). So in advance, we can see that the weak plau­si­ble effects for Noopept are not going to be detected here at our usual sta­tis­ti­cal lev­els with just the sam­ple I have (a more plau­si­ble exper­i­ment might use 178 pairs over a year, detect­ing down to d>=0.18). But if the sign is right, it might make Noopept worth­while to inves­ti­gate fur­ther. And the hard­est part of this was just mak­ing the pills, so it’s not a waste of effort.

Data

Avail­able as a CSV span­ning 15 May - 2013-07-09, with mag­ne­sium l-thre­onate con­sump­tion as a covari­ate (see the mag­ne­sium page).

Analysis

Some quick tests turn in sim­i­lar con­clu­sions: both Noopept and the “Magtein” increased self­-rat­ing but not sta­tis­ti­cal­ly-sig­nifi­cantly (as expected from the begin­ning due to the lack of pow­er).

npt <- read.csv("https://www.gwern.net/docs/nootropics/2013-gwern-noopept.csv")
wilcox.test(MP ~ Noopept, alternative="less", data = npt)
#
#     Wilcoxon rank sum test with continuity correction
#
# data:  MP by Noopept
# W = 343, p-value = 0.2607
summary(lm(MP ~ Noopept + Magtein, data = npt))
# ...Coefficients:
#             Estimate Std. Error t value Pr(>|t|)
# (Intercept)   2.8038     0.1556   18.02   <2e-16
# Noopept       0.0886     0.2098    0.42     0.67
# Magtein       0.2673     0.2070    1.29     0.20
#
# Residual standard error: 0.761 on 53 degrees of freedom
# Multiple R-squared:  0.0379,    Adjusted R-squared:  0.00164
# F-statistic: 1.05 on 2 and 53 DF,  p-value: 0.359

More specifi­cal­ly, the ordi­nal logis­tic regres­sion esti­mates effect sizes of odd­s-ra­tio 1.3 for the Noopept and 1.9 for the mag­ne­sium:

library(rms)
npt$MP <- as.ordered(npt$MP)
lmodel <- lrm(MP ~ Noopept + Magtein, data = npt); lmodel
# ...
#         Coef    S.E.   Wald Z Pr(>|Z|)
# y>=3     0.4330 0.4049  1.07  0.2849
# y>=4    -1.4625 0.4524 -3.23  0.0012
# Noopept  0.2336 0.5114  0.46  0.6479
# Magtein  0.6748 0.5098  1.32  0.1856

The mag­ne­sium was nei­ther ran­dom­ized nor blinded and included mostly as a covari­ate to avoid con­found­ing (the Noopept coeffi­cient & t-value increase some­what with­out the Magtein vari­able), so an OR of 1.9 is likely too high; in any case, this exper­i­ment was too small to reli­ably detect any effect (~26% pow­er, see boot­strap power sim­u­la­tion in the mag­ne­sium sec­tion) so we can’t say too much.

set.seed(3333)
library(boot)
noopeptPower <- function(dt, indices) {
    d <- dt[indices,] # bootstrap's _n_ = original _n_
    lmodel <- lrm(MP ~ Noopept + Magtein, data = d)
    return(anova(lmodel)[7]) # _p_-value for the Noopept coefficient
}
bs <- boot(data=npt, statistic=noopeptPower, R=100000, parallel="multicore", ncpus=4)
alpha <- 0.05
print(sum(bs$t<=alpha) / length(bs$t))
# [1] 0.073

So for the observed effect size, the small Noopept sam­ple had only 7% power to turn in a sta­tis­ti­cal­ly-sig­nifi­cant result. Given the plau­si­ble effect size, and weak­ness of the exper­i­ment, I find these results encour­ag­ing.

Noopept followup experiment

Noopept is a Russ­ian stim­u­lant some­times sug­gested for nootrop­ics use as it may be more effec­tive than pirac­etam or other -rac­etams, and its smaller doses make it more con­ve­nient & pos­si­bly safer. Fol­low­ing up on a pilot study, I ran a well-pow­ered blind ran­dom­ized self­-ex­per­i­ment between Sep­tem­ber 2013 and August 2014 using doses of 12-60mg Noopept & pairs of 3-day blocks to inves­ti­gate the impact of Noopept on self­-rat­ings of daily func­tion­ing in addi­tion to my exist­ing sup­ple­men­ta­tion reg­i­men involv­ing smal­l­-to-mod­er­ate doses of pirac­etam. A lin­ear regres­sion, which included other con­cur­rent exper­i­ments as covari­ates & used mul­ti­ple impu­ta­tion for miss­ing data, indi­cates a small ben­e­fit to the lower dose lev­els and harm from the high­est 60mg dose lev­el, but no dose nor Noopept as a whole was sta­tis­ti­cal­ly-sig­nifi­cant. It seems Noopep­t’s effects are too sub­tle to eas­ily notice if they exist, but if one uses it, one should prob­a­bly avoid 60mg+.

Design

In avoid­ing exper­i­ment­ing with more Russ­ian Noopept pills and using instead the eas­i­ly-pur­chased pow­der form of Noopept, there are two oppos­ing con­sid­er­a­tions: Russ­ian Noopept is report­edly the best, so we might expect any­thing I buy online to be weaker or impure or infe­rior some­how and the effect size smaller than in the pilot exper­i­ment; but by buy­ing my own sup­ply & using pow­der I can dou­ble or triple the dose to 20mg or 30mg (to com­pen­sate for the orig­i­nal under­-dos­ing of 10mg) and so the effect size larger than in the pilot exper­i­ment.

As it hap­pened, Health Sup­ple­ment Whole­salers (since renamed Pow­der City) offered me a sam­ple of their prod­ucts, includ­ing their 5g Noopept pow­der ($13). I’d never used HSW before & they had some issues in the past; but I haven’t seen any recent com­plaints, so I was will­ing to try them. My 5g from batch #130830 arrived quickly (pho­tos: pack­ag­ing, pow­der con­tents). I tried some (tastes just slightly unpleas­ant, like an ultra­-weak pirac­etam), and I set about cap­ping the fluffy white flour-like pow­der with the hilar­i­ously tiny scoop they pro­vide.

It took 4 hours to cap 432 Noopept pills and another 432 flour pills. I tried to allo­cate the Noopept as evenly as pos­si­ble (3 lit­tle scoops per pill) which the HSW pack­ag­ing sug­gested would be 10-30mg; run­ning out after 432 implies I man­aged to get ~12mg into each (). At 2 pills a day, the exper­i­ment will run under a year.

I don’t want to syn­chro­nize with the mag­ne­sium or lithium exper­i­ments, so I’ll use paired blocks of 3 days ran­dom­ized 50:50, which will help with the reported tol­er­ance of Noopept set­ting in after a few days and one need­ing to ‘cycle’.

To make things more inter­est­ing, I think I would like to try ran­dom­iz­ing differ­ent dosages as well: 12mg, 24mg, and 36mg (1-3 pill­s); on 2014-05-05, because I wanted to fin­ish up the exper­i­ment ear­lier, I decided to add 2 larger doses of 48 & 60mg (4-5 pills) as options. Then I can include the pre­vi­ous pilot study as 10mg dos­es, and regress over dose amount.

Dur­ing this time peri­od, I gen­er­ally refrained from using any nico­tine (I wound up using it only 3x in the exper­i­men­tal peri­od) or modafinil (0x) to avoid adding vari­a­tion to results. I did use mag­ne­sium cit­rate & LLLT (dis­cussed lat­er). Final­ly, I was tak­ing a stack like this:

  1. 1mg mela­tonin at bed­time
  2. 5000IU vit­a­min D & mul­ti­vi­t­a­min at morn­ing; an iron sup­ple­ment every 3 days
  3. from 25 March to 2014-09-18, ~5g of cre­a­tine mono­hy­drate per day
  4. a few times a day, tak­ing a cus­tom gel pill which in total sup­plies ~1g pirac­etam & 200mg caffeine

Power

I’ll first assume the effect size is the same. Using the usual alpha, we can find the nec­es­sary sam­ple size by a slight vari­a­tion on the mag­ne­sium boot­strap power cal­cu­la­tion. Since the 56 days gave a power of 7% while we want closer to 80%, we prob­a­bly want to start our power esti­ma­tion much high­er, with n in the 300s:

library(boot)
library(rms)
npt <- read.csv("https://www.gwern.net/docs/nootropics/2013-gwern-noopept.csv")
newNoopeptPower <- function(dt, indices) {
    d <- dt[sample(nrow(dt), n, replace=TRUE), ] # new dataset, possibly larger than the original
    lmodel <- lrm(MP ~ Noopept + Magtein, data = d)
    return(anova(lmodel)[7])
}
alpha <- 0.05
for (n in seq(from = 300, to = 600, by = 30)) {
   bs <- boot(data=npt, statistic=newNoopeptPower, R=10000, parallel="multicore", ncpus=4)
   print(c(n, sum(bs$t<=alpha)/length(bs$t)))
}
# 0.18/0.19/0.21/0.21/0.23/0.25/0.26/0.28/0.29/0.32/0.32

Even at n = 600 (nearly 2 years), the esti­mated power is only 32%. This is absurdly small and such an exper­i­ment would be a waste of time.

Sup­pose we were opti­mistic and we dou­bled the effect from 0.23 to 0.47 (this can be done by edit­ing the first two Noopept rows and incre­ment­ing the MP vari­able by 1), and then looked again at pow­er? At n = 300, power has reached 60%, and by n = 530, we have hit the desired 80%.

npt[1,2] <- npt[1,2] + 1
npt[2,2] <- npt[2,2] + 1
n <- 530
bs <- boot(data=npt, statistic=newNoopeptPower, R=100000, parallel="multicore", ncpus=4)
print(c(n, sum(bs$t<=alpha)/length(bs$t)))
# [1] 530.0000   0.8241

530 is more accept­able, albeit I am wor­ried about dou­bling the effect.

Data

  1. 20mg: 15 Sep­tem­ber - 17 Sep­tem­ber: 0

    18 - 20 Sep­tem­ber: 1

  2. 30mg: 21 Sep­tem­ber - 23? Sep­tem­ber: 1

    24 - 26: 0

  3. 20mg: 27 - 29 Sep­tem­ber: 0

    30 - 2 Octo­ber: 1

  4. 10mg: 3 - 5 Octo­ber: 1

    6 - 8 Octo­ber: 0

  5. 30mg: 9 - 11 Octo­ber: 1

    12 - 14 Octo­ber: 0

  6. 10mg: 15 - 17 Octo­ber: 1

    18 - 20 Octo­ber: 0

  7. 30mg: 22 - 24 Octo­ber: 1

    25 - 27 Octo­ber: 0

  8. 10mg: 28 - 30 Octo­ber: 1

    31 - 2 Novem­ber: 0

  9. 30mg: 4 - 6 Novem­ber: 1

    7 - 9 Novem­ber: 0

  10. 20mg: 11 - 13 Nov: 0

    14 - 16 Nov: 1

  11. 30mg: 20 - 22 Novem­ber: 1

    23 - 25 Novem­ber: 0

  12. 20mg: 26 - 28 Novem­ber: 1

    29 - 1 Decem­ber: 0

  13. 30mg: 2 - 4 Decem­ber: 1

    5 - 7 Decem­ber: 0

  14. 10mg: 8 - 10 Decem­ber: 1

    11 - 13 Decem­ber: 0

  15. 30mg: 14 - 16 Decem­ber: 0

    17 - 19 Decem­ber: 1

  16. 20mg: 20 - 22 Decem­ber: 0

    27 - 29 Decem­ber: 1

  17. 10mg: 1 - 2014-01-03: 1

    4 - 2014-01-06: 0

  18. 30mg: 7 - 9 Jan­u­ary: 1

    10 - 12 Jan­u­ary: 0

  19. 10mg: 13 - 15 Jan­u­ary: 1

    16 - 17 Jan­u­ary: 0

  20. 20mg: 18 - 20 Jan­u­ary: 0

    21 - 23 Jan­u­ary: 1

  21. 30mg: 25 - 27 Jan­u­ary: 0

    28 - 30 Jan­u­ary: 1

  22. 10mg: 31 Jan­u­ary - 2 Feb­ru­ary: 1

    3 - 5 Feb­ru­ary: 0

  23. 30mg: 8 - 10 Feb­ru­ary: 1

    11 - 13 Feb­ru­ary: 1

  24. 10mg: 14 - 16 Feb­ru­ary: 0

    17 - 19 Feb­ru­ary: 1

  25. 30mg: 20 - 22 Feb­ru­ary: 1

    22 - 25 Feb­ru­ary: 0

  26. 20mg: 26 - 28 Feb­ru­ary: 0

    1 March - 3 March: 1

  27. 10mg: 4 March - 6 March: 1

    7 March - 9 March: 0

  28. 30mg: 10 - 11 March: 0; acci­den­tally unblinded & restarted on the 12th (a spare rice place­bo, which is vis­i­bly differ­ent from the flour/Noopept cap­sules, was mixed in)

  29. 30mg: 12 - 14 March : 1

    15 - 17 March: 0

  30. 20mg: 18 - 20 March: 0

    21 - 23 March: 1

  31. 10mg: 24 - 26 March: 1

    27 - 29 March: 0

  32. 20mg: 30 - 1 April: 0

    2 - 4 April: 1

  33. 10mg: 5 - 7 April: 1

    8 - 10 April: 0

  34. 30mg: 11 - 13 April: 1

    14 - 16 April: 0

  35. 20mg: 17 - 19 April: 0

    20 - 22 April: 1

  36. 10mg: 23 - 25 April: 1

    26 - 28 April: 0

  37. 30mg: 29 - 1 May: 1

    2 - 4 May: 0

  38. 48mg: 5 - 7 May: 0

    8 - 10 May: 1

  39. 60mg: 11 - 13 May: 0

    14 - 17 May: 1

  40. 20mg: 18 - 20 May: 0

    21 - 23 May: 1

  41. 48mg: 24 - 26 May: 1

    27 - 29 May: 0

  42. 60mg: 30 - 1 June: 0

    2 - 4 June: 1

  43. 30mg: 5 - 7 June: 1

    8 - 10 June: 0

  44. 5x: 11 - 13 June: 1

    14 - 16 June: 0

  45. 3x: 17 - 19 June: 0

    20 - 22 June: 1

  46. 5x: 23 - 25 June: 0

    26 - 28 June: 1

  47. 4x: 29 June - 1 July: 1

    2 - 4 July: 0

  48. 3x: 5 - 7 July: 1

    8 - 9 July: 0

  49. 5x: 10 - 12 July: 1

    13 - 15 July: 0

  50. 3x: 16 - 18 July: 0

    19 - 21 July: 1

  51. 4x: 23 - 25 July: 0

    26 - 28 July: 1

  52. 5x: 29 - 31 July: 0

    1 - 3 August: 1

  53. 3x: 4 - 6 August: 1

    7 - 9 August: 0

  54. 3x: 10 - 12 August: 0

    13 - 15 August: 1

  55. 3x: 16 - 18 August: 0

    19 - 21 August: 1

  56. 2x: 23 - 25 August: 0

    26 - 28 August: 1

Analysis

Ana­lyz­ing the results is a lit­tle tricky because I was simul­ta­ne­ously run­ning the first mag­ne­sium cit­rate self­-ex­per­i­ment, which turned out to cause a quite com­plex result which looks like a grad­u­al­ly-ac­cu­mu­lat­ing over­dose negat­ing an ini­tial ben­e­fit for net harm, and also toy­ing with LLLT, which turned out to have a strong cor­re­la­tion with ben­e­fits. So for the poten­tial small Noopept effect to not be swamped, I need to include those in the analy­sis. I designed the exper­i­ment to try to find the best dose lev­el, so I want to look at an aver­age Noopept effect but also the esti­mated effect at each dose size in case some are neg­a­tive (espe­cially in the case of 5-pills/60mg); I included the pilot exper­i­ment data as 10mg doses since they were also blind & ran­dom­ized. Final­ly, affects analy­sis: because not every vari­able is recorded for each date (what was the value of the vari­able for the blind ran­dom­ized mag­ne­sium cit­rate before and after I fin­ished that exper­i­ment? what value do you assign the Magtein vari­able before I bought it and after I used it all up?), just run­ning a lin­ear regres­sion may not work exactly as one expects as var­i­ous days get omit­ted because part of the data was miss­ing.

noopeptSecond <- read.csv("https://www.gwern.net/docs/nootropics/2013-2014-gwern-noopept.csv", colClasses=c("Date","integer","integer","integer","logical"))
l <- lm(MP ~ Noopept +
             LLLT +
             as.logical(Magnesium.citrate) + as.integer(Date) + as.logical(Magnesium.citrate):as.integer(Date),
        data=noopeptSecond)
summary(l)
# Coefficients:
#                                                        Estimate   Std. Error  t value   Pr(>|t|)
# (Intercept)                                        24.254373177 14.252905125  1.70171 0.09043607
# Noopept                                             0.002069507  0.003937337  0.52561 0.59976836
# LLLTTRUE                                            0.330112028  0.096133360  3.43390 0.00072963
# as.logical(Magnesium.citrate)TRUE                  27.058060337 19.655569654  1.37661 0.17024431
# as.integer(Date)                                   -0.001313316  0.000886616 -1.48127 0.14018300
# as.logical(Magnesium.citrate)TRUE:as.integer(Date) -0.001699162  0.001222719 -1.38966 0.16625033
#
# Residual standard error: 0.640741 on 191 degrees of freedom
#   (731 observations deleted due to missingness)
# Multiple R-squared:  0.154383,    Adjusted R-squared:  0.132246
# F-statistic: 6.97411 on 5 and 191 DF,  p-value: 5.23897e-06

As expected since most of the data over­laps with the pre­vi­ous LLLT analy­sis, the LLLT vari­able cor­re­lates strong­ly; the indi­vid­ual mag­ne­sium vari­ables may look a lit­tle more ques­tion­able but were jus­ti­fied in the mag­ne­sium cit­rate analy­sis. The Noopept result looks a lit­tle sur­pris­ing - almost zero effect? Let’s split by dose (which was the point of the whole rig­ma­role of chang­ing dose lev­el­s):

l2 <- lm(MP ~ as.factor(Noopept) +
              LLLT +
              as.logical(Magnesium.citrate) + as.integer(Date) + as.logical(Magnesium.citrate):as.integer(Date),
         data=noopeptSecond)
summary(l2)
# Coefficients:
#                                                        Estimate   Std. Error  t value   Pr(>|t|)
# (Intercept)                                        27.044709119 14.677995235  1.84253 0.06697191
# as.factor(Noopept)10                                0.099920147  0.139287051  0.71737 0.47403711
# as.factor(Noopept)15                                0.526389063  0.297940313  1.76676 0.07889108
# as.factor(Noopept)20                                0.114943375  0.147994400  0.77667 0.43832733
# as.factor(Noopept)30                                0.019029776  0.125504996  0.15163 0.87964479
# LLLTTRUE                                            0.329976497  0.096071943  3.43468 0.00072993
# as.logical(Magnesium.citrate)TRUE                  25.615810606 20.397271406  1.25584 0.21073068
# as.integer(Date)                                   -0.001488184  0.000913563 -1.62899 0.10499001
# as.logical(Magnesium.citrate)TRUE:as.integer(Date) -0.001610059  0.001269219 -1.26854 0.20617256
#
# Residual standard error: 0.639823 on 188 degrees of freedom
#   (731 observations deleted due to missingness)
# Multiple R-squared:  0.170047,    Adjusted R-squared:  0.13473
# F-statistic: 4.81487 on 8 and 188 DF,  p-value: 2.08804e-05

This looks inter­est­ing: the Noopept effect is pos­i­tive for all the dose lev­els, but it looks like a U-curve - low at 10mg, high at 15mg, lower at 20mg, and even lower at 30mg 48mg and 60mg aren’t esti­mated because they are hit by the miss­ing­ness prob­lem: the mag­ne­sium cit­rate vari­able is unavail­able for the days the higher doses were taken on, and so their days are omit­ted and those lev­els of the fac­tor are not esti­mat­ed. One way to fix this is to drop mag­ne­sium from the model entire­ly, at the cost of fit­ting the data much more poorly and los­ing a lot of R2:

l3 <- lm(MP ~ as.factor(Noopept) + LLLT, data=noopeptSecond)
summary(l3)
# Coefficients:
#                        Estimate Std. Error  t value   Pr(>|t|)
# (Intercept)           3.0564075  0.0578283 52.85318 < 2.22e-16
# as.factor(Noopept)10  0.1079878  0.1255354  0.86022 0.39031118
# as.factor(Noopept)15  0.1835389  0.2848069  0.64443 0.51975512
# as.factor(Noopept)20  0.1314225  0.1301826  1.00952 0.31348347
# as.factor(Noopept)30  0.0125616  0.1091561  0.11508 0.90845401
# as.factor(Noopept)48  0.2302323  0.2050326  1.12291 0.26231647
# as.factor(Noopept)60 -0.1714377  0.1794377 -0.95542 0.34008626
# LLLTTRUE              0.2801608  0.0829625  3.37696 0.00082304
#
# Residual standard error: 0.685953 on 321 degrees of freedom
#   (599 observations deleted due to missingness)
# Multiple R-squared:  0.0468695,   Adjusted R-squared:  0.0260848
# F-statistic: 2.25499 on 7 and 321 DF,  p-value: 0.0297924

This does­n’t fit the U-curve so well: while 60mg is sub­stan­tially neg­a­tive as one would extrap­o­late from 30mg being ~0, 48mg is actu­ally bet­ter than 15mg. But we bought the esti­mates of 48mg/60mg at a steep price - we ignore the influ­ence of mag­ne­sium which we know influ­ences the data a great deal. And the higher doses were added towards the end, so may be influ­enced by the mag­ne­sium starting/stopping. Another fix for the miss­ing­ness is to . In this case, we might argue that the placebo days of the mag­ne­sium exper­i­ment were iden­ti­cal to tak­ing no mag­ne­sium at all and so we can clas­sify each NA as a placebo day, and rerun the desired analy­sis:

noopeptImputed <- noopeptSecond
noopeptImputed[is.na(noopeptImputed$Magnesium.citrate),]$Magnesium.citrate <- 0
li <- lm(MP ~ as.factor(Noopept) +
              LLLT +
              as.logical(Magnesium.citrate) + as.integer(Date) + as.logical(Magnesium.citrate):as.integer(Date),
          data=noopeptImputed)
summary(li)
# Coefficients:
#                                                        Estimate   Std. Error  t value  Pr(>|t|)
# (Intercept)                                        10.430818153  8.189365582  1.27370 0.2036989
# as.factor(Noopept)10                                0.049595514  0.122841008  0.40374 0.6866772
# as.factor(Noopept)15                                0.405925320  0.281291053  1.44308 0.1499824
# as.factor(Noopept)20                                0.088343999  0.127014107  0.69554 0.4872219
# as.factor(Noopept)30                                0.029464990  0.106375169  0.27699 0.7819668
# as.factor(Noopept)48                                0.190340419  0.207736878  0.91626 0.3602263
# as.factor(Noopept)60                               -0.210638501  0.184357630 -1.14255 0.2540834
# LLLTTRUE                                            0.286295998  0.081098102  3.53024 0.0004765
# as.logical(Magnesium.citrate)TRUE                  42.273941799 16.288481089  2.59533 0.0098882
# as.integer(Date)                                   -0.000451814  0.000507568 -0.89015 0.3740561
# as.logical(Magnesium.citrate)TRUE:as.integer(Date) -0.002647546  0.001012691 -2.61437 0.0093648
#
# Residual standard error: 0.666405 on 318 degrees of freedom
#   (599 observations deleted due to missingness)
# Multiple R-squared:  0.108827,    Adjusted R-squared:  0.0808031
# F-statistic: 3.88332 on 10 and 318 DF,  p-value: 5.4512e-05

The 48mg/60mg coeffi­cients shift down­wards as expect­ed. If we plot the coeffi­cients with arm’s coefplot(), and one squints, the con­fi­dence intervals/point-values for Noopept look sort of con­sis­tent with a U-curve. What if we switch to a qua­dratic term to try to turn the Noopept val­ues into a curve?

li2 <- lm(MP ~ Noopept + I(Noopept^2) +
               LLLT +
               as.logical(Magnesium.citrate) + as.integer(Date) + as.logical(Magnesium.citrate):as.integer(Date),
          data=noopeptImputed)
summary(li2)
# Coefficients:
#                                                        Estimate   Std. Error  t value   Pr(>|t|)
# (Intercept)                                         9.172594278  8.112803113  1.13063 0.25905147
# Noopept                                             0.008079500  0.006074315  1.33011 0.18442378
# I(Noopept^2)                                       -0.000178179  0.000122736 -1.45172 0.14755366
# LLLTTRUE                                            0.284419402  0.080959896  3.51309 0.00050627
# as.logical(Magnesium.citrate)TRUE                  41.589054331 16.141539488  2.57652 0.01042501
# as.integer(Date)                                   -0.000373812  0.000502850 -0.74339 0.45778931
# as.logical(Magnesium.citrate)TRUE:as.integer(Date) -0.002604384  0.001003433 -2.59547 0.00987860
#
# Residual standard error: 0.665408 on 322 degrees of freedom
#   (599 observations deleted due to missingness)
# Multiple R-squared:  0.100316,    Adjusted R-squared:  0.0835521
# F-statistic: 5.98394 on 6 and 322 DF,  p-value: 6.02357e-06

Looks bet­ter, but I’m not sure how well it fits. The qua­dratic has its max­i­mum around 40mg, though, which seems sus­pi­ciously high; it seems that in order to fit the neg­a­tive esti­mate for 60mg, the ‘top’ of the curve gets pulled over to 48mg since it’s almost as big as 15mg. I don’t find that entirely plau­si­ble.

A fancier method of impu­ta­tion would be using, for exam­ple, the R library mice (“Mul­ti­vari­ate Impu­ta­tion by Chained Equa­tions”) (guide), which will try to impute all miss­ing val­ues in a way which mim­icks the inter­nal struc­ture of the data and pro­vide sev­eral ‘pos­si­ble’ datasets to give us an idea of what the under­ly­ing data might have looked like, so we can see how our esti­mates improve with no miss­ing­ness & how much of the esti­mate is now due to the impu­ta­tion:

library(mice)
## work around apparent error in MICE: can't handle Dates type
## even though no missing-values in that column...?
noopeptSecond$Date <- as.integer(noopeptSecond$Date)
nimp <- mice(noopeptSecond, m=200, maxit=200)
li3 <- with(nimp, lm(MP ~ Noopept + I(Noopept^2) +
                          LLLT +
                          as.logical(Magnesium.citrate) + as.integer(Date) +
                            as.logical(Magnesium.citrate):as.integer(Date)))
round(summary(pool(li3)), 4)
#                                                        est     se       t       df Pr(>|t|)
# (Intercept)                                        -8.3369 3.2520 -2.5636 296.1619   0.0109
# Noopept                                             0.0073 0.0057  1.2790 521.5756   0.2015
# I(Noopept^2)                                       -0.0001 0.0001 -1.2808 583.2136   0.2008
# LLLT                                                0.3069 0.0910  3.3737 168.4541   0.0009
# as.logical(Magnesium.citrate)TRUE                   7.0763 3.9584  1.7877 298.7476   0.0748
# as.integer(Date)                                    0.0007 0.0002  3.4911 299.6728   0.0006
# as.logical(Magnesium.citrate)TRUE:as.integer(Date) -0.0005 0.0002 -1.8119 300.7040   0.0710
#                                                       lo 95   hi 95 nmis    fmi lambda
# (Intercept)                                        -14.7369 -1.9368   NA 0.4974 0.4940
# Noopept                                             -0.0039  0.0185  457 0.2852 0.2824
# I(Noopept^2)                                        -0.0004  0.0001   NA 0.2411 0.2385
# LLLT                                                 0.1273  0.4864  599 0.6954 0.6918
# as.logical(Magnesium.citrate)TRUE                   -0.7135 14.8662   NA 0.4942 0.4908
# as.integer(Date)                                     0.0003  0.0011   NA 0.4930 0.4897
# as.logical(Magnesium.citrate)TRUE:as.integer(Date)  -0.0009  0.0000   NA 0.4918 0.4884

The coeffi­cients & p-val­ues agree, so it seems that it does­n’t make too much differ­ence how we deal with miss­ing­ness.

Final­ly, we can see if some weak priors/regularization changes the pic­ture much by using a Bayesian regres­sion instead:

library(arm)
bl1 <- bayesglm(MP ~ as.factor(Noopept) +
              LLLT +
              as.logical(Magnesium.citrate) + as.integer(Date) + as.logical(Magnesium.citrate):as.integer(Date),
          data=noopeptImputed)
display(bl1)
#                                                    coef.est coef.se
# (Intercept)                                        20.86     7.18
# as.factor(Noopept)10                                0.06     0.12
# as.factor(Noopept)15                                0.32     0.28
# as.factor(Noopept)20                                0.10     0.13
# as.factor(Noopept)30                                0.04     0.11
# as.factor(Noopept)48                                0.26     0.20
# as.factor(Noopept)60                               -0.13     0.18
# LLLTTRUE                                            0.27     0.08
# as.logical(Magnesium.citrate)TRUE                   0.28     1.33
# as.integer(Date)                                    0.00     0.00
# as.logical(Magnesium.citrate)TRUE:as.integer(Date)  0.00     0.00
# ---
# n = 329, k = 11
# residual deviance = 144.2, null deviance = 158.5 (difference = 14.3)
# overdispersion parameter = 0.5
# residual sd is sqrt(overdispersion) = 0.67
coefplot(bl1)
Coeffi­cient esti­mates and uncer­tainty for the Bayesian analy­sis (weak pri­ors) of the mag­ne­sium, LLLT, and Noopept vari­ables.

simulates <- as.data.frame(coef(sim(bl1, n.sims=100000)))
sapply(simulates[1:11], function(c) { quantile(c, c(.025, .975)) } )
#       (Intercept) as.factor(Noopept)10 as.factor(Noopept)15 as.factor(Noopept)20
# 2.5%   6.80794518         -0.179116006         -0.218679929         -0.151787205
# 97.5% 34.85995773          0.304713370          0.865894125          0.348912986
#       as.factor(Noopept)30 as.factor(Noopept)48 as.factor(Noopept)60    LLLTTRUE
# 2.5%          -0.174273139         -0.143056371         -0.490166499 0.114146706
# 97.5%          0.247145243          0.660125966          0.221157470 0.433830363
#       as.logical(Magnesium.citrate)TRUE as.integer(Date)
# 2.5%                        -2.29986917  -0.001966335149
# 97.5%                        2.86557048  -0.000227816111
#       as.logical(Magnesium.citrate)TRUE:as.integer(Date)
# 2.5%                                     -0.000197411805
# 97.5%                                     0.000124153915

The 95% cred­i­ble inter­vals empha­size that while the mean esti­mates of the pos­te­rior for the Noopept para­me­ters are pos­i­tive, there’s sub­stan­tial uncer­tainty after updat­ing on the data, and the effects are small.

Should I run another fol­lowup exper­i­ment? No; the implied effect is so small a con­fir­ma­tory exper­i­ment would have to run a mis­er­ably long time, it seems:

library(boot)
library(rms)
newNoopeptPower <- function(dt, indices) {
    d <- dt[sample(nrow(dt), n, replace=TRUE), ] # new dataset, possibly larger than the original
    lmodel <- lm(MP ~ Noopept + I(Noopept^2) +
               LLLT +
               as.logical(Magnesium.citrate) + as.integer(Date) + as.logical(Magnesium.citrate):as.integer(Date),
          data=d)
    return(anova(lmodel)[1:2,][5]$`Pr(>F)`)
}
alpha <- 0.05
for (n in seq(from = 100, to = 3000, by = 200)) {
   bs <- boot(data=noopeptImputed, statistic=newNoopeptPower, R=10000, parallel="multicore", ncpus=4)
   print(c(n, sum(bs$t<=alpha)/length(bs$t)))
}
# [1] 100.0000   0.0817
# [1] 300.0000   0.1145
# [1] 500.00000   0.15175
# [1] 700.00000   0.17825
# [1] 900.0000   0.2132
# [1] 1100.0000    0.2401
# [1] 1300.00000    0.26345
# [1] 1500.00000    0.28595
# [1] 1700.0000    0.3146
# [1] 1900.00000    0.33695
# [1] 2100.0000    0.3513
# [1] 2300.00000    0.37485
# [1] 2500.00000    0.39065
# [1] 2700.0000    0.4068
# [1] 2900.0000    0.4238

(I am not run­ning an blind ran­dom self­-ex­per­i­ment for 8 years just to get barely 40% pow­er.)

Conclusion

So on net, I think there may be an effect but it’s small and I don’t know whether the opti­mal dose would be lower (~10mg) or much higher (~40mg). I don’t find this a par­tic­u­larly good rea­son to con­tinue tak­ing Noopept: it seems to either not be help­ful in a notice­able way or to be redun­dant with the pirac­etam.

Oxiracetam

is one of the 3 most pop­u­lar -rac­etams; less pop­u­lar than pirac­etam but seems to be more pop­u­lar than anirac­etam. Prices have come down sub­stan­tially since the early 2000s, and stand at around 1.2g/$ or roughly 50 cents a dose, which was low enough to exper­i­ment with; key ques­tion, does it stack with pirac­etam or is it redun­dant for me? (Oxirac­etam can’t com­pete on price with my pirac­etam pile stock­pile: the lat­ter is now a sunk cost and hence free.)

I bought 60 grams from Smart Pow­ders and com­bined it with the DMAE; I could­n’t com­pare oxiracetam+DMAE vs oxirac­etam+­choline-bitar­trate because I had capped all the choline with the pirac­etam. One imme­di­ate advan­tage of oxirac­etam: it is not unbe­liev­ably foul tast­ing like pirac­etam, but slightly sweet.

Regard­less, while in the absence of pirac­etam, I did notice some stim­u­lant effects (some­what neg­a­tive - more aggres­sive than usual while dri­ving) and sim­i­lar effects to pirac­etam, I did not notice any men­tal per­for­mance beyond pirac­etam when using them both. The most I can say is that on some nights, I seemed to be less eas­ily tired when writ­ing or edit­ing or n-back­ing, but those were also often nights I was also try­ing out all the other things I had got­ten in that order from Smart Pow­ders, and I am still dis­-en­tan­gling what was respon­si­ble. (Prob­a­bly the l-thea­nine or sul­bu­ti­amine.)

In other words, for me, the two -rac­etams did not seem to ‘stack’. The fol­low­ing are a num­ber of n-back scores from before (pirac­etam only) and after (pirac­etam and oxirac­etam):

  1. [28,39,26,48,34]; [34,60]; [37,53,55] (▁▂▁▄▁▁▆▂▄▅▆)
  2. [56,66,44,46,30,24,50,56,34,39,34]; [30,50,31,37,41,23]; [53,35,40] (▅▇▃▃▁▁▄▅▁▂▁▁▄▁▂▂▁▄▁▂)

There may be some improve­ment hid­den in there, but noth­ing jumps out to my eye. Oxirac­etam has smaller rec­om­mended doses than pirac­etam, true, but even after tak­ing that into account, oxirac­etam is still more expen­sive per dose. When I fin­ished it off, I decided it had­n’t shown any ben­e­fits so there was no point in con­tin­u­ing it.

Piracetam

I bought 500g of (Exam­ine.­com; FDA adverse events) from Smart Pow­ders (pirac­etam is one of the cheap­est nootrop­ics and SP was one of the cheap­est sup­pli­ers; the oth­ers were much more expen­sive as of Octo­ber 2010), and I’ve tried it out for sev­eral days (started on 2009-09-07, and used it steadily up to mid-De­cem­ber). I’ve var­ied my dose from 3 grams to 12 grams (at least, I think the lit­tle scoop mea­sures in gram­s), tak­ing them in my tea or bit­ter fruit juice. Cran­berry worked the best, although orange juice masks the taste pretty well; I also acci­den­tally learned that pirac­etam stings hor­ri­bly when I got some on a cat scratch. 3 grams (alone) did­n’t seem to do much of any­thing while 12 grams gave me a nasty headache. I also ate 2 or 3 eggs a day.

Sub­jec­tive­ly, I did­n’t notice dras­tic changes. Here’s what I did notice:

  • My think­ing seems a lit­tle clearer

  • I’m not so easy to tire - I went through a mon­th’s worth of my Wikipedia watch­list with less fatigue than usu­al, and n-back­ing does­n’t seem so tir­ing.

  • -wise, eye­balling my stats file seems to indi­cate a small increase: when I com­pare peak scores D4B scores, I see mostly 50s and a few 60s before pirac­etam, and after start­ing pirac­etam, a few 70s mixed into the 50s and 60s. Nat­ural increase from train­ing? Dunno - I’ve been stuck on D4B since June, so 5 or 10% in a week or 3 seems a lit­tle sus­pi­cious. A graph of the score series26:

    ▁▅▂▁▅▅▂▄▁▂▁▄▄▁▄▂▁▃▃▂▂▂▁▆▁▂▁▄▃▁▃▄▁▄▁▂▅▅▂▃▁▃▃▂▄▂▄▇▄▄▄▅▃▄▂▄▅▅▁▅▃▃▄▅▅▃▃▂▄▄▃▄▆▃▅▃▄▅ ▃▅▄▄▄▂▄▂▄▃▄▄▃▄▄▂▃▆▂▁

    vs

    ▆▅▆▄▄▅▃▅▁▁▃▄▅▃▁▅▃▅▂▃▄▃▁▄▅▅▂▃▁▁▆▃▁▄▄▃▁▅▄▄▃▃▄▂▅▃▁▄▂▅▃▆▆▂▃▃▆▄▃▃▂▂▂▁▄▃▃▄▄▂

  • The other day, I also noticed I was fid­get­ing less

  • After a week or two, I think I noticed bet­ter reflexes - both in catch­ing falling cups and the in BW seems slightly eas­i­er. But I could be imag­in­ing this since I just saw an Erowid report men­tion­ing bet­ter reflexes & I may’ve read that one before I start­ed. (Darn those sub­con­scious impres­sions and mem­o­ries! :)

After 7 days, I ordered a kg of bitar­trate from Bulk Pow­ders. Choline is stan­dard among pirac­etam-users because it is pretty uni­ver­sally sup­ported by anec­dotes about “pirac­etam headaches”, has sup­port in rat/mice exper­i­ments27, and also some . So I fig­ured I could­n’t fairly test pirac­etam with­out some reg­u­lar choline - the eggs might not be enough, might be the wrong kind, etc. It has a quite dis­tinctly fishy smell, but the actual taste is more cit­rus-y, and it seems to neu­tral­ize the pirac­etam taste in tea (which makes things much eas­ier for me).

The first day (22 Sep­tem­ber) I took ~10g since I was tak­ing 5g of pirac­etam; I wound up with some diar­rhea & fart­ing. Oops.

On the plus side: - I noticed the less-fa­tigue thing to a greater extent, get­ting out of my classes much less tired than usu­al. (Caveat: my sleep sched­ule recently changed for the san­er, so it’s pos­si­ble that’s respon­si­ble. I think it’s more the pirac­etam+­choline, though.) - One thing I was­n’t expect­ing was a decrease in my appetite - nobody had men­tioned that in their report­s.I don’t like being both­ered by my appetite (I know how to eat fine with­out it remind­ing me), so I count this as a plus. - Fid­get­ing was reduced fur­ther

The sec­ond day I went with ~6g of choline; much less intesti­nal dis­tress, but sim­i­lar effects vis-a-vis fid­get­ing, loss of appetite, & reduced fatigue. So in gen­eral I thought this was a pos­i­tive expe­ri­ence, but I’m not sure it was worth $40 for ~2 months’ worth, and it was tedious con­sum­ing it dis­solved.

For­tu­nately for me, the FDA decided Smart Pow­der’s adver­tis­ing was too explicit and ordered its pirac­etam sales stopped; I was equiv­o­cal at the pre­vi­ous price point, but then I saw that between the bulk dis­count and the fire-sale coupon, 3kg was only $99.99 (ship­ping was amor­tized over that, the choline, caffeine, and tryp­to­phan). So I ordered in Sep­tem­ber 2010. As well, I had decided to cap my own pills, elim­i­nat­ing the incon­ve­nience and bad taste. 3kg goes a very long way so I am nowhere close to run­ning out of my pills; there is noth­ing to report since, as the pills are sim­ply part of my daily rou­tine.

Piracetam natural experiment

I take my pirac­etam in the form of capped pills con­sist­ing (in descend­ing order) of pirac­etam, choline bitar­trate, anhy­drous caffeine, and l-ty­ro­sine. On 2012-12-08, I hap­pened to run out of them and could­n’t fetch more from my stock until 27 Decem­ber. This forms a sort of (non-ran­dom­ized, non-blind) short “”: did my daily 1-5 mood/productivity rat­ings fall dur­ing 8-27 Decem­ber com­pared to Novem­ber 2012 & Jan­u­ary 2013? The graphed data28 sug­gests to me a decline:

See foot­note for R code

The BEST results29 give a small effect size of -0.26 and only par­tial exclu­sion of zero effect size (which a one-tailed two-sam­ple test agrees with30):

postInfo = BESTplot(poff, c(pone, ptwo), mcmcChain)

So the answer is yes, M/P did fall as I expect­ed; but also as one would expect given daily vari­a­tion and the small sam­ple of ‘off’ days (19 days), the result is not very sta­tis­ti­cally robust (even ignor­ing the low qual­ity of data from a nat­ural exper­i­men­t). But it was an easy ‘exper­i­ment’ to run and the result had the right sign, as they say.

Potassium

In the 2011-2012 Quan­ti­fied Health Prize, (FDA adverse events) came up twice as a rec­om­men­da­tion. Potas­sium is vital to nerve con­duc­tion, since nerve impulses are noth­ing but potas­sium and sodium rush­ing around, but it did­n’t seem like a pri­or­ity to inves­ti­gate since I am not an ath­lete nor do I sweat a great deal.

A Less­Wrong user Kevin claimed it worked well for him:

By which I mean that sim­ple potas­sium is prob­a­bly the most pos­i­tively mind alter­ing sup­ple­ment I’ve ever tried…About 15 min­utes after con­sump­tion, it man­i­fests as a kind of pres­sure in the head or tem­ples or eyes, a clear­ing up of brain fog, increased focus, and the kind of energy that is not jit­tery but the kind that makes you feel like exer­cis­ing would be the rea­son­able and pru­dent thing to do. I have done no tests, but “feel” smarter from this in a way that seems much stronger than pirac­etam or any of the con­ven­tional weak nootrop­ics. It is not just me – I have been intro­duc­ing this around my inner social cir­cle and I’m at 7/10 peo­ple felt imme­di­ately notice­able effects. The 3 that did­n’t notice much were veg­e­tar­i­ans and less likely to have been defi­cient. Now that I’m not defi­cient, it is of course not notice­able as mind alter­ing, but still serves to be ener­giz­ing, par­tic­u­larly for sus­tained men­tal energy as the night goes on…Potas­sium chlo­ride ini­tial­ly, but since bought some potas­sium glu­conate pills… research indi­cates you don’t want to con­sume large amounts of chlo­ride (just mod­er­ate amounts).

…The first time I took sup­ple­men­tal potas­sium (50% US in a lot of water), it was like a brain fog lifted that I never knew I had, and I felt pro­foundly ener­gized in a way that made me feel exer­cise was rea­son­able and pru­dent, which resulted in me and the room­mate that had just sup­ple­mented potas­sium going for an hour long walk at 2AM. Expe­ri­ences since then have not been quite so pro­found (which prob­a­bly was so stark for me as I was likely fix­ing an acute defi­cien­cy), but I can still count on a mod­er­ately large amount of potas­sium to give me a solid, nearly side effect free per­for­mance boost for a few hours…I had been doing Bikram yoga on and off, and I think I was­n’t keep­ing up the prac­tice because I was­n’t able to prop­erly rehy­drate myself.

One claim was par­tially ver­i­fied in pass­ing by Eliezer Yud­kowsky (“Sup­ple­ment­ing potas­sium (ci­trate) has­n’t helped me much, but works dra­mat­i­cally for Anna, Kev­in, and Vas­sar…About the same as drink­ing a cup of coffee - i.e., it works as a perk­er-up­per, some­how. I’m not sure, since it does­n’t do any­thing for me except pos­si­bly mit­i­gate foot cramps.”)

I largely ignored this since the dis­cus­sions were of sub-RDA dos­es, and my expe­ri­ence has usu­ally been that RDAs are a poor bench­mark and fre­quently far too low (con­sider the RDA for vit­a­min D). This time, I checked the actual RDA - and was imme­di­ately shocked and sure I was look­ing at a bad ref­er­ence: there was no way the was seri­ously 3700-4700mg or 4-5 grams dai­ly, was there? Just as an Amer­i­can, that implied that I was get­ting less than half my RDA. (How would I get 4g of potas­sium in the first place? Eat a dozen bananas a day⸮) I am not a veg­e­tar­i­an, nor is my diet that fan­tas­tic: I fig­ured I was get­ting some potas­sium from the ~2 fresh toma­toes I was eat­ing dai­ly, but oth­er­wise my diet was not rich in potas­sium sources. I have no blood tests demon­strat­ing defi­cien­cy, but given the fig­ures, I can­not see how I could not be defi­cient.

Potas­sium is not the safest sup­ple­ment ever, but it’s rea­son­ably safe (kid­neys can fil­ter out over­dos­es), and between the anec­dotes and my sud­den real­iza­tion that I was highly likely defi­cient, I decided to try it out.

pow­der is nei­ther expen­sive nor cheap: I pur­chased 453g for $21. The pow­der is crys­talline white, dis­solves instantly in water, and largely taste­less (sort of saline & slightly unpleas­an­t). The pow­der is 37% potas­sium by weight (the for­mula is C6H5K3O7) so 453g is actu­ally 167g of potas­si­um, so 80-160 days’ worth depend­ing on dose.

My first impres­sion of ~1g around 12:30PM was that while I do not feel like run­ning around, within an hour I did feel like the ‘brain fog’ was lighter than before. The effect was­n’t dra­mat­ic, so I can’t be very con­fi­dent. Oper­a­tional­iz­ing ‘brain fog’ for an exper­i­ment might be hard: it does­n’t nec­es­sar­ily feel like I would do bet­ter on dual n-back. I took 2 smaller doses 3 and 6 hours lat­er, to no fur­ther effect. Over the fol­low­ing weeks and months, I con­tin­ued to ran­domly alter­nate between potas­sium & non-potas­sium days. I noticed no effects other than sleep prob­lems.

Potassium sleep

That first night, I had severe trou­ble sleep­ing, falling asleep in 30 min­utes rather than my usual 19.6±11.9, wak­ing up 12 times (5.9±3.4), and spend­ing ~90 min­utes awake (18.1±16.2), and nat­u­rally I felt unrested the next day; I ini­tially assumed it was because I had left a fan on (mov­ing air keeps me awake) but the new potas­sium is also a pos­si­ble cul­prit. When I asked, Kevin said:

I think a gen­eral high water high elec­trolyte diet has ben­e­fited my sleep. I haven’t noticed potas­sium imme­di­ately before bed decreas­ing sleep qual­i­ty.

I began record­ing a sub­set of sleep data by hand as . The con­clu­sion was that there was a very strong neg­a­tive effect on my sleep (d=-1.1) and no ben­e­fit to my mood/productivity self­-rat­ings.

Since my exper­i­ment had a num­ber of flaws (non-blind, vary­ing doses at vary­ing times of day), I wound up doing a using blind stan­dard­ized smaller doses in the morn­ing. The neg­a­tive effect was much small­er, but there was still no mood/productivity ben­e­fit. Hav­ing used up my first batch of potas­sium cit­rate in these 2 exper­i­ments, I will not be order­ing again since it clearly does­n’t work for me.

Selegiline / Deprenyl

is a some­what pop­u­lar (Erowid, r/nootropics, FDA adverse events) stimulant/anti-depressant which affects dopamine.

Dosage is appar­ently 5-10mg a day. (Prices can be bet­ter else­where; selegi­line is pop­u­lar for treat­ing dogs with senile demen­tia, where those 60x5mg will cost $2 rather than $3531. One needs a vet­eri­nar­i­an’s pre­scrip­tion to pur­chase from pet-ori­ented online phar­ma­cies, though.) I ordered it & modafinil from Nubrain.­com at $35 for 60x5mg; Nubrain delayed and even­tu­ally can­celed my order - and my enthu­si­asm. Between that and real­iz­ing how much of a pre­mium I was pay­ing for Nubrain’s deprenyl, I’m tabling deprenyl along with nico­tine & modafinil for now. Which is too bad, because I had even ordered 20g of PEA from Smart Pow­ders to try out with the deprenyl. (My later attempt to order some off the Silk Road also failed when the seller can­celed the order.)

Sulbutiamine

2 expe­ri­ences with (Exam­ine.­com) on Red­dit moved me to check it out.

My gen­eral impres­sion is pos­i­tive; it does seem to help with endurance and extended the effect of pirac­etam+­choline, but is not as effec­tive as that com­bo. At $20 for 30g (bought from Smart Pow­der­s), I’m not sure it’s worth­while, but I think at $10-15 it would prob­a­bly be worth­while. Sul­bu­ti­amine seems to affect my sleep neg­a­tive­ly, like caffeine. I bought 2 or 3 can­is­ters for my third batch of pills along with the thea­nine. For a few nights in a row, I slept ter­ri­bly and stayed awake think­ing until the wee hours of the morn­ing; even­tu­ally I real­ized it was because I was tak­ing the thea­nine pills along with the sleep­-mix pills, and the only ingre­di­ent that was a stim­u­lant in the batch was - sul­bu­ti­amine. I cut out the thea­nine pills at night, and my sleep went back to nor­mal. (While very annoy­ing, this, like the cre­a­tine & taek­wondo exam­ple, does tend to prove to me that sul­bu­ti­amine was doing some­thing and it is not pure placebo effec­t.)

It’s worth not­ing that sul­bu­ti­amine reports vary dra­mat­i­cal­ly, and it seems pos­si­ble that some peo­ple are thi­amine-d­e­fi­cient and so would dis­pro­por­tion­ate­ly; Silas­Barta noticed lit­tle to noth­ing (like me), but Jim­ran­domh reports his life was trans­formed (and he sus­pects that his dia­betes caused or exac­er­bated a defi­cien­cy).

Taurine

(Exam­ine.­com) was another gam­ble on my part, based mostly on its inclu­sion in energy drinks. I did­n’t do as much research as I should have: it came as a shock to me when I read in that “tau­rine has been shown to pre­vent oxida­tive stress induced by exer­cise” and was an antiox­i­dant - oxida­tive stress is a key part of how exer­cise cre­ates health ben­e­fits and antiox­i­dants those ben­e­fits.

So now I have to be care­ful about when I take it so it isn’t near a ses­sion of exer­cise or just accept what­ever dam­age tau­rine does me. I’m not sure what I’ll do with it when I cap my cur­rent sup­ply of pow­ders. (It would make lit­tle sense to cap it with the cre­a­tine since I would often take the cre­a­tine before exer­cise.)

And the effects? Well, if you look through the WP arti­cle or other places, you see it jus­ti­fied in part due to sup­posed long term ben­e­fits or effects on blood sugar. I can’t say I’ve noticed any absence of ‘crashes’, tak­ing it on alter­nate days or alone. (At least it was­n’t too expen­sive - $9 for 500g.)

Testosterone

The hor­mone (Exam­ine.­com; FDA adverse events) needs no intro­duc­tion. This is one of the scari­est sub­stances I have con­sid­ered using: it affects so many bod­ily sys­tems in so many ways that it seems almost impos­si­ble to come up with a net sum­ma­ry, either pos­i­tive or neg­a­tive. With testos­terone, the prob­lem is not the usual nootrop­ics prob­lem that that there is a lack of human research, the prob­lem is that the sum­mary con­sti­tutes a text­book - or two. That said, the 2011 review “The role of testos­terone in social inter­ac­tion” (excerpts) gives me the impres­sion that testos­terone does indeed play into risk-tak­ing, moti­va­tion, and social sta­tus-seek­ing; some use­ful links and a rep­re­sen­ta­tive anec­dote:

  • :

  • “The Manly Mol­e­cule”, 2000

  • Wedri­fid, 2012:

    While the pri­mary effect of the drug is mas­sive mus­cle growth the psy­cho­log­i­cal side effects actu­ally improved his san­ity by an absurd degree. He went from barely func­tional to highly pro­duc­tive. When one observes that the deci­sion to not attempt to ful­fill one’s CEV at a given moment is a bad deci­sion it fol­lows that all else being equal improved moti­va­tion is improved san­i­ty.

    Elab­o­rat­ing on why the psy­cho­log­i­cal side effects of testos­terone injec­tion are indi­vid­ual depen­dent: Not every­one get the same amount of moti­va­tion and increased goal seek­ing from the steroid and most peo­ple do not expe­ri­ence peri­ods of chronic avo­li­tion. Another psy­cho­log­i­cal effect is a poten­tially dras­tic increase in aggres­sion which in turn can have neg­a­tive social con­se­quences. In the case of coun­ter­fac­tual Wedri­fid he gets a net improve­ment in social con­se­quences. He has observed that aggres­sion and anger are a prompt for increased ruth­less self­-in­ter­ested goal seek­ing. Ruth­less self­-in­ter­ested goal seek­ing involves actu­ally both­er­ing to pay atten­tion to social pol­i­tics. Peo­ple like peo­ple who do social pol­i­tics well. Most par­tic­u­larly it pre­vents act­ing on con­tempt which is what Wedri­fid finds prompts the most hos­til­ity and resent­ment in oth­ers. Point is, what is a san­ity pro­mot­ing change in one per­son may not be in anoth­er.

As it hap­pens, these are areas I am dis­tinctly lack­ing in. When I first began read­ing about testos­terone I had no par­tic­u­lar rea­son to think it might be an issue for me, but it increas­ingly sounded plau­si­ble, an aunt inde­pen­dently sug­gested I might be defi­cient, a bio­log­i­cal uncle turned out to be severely defi­cient with lev­els around 90 ng/dl (where the nor­mal range for 20-49yo males is 249-839), and finally my blood test in August 2013 revealed that my actual level was 305 ng/dl; inas­much as I was 25 and not 49, this is a tad low.

One idea I’ve been mus­ing about is the con­nec­tions between IQ, Con­sci­en­tious­ness, and testos­terone. IQ and Con­sci­en­tious­ness do not cor­re­late to a remark­able degree - even though one would expect IQ to at least some­what enable a long-term per­spec­tive, self­-dis­ci­pline, metacog­ni­tion, etc! There are indi­ca­tions in stud­ies of gifted youth that they have lower testos­terone lev­els. The stud­ies I’ve read on testos­terone indi­cate no improve­ments to raw abil­i­ty. So, could there be a self­-s­ab­o­tag­ing aspect to human intel­li­gence whereby greater intel­li­gence depends on lack of testos­terone, but this same lack also holds back Con­sci­en­tious­ness (de­spite one’s expec­ta­tion that intel­li­gence would pro­duce greater self­-dis­ci­pline and plan­ning), under­min­ing the util­ity of greater intel­li­gence? Could cases of high IQ types who sud­denly stop slack­ing and accom­plish great things some­times be due to changes in testos­terone? Stud­ies on the cor­re­la­tions between IQ, testos­terone, Con­sci­en­tious­ness, and var­i­ous mea­sures of accom­plish­ment are con­fus­ing and don’t always sup­port this the­o­ry, but it’s an idea to keep in mind.

One might sug­gest just going to the gym or doing other activ­i­ties which may increase endoge­nous testos­terone secre­tion. This would be unsat­is­fy­ing to me as it intro­duces con­founds: the exer­cise may be doing all the work in any observed effect, and cer­tainly can’t be blind­ed. And blind­ing is espe­cially impor­tant because the 2011 review dis­cusses how some stud­ies report that the famed influ­ence of testos­terone on aggres­sion (eg. Wedri­fid’s anec­dote above) is a placebo effect caused by the “folk wis­dom” that testos­terone causes aggres­sion & rage!

I have a nee­dle pho­bia, so injec­tions are right out; but from the images I have found, it looks like testos­terone enan­thate gels using resem­ble other gels like Vase­line. This sug­gests an easy exper­i­men­tal pro­ce­dure: spoon an appro­pri­ate dose of testos­terone gel into one opaque jar, spoon some Vase­line gel into anoth­er, and pick one ran­domly to apply while not look­ing. If one gel evap­o­rates but the other does­n’t, or they have some other differ­ence in behav­ior, the pro­ce­dure can be expanded to some­thing like “and then half an hour lat­er, take a shower to remove all vis­i­ble traces of the gel”. Testos­terone itself has a fairly short half-life of 2-4 hours, but the gel or effects might linger. (In­jec­tions appar­ently oper­ate on a time-s­cale of weeks; I’m not clear on whether this is because the oil takes that long to be absorbed by sur­round­ing mate­ri­als or some­thing else.) Exper­i­men­tal design will depend on the specifics of the obtained sub­stance. As a con­trolled sub­stance (Sched­ule III in the US), sup­plies will be hard to obtain; I may have to resort to the Silk Road.

Pow­er-wise, the effects of testos­terone are gen­er­ally reported to be strong and unmis­tak­able. Even a short exper­i­ment should work. I would want to mea­sure DNB scores & Mnemosyne review aver­ages as usu­al, to ver­ify no gross men­tal deficits; the impor­tant mea­sures would be phys­i­cal activ­i­ty, so either pedome­ter or miles on tread­mill, and gen­eral productivity/mood. The for­mer 2 vari­ables should remain the same or increase, and the lat­ter 2 should increase.

Either pre­scrip­tion or ille­gal, daily use of testos­terone would not be cheap. On the other hand, if I am one of the peo­ple for whom testos­terone works very well, it would be even more valu­able than modafinil, in which case it is well worth even ardu­ous exper­i­ment­ing. Since I am on the fence on whether it would help, this sug­gests the value of infor­ma­tion is high.

Theanine

(Exam­ine.­com) is occa­sion­ally men­tioned on Red­dit or Imminst or Less­Wrong32 but is rarely a top-level post or arti­cle; this is prob­a­bly because thea­nine was dis­cov­ered a very long time ago (>61 years ago), and it’s a pretty straight­for­ward sub­stance. It’s a weak relaxant/ (Google Scholar) which is pos­si­bly respon­si­ble for a few of the of tea, and which works syn­er­gis­ti­cally with caffeine (and is prob­a­bly why caffeine deliv­ered through coffee feels differ­ent from the same amount con­sumed in tea - in one study, sep­a­rate caffeine and thea­nine were a mixed bag, but the com­bi­na­tion beat placebo on all mea­sure­ments). The half-life in humans seems to be pretty short, with van der Pijl 2010 putting it ~60 min­utes. This sug­gests to me that reg­u­lar tea con­sump­tion over a day is best, or at least that one should lower caffeine use - com­bin­ing caffeine and thea­nine into a sin­gle-dose pill has the prob­lem of caffeine’s half-life being much longer so the caffeine will be act­ing after the thea­nine has been largely elim­i­nat­ed. The prob­lem with get­ting it via tea is that teas can vary widely in their thea­nine lev­els and the vari­a­tions don’t seem to be con­sis­tent either, nor is it clear how to esti­mate them. (If you take a large dose in thea­nine like 400mg in water, you can taste the sweet­ness, but it’s sub­tle enough I doubt any­one can actu­ally dis­tin­guish the thea­nine lev­els of tea; inci­den­tal­ly, r-thea­nine - the use­less racemic other ver­sion - anec­do­tally tastes weaker and less sweet than l-thea­nine.)

On 2011-04-08, I pur­chased from Smart Pow­ders (20g for $8); as before, some light search­ing seemed to turn up SP as the best seller given ship­ping over­head; it was on sale and I planned to cap it so I got 80g. This may seem like a lot, but I was highly con­fi­dent that thea­nine and I would get along since I already drink so much tea and was a tad annoyed at the edge I got with straight caffeine. So far I’m pretty happy with it. My goal was to elim­i­nate the phys­i­cal & men­tal “twitch­i­ness” of caffeine, which sub­jec­tively it seems to do.

Run­ning low on my thea­nine in May 2013, I learned SP was now under­cut by Lift­Mode sell­ing 50g for $14, so I got 2 (I was doing a big Ama­zon order any­way). Like the SP thea­nine it is a nice fluffy white pow­der and seems to work as well.

TruBrain

A new all-in-one nootropic mix/company run by some peo­ple active on /r/nootropics; they offered me a mon­th’s sup­ply for free to try & review for them. At ~$125 a month (it depends on how many months one buys), it is not cheap (John Backus esti­mates one could buy the raw ingre­di­ents for $31/month) but it pro­vides con­ve­nience & is aimed at peo­ple unin­ter­ested in spend­ing a great deal of time review­ing research papers & anec­dotes or cap­ping their own pills (ie. peo­ple with lives) and it’s unlikely I could spare the money to sub­scribe if TruBrain worked well for me - but cer­tainly there was no harm in try­ing it out.

The ingre­di­ents list was sane and sim­i­lar to what I would have cho­sen, and does­n’t include any jok­ers like caffeine:

  1. Pirac­etam: 3g

    Nat­u­ral­ly, as pirac­etam is the stan­dard -rac­etam to use. It’s always worked well for me. 3g is a rea­son­able amount for peo­ple who aren’t tak­ing any other sources of pirac­etam.

  2. ALCAR: 0.5g

    I did­n’t notice any per­sonal ben­e­fits from ALCAR, but I did­n’t notice any bad effects either and many peo­ple claim to ben­e­fit.

  3. CDP-Choline: 0.25g

    You’ll want choline when using -rac­etams. 0.25g strikes me as low.

  4. EPA/DHA: 1.2g

    Fish oil is a safe bet for sup­ple­ments. 1.2g is also low, I would pre­fer dou­ble that. (In the batch I got, there was a sort of fruity/gummy taste & after­taste. Appar­ently it’s cher­ry-fla­vored.)

  5. Mag­ne­sium glycinate/lycinate: 0.2g

    My mag­ne­sium l-thre­onate cor­re­la­tion from the Noopept self­-ex­per­i­ment sug­gested mag­ne­sium would help me, so I don’t mind see­ing mag­ne­sium here as well.

  6. : 0.3g

    I don’t know very much about pramirac­etam.

  7. Thea­nine: 0.2g

    An old favorite of mine.

  8. Tyrosine: 0.35g

    Like ALCAR, did noth­ing sub­jec­tively notice­able for me, but noth­ing bad either.

The pack­ag­ing is nice, if a lit­tle con­fus­ing (it’s not entirely clear what pack­ets are sup­posed to be taken on the ini­tial days as part of the “load­ing”). The pills are swal­low­able (one takes a set with break­fast and a sec­ond set with lunch). I do not seem to have died or gone into unto­ward states like seizures, and the first day went swim­ming­ly.

Tryptophan

l- is in a sense redun­dant with tak­ing mela­tonin, since mela­tonin is one of the most promi­nent metabo­lites of tryp­to­phan. Nev­er­the­less, sub­jec­tively I seem to sleep bet­ter by tak­ing 1.5mg of mela­tonin & 0.5g of tryp­to­phan than I do by tak­ing, say, 3mg of mela­tonin.

One of the other sug­gested ben­e­fits is for boost­ing sero­tonin lev­els; low lev­els of sero­tonin are impli­cated in a num­ber of issues like depres­sion. I’m not yet sure whether tryp­to­phan has helped with moti­va­tion or hap­pi­ness. Trial and error has taught me that it’s a bad idea to take tryp­to­phan in the morn­ing or after­noon, how­ev­er, even smaller quan­ti­ties like 0.25g. Like mela­ton­in, the dose-re­sponse curve is a U: ~1g is great and induces mul­ti­ple vivid dreams for me, but ~1.5g leads to an awful night and a headache the next day that was worse, if any­thing, than mela­tonin. (One morn­ing I woke up with traces of at least 7 dreams, although I man­aged to write down only 2. No lucid dreams, though.)

Tak­ing the tryp­to­phan is fairly diffi­cult. The pow­der as sup­plied by Bulk Nutri­tion is extra­or­di­nar­ily dry and fine; it seems to be pos­i­tively . The first time I tried to swal­low a tea­spoon, I nearly coughed it out - the power had seemed to explode in my mouth and go down my lungs. Thence­forth I made sure to have a mouth of water first. After a while, I took a differ­ent tack: I mixed in as much Heri­cium as would fit in the con­tain­er. The mush­room pow­der is wet­ter and chunkier than the tryp­to­phan, and seems to reduce the prob­lem. Com­bin­ing the mix with chunks of mela­tonin inside a pill works even bet­ter.

Tyrosine

(Exam­ine.­com) is an amino acid; peo­ple on the Imminst.org forums (as well as Wikipedia) sug­gest that it helps with energy and cop­ing with stress. I ordered 4oz (bought from Smart Pow­ders) to try it out, and I began tak­ing 1g with my usual caffeine+pirac­etam+­choline mix. It does not dis­solve eas­ily in hot water, and is very chalky and not espe­cially tasty. I have not noticed any par­tic­u­lar effects from it.

Vitamin D

Bought 5,000 IU soft­-gels of -333 (Exam­ine.­com; FDA adverse events) because I was feel­ing very apa­thetic in Jan­u­ary 2011 and not get­ting much done, even slack­ing on reg­u­lar habits like or or my Wikipedia watch­list. Intro­spect­ing, I was reminded of depres­sion & & .

There are a num­ber of treat­ments for the last. I already use mela­tonin. I sort of have from a flu­o­res­cent desk lamp. But I get very lit­tle sun­light; the sur­pris­ing thing would be if I did­n’t have a vit­a­min D defi­cien­cy. And vit­a­min D defi­cien­cies have been linked with all sorts of inter­est­ing things like near-sight­ed­ness, with time out­doors inversely cor­re­lat­ing with myopia and not read­ing or near-work time. (It has been claimed that caffeine inter­feres with vit­a­min D absorp­tion and so peo­ple like me espe­cially need to take vit­a­min D, on top of the deficits caused by our vam­piric habits, but I don’t think this is true34.) Unfor­tu­nate­ly, there’s not very good evi­dence that vit­a­min D sup­ple­men­ta­tion helps with mood/SAD/depression: there’s ~6 small RCTs with some find­ings of ben­e­fits, with their respec­tive meta-analy­sis turn­ing in a pos­i­tive but cur­rently non-s­ta­tis­ti­cal­ly-sig­nifi­cant result. Bet­ter con­firmed is reduc­ing all-cause mor­tal­ity in elderly peo­ple (see, in order of increas­ing com­pre­hen­sive­ness: Evi­dence Syn­the­ses 2013, Chung et al 2009, Autier & Gan­dini 2007, Bol­land et al 2014).

Given the involve­ment with cir­ca­dian rhythms and the syn­the­sis involv­ing direct sun­light, it is likely a bad idea to take vit­a­min D close to bed­time, and there have been anec­dotes that it dam­ages sleep qual­i­ty; I inves­ti­gated this with my Zeo and con­cluded it seemed to be true for me.

The soft gels are very small; one needs to be a bit care­ful - Vit­a­min D is fat-sol­u­ble and in the range of 70,000 IU35, so it would take at least 14 pills, and it’s unclear where prob­lems start with chronic use. Vit­a­min D, like many sup­ple­ments, fol­lows a U-shaped response curve (see also and Durup et al 2012) - too much can be quite as bad as too lit­tle. Too lit­tle, though, is likely very bad. The pre­vi­ously cited stud­ies with high acute doses worked out to <1,000 IU a day, so they may reas­sure us about the risks of a large acute dose but not tell us much about smaller chronic dos­es; the mor­tal­ity increases due to too-high blood lev­els begin at ~140nmol/l and read­ing anec­dotes online sug­gest that 5k IU daily doses tend to put peo­ple well below that (around 70-100nmol/l). I prob­a­bly should get a blood test to be sure, but I have some­thing of a nee­dle pho­bia.

I have else­where remarked on the appar­ent lack of ben­e­fit to tak­ing and the pos­si­ble harm; so one might well won­der about a spe­cific vit­a­min like vit­a­min D. How­ev­er, a ‘mul­ti­vi­t­a­min’ is not ‘vit­a­min D’, so it’s no sur­prise that they might do differ­ent things. If a mul­ti­vi­t­a­min had no vit­a­min D in it, or if it had vit­a­min D in differ­ent dos­es, or if it had sub­stances which inter­acted with vit­a­min D (such as cal­ci­um), or if it had sub­stances which had neg­a­tive effects which out­weigh the pos­i­tive (such as vit­a­min A?), we could well expect differ­ing results. In this case, all of those are true to vary­ing extents. Some mul­ti­vi­t­a­mins I’ve had con­tained no vit­a­min D. The last mul­ti­vi­t­a­min I was tak­ing both con­tains vit­a­mins used in the neg­a­tive tri­als and also some cal­ci­um; the listed vit­a­min D dosage was a triv­ial ~400IU, while I take >10x as much now (5000I­U).

10,000 IU is highly likely to be enough, and is sim­i­lar to what one might get from an hour on the beach; so 5000 IU should be sat­is­fac­to­ry.

Appendices

Powder advantages

With the more sub­tle nootrop­ics, poor shop­ping can lead to the price per dose becom­ing so high that they are not cost-effec­tive; this does not have to be the case.

This ten­dency is exac­er­bated by gen­eral ineffi­cien­cies in the nootrop­ics mar­ket - they are man­u­fac­tured for vastly less than they sell for, although the mar­gins aren’t as high as they are in other sup­ple­ment mar­kets, and not nearly as com­i­cal as ille­gal recre­ational drugs. (Global Price Fix­ing: Our Cus­tomers are the Enemy (Con­nor 2001) briefly cov­ers the vit­a­min car­tel that oper­ated for most of the 20th cen­tu­ry, forc­ing food-grade vit­a­mins prices up to well over 100x the man­u­fac­tur­ing cost.) For exam­ple, the noto­ri­ous (of The Four-hour Work Week) advises imi­ta­tors to find a niche mar­ket with very high mar­gins which they can insert them­selves into as mid­dle­men and reap the profits; one of his first busi­nesses spe­cial­ized in… nootrop­ics & body­build­ing. Or, when Smart Pow­ders - usu­ally one of the cheap­est sup­pli­ers - was dump­ing its pirac­etam in a fire sale of half-off after the FDA warn­ing, its owner men­tioned on forums that the pirac­etam was still profitable (and that he did­n’t really care because sell­ing to body­builders was so lucra­tive); this was because while SP was sell­ing 2kg of pirac­etam for ~$90, Chi­nese sup­pli­ers were offer­ing pirac­etam on for $30 a kilo­gram or a third of that in bulk. (Of course, you need to order in quan­ti­ties like 30kg - this is more or less the only prob­lem the mid­dle­men retail­ers solve.) It goes with­out say­ing that pre­mixed pills or prod­ucts are even more expen­sive than the pow­ders.

Pow­ders are good for exper­i­ment­ing with (easy to vary doses and mix), but not so good for reg­u­lar tak­ing. I use OO gel cap­sules with a Cap­sule Machine: it’s hard to beat $20, it works, it’s not that messy after prac­tice, and it’s not too bad to do 100 pills. How­ev­er, I once did 3kg of pirac­etam + my other pow­ders, and doing that nearly burned me out on ever using cap­sules again. If you’re going to do that much, some­thing more auto­mated is a seri­ous ques­tion! (What actu­ally wound up infu­ri­at­ing me the most was when cap­sules would stick in either the bot­tom or top try - requir­ing you to very gin­gerly pull and twist them out, lest the two halves slip and spill pow­der - or when the two halves would­n’t lock and you had to join them by hand. In con­trast: load­ing the gel caps could be done auto­mat­i­cally with­out look­ing, after some expe­ri­ence.)

3 years supply in pill form (2010)

Man­u­ally mix­ing pow­ders is too annoy­ing, and pre-mixed pills are expen­sive in bulk. So if I’m not actively exper­i­ment­ing with some­thing, and not yet rich, the best thing is to make my own pills, and if I’m mak­ing my own pills, I might as well make a cus­tom for­mu­la­tion using the ones I’ve found per­son­ally effec­tive. And since mak­ing pills is tedious, I want to not have to do it again for years. 3 years seems like a good inter­val - 1095 days. Since one is often busy and mayn’t take that day’s pills (there are enough ingre­di­ents it has to be mul­ti­ple pill­s), it’s safe to round it down to a nice even 1000 days. What sort of hypo­thet­i­cal stack could I make? What do the prices come out to be, and what might we omit in the inter­ests of pro­tect­ing our pock­et­book?

We omit tryp­to­phan and mela­ton­in, of course, because they are most use­ful for sleep­ing and this is a stim­u­lus pill for day­time usage. That leaves from the above the fol­low­ing, with some basic com­mer­cial specs from the usual retail­ers:

Ingre­di­ent Dose (g) g/day Days Price Sup­plier
anirac­etam 180 1 180 $50 Smart­Pow­der­s.­com
caffeine 400 2 200 $18 Smart­Pow­der­s.­com
choline cit­rate 500 2 250 $17 Smart­Pow­der­s.­com
cre­a­tine 1000 4 250 $17 Smart­Pow­der­s.­com
lithium oro­tate 25 0.2 125 $11 Ama­zon
modafinil 2 0.2 10 $8 United Phar­ma­cies36
sul­bu­ti­amine 30 0.25 120 $20 Smart­Pow­der­s.­com
thea­nine 20 0.1 200 $10 Smart­Pow­der­s.­com

We cal­cu­late how many days each unit gets us sim­ply by dose divided by dose per day. We get quite a range; with some prod­ucts, we only need 4 units to cover at least 1000 days, but we need 100 units for modafinil!

Ingre­di­ent Units Cost
anirac­etam 6 $300
caffeine 5 $90
choline cit­rate 4 $68
cre­a­tine 4 $68
lithium oro­tate 8 $88
modafinil 100 $800
sul­bu­ti­amine 9 $180
thea­nine 5 $50

Sum total, $1644, or $1.65 per day for the ingre­di­ents.

But how many pills does this make and how much do those pills cost?

Cap­sule Con­nec­tion sells 1000 00 pills (the largest pills) for $9. I already have a pill machine, so that does­n’t count (a sunk cost). If we sum the grams per day col­umn from the first table, we get 9.75 grams a day. Each 00 pill can take around 0.75 grams, so we need 13 pills. (Cre­a­tine is very bulky, alas.) 13 pills per day for 1000 days is 13,000 pills, and 1,000 pills is $9 so we need 13 units and 13 times 9 is $117.

Redo­ing the above, the total expense is $1761 or $1.76 per day.

13 pills a day sounds like a lot, and $1.76 is actu­ally a fair amount per day com­pared to what most peo­ple take. If I could­n’t swing a round $1800 (even to cover years of con­sump­tion), how would I econ­o­mize?

Look­ing at the prices, the over­whelm­ing expense is for modafinil. It’s a pow­er­ful stim­u­lant - pos­si­bly the sin­gle most effec­tive ingre­di­ent in the list - but dang expen­sive. Worse, there’s anec­do­tal evi­dence that one can develop tol­er­ance to modafinil, so we might be wast­ing a great deal of money on it. (And for me, modafinil isn’t even very use­ful in the day­time: I can’t even notice it.) If we drop it, the cost drops by a full $800 from $1761 to $961 (al­most halv­ing) and to $0.96 per day. A remark­able differ­ence, and if one were genet­i­cally insen­si­tive to modafinil, one would defi­nitely want to remove it.

On the other met­ric, sup­pose we removed the cre­atine? Drop­ping 4 grams of mate­r­ial means we only need to con­sume 5.75 grams a day, cov­ered by 8 pills (com­pared to 13 pill­s). We save 5,000 pills, which would have cost $45 and also don’t spend the $68 for the cre­atine; assum­ing a modafinil for­mu­la­tion, that drops our $1761 down to $1648 or $1.65 a day. Or we could remove both the cre­a­tine and modafinil, for a grand total of $848 or $0.85 a day, which is pretty rea­son­able.


  1. Stew­art Brand on the ’60s:

    …The drugs did­n’t work. Or at least only for a bit. “We believed there was no hope with­out dope but we were wrong. I’m always amazed there aren’t drugs by now, but there aren’t. They did­n’t get any bet­ter, whereas com­put­ers never stopped get­ting bet­ter.”

    ↩︎
  2. More than once I have seen results indi­cat­ing that high­-IQ types ben­e­fit the least from ran­dom nootrop­ics; nutri­tional deficits are the pre­mier exam­ple, because high­-IQ types almost by defi­n­i­tion suffer from no major defi­cien­cies like . But a stim­u­lant modafinil may be another such nootropic (see “Cog­ni­tive effects of modafinil in stu­dent vol­un­teers may depend on IQ”, Ran­dall et al 2005), which men­tions:

    Sim­i­lar­ly, Mehta et al 2000 noted that the pos­i­tive effects of methylphenidate (40 mg) on spa­tial work­ing mem­ory per­for­mance were great­est in those vol­un­teers with lower base­line work­ing mem­ory capac­i­ty. In a study of the effects of ginkgo biloba in healthy young adults, Stough et al 2001 found improved per­for­mance in the Trail-Mak­ing Test A only in the half with the lower ver­bal IQ.

    ↩︎
  3. From , Hills & Her­twig 2011:

    For illus­tra­tion, con­sider amphet­a­mi­nes, Rital­in, and modafinil, all of which have been pro­posed as cog­ni­tive enhancers of atten­tion. These drugs exhibit some pos­i­tive effects on cog­ni­tion, espe­cially among indi­vid­u­als with lower base­line abil­i­ties. How­ev­er, indi­vid­u­als of nor­mal or above-av­er­age cog­ni­tive abil­ity often show neg­li­gi­ble improve­ments or even decre­ments in per­for­mance fol­low­ing drug treat­ment (for details, see ). For instance, Ran­dall, Shneer­son, and File (2005) found that modafinil improved per­for­mance only among indi­vid­u­als with lower IQ, not among those with higher IQ. [See also Finke et al 2010 on visual atten­tion.] Farah, Haimm, Sankoorikal, & Chat­ter­jee 2009 found a sim­i­lar non­lin­ear rela­tion­ship of dose to response for amphet­a­mines in a remote-as­so­ci­ates task, with low-per­form­ing indi­vid­u­als show­ing enhanced per­for­mance but high­-per­form­ing indi­vid­u­als show­ing reduced per­for­mance. Such ∩-shaped dose-re­sponse curves are quite com­mon (see )

    Among other things, these con­sid­er­a­tions warn us against expect­ing much from nootrop­ics whose prin­ci­pal jus­ti­fi­ca­tion come from their results in the ill or the old (since we could call being old an ill­ness) - they are already brain-dam­aged.↩︎

  4. For exam­ple, I am have used my to mea­sure the effects of mela­tonin or of dou­ble-blinded4 vit­a­min D on my Zeo sleep data; the lat­ter is novel and inter­est­ing.↩︎

  5. This is report­edly the result of ‘Ilieva, I., Boland, J., Chat­ter­jee, A. & Farah, M.J. (2010). “Adder­al­l’s per­ceived and actual effects on healthy peo­ple’s cog­ni­tion”. Poster pre­sented at the annual meet­ing of the Soci­ety for Neu­ro­science, San Diego, CA’; blog­ger Casey Schwartz describes it:

    …re­searchers have added a new layer to the “smart pill” con­ver­sa­tion. Adder­all, they’ve found, makes you think you’re doing bet­ter than you actu­ally are….Those sub­jects who had been given Adder­all were sig­nifi­cantly more likely to report that the pill had caused them to do a bet­ter job….But the results of the new Uni­ver­sity of Penn­syl­va­nia study, funded by the U.S. Navy and not yet pub­lished but pre­sented at the annual Soci­ety for Neu­ro­science con­fer­ence last mon­th, are con­sis­tent with much of the exist­ing research. As a group, no over­all sta­tis­ti­cal­ly-sig­nifi­cant improve­ment or impair­ment was seen as a result of tak­ing Adder­all. The research team tested 47 sub­jects, all in their 20s, all with­out a diag­no­sis of ADHD, on a vari­ety of cog­ni­tive func­tions, from work­ing mem­o­ry-how much infor­ma­tion they could keep in mind and manip­u­late-to raw intel­li­gence, to mem­o­ries for spe­cific events and faces….The last ques­tion they asked their sub­jects was: “How and how much did the pill influ­ence your per­for­mance on today’s tests?” Those sub­jects who had been given Adder­all were sig­nifi­cantly more likely to report that the pill had caused them to do a bet­ter job on the tasks they’d been given, even though their per­for­mance did not show an improve­ment over that of those who had taken the place­bo. Accord­ing to Irena Ilieva…it’s the first time since the 1960s that a study on the effects of amphet­a­mine, a close cousin of Adder­all, has asked how sub­jects per­ceive the effect of the drug on their per­for­mance.

    ↩︎
  6. Much bet­ter than I had expect­ed. One of the best super­hero movies so far, bet­ter than Thor or Watch­men (and espe­cially bet­ter than the Iron Man movies). I espe­cially appre­ci­ated how it did­n’t launch right into the usual hack­neyed cre­ation of the hero plot-line but made Cap­tain Amer­ica cool his heels per­form­ing & sell­ing war bonds for 10 or 20 min­utes. The end­ing left me a lit­tle non­plussed, although I sort of knew it was envi­sioned as a fran­chise and I would have to admit that show­ing Cap­tain Amer­ica won­der­ing at Times Square is much bet­ter an end­ing than some­thing as cliche as a close-up of his sud­den­ly-opened eyes and then a fade out. (The movie con­tin­ued the lam­en­ta­ble trend in super­hero movies of hav­ing a strong female love inter­est… who only gets the hots for the hero after they get mus­cles or pow­ers. It was par­tic­u­larly bad in CA because she knows him and his heart of gold before­hand! What is the point of a fem­i­nist char­ac­ter who is imme­di­ately forced to do that?)↩︎

  7. With just 16 pre­dic­tions, I can’t sim­ply bin the pre­dic­tions and say “yep, that looks good”. Instead, we can treat each pre­dic­tion as equiv­a­lent to a bet and see what my win­nings (or loss­es) were; the stan­dard such is the log­a­rith­mic rule which pretty sim­ple: you ‘earn’ the log­a­rithm of the prob­a­bil­ity if you were right, and the log­a­rithm of the nega­tion if you were wrong; he who racks up the fewest neg­a­tive points wins. We feed in a list and get back a num­ber:

    logScore ps = sum $ map (\(result,p) -> if result then log p else log (1-p)) ps
    logScore [(True,0.95),(False,0.30),(True,0.85),(True,0.75),(False,0.50),(False,0.25),
              (False,0.60),(True,0.70),(True,0.65),(True,0.60),(False,0.30),(True,0.50),
              (True,0.90),(True,0.40)]
    -- -6.125

    In this case, a blind guesser would guess 50% every time (roughly half the days were Adder­all and roughly half were not) so the ques­tion is, did the 50% guesser beat me?

    logScore [(True,0.5),(False,0.5),(True,0.5),(True,0.5),(False,0.5),
              (False,0.5),(False,0.5),(True,0.5),(True,0.5),(True,0.5),
              (False,0.5),(True,0.50),(True,0.5),(True,0.5)]
    -- -9.7
    (-9.7) > logScore [(True,0.95),(False,0.30),(True,0.85),(True,0.75),(False,0.50),
                               (False,0.25),(False,0.60),(True,0.70),(True,0.65),(True,0.60),
                               (False,0.30),(True,0.50),(True,0.90),(True,0.40)]
    -- False

    We can also express this as a sin­gle func­tion by using a base-2 log (higher num­bers are bet­ter):

    logBinaryScore = sum . map (\(result,p) -> if result then 1 + logBase 2 p else 1 + logBase 2 (1-p))
    logBinaryScore [(True,0.95),(False,0.30),(True,0.85),(True,0.75),(False,0.50),(False,0.25),
                    (False,0.60),(True,0.70),(True,0.65),(True,0.60),(False,0.30),(True,0.50),
                    (True,0.90),(True,0.40)]
    -- 5.16

    So I had a pal­pa­ble edge over the ran­dom guesser, although the sam­ple size is not fan­tas­tic.↩︎

  8. For exam­ple, famous book on deriv­a­tives of PEA com­ments on PEA proper that:

    • (with 200, 400, 800 and 1600 mg) “No effects.”
    • (with 500 mg) “No effects.”
    • (with 800 and 1600 mg) “No effects.”
    • (with 25 and 50 mg i.v.) “No effects.”

    …It is with­out activ­ity in man! Cer­tainly not for the lack of try­ing, as some of the dosage tri­als that are tucked away in the lit­er­a­ture (as abstracted in the “Qual­i­ta­tive Com­ments” given above) are pretty heavy duty. Actu­al­ly, I truly doubt that all of the exper­i­menters used exactly that phrase, “No effects”, but it is patently obvi­ous that no effects were found. It hap­pened to be the phrase I had used in my own notes.

    …Phenethy­lamine is intrin­si­cally a stim­u­lant, although it does­n’t last long enough to express this prop­er­ty. In other words, it is rapidly and com­pletely destroyed in the human body. It is only when a num­ber of sub­stituent groups are placed here or there on the mol­e­cule that this meta­bolic fate is avoided and phar­ma­co­log­i­cal activ­ity becomes appar­ent.

    ↩︎
  9. “The Use of Stim­u­lants to Mod­ify Per­for­mance Dur­ing Sleep Loss: A Review by the Sleep Depri­va­tion and Stim­u­lant Task Force of the Amer­i­can Acad­emy of Sleep Med­i­cine”, Bon­net et al 2005:

    The abuse lia­bil­ity of caffeine has been eval­u­at­ed.147,148 Tol­er­ance devel­op­ment to the sub­jec­tive effects of caffeine was shown in a study in which caffeine was admin­is­tered at 300 mg twice each day for 18 days.148 Tol­er­ance to the day­time alert­ing effects of caffeine, as mea­sured by the MSLT, was shown over 2 days on which 250 g of caffeine was given twice each day48 and to the sleep­-dis­rup­tive effects (but not REM per­cent­age) over 7 days of 400 mg of caffeine given 3 times each day.7 In humans, place­bo-con­trolled caffeine-dis­con­tin­u­a­tion stud­ies have shown phys­i­cal depen­dence on caffeine, as evi­denced by a with­drawal syn­drome.147 The most fre­quently observed with­drawal symp­tom is headache, but day­time sleepi­ness and fatigue are also often report­ed. The with­drawal-syn­drome sever­ity is a func­tion of the dose and dura­tion of prior caffeine use…At higher dos­es, neg­a­tive effects such as dys­pho­ria, anx­i­ety, and ner­vous­ness are expe­ri­enced. The sub­jec­tive-effect pro­file of caffeine is sim­i­lar to that of amphet­a­mine,147 with the excep­tion that dysphoria/anxiety is more likely to occur with higher caffeine doses than with higher amphet­a­mine dos­es. Caffeine can be dis­crim­i­nated from placebo by the major­ity of par­tic­i­pants, and cor­rect caffeine iden­ti­fi­ca­tion increases with dose.147 Caffeine is self­-ad­min­is­tered by about 50% of nor­mal sub­jects who report mod­er­ate to heavy caffeine use. In post-hoc analy­ses of the sub­jec­tive effects reported by caffeine choosers ver­sus non­choosers, the choosers report pos­i­tive effects and the non­choosers report neg­a­tive effects. Inter­est­ing­ly, choosers also report neg­a­tive effects such as headache and fatigue with place­bo, and this sug­gests that caffeine-with­drawal syn­drome, sec­ondary to placebo choice, con­tributes to the like­li­hood of caffeine self­-ad­min­is­tra­tion. This implies that phys­i­cal depen­dence poten­ti­ates behav­ioral depen­dence to caffeine.

    ↩︎
  10. Evi­dence in sup­port of the neu­ro­pro­tec­tive effects of flavonoids has increased sig­nifi­cantly in recent years, although to date much of this evi­dence has emerged from ani­mal rather than human stud­ies. Nonethe­less, with a view to mak­ing rec­om­men­da­tions for future good prac­tice, we review 15 exist­ing human dietary inter­ven­tion stud­ies that have exam­ined the effects of par­tic­u­lar types of flavonoid on cog­ni­tive per­for­mance. The stud­ies employed a total of 55 differ­ent cog­ni­tive tests cov­er­ing a broad range of cog­ni­tive domains. Most stud­ies incor­po­rated at least one mea­sure of exec­u­tive function/working mem­o­ry, with nine report­ing sig­nifi­cant improve­ments in per­for­mance as a func­tion of flavonoid sup­ple­men­ta­tion com­pared to a con­trol group. How­ev­er, some domains were over­looked com­pletely (e.g. implicit mem­o­ry, prospec­tive mem­o­ry), and for the most part there was lit­tle con­sis­tency in terms of the par­tic­u­lar cog­ni­tive tests used mak­ing across study com­par­isons diffi­cult. Fur­ther­more, there was some con­fu­sion con­cern­ing what aspects of cog­ni­tive func­tion par­tic­u­lar tests were actu­ally mea­sur­ing. Over­all, while ini­tial results are encour­ag­ing, future stud­ies need to pay care­ful atten­tion when select­ing cog­ni­tive mea­sures, espe­cially in terms of ensur­ing that tasks are actu­ally sen­si­tive enough to detect treat­ment effects.

    ↩︎
  11. The abstract:

    Cocoa fla­vanols (CF) pos­i­tively influ­ence phys­i­o­log­i­cal processes in ways which sug­gest that their con­sump­tion may improve aspects of cog­ni­tive func­tion. This study inves­ti­gated the acute cog­ni­tive and sub­jec­tive effects of CF con­sump­tion dur­ing sus­tained men­tal demand. In this ran­dom­ized, con­trolled, dou­ble-blind­ed, bal­anced, three period crossover trial 30 healthy adults con­sumed drinks con­tain­ing 520 mg, 994 mg CF and a matched con­trol, with a 3-day washout between drinks. Assess­ments included the state anx­i­ety inven­tory and repeated 10-min cycles of a Cog­ni­tive Demand Bat­tery com­pris­ing of two ser­ial sub­trac­tion tasks (Se­r­ial Threes and Ser­ial Sev­en­s), a Rapid Visual Infor­ma­tion Pro­cess­ing (RVIP) task and a ‘men­tal fatigue’ scale, over the course of 1 h. Con­sump­tion of both 520 mg and 994 mg CF sig­nifi­cantly improved Ser­ial Threes per­for­mance. The 994 mg CF bev­er­age sig­nifi­cantly speeded RVIP responses but also resulted in more errors dur­ing Ser­ial Sev­ens. Increases in self­-re­ported ‘men­tal fatigue’ were sig­nifi­cantly atten­u­ated by the con­sump­tion of the 520 mg CF bev­er­age only. This is the first report of acute cog­ni­tive improve­ments fol­low­ing CF con­sump­tion in healthy adults. While the mech­a­nisms under­ly­ing the effects are unknown they may be related to known effects of CF on endothe­lial func­tion and blood flow.

    ↩︎
  12. If we assume the vari­ance of the daily scores are equal and we exclude the hypoth­e­sis that fish oil might make scores worse, then we get a smaller p-val­ue:

    before <- c(54,69,42,54,44,62,44,35,85,50,44,42,57,65,51,56,42,53,40,47,
                  45,51,57,57,56,76,66,60,46,52,59,48,28,45,43,47,50,40,57,46,33,19,43,58,36,52,44,64)
    after <- c(55,76,56,55,44,41,44,45,65,70,46,65,46,52,68,52,57,50,64,43,
                  41,50,69,44,47,63,34,57)
    
    wilcox.test(before,after,alternative="less")
    #     Wilcoxon rank sum test with continuity correction
    #
    # data:  before and after
    # W = 570.5, p-value = 0.1381
    # alternative hypothesis: true location shift is less than 0
    
    (mean(after) - mean(before)) / sd(append(before,after)) # the effect size
    # 0.28

    A Bayesian analy­sis using the BEST library gives a sim­i­lar answer - too much over­lap, not enough data:

    $ sudo apt-get install  jags r-cran-rjags
    $ R
    install.packages("rjags")
    source("BEST.R") # assumed downloaded & unzipped BEST to ./
    before <- c(54,69,42,54,44,62,44,35,85,50,44,42,57,65,51,56,42,53,40,47,
                       45,51,57,57,56,76,66,60,46,52,59,48,28,45,43,47,50,40,57,46,33,19,43,58,36,52,44,64)
    after <- c(55,76,56,55,44,41,44,45,65,70,46,65,46,52,68,52,57,50,64,43,41,50,69,44,47,63,34,57)
    mcmcChain = BESTmcmc(before, after)
    postInfo = BESTplot(before, after, mcmcChain) # the generated image
    show(postInfo)
    #            SUMMARY.INFO
    # PARAMETER         mean     median       mode     HDIlow    HDIhigh pcgtZero
    #   mu1       50.1419390 50.1377127 50.1913377 46.8630997 53.6056828       NA
    #   mu2       53.3331611 53.3335072 53.4984856 49.0140883 57.5923759       NA
    #   muDiff    -3.1912221 -3.1790710 -2.8965497 -8.6114644  2.2571314 12.11276
    #   sigma1    11.1989483 11.1365632 11.0708164  8.3699263 14.0987125       NA
    #   sigma2    10.7999759 10.6280744 10.3198861  7.7835957 14.2214647       NA
    #   sigmaDiff  0.3989724  0.4697451  0.5809042 -3.8825471  4.5266108 59.15182
    #   nu        31.2485911 22.6401577  9.1936838  2.3043610 86.5712602       NA
    #   nuLog10    1.3484496  1.3548794  1.3570830  0.6442172  2.0117475       NA
    #   effSz     -0.2917182 -0.2898252 -0.2621231 -0.7942141  0.1909223 12.11276

    Graphs of the 2 datasets com­pared↩︎

  13. This met­ric is a lit­tle trou­bling since work­ing mem­ory is train­able and that’s the point of dual n-back - but my own scores have been stag­nant for a long time and the block­ing should reduce the impact of any very slow lin­ear growth in scores.↩︎

  14. That is, per­haps light of the right wave­length can indeed save the brain some energy by mak­ing it eas­ier to gen­er­ate ATP. Would 15 min­utes of LLLT cre­ate enough ATP to make any mean­ing­ful differ­ence, which could pos­si­bly cause the claimed ben­e­fits? The prob­lem here is like that of the famous blood­-glu­cose the­ory of - while the brain does indeed use up more glu­cose while active, high activ­ity uses up very small quan­ti­ties of glucose/energy which does­n’t seem like enough to jus­tify a men­tal mech­a­nism like weak willpow­er.↩︎

  15. Kurzban, in a blog post puts it well:

    In my last post, I talked about the idea that there is a resource that is nec­es­sary for self­-con­trol…I want to talk a lit­tle bit about the can­di­date for this resource, glu­cose. Could willpower fail because the brain is low on sug­ar? Let’s look at the num­bers. A well-known sta­tis­tic is that the brain, while only 2% of body weight, con­sumes 20% of the body’s ener­gy. That sounds like the brain con­sumes a lot of calo­ries, but if we assume a 2,400 calorie/day diet - only to make the divi­sion really easy - that’s 100 calo­ries per hour on aver­age, 20 of which, then, are being used by the brain. Every three min­utes, then, the brain - which includes mem­ory sys­tems, the visual sys­tem, work­ing mem­o­ry, then emo­tion sys­tems, and so on - con­sumes one (1) calo­rie. One. Yes, the brain is a greedy organ, but it’s impor­tant to keep its greed­i­ness in per­spec­tive… Sup­pose, for instance, that a brain in a per­son exert­ing their willpower - resist­ing eat­ing brown­ies or what have you - used twice as many calo­ries as a per­son not exert­ing willpow­er. That per­son would need an extra one third of a calo­rie per minute to make up the differ­ence com­pared to some­one not exert­ing willpow­er. Does exert­ing “self con­trol” burn more calo­ries?

    ↩︎
  16. Kurzban gives some addi­tional skep­tics:

    • Clarke and Sokoloff (1998) remarked that although “[a] com­mon view equates con­cen­trated men­tal effort with men­tal work…there appears to be no increased energy uti­liza­tion by the brain dur­ing such processes” (p. 664), and “…the areas that par­tic­i­pate in the processes of such rea­son­ing rep­re­sent too small a frac­tion of the brain for changes in their func­tional and meta­bolic activ­i­ties to be reflected in the energy metab­o­lism of the brain…” (p. 675).
    • Gib­son and Green (2002), talk­ing about a pos­si­ble link between glu­cose and cog­ni­tion, wrote that research in the area “…is based on the assump­tion that, since glu­cose is the major source of fuel for the brain, alter­ations in plasma lev­els of glu­cose will result in alter­ations in brain lev­els of glu­cose, and thus neu­ronal func­tion. How­ev­er, the strength of this notion lies in its com­mon-sense plau­si­bil­i­ty, not in sci­en­tific evi­dence…” (p. 185).
    • Lennie (2003) con­cluded that “[t]he brain’s energy con­sump­tion does not change with nor­mal vari­a­tions in men­tal activ­ity” and that “over­all energy con­sump­tion is essen­tially con­stant” (p. 495).
    • Messier (2004) con­cluded that it is “unlikely that the blood glu­cose changes observed dur­ing and after a diffi­cult cog­ni­tive task are due to increased brain glu­cose uptake” (p. 39).
    • Gib­son (2007), con­cluded that “task-in­duced changes in human periph­eral blood glu­cose are unlikely to reflect changes in rel­e­vant areas of brain glu­cose sup­ply” (p. 75).
    ↩︎
  17. And in his fol­lowup work, “An oppor­tu­nity cost model of sub­jec­tive effort and task per­for­mance” (dis­cus­sion). Kurzban seems to have suc­cess­fully refuted the blood­-glu­cose the­o­ry, with few dis­senters from com­ment­ing researchers. The more recent opin­ion seems to be that the sugar inter­ven­tions serve more as a reward-sig­nal indi­cat­ing more effort is a good idea, not refu­el­ing the engine of the brain (which would seem to fit well with research on pro­cras­ti­na­tion).↩︎

  18. This cal­cu­la­tion - reap­ing only 7⁄9 of the naive expec­ta­tion - gives one pause. How seri­ous is the sleep rebound? In another arti­cle, I point to a mice study that sleep deficits can take 28 days to repay. What if the gain from modafinil is entirely wiped out by repay­ment and all it did was defer sleep? Would that ren­der modafinil a waste of mon­ey? Per­haps. Think­ing on it, I believe defer­ring sleep is of some val­ue, but I can­not decide whether it is a net profit.

    That it is some­what valu­able is clear if we con­sider it under another guise. Imag­ine you received the same salary you do, but paid every day. Account­ing sys­tems would incur con­sid­er­able costs han­dling daily pay­ments, since they would be mak­ing so many more and so much smaller pay­ments, and they would have to know instantly whether you showed up to work that day and all sorts of other details, and the recip­i­ents them­selves would waste time deal­ing with all these checks or look­ing through all the deposits to their account, and any errors would be that much harder to track down. (And con­verse­ly, expen­sive ‘pay­day loans’ are strong evi­dence that for poor peo­ple, a bi-weekly pay­ment is much too infre­quen­t.) One might draw a com­par­i­son to batch­ing or buffers in com­put­ers: by let­ting data pile up in buffers, the com­puter can then deal with them in one batch, amor­tiz­ing over­head over many items rather than incur­ring the over­head again and again. The down­side, of course, is that latency will suffer and per­for­mance may drop based on that or the items becom­ing out­dated & use­less. The right trade-off will depend on the specifics; one would not expect ran­dom buffer­-sizes to be opti­mal, but one would have to test and see what works best.

    Sim­i­lar­ly, we could try apply­ing Nick Bostrom’s rever­sal test and ask our­selves, how would we react to a virus which had no effect but to elim­i­nate sleep from alter­nat­ing nights and dou­ble sleep in the inter­ven­ing nights? We would prob­a­bly grouch about it for a while and then adapt to our new hedo­nis­tic lifestyle of par­ty­ing or work­ing hard. On the other hand, imag­ine the virus had the effect of elim­i­nat­ing nor­mal sleep but instead, every 2 min­utes, a per­son would fall asleep for a minute. This would be dis­as­trous! Besides the most imme­di­ate prob­lems like safely dri­ving vehi­cles, how would any­thing get done? You would hold a meet­ing and at any point, a third of the par­tic­i­pants would be asleep. If the virus made it instead 2 hours on, one hour off, that would be bet­ter but still prob­lem­at­ic: there would be con­stant inter­rup­tions. And so on, until we reach our present state of 16 hours on, 8 hours off. Given that we rejected all the ear­lier buffer sizes, one won­ders if 16:8 can be defended as uniquely suited to cir­cum­stances. Is that opti­mal? It may be, given the syn­chro­niza­tion with the night-day cycle, but I won­der; rush hour alone stands as an argu­ment against syn­chro­nized sleep - would­n’t our infra­struc­ture would be much cheaper if it only had to han­dle the aver­age daily load rather than cope with the pro­jected peak loads? Might not a longer cycle be bet­ter? The longer the day, the less we are inter­rupted by sleep; it’s a hoary cliche about pro­gram­mers that they pre­fer to work in long sus­tained marathons dur­ing long nights rather than sprint occa­sion­ally dur­ing a dis­trac­tion-filled day, to the point where some famously adopt a 28 hour day (which evenly divides a week into 6 days). Are there other occu­pa­tions which would ben­e­fit from a 20 hour wak­ing peri­od? Or 24 hour wak­ing peri­od? We might not know because with­out chem­i­cal assis­tance, cir­ca­dian rhythms would over­power any­one attempt­ing such sched­ules. It cer­tainly would be nice if one had long time chunks in which could read a chal­leng­ing book in one sit­ting, with­out heroic arrange­ments.↩︎

  19. As before in the Adder­all tri­al, we use a binary log­a­rith­mic :

    logBinaryScore = sum . map (\(result,p) -> if result then 1 + logBase 2 p else 1 + logBase 2 (1-p))
    logBinaryScore [(True,0.40),(True,0.50),(False,0.65),(False,0.50),
                    (True,0.75),(False,0.40),(False,0.35),(False,0.60)]
    -- 0.007

    Com­pare 0.007 to the 5.16 I racked up guess­ing Adder­all! My score is essen­tially 0.↩︎

  20. I don’t under­stand how Sun can pro­duce any armodafinil, as the armodafinil patents are recent enough that the modafinil loop­hole should­n’t apply.↩︎

  21. From slide 6 in the sec­ond link:

    Kinetic Pro­files (Dar­wish et al.) [Dar­wish et al 2009, “Armodafinil and Modafinil have sub­stan­tially differ­ent phar­ma­co­ki­netic pro­files despite hav­ing the same ter­mi­nal half-lives”]

    • S-modafinil has a rel­a­tively short half-life (4-5 hours)
    • R-modafinil has a 3-4 fold longer half-life (~15 hours)
    • R-modafinil has 43% higher con­cen­tra­tions 7-11 hours after dos­ing
    • Greater sys­temic expo­sure to R-modafinil; AUC∞ was 40% higher
    • R-modafinil’s plasma fluc­tu­a­tion was 28% less than S-modafinil over 24-hours
    • More lin­ear, monopha­sic elim­i­na­tion of R-modafinil"

    Slide 8:

    “Patients report a more pro­found & sus­tained”wake­ful­ness" with armodafinil.

    Slightly bet­ter side-effect pro­file?*

    • Slightly less inci­dence of headache/anxiety
    • Longer last­ing armodafinil = more insom­nia?
    • Reduced “med­ica­tion-load” on the body, since it does not have to metab­o­lize S-modafinil.

    *Doses com­pared may influ­ence the reli­a­bil­ity of this data (400mg modafinil vs 250mg armodafinil)

    ↩︎
  22. Specifi­cal­ly, the film is com­pletely unin­tel­li­gi­ble if you had not read the book. The best I can say for it is that it deliv­ers the action and events one expects in the right order and with basic com­pe­tence, but its artis­tic mer­its are few. It seems gen­er­ally devoid of the imag­i­na­tion and visual flights of fancy that ani­mated movies 1 and 3 espe­cially (although Mike Dar­win dis­agrees), cop­ping out on stan­dard imagery like a Star Wars-style force field over Hog­warts Castle, or lumi­nes­cent white fog when Harry was dead and in his head; I was deeply dis­ap­pointed to not see any sights that struck me as novel and new. (For exam­ple, the afore­men­tioned dead scene could have been done in so many inter­est­ing ways, like why not show Harry & Dum­b­le­dore in a bustling King’s Cross shot in bright sharp detail, but with not a sin­gle per­son in sight and all the lug­gage and equip­ment ani­mat­edly mov­ing pur­pose­fully on their own?) The end­ing in par­tic­u­lar bog­gles me. I actu­ally turned to the per­son next to me and asked them whether that really was the cli­max and Volde­mort was dead, his death was so lit­tle dwelt upon or laden with sig­nifi­cance (de­spite a musi­cal score that beat you over the head about every­thing else). In the book, I remem­ber it feel­ing like a cli­mac­tic scene, with every­one watch­ing and lit­tle speeches explain­ing why Volde­mort was about to be defeat­ed, and a suit­able vic­tory cel­e­bra­tion; I read in the paper the next day a quote from the direc­tor or screen­writer who said one scene was cut because Volde­mort would not talk but sim­ply try to effi­ciently kill Har­ry. (This is pre­sum­ably the expla­na­tion for the incred­i­ble anti-cli­max. Hope­ful­ly.) I was dumb­founded by the depths of dis­hon­esty or delu­sion or dis­re­gard: Volde­mort not only does that in Deathly Hal­lows mul­ti­ple times, he does it every time he deals with Har­ry, exactly as the clas­sic vil­lains (he is num­bered among) always do! How was it pos­si­ble for this man to read the books many times, as he must have, and still say such a thing?↩︎

  23. This was using Brain Work­shop, D5B, 45 tri­als over 157 sec­onds.↩︎

  24. “Cog­ni­tive effects of nico­tine in humans: an fMRI study”, Kumari et al 2003

    …Four sub­jects cor­rectly stated when they received nicotine, five sub­jects were unsure, and the remain­ing two stated incor­rectly which treat­ment they received on each occa­sion of test­ing. These num­bers are suffi­ciently close to chance expec­ta­tion that even the four sub­jects whose state­ments cor­re­sponded to the treat­ments received may have been guess­ing.

    ↩︎
  25. On the Quan­ti­fied Self forum, Chris­t­ian Kleinei­dam asked:

    As I see you did­n’t con­trol for the train­ing effect of dual-n-back. Are your dual-n-back scores gen­er­ally sta­ble enough that you don’t have a strong train­ing effect any­more?

    I don’t believe there’s any need to con­trol for train­ing with repeated with­in-sub­ject sam­pling, since there will be as many sam­ples on both con­trol and active days drawn from the later “trained” period as with the ini­tial “untrained” peri­od. But yes, my D5B scores seem to have plateaued pretty much and only very slowly increase; you can look at the stats file your­self.

    But to inves­ti­gate, let’s look a graph of my last ~200 D5B scores:

    dnb <- c(30,34,41,45,44,33,30,38,48,52,37,50,45,30,53,46,50,25,20,52,40,54,36,58,10,32,
             33,36,43,36,41,29,40,29,28,36,25,27,38,50,25,34,30,40,57,34,41,51,36,26,34,62,
             33,22,40,28,37,50,25,37,42,40,45,31,24,38,40,47,42,44,58,47,55,35,31,27,66,25,
             38,35,43,60,47,17,43,46,50,36,38,58,50,23,50,31,38,33,66,30,68,42,40,29,69,45,
             60,37,22,28,40,41,45,37,18,50,20,41,42,47,44,60,31,46,46,55,47,42,35,40,45,27,
             35,45,30,29,47,56,37,50,44,40,33,44,19,58,38,41,52,41,33,47,45,45,55,20,31,42,
             53,27,45,50,65,33,33,30,52,36,28,43,33,40,47,41,25,55,40,31,30,45,50,20,25,30,
             70,45,50,27,29,55,47,47,42,40,35,45,60,37,22,38,36,54,64,25,28,31,15,47,64,35,
             33,60,38,28,60,45,64,50,44,38,50,42,31,50,30,35,61,56,30,44,37,43,38)
    231 dual 5-back scores plot­ted in chrono­log­i­cal order: plot(dnb)

    The point about ran­dom­iza­tion is key, BTW, because the the­o­ret­i­cal train­ing effect is actu­ally greater than the observed improve­ment between ran­dom­ized days. Watch:

    lm(dnb ~ c(1:231))
    # Coefficients:
    # (Intercept)     c(1:231)
    #    38.37041      0.01752
    ## 0.017 is a positive slope!
    DNB scores per day with a lin­ear fit over­laid; plot(dnb); abline(lm(dnb ~ c(1:231)))

    It’s not much of a slope but it’s there. Now, I spent 200 rounds of n-back doing the ran­dom­ized nico­tine exper­i­ment, and those would be the lat­ter 200 rounds graphed; how much of an improve­ment should I expect?

    The model is: . We want the end­point, score 231, and what is 200 before 231? 31:

    (38.37041 + 0.01752*231) - (38.37041 + 0.01752*31)
    # 3.504

    Notice that 3.5 > 1.1. So if this was just train­ing effect, why isn’t the “ben­e­fit” from nico­tine greater?↩︎

  26. The full series:

    28,61,36,25,61,57,39,56,23,37,24,50,54,32,50,33,16,42,41,40,34,33,31,65,23,36,29,51,46,31,45,52,30, 50,29,36,57,60,34,48,32,41,48,34,51,40,53,73,56,53,53,57,46,50,35,50,60,62,30,60,48,46,52,60,60,48, 47,34,50,51,45,54,70,48,61,43,53,60,44,57,50,50,52,37,55,40,53,48,50,52,44,50,50,38,43,66,40,24,67, 60,71,54,51,60,41,58,20,28,42,53,59,42,31,60,42,58,36,48,53,46,25,53,57,60,35,46,32,26,68,45,20,51, 56,48,25,62,50,54,47,42,55,39,60,44,32,50,34,60,47,70,68,38,47,48,70,51,42,41,35,36,39,23,50,46,44,56,50,39

    ↩︎
  27. That study is also inter­est­ing for find­ing ben­e­fits to chronic pirac­etam+­choline sup­ple­men­ta­tion in the mice, which seems con­nected to a Russ­ian study which report­edly found that pirac­etam (among other more obscure nootrop­ics) increased secre­tion of in mice. See also Drug heuris­tics on a study involv­ing choline sup­ple­men­ta­tion in preg­nant rats.↩︎

  28. Graph­ing each time peri­od:

    pone <- c(4,3,4,3,4,3,4,4,3,3,2,3,2,4,4,3,4,2,3,4,2,3,3,2,2,2,3,2,3,3,4,2,3,4,3,4,3)
    poff <- c(3,2,2,3,4,4,3,4,2,2,3,2,3,2,2,2,4,3,3)
    ptwo <- c(4,2,2,3,3,3,4,4,3,2,3,2,2,2,3,3,3,4,3,4,3,3,3,2,2,3,3,3,4,4,3,2,2,2,3,3)
    
    plot(1:92, rep(3, 92), type="n", ylab="mood/productivity (1-4)", xlab="days")
    points(1:37, pone, col="blue")
    points(38:56, poff, col="red")
    points(57:92, ptwo, col="blue")
    ↩︎
  29. The usu­al:

    source("BEST.R")
    mcmcChain = BESTmcmc(poff, c(pone, ptwo))
    postInfo = BESTplot(poff, c(pone, ptwo), mcmcChain); postInfo
    #            SUMMARY.INFO
    # PARAMETER       mean   median     mode  HDIlow  HDIhigh pcgtZero
    #   mu1        2.78153  2.78130  2.77061  2.3832   3.1752       NA
    #   mu2        2.98579  2.98566  2.98369  2.8103   3.1606       NA
    #   muDiff    -0.20426 -0.20463 -0.21982 -0.6315   0.2316    17.07
    #   sigma1     0.83778  0.81619  0.78042  0.5665   1.1559       NA
    #   sigma2     0.73900  0.73476  0.73031  0.6158   0.8690       NA
    #   sigmaDiff  0.09877  0.08114  0.05378 -0.2103   0.4443    70.61
    #   nu        50.19929 42.00024 28.00379  5.8283 115.9430       NA
    #   nuLog10    1.61236  1.62325  1.63557  1.0515   2.1480       NA
    #   effSz     -0.26083 -0.26144 -0.28521 -0.7992   0.2774    17.07
    ↩︎
  30. We do a one-tailed test because the orig­i­nal hypoth­e­sis was that M/P would fall, cer­tainly not that it would increase:

    wilcox.test(poff,c(pone,ptwo), alternative="less")
    #     Wilcoxon rank sum test with continuity correction
    #
    # data:  poff and c(pone, ptwo)
    # W = 593, p-value = 0.1502
    ↩︎
  31. One might expect some sort of catch - surely there’s a mas­sive qual­ity differ­ence to go with the mas­sive price differ­ence? But there could well not be; I would not be sur­prised to learn that the dog selegi­line and the human selegi­line came out of the same vat.

    It’s basic eco­nom­ics: the price of a good must be greater than cost of pro­duc­ing said good, but only under will price = cost. Oth­er­wise, the price is sim­ply what­ever max­i­mizes profit for the sell­er. (Bot­tled water does­n’t really cost $2 to pro­duce.) This can lead to appar­ently coun­ter-in­tu­itive con­se­quences involv­ing & - such as which are the pre­mium prod­uct which has been delib­er­ately degraded and sold for less (some Intel CPUs, some head­phones etc.). The most famous exam­ples were rail­roads; one notable pas­sage by French engi­neer-e­con­o­mist Jules Dupuit describes the moti­va­tion for the con­di­tions in 1849:

    It is not because of the few thou­sand francs which would have to be spent to put a roof [!] over the third-class car­riages or to uphol­ster the third-class seats that some com­pany or other has open car­riages with wooden bench­es. What the com­pany is try­ing to do is to pre­vent the pas­sen­gers who can pay the sec­ond class fare from trav­el­ing third class; it hits the poor, not because it wants to hurt them, but to frighten the rich. And it is again for the same rea­son that the com­pa­nies, hav­ing proved almost cruel to the third-class pas­sen­gers and mean to the sec­ond-class ones, become lav­ish in deal­ing with first-class pas­sen­gers. Hav­ing refused the poor what is nec­es­sary, they give the rich what is super­flu­ous.

    Price dis­crim­i­na­tion is aided by bar­ri­ers such as igno­rance and oli­gop­o­lies. An exam­ple of the for­mer would be when I went to a Food Lion gro­cery store in search of spices, and noticed that there was a sec­ond selec­tion of spices in the “Hispanic/Latino” eth­nic food aisle, with unit prices per­haps a fourth of the reg­u­lar McCormick­-brand spices; I rather doubt that reg­u­lar cin­na­mon varies that much in qual­i­ty. An exam­ple of the lat­ter would be using vet­eri­nary drugs on humans - any doc­tor to do so would prob­a­bly be guilty of med­ical mal­prac­tice even if the drugs were man­u­fac­tured in the same fac­to­ries (as well they might be, con­sid­er­ing economies of scale). Sim­i­lar­ly, we can pre­dict that when­ever there is a vet­eri­nary drug which is chem­i­cally iden­ti­cal to a human drug, the vet­eri­nary drug will be much cheap­er, regard­less of actual man­u­fac­tur­ing cost, than the human drug because pet own­ers do not value their pets more than them­selves. Human drugs are osten­si­bly held to a higher stan­dard than vet­eri­nary drugs; so if vet­eri­nary prices are higher, then there will be an arbi­trage incen­tive to sim­ply buy the cheaper human ver­sion and ‘down­grade’ them to vet­eri­nary drugs.

    As with any the­sis, there are excep­tions to this gen­eral prac­tice. For exam­ple, thea­nine for dogs is sold under the brand Anx­i­tane is sold at almost a dol­lar a pill, and appar­ently a mon­th’s sup­ply costs $50+ vs $13 for human-branded thea­nine; on the other hand, this the­sis pre­dicts ‘down­grad­ing’ if the mar­ket priced pet ver­sions higher than human ver­sions, and that Red­dit poster appears to be doing just that with her dog.↩︎

  32. See for exam­ple the men­tions in “A ratio­nal­ist’s guide to psy­choac­tive drugs” or the dis­cus­sion in the post “Coffee: When it helps, when it hurts”; see also the descrip­tion of a rare bad expe­ri­ence with thea­nine.↩︎

  33. It’s impor­tant one uses D-3 and not vit­a­min D-2, , or : the Cochrane review found mor­tal­ity ben­e­fits only with D-3. (And use with cal­cium does­n’t look too good either.)↩︎

  34. It’s been sug­gested that caffeine inter­feres with pro­duc­tion or absorp­tion of vit­a­min D and this may be a bad thing; eg. Med­pe­dia or blog­ger Chris Hunt (HN dis­cus­sion):

    Caffeine keeps you awake, which keeps you cod­ing. It may also be a nootrop­ic, increas­ing brain-pow­er. Both desir­able results. How­ev­er, it also inhibits vit­a­min D recep­tors, and as such decreases the body’s uptake of this-much-need­ed-vi­t­a­min. OK, that’s not so bad, you’re not get­ting the max­i­mum dose of vit­a­min D. So what? Well, by itself caffeine may not cause you any prob­lems, but com­bined with cut­ting off a major source of the vit­a­min - the pro­duc­tion via sun­light - you’re leav­ing your­self open to defi­ciency in dou­ble-quick time.

    Or Live­Strong’s arti­cles:

    Too much caffeine may be bad for bone health because it can deplete cal­ci­um. Over­do­ing the caffeine also may affect the vit­a­min D in your body, which plays a crit­i­cal role in your body’s bone metab­o­lism. How­ev­er, the roles of vit­a­min D as well as caffeine in the devel­op­ment of osteo­poro­sis con­tinue to be a source of debate. Sig­nifi­cance: Caffeine may inter­fere with your body’s metab­o­lism of vit­a­min D, accord­ing to a 2007 “Jour­nal of Steroid Bio­chem­istry & Mol­e­c­u­lar Biol­ogy” study. You have vit­a­min D recep­tors, or VDRs, in your osteoblast cells. These large cells are respon­si­ble for the min­er­al­iza­tion and syn­the­sis of bone in your body. They cre­ate a sheet on the sur­face of your bones. The D recep­tors are nuclear hor­mone recep­tors that con­trol the action of vit­a­min D-3 by con­trol­ling hor­mone-sen­si­tive gene expres­sion. These recep­tors are crit­i­cal to good bone health. For exam­ple, a vit­a­min D metab­o­lism dis­or­der in which these recep­tors don’t work prop­erly causes rick­ets.

    The only study ever cited is “Caffeine decreases vit­a­min D recep­tor pro­tein expres­sion and 1,25(O­H)2D3 stim­u­lated alka­line phos­phatase activ­ity in human osteoblast cells”, Rapuri et al 2007:

    Caffeine dose depen­dently decreased the 1,25(O­H)(2)D(3) induced VDR expres­sion and at con­cen­tra­tions of 1 and 10mM, VDR expres­sion was decreased by about 50-70%, respec­tive­ly. In addi­tion, the 1,25(O­H)(2)D(3) induced alka­line phos­phatase activ­ity was also reduced at sim­i­lar doses thus affect­ing the osteoblas­tic func­tion. The basal ALP activ­ity was not affected with increas­ing doses of caffeine. Over­all, our results sug­gest that caffeine affects 1,25(O­H)(2)D(3) stim­u­lated VDR pro­tein expres­sion and 1,25(O­H)(2)D(3) medi­ated actions in human osteoblast cells.

    One should note the seri­ous caveats here: it is a small in vitro study of a sin­gle cat­e­gory of human cells with an effect size that is not clear on a pro­tein which feeds into who-knows-what path­ways. It is not a result in a whole organ­ism on any clin­i­cally mean­ing­ful end­point, even if we take it at face-value (many results ). A look at fol­lowup work cit­ing Rapuri et al 2007 is not encour­ag­ing: Google Scholar lists no human stud­ies of any kind, much less high­-qual­ity stud­ies like RCTs; just some rat fol­lowups on the cal­cium effect. This is not to say Rapuri et al 2007 is a bad study, just that it does­n’t bear the weight peo­ple are putting on it: if you enjoy caffeine, this is close to zero evi­dence that you should reduce or drop caffeine con­sump­tion; if you’re tak­ing too much caffeine, you already have plenty of rea­sons to reduce; if you’re drink­ing lots of coffee, you already have plenty of rea­sons to switch to tea; etc.

    If we go look­ing for mean­ing­ful human stud­ies, what we find is that there’s clear evi­dence that caffeine dam­ages bone den­sity via cal­cium uptake, espe­cially in old wom­en, but there is lit­tle or no inter­ac­tion between vit­a­min D and caffeine, and some reports of cor­re­la­tions entirely oppo­site the claimed cor­re­la­tion.

    • “Caffeine intake increases the rate of bone loss in elderly women and inter­acts with vit­a­min D recep­tor geno­types”, Rapuri et al 2001:

      Results: Women with high caffeine intakes had sig­nifi­cantly higher rates of bone loss at the spine than did those with low intakes (−1.90 ± 0.97% com­pared with 1.19 ± 1.08%; P = 0.038). When the data were ana­lyzed accord­ing to VDR geno­type and caffeine intake, women with the tt geno­type had sig­nifi­cantly (P = 0.054) higher rates of bone loss at the spine (−8.14 ± 2.62%) than did women with the TT geno­type (−0.34 ± 1.42%) when their caffeine intake was >300 mg/d…In 1994, Mor­ri­son et al (22) first reported an asso­ci­a­tion between vit­a­min D recep­tor gene (VDR) poly­mor­phism and BMD of the spine and hip in adults. After this ini­tial report, the rela­tion between VDR poly­mor­phism and BMD, bone turnover, and bone loss has been exten­sively eval­u­at­ed. The results of some stud­ies sup­port an asso­ci­a­tion between VDR poly­mor­phism and BMD (23-,25), whereas other stud­ies showed no evi­dence for this asso­ci­a­tion (26,27)…At base­line, no sig­nifi­cant differ­ences existed in serum parathy­roid hor­mone, serum 25-hy­drox­yvi­t­a­min D, serum osteo­cal­cin, and uri­nary N-telopep­tide between the low- and high­-caffeine groups (Table 1⇑). In the lon­gi­tu­di­nal study, the per­cent­age of change in serum parathy­roid hor­mone con­cen­tra­tions was sig­nifi­cantly lower in the high­-caffeine group than in the low-caffeine group (Table 2⇑). How­ev­er, no sig­nifi­cant differ­ences existed in the per­cent­age of change in serum 25-hy­drox­yvi­t­a­min D

    • “Effects of caffeine, vit­a­min D, and other nutri­ents on quan­ti­ta­tive pha­langeal bone ultra­sound in post­menopausal women” Rico et al 2002:

      In sim­ple and mul­ti­ple regres­sion analy­ses, the only sig­nifi­cant vari­able that affected Ad-SOS and nutri­ent intake was vit­a­min D (p < 0.0001). Pha­langeal bone Ad-SOS was influ­enced only by the intake of vit­a­min D, not of caffeine or other nutri­ents.

    • “Colas, but not other car­bon­ated bev­er­ages, are asso­ci­ated with low bone min­eral den­sity in older wom­en: The Fram­ing­ham Osteo­poro­sis Study”, Tucker et al 2006:

      In this large pop­u­la­tion-based cohort, we saw con­sis­tent robust asso­ci­a­tions between cola con­sump­tion and low BMD in women. The con­sis­tency of pat­tern across cola types and after adjust­ment for poten­tial con­found­ing vari­ables, includ­ing cal­cium intake, sup­ports the like­li­hood that this is not due to dis­place­ment of milk or other healthy bev­er­ages in the diet. The major differ­ences between cola and other car­bon­ated bev­er­ages are caffeine, phos­phoric acid, and cola extract. Although caffeine likely con­tributes to lower BMD, the result also observed for decaffeinated cola, the lack of differ­ence in total caffeine intake across cola intake groups, and the lack of atten­u­a­tion after adjust­ment for caffeine con­tent sug­gest that caffeine does not explain these results. A dele­te­ri­ous effect of phos­phoric acid has been pro­posed (26). Cola bev­er­ages con­tain phos­phoric acid, whereas other car­bon­ated soft drinks (with some excep­tions) do not.

    • “Coffee, Tea, and Caffeine Con­sump­tion and Risk of Rheuma­toid Arthri­tis: Results From the Iowa Wom­en’s Health Study”, Mikuls et al 2002:

      Com­pared with those report­ing no use, sub­jects drink­ing >4 cups/day of decaffeinated coffee were at increased risk of RA [rheuma­toid arthri­tis] (RR 2.58, 95% CI 1.63-4.06). In con­trast, women con­sum­ing >3 cups/day of tea dis­played a decreased risk of RA (RR 0.39, 95% CI 0.16-0.97) com­pared with women who never drank tea. Caffeinated coffee and daily caffeine intake were not asso­ci­ated with the devel­op­ment of RA.

    • see also “Vit­a­min D intake is inversely asso­ci­ated with rheuma­toid arthri­tis: results from the Iowa Wom­en’s Health Study”, Mer­lino et al 2004

    • “Differ­en­tial effect of caffeine admin­is­tra­tion on cal­cium and vit­a­min D metab­o­lism in young and adult rats”, Yeh & Aloia 1986:

      Since coffee drink­ing may lead to a wors­en­ing of cal­cium bal­ance in humans, we stud­ied the ser­ial changes of serum cal­ci­um, PTH, 1,25-di­hy­drox­yvi­t­a­min D (1,25(O­H)2D) vit­a­min D and cal­cium bal­ance in young and adult rats after daily admin­is­tra­tion of caffeine for 4 weeks. In the young rats, there was an increase in uri­nary cal­cium and endoge­nous fecal cal­cium excre­tion after four days of caffeine admin­is­tra­tion that per­sisted for the dura­tion of the exper­i­ment. Serum cal­cium decreased on the fourth day of caffeine admin­is­tra­tion and then returned to con­trol lev­els. In con­trast, the serum PTH and 1,25(O­H)2D remained unchanged ini­tial­ly, but increased after 2 weeks of caffeine admin­is­tra­tion…In the adult rat group, an increase in the uri­nary cal­cium and endoge­nous fecal cal­cium excre­tion and serum lev­els of PTH was found after caffeine admin­is­tra­tion. How­ev­er, the serum 1,25(O­H)2D lev­els and intesti­nal absorp­tion coeffi­cient of cal­cium remained the same as in the adult con­trol group.

    • “Vit­a­min D Recep­tor Geno­type and the Risk of Bone Frac­tures in Women”, Fes­kanich et al 1998:

      The addi­tion of body mass index, phys­i­cal activ­i­ty, cal­cium intake, and alco­hol con­sump­tion to the regres­sion model raised the effect esti­mate slight­ly. The fur­ther addi­tion of vit­a­min D, pro­tein, and caffeine intakes had lit­tle effect on the results.

    • “Tea and coffee con­sump­tion in rela­tion to vit­a­min D and cal­cium lev­els in Saudi ado­les­cents”, Al-Oth­man et al 2012 (em­pha­sis added):

      A total of 330 ran­domly selected Saudi ado­les­cents were includ­ed. Anthro­po­met­rics were recorded and fast­ing blood sam­ples were ana­lyzed for rou­tine analy­sis of fast­ing glu­cose, lipid lev­els, cal­ci­um, albu­min and phos­pho­rous. Fre­quency of coffee and tea intake was not­ed. 25-hy­drox­yvi­t­a­min D lev­els were mea­sured using enzyme-linked immunosor­bent assays…Vi­t­a­min D lev­els were sig­nifi­cantly high­est among those con­sum­ing 9-12 cups of tea/week in all sub­jects (p-value 0.009) inde­pen­dent of age, gen­der, BMI, phys­i­cal activ­ity and sun expo­sure.

    ↩︎
  35. Although there have been large tri­als with the elderly using much higher Vit­a­min D dos­es, such as 4 doses every year of 100,000 IU, or a sin­gle annual dose of up to 300,000 IU with­out observed prob­lems.↩︎

  36. See also Modafinil for other sources & prices↩︎