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 move­ment45; modafinil it­self demon­strates the un­der­ap­pre­ci­ated 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 not6. 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 Amer­ica7, 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 chance8, 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 own9, 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 ad­dic­tion10; 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 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 help­ful11, 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”12, 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 blocks. (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 = 0.138113. 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 im��proved 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 Work­shop14); 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 level15161718), 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 Bon­fer­roni cor­rec­tion (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 sleep19.
  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 -5.5420. (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’21). Ar­modafinil acts much the same way (see the ADS Drug Pro­file) but the modafinil vari­ant fil­tered out are the faster-act­ing mol­e­cules22. 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)23. 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: 60/38/62/44/5024. 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 placebo25.) 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 not26.)

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 se­ries27:

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

    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 ex­per­i­ments28, 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 data29 sug­gests to me a de­cline:

See foot­note for R code

The BEST re­sults30 give a small effect size of -0.26 and only par­tial ex­clu­sion of zero effect size (which a one-tailed two-sam­ple test agrees with31):

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 $3532. 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 Less­Wrong33 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$1002013 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$252013/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 -334 (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 true35.) 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 IU36, 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 Phar­ma­cies37
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.

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  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-blinded vi­t­a­min D on my Zeo sleep data; the lat­ter is novel and in­ter­est­ing.↩︎

  5. I’ve been crit­i­cized for call­ing it “”. But if I am both the ‘sub­ject’ and the ‘ex­per­i­menter’, then blind­ing one per­son blinds both roles, and one ought to just call it “blind­ing”. I be­lieve that “blind­ing” is am­bigu­ous, though: per­haps I am us­ing a friend or room­mate to ran­dom­ize each dose, in which sin­gle-blind­ing case it is not as good as when I “blind” my­self (and achieve a dou­ble-blind). The ter­mi­nol­ogy should re­flect the true qual­ity of each de­sign, and not con­flate sin­gle-blind­ing with dou­ble-blind­ing.↩︎

  6. 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.

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  7. 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?)↩︎

  8. 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.↩︎

  9. 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.

    ↩︎
  10. “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.

    ↩︎
  11. 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.

    ↩︎
  12. 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.

    ↩︎
  13. 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↩︎

  14. 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.↩︎

  15. 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.↩︎

  16. 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?

    ↩︎
  17. 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).
    ↩︎
  18. And in his fol­lowup work, (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).↩︎

  19. 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.↩︎

  20. 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.↩︎

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

  22. 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)

    ↩︎
  23. 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?↩︎

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

  25. “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.

    ↩︎
  26. 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?↩︎

  27. 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

    ↩︎
  28. 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.↩︎

  29. 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")
    ↩︎
  30. 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
    ↩︎
  31. 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
    ↩︎
  32. 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.↩︎

  33. 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.↩︎

  34. 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.)↩︎

  35. 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.

    ↩︎
  36. 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.↩︎

  37. See also Modafinil for other sources & prices↩︎