Maj. Jamie Schwandt, USAR, is a logistics officer and has served as an operations officer, planner and commander. He is certified as a Department of the Army Lean Six Sigma Master Black Belt, certified Red Team Member, and holds a doctorate from Kansas State University. This article represents his own personal views, which are not necessarily those of the Department of the Army.
P.S. Even though Thrive Natural’s Super Brain Renew is the best brain and memory supplement we have found, we would still love to hear about other Brain and Memory Supplements that you have tried! If you have had a great experience with a memory supplement that we did not cover in this article, let us know! E-mail me at : [email protected] We’ll check it out for you and if it looks good, we’ll post it on our site!
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 State-Trait of Anxiety Inventory (STAI) and Profiles of Mood States 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.
The choline-based class of smart drugs play important cognitive roles in memory, attention, and mood regulation. Acetylcholine (ACh) is one of the brain’s primary neurotransmitters, and also vital in the proper functioning of the peripheral nervous system. Studies with rats have shown that certain forms of learning and neural plasticity seem to be impossible in acetylcholine-depleted areas of the brain. This is particularly worth mentioning because (as noted above under the Racetams section), the Racetam class of smart drugs tends to deplete cholines from the brain, so one of the classic “supplement stacks” – chemical supplements that are used together – are Piracetam and Choline Bitartrate. Cholines can also be found in normal food sources, like egg yolks and soybeans.
Prescription smart pills are common psychostimulants that can be purchased and used after receiving a prescription. They are most commonly given to patients diagnosed with ADD or ADHD, as well as narcolepsy. However many healthy people use them as cognitive enhancers due to their proven ability to improve focus, attention, and support the overall process of learning.
Exercise and nutrition also play an important role in neuroplasticity. Many vitamins and ingredients found naturally in food products have been shown to have cognitive enhancing effects. Some of these include vitamins B6 and B12, caffeine, phenethylamine found in chocolate and l-theanine, found in green tea, whose combined effects with caffeine are more extensively researched.
Smart pills have revolutionized the diagnosis of gastrointestinal disorders and could replace conventional diagnostic techniques such as endoscopy. Traditionally, an endoscopy probe is inserted into a patient’s esophagus, and subsequently the upper and lower gastrointestinal tract, for diagnostic purposes. There is a risk of perforation or tearing of the esophageal lining, and the patient faces discomfort during and after the procedure. A smart pill or wireless capsule endoscopy (WCE), however, can easily be swallowed and maneuvered to capture images, and requires minimal patient preparation, such as sedation. The built-in sensors allow the measurement of all fluids and gases in the gut, giving the physician a multidimensional picture of the human body.
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 (Amagami and Voices of a Distant Star) for the rest of the day with occasional reading breaks (eg. to start James C. Scotts 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.
Or in other words, since the standard deviation of my previous self-ratings is 0.75 (see the Weather and my productivity 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.
Weyandt et al. (2009) Large public university undergraduates (N = 390) 7.5% (past 30 days) Highest rated reasons were to perform better on schoolwork, perform better on tests, and focus better in class 21.2% had occasionally been offered by other students; 9.8% occasionally or frequently have purchased from other students; 1.4% had sold to other students
Cognitive control is a broad concept that refers to guidance of cognitive processes in situations where the most natural, automatic, or available action is not necessarily the correct one. Such situations typically evoke a strong inclination to respond but require people to resist responding, or they evoke a strong inclination to carry out one type of action but require a different type of action. The sources of these inclinations that must be overridden are various and include overlearning (e.g., the overlearned tendency to read printed words in the Stroop task), priming by recent practice (e.g., the tendency to respond in the go/no-go task when the majority of the trials are go trials, or the tendency to continue sorting cards according to the previously correct dimension in the Wisconsin Card Sorting Test [WCST]; Grant & Berg, 1948) and perceptual salience (e.g., the tendency to respond to the numerous flanker stimuli as opposed to the single target stimulus in the flanker task). For the sake of inclusiveness, we also consider the results of studies of reward processing in this section, in which the response tendency to be overridden comes from the desire to have the reward immediately.
A big part is that we are finally starting to apply complex systems science to psycho-neuro-pharmacology and a nootropic approach. The neural system is awesomely complex and old-fashioned reductionist science has a really hard time with complexity. Big companies spends hundreds of millions of dollars trying to separate the effects of just a single molecule from placebo – and nootropics invariably show up as “stacks” of many different ingredients (ours, Qualia , currently has 42 separate synergistic nootropics ingredients from alpha GPC to bacopa monnieri and L-theanine). That kind of complex, multi pathway input requires a different methodology to understand well that goes beyond simply what’s put in capsules.

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).
By the end of 2009, at least 25 studies reported surveys of college students’ rates of nonmedical stimulant use. Of the studies using relatively smaller samples, prevalence was, in chronological order, 16.6% (lifetime; Babcock & Byrne, 2000), 35.3% (past year; Low & Gendaszek, 2002), 13.7% (lifetime; Hall, Irwin, Bowman, Frankenberger, & Jewett, 2005), 9.2% (lifetime; Carroll, McLaughlin, & Blake, 2006), and 55% (lifetime, fraternity students only; DeSantis, Noar, & Web, 2009). Of the studies using samples of more than a thousand students, somewhat lower rates of nonmedical stimulant use were found, although the range extends into the same high rates as the small studies: 2.5% (past year, Ritalin only; Teter, McCabe, Boyd, & Guthrie, 2003), 5.4% (past year; McCabe & Boyd, 2005), 4.1% (past year; McCabe, Knight, Teter, & Wechsler, 2005), 11.2% (past year; Shillington, Reed, Lange, Clapp, & Henry, 2006), 5.9% (past year; Teter, McCabe, LaGrange, Cranford, & Boyd, 2006), 16.2% (lifetime; White, Becker-Blease, & Grace-Bishop, 2006), 1.7% (past month; Kaloyanides, McCabe, Cranford, & Teter, 2007), 10.8% (past year; Arria, O’Grady, Caldeira, Vincent, & Wish, 2008); 5.3% (MPH only, lifetime; Du-Pont, Coleman, Bucher, & Wilford, 2008); 34% (lifetime; DeSantis, Webb, & Noar, 2008), 8.9% (lifetime; Rabiner et al., 2009), and 7.5% (past month; Weyandt et al., 2009).
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).
Hall, Irwin, Bowman, Frankenberger, & Jewett (2005) Large public university undergraduates (N = 379) 13.7% (lifetime) 27%: use during finals week; 12%: use when party; 15.4%: use before tests; 14%: believe stimulants have a positive effect on academic achievement in the long run M = 2.06 (SD = 1.19) purchased stimulants from other students; M = 2.81 (SD = 1.40) have been given stimulants by other studentsb
This calculation - reaping only \frac{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.

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.
Methylphenidate – a benzylpiperidine that had cognitive effects (e.g., working memory, episodic memory, and inhibitory control, aspects of attention, and planning latency) in healthy people.[21][22][23] It also may improve task saliency and performance on tedious tasks.[25] At above optimal doses, methylphenidate had off–target effects that decreased learning.[26]
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