Should raw response time data be transformed? I am a statistician and doing some data analysis in cognitive sciences.
I noticed that the distribution of response time (RT) is chisq-squared-like, and I want to do Box-cox transformation to make it look normal distributed. Because before I did not think much for this transform, my question is:

Does a box-cox transformation  need to be applied to response times?
If so, what do the results mean?
For t-test, ANOVA and other tests, will the result be valid for the original response time data?
If not, should we transform the data since analysis of these data is based on the normality hypothesis?

You can transform RT, i.e., by log(1/RT). This makes the distribution roughly normal.  The problem is that you don't usually run the ANOVA on the RT values collected at each trial, but on the average for each participant. So the distribution across participants need to be normal. A trick is to transform the single RT values, calculate the mean for each participant and condition, and then transform the value back with the inverse.

Alternatively, you can run ANOVAs without corrections if you use the appropriate one (i.e., normality not assumed... this will lead to oddly-looking DOF with decimal values).


Why doesn't the brain get into infinite loops when being queried? In computer programming, when algorithms are using loops/recursion without an exit condition, the algorithm will never end or get out of resources.

How does the brain work around getting into endless loops/recursions due to interconnected nets, i.e. when there are circularities in the nets? For example, neuron A activates neuron B which activates C which activates A, and so on. Or are there no circularities in the brain structure?

The brain often does create looping conditions. When these loops involve a large number of neurons, we call it a seizure. An analogy in electrical engineering would be a feedback loop -- such as literal feedback between a microphone and speakers. In the brain, fortunately, these loops are usually self-dissolving since the neurons involved will often run out of neurotransmitter or energy, or inhibitory neurons will get involved (like referees breaking up a fight). Many of the neurotransmitters and hormones in the body act as regulators of ongoing processes. There are almost always negative feedback mechanisms whose purpose is to prevent overload on various systems. The equivalent in programming would be using a counter variable in a while loop to break if it loops too many times.

This all, of course, was with respect to short pathways (small number of links). Larger, more complex pathways such as thoughts and goals are probably handled in part by different mechanisms, such as the instinct of not wanting to waste too much time getting nowhere. At the same time, getting frustrated and rage quitting is a perfect example of hormones and neurotransmitters rising to the point of stopping the loop of trying to do something that is not working as desired.


At what point do multiple personas for social context cross into multiple personalities disorder? Recently I took part in a conversation about the difference between the "many hats" of a successful corporate executive, and "multiple personality disorder." Although humorously bantered, the ideas shared in that conversation shed a light on the fuzziness between when consistent multiplicity of personality characteristics is useful and good (to better adapt to a variety of environments), and when is it counter-productive or self-defeating, and labeled multiple personality disorder? What are the "cross-over" points?

Multi-tasking in executive management positions require being able to speak in the vernacular of many stake holders and to be able to communicate effectively with a wide variety of groups and collaborators. Corporate cultures vary between industries, countries, even regions, and size of the enterprise, etcetera, and yet, a successful corporate executive can walk in any of these with ease. How can the effective use of these "chameleon expressions" be distinguished from split personality?

I use this example tongue in cheek, but Mitt Romney is the perfect example of someone whose personalities clashed in company with one another (fund raiser, 47% vs. 100%). He is a very successful businessman, did his changing faces in the media unravel a persona that didn't really exist?

I think the difference comes down to awareness and control. A person who "wears many hats" and can step into different archetypes is a sort of personality chameleon, whereas a person with dissociative identity disorder has little or no control over changing personalities, and certain personalities within that person may be only partially or completely unaware of other personalities.


Are Pareto charts identified in the cognitive sciences (and for willpower in particular)? I'm a layman when it comes to the cognitive sciences. I've read some number of popular self-help books, but not any academic journals. I've noticed that many times a book suggests some techniques for willpower, anxiety management etc., but will never list them out in a prioritized fashion.

While there might be some variation based on the circumstances and the individuals involved, I feel like a one or a few techniques should always dominate the list. The effectiveness of techniques that deal with different cognitive issues is most likely somwhat geometrically distributed (all else being equal), i.e., most of the time they obey the power law (most techniques are moderately effective, but a few are really effective).

In particular I'm currently interested in effective techniques for willpower. I'm aware of which techniques are recommended (split a task into subtasks, positive self-talk and many more), but what are their relative effectiveness? Are there some well-executed studies out there that determined which techniques work comparatively better?

What are effective and generalizable self-regulatory skills and strategies?

How do their relative efficacy compare?

Regarding reducing one's anxiety, a "meta-analytic review" by Cheng et al. (2014) published in a fairly high-impact venue suggests that coping flexibility is the stuff that matters... when it comes to coping outcomes, of course. (As the joke goes, madness is doing the same thing and expecting different results.) What exactly coping flexibility is isn't so easy to pin down, but apparently some conceptions of that notion are better than others:

  Researchers have conceptualized coping flexibility in diverse ways: as a broad coping repertoire, a well-balanced coping profile, cross-situational variability in strategy deployment, a good strategy–situation fit, or the perceived ability to cope with environmental changes. [...] Studies adopting the perceived ability or strategy–situation fit conceptualization yielded moderate effect sizes, whereas those adopting the broad repertoire, balanced profile, or cross-situational variability conceptualization yielded small effect sizes.

The notion of strategy–situation fit seems largely derived from the CAPS theory. For a more recent (quantitative) work of that kind see e.g. Kato (2012).

The meta-analysis by Cheng et al. also identified a small role played by individualism (and age):

  In addition, the positive link between coping flexibility and psychological adjustment was stronger in samples from countries lower (vs. higher) in individualism and samples with higher (vs. lower) average ages. Individualism and age explained 10% and 13% of the variance, respectively.

(Cheng et al. also conducted a quantitative analysis of publication bias for the set of studies they considered and concluded that "publication bias is not a concern".)

Having said that coping is basically reducing your own stress, which is not the same thing as achieving some externally set goal (e.g. meeting society's expectation in some regard). I'm not sure what research has to say with respect to "willpower" strategies for the latter. Clearly if one considers unreasonable goals in some societies (e.g. eliminating homosexuality) probably no such "willpower" strategy is going to work. It would be more interesting how less incongruent goals fare; from Koestner et al. (2014)

  research has begun to show that support for
  autonomy facilitates goal progress, whereas more directive
  forms of support appear to be less consistently helpful, or even
  unhelpful.

There's a substantial body of work on the effects of goal setting. I'm not incredibly familiar with it, but one highly cited line of work by Locke and Latham (see 2006 update or the Wikipedia page on it) finds that setting high bars is better than "best effort" approaches as far as achievements go.

There's also a substantial body of work on conflicting goals, e.g. see Fishbach and Dhar (2005), but such research doesn't seem to involve ranking strategies. Note that reducing your own anxiety and achieving some externally imposed goal may well be conflicting goals.


Need good example of two domains involving different procedural knowledge yet sharing same high-level strategies Working in the domain of intelligent tutoring systems, I have to prove (or disprove) that explicit teaching of high-level strategies will allow students to use learned strategies across different domains.

I implemented a tutorial system teaching the best way to add a sequence of natural numbers. The procedural knowledge here is being the addition process, and the higher level strategy is choosing the order of the numbers to add. Another tutorial system  implemented is a system teaching the reduction of boolean expressions. The procedural knowledge here is the application of the different boolean reduction rules, and the higher level is the wise choice of the rules to apply to obtain an effective reduction with minimum steps.

Yet these two domains are too different to have the same strategies, unless we use very abstract terms (e.g. "start with the easy parts"). What I desperately seek is two rather simple teachable domains which would be different enough to have different procedural knowledge, yet similar enough to have a set of common explicit strategies. I guess the answer would be in the domain of physics and/or math. I could also examine "fake" domains, i.e., domains that exists solely to prove my point mentioned earlier.

I think "teaching of high-level strategies will allow students to use learned strategies across different domains" is the very rationale of mathematics. Math gives very good examples of both abstract strategies for solving problems across different domains and also specific, explicit strategies. You don't seem to want the abstract strategies, but if you change your mind on that, George Polya's How to Solve It is one of the best books on this topic.

Your other constraint is that the domains should be simple, otherwise differential equations or graph theory would be great examples of explicit solution strategies having applications across multiple domains.

I guess something that will meet your needs well is linear algebra and, in particular, solution strategies for systems of linear equations.


Waking around the same time without an alarm Anecdotal background

I find that regardless of what time I go to bed, or how exhausted I am, I always wake up the next morning between 5 and 6am.  This is despite my alarm being consistently set for 6:15am.  I used to work in an industry, over 15 years ago, where earlier morning starts were part of the job (started work at 6am then), but none quite as drastic since then.  I do not take naps, either.

This happens irrespective of the conditions (temperature, etc).

So, I do not have a fixed time of sleep and it is not necessarily easy to get of bed at that time (some mornings here are very cold).

The question

What are the neurological triggers that cause someone to continually wake up at a set time in the morning, regardless of time of sleep and conditions?

Note - this not a self help question.  I have read the questions and answers for "What defines the easiest time to get out of bed in the morning for humans?" and "How are people able to wake themselves up after a pre-specified amount of time?" and they did not quite have the answers I am after.

Ever wondered why you wake up in the morning—even when the alarm clock isn't making jarring noises? Wonder no more. Researchers at the Salk Institute for Biological Studies have identified a new component of the biological clock, a gene responsible for starting the clock from its restful state every morning.

http://www.salk.edu/news/pressrelease_details.php?press_id=521


How do people estimate smoking's impact on their mortality? I am working on a project that looks at how information about one's health affects smoking decisions. I have an economic background, and not familiar with the psychology literature. So my questions are:

How accurate are people in estimating their mortality risk?
How well can people estimate smoking's impact on their mortality ?
How does the new information about health status change people's belief about their mortality and smoking's impact on their mortality?

"How accurate are people in estimating their mortality risk?" "How well can people estimate smoking's impact on their mortality?" (I grouped these.)

Not accurate at all. One problem with your question is that the accuracy of predicting/estimating risk is difficult to do without the actual outcome: if a smoker predicts he will get cancer, and does develop it, that's 100% accuracy. (See [1] and [2].)

Many studies show that smokers underestimate their relative risk of all smoking-related disorders (including cancer, heart disease, chronic lung infections, etc.) compared to non-smokers. Also, smokers believe they have a lower risk of developing lung cancer than the average smoker. This has been labeled by some as “unrealistic optimism”. [1][2]

  Together, the accumulated data demonstrate convincingly that smokers have a very imperfect understanding of the risks of smoking and of risk statistics in general. Furthermore, regardless of what they may acknowledge about the risks faced by other smokers, they believe that their own risk is less. Given the accumulated evidence, the argument that people begin to smoke or continue to smoke with adequate knowledge of the potential risks appears indefensible. [2]

Smokers do react behaviorally to bad news. In one study of smokers who received annual spiral CT scans x 3, 48% of smokers quit after three abnormal scans; 28.0% quit after two abnormal scans; 24.2% quit after one abnormal scan (compared to 19.8% with no abnormal screens).[3] A larger, later study (the Danish Lung Cancer Screening Trial [DLCST]) confirmed that quit rates were higher and relapse rate lower among subjects with initial CT findings that necessitated a repeat scan 3 months later.[4]

Regarding other forms of "bad news", the effect was less pronounced:

  Of the fifteen included studies, only two detected a significant effect of the intervention. Spirometry combined with an interpretation of the results in terms of 'lung age' had a significant effect in a single good quality trial but the evidence is not optimal. A trial of carotid plaque screening using ultrasound also detected a significant effect, but a second larger study of a similar feedback mechanism did not detect evidence of an effect. Only two pairs of studies were similar enough in terms of recruitment, setting, and intervention to allow meta-analyses; neither of these found evidence of an effect. Mixed quality evidence does not support the hypothesis that other types of biomedical risk assessment increase smoking cessation in comparison to standard treatment. There is insufficient evidence with which to evaluate the hypothesis that multiple types of assessment are more effective than single forms of assessment.[5]

I hope this is enough to get you started.

[1] Smokers’ unrealistic optimism about their risk, N D Weinstein et. al.,
Tob Control 2005;14:55-59 doi:10.1136/tc.2004.008375
[2] Perceived risks of heart disease and cancer among cigarette smokers, Ayanian JZ, JAMA. 1999 Mar 17;281(11):1019-21.
[3] Relation between smoking cessation and receiving results from three annual spiral chest computed tomography scans for lung carcinoma screening, CO Townsend et. al., Cancer. 2005 May 15;103(10):2154-62.
[4] Effect of CT screening on smoking habits at 1-year follow-up in the Danish Lung Cancer Screening Trial (DLCST). Ashraf H et. al., Thorax. 2009 May;64(5):388-92.
[5] Biomedical risk assessment as an aid for smoking cessation. Bize R, et. al., Cochrane Database Syst Rev. 2012 Dec 12;12:CD004705.


Brain's differences in introverts vs. extroverts I know that introverts have a higher sensitivity to dopamine, for example. Are there are other chemical and neuronal differences?

If you are interested in a subfacet of extraversion, i.e. agentic extraversion, a trait covering positive incentive motivation, positive emotionality, and social dominance (among others), I recommend Depue & Collins' paper Neurobiology of the structure of personality: Dopamine, facilitation of incentive motivation, and extraversion, Behavioral and Brain Sciences, 1999, as a starting point.

Furthermore, I'd point to papers such as Wacker, Chavanon, and Stemmler (2006): Investigating the dopaminergic basis of extraversion in humans: a multilevel approach, Journal of personality and social psychology, and related papers, which provide evidence concerning behavioral and electrophysiological indices of agentic extraversion sensitive to pharmacological interventions (DRD2 antagonist sulpiride).

These papers will, however, challenge your statement that introverts are more sensitive to dopamine. Just so you know.

On a more general level and as argued convincingly by Depue & Collins (1999) it is a more fruitful approach to study subfacets of personality traits, rather than broad traits such as broad extraversion. This is imaginable when considering that broad extraversion covers not only positive incentive motivation (likely related to dopaminergic neurotransmission) but also affiliative extraversion (feeling close to others etc., likely mediated by oxytocin). Thus, there is not necessarily an 'extravert' that shows high activity/levels/etc. of this or that specific neurobiological variable such as dopaminergic neurotransmission, because a person might also be considered an extravert (and score high on, let's say the Big Five Inventory Extraversion scale when experiencing tight bonds and affection for others, while he or she is not very agentically extraverted. However, it is more likely that you will measure certain levels of a specific neurobiological variable (such as dopamine-related measures) when studying a more specific and less "fuzzy" trait (such as agentic extraversion).


Is learning facts via audio while sleeping possible? Is there a way to make onself remember facts from an audiobook (containing for instance a list of countries and their capitals) played out loud while sleeping?

Theoretical perspective:
No. I don't think so. From a cognitive information processing perspective, I would hypothesise that declarative learning of new facts would not occur while sleeping. Of course, learning declarative facts while awake, but in bed (e.g., when going to sleep or when waking up in the morning) is possible, and sleep is important in consolidating what is learnt during the day.
I don't think the mind is capable of the kinds of information processing required to process facts when asleep.

Empirical perspective:
Nonetheless, my theoretical perspective above may be wrong, so it is worth while looking at the empirical evidence. I found an early review of research in Simon and Emmons (1955). The study critically evaluates 10 or so studies on sleep learning and suggests that each of them suffers from some form of methodological weakness.

Wood et al (1992) provide a more recent summary of the literature:

  When a distinguished committee of the National Research Council (NRC)
  recently concluded that sleep learning deserves a "second look" from
  experimenters (Druckman & Swets, 1988; Swets & Bjork, 1990). a
  distinguished sleep researcher swiftly and pungently disagreed (Webb,
  1990). This controversy is not new to the field of sleep learning.
  Disagreement has been common since the mid-1950s, when Simon and
  Emmons (1955. 1956) severely criticized the methodology of existing
  studies and demonstrated that recall and recognition for verbal
  material presented during sleep do not occur when proper experimental
  controls are exercised.

  Although the views of Simon and Emmons were
  generally accepted, in ensuing years some empirical studies continued
  to report evidence of learning for verba! information presented during
  sleep (see reviews by Aarons. 1976; Eich, 1990; Hoskovec, 1966).
  Though subject to methodological criticism, their findings were
  buttressed by evidence from electroencephalographic and evoked
  potential studies that (a) transmission of auditory information to the primary auditory cortex is not different during sleep and the waking state, (b) habituation
  and conditioning can occur during sleep in both nonhuman animals and
  humans, and (c) some transfer of information to long-term memory
  occurs during sleep (see review by Wood, 1990). Furthermore, recent
  studies have suggested the existence of a cognitive unconscious
  (Kihistrom. 1987) and indicated that information processed outside of
  conscious awareness, for example, while under anesthesia (Kihistrom,
  Schacter, Cork, Hurt, & Behr, 1990), can be stored in memory and exert
  an influence on later performance. In addition, research with both
  amnesic and normal subjects has demonstrated the existence of implicit
  memory, that is, learning that does not require deliberate or
  conscious recollection of experience (see reviews by
  Richardson-Klavehn & Bjork. 1988, and Schacter, 1987).

Specifically, it appears that in their study Wood et al (1992) did not find any effect:

  This study examined implicit memory for words presented during sleep.
  Ten experimental subjects were presented with word pairs including a
  homophone and a close associate (e.g., “tortoise-hare”) and with
  category-instance pairs (e.g., “bird-cardinal”) during REM or Stage 2
  sleep and tested immediately afterward. Twelve control subjects
  underwent the same procedure while awake. Unlike the controls,
  subjects in the sleeping condition showed no learning effects on the
  implicit memory tasks. Recall and recognition were observed in a few
  cases, but only when presentation was immediately followed by arousal.

References

Simon, C. W., & Emmons, W. H. (1955). LEARNING DURING SI. EEP?. LEARNING, 52(4), 1055. PDF
Wood, J. M., Bootzin, R. R., Kihlstrom, J. F., & Schacter, D. L. (1992). Implicit and explicit memory for verbal information presented during sleep. Psychological Science, 3(4), 236-239.


What is our higher self? Some religious or philosophical systems hold that there is an immaterial divine component to human existence, like the Soul or the Higher Self.

Is there any kind of scientific evidence that such a supernatural essence of the person exists, and if so, can it be located in a specific part of the brain?

Wikipedia's answer is a better answer than I could offer as to what the higher self is, because that's all you've used to define it, and as Wikipedia says, it's "a term associated with multiple belief systems," and probably differs rather widely across the gamut. Regardless of how odd some of those beliefs might get, it probably shouldn't be synonymous with the prefrontal neocortex or basal ganglia, each of which has multiple functions that couldn't simply be equated to what most people mean when they say "higher self."

In one aspect at least, there may be some overlap between the "higher self" concept and the prefrontal cortex. To whatever extent "higher self" means "self-awareness," the prefrontal cortex is probably involved in that...This article offers an interesting image from magnetic resonance tomography, and these quotes [emphasis added]:

  A specific cortical network consisting of the right dorsolateral prefrontal cortex, the frontopolar regions and the precuneus is...associated with self-reflective functions...

  By comparing the activity of the brain during...lucid periods with the activity measured immediately before in a normal dream, the scientists were able to identify the characteristic brain activities of lucid awareness.

So note that this is self-awareness in the context of dreaming. The original article (Dresler et al., 2012) is free, and mentions an interesting method for distinguishing lucid from normal dreaming, BTW. As for consciousness in general, we have some pretty interesting questions with richly informative answers here already, including:

What are current neuronal explanations and models of 'consciousness'?
Is there a region of cortex which over a period of development becomes the seat of self?
Research suggesting conscious control over brain region activation?
If someone becomes a split-brain patient, which side will "maintain" the continuity in their consciousness?

And as for the subconscious, Wikipedia again gives a pretty decent answer. Since the term is frequently misattributed to psychoanalysis, and may be most popular in pseudoscientific contexts, I prefer to point you directly to the section on Freud's answer and advocate his general practice of avoiding the term altogether (except for the sake of criticizing it). Freud used "preconscious" and "unconscious" in distinct ways that cognitive psychology has adopted somewhat as well, so those terms are generally much more useful and well-defined scientifically...though that's not saying all that much. However, thanks to @ArtemKaznatcheev, we also have a question here that says a little more: Subconscious vs Unconscious

Reference

Dresler, M., Wehrle, R., Spoormaker, V. I., Koch, S. P., Holsboer, F., Steiger, A., Obrig, H., Sämann, P. G., & Czisch, M. (2012). Neural correlates of dream lucidity obtained from contrasting lucid versus non-lucid REM sleep: A combined EEG/fMRI case study. Sleep, 35(7), 1017-1020. Available online, URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3369221/. Retrieved January 25, 2014.


Flashforward moments I've heard someone describe having what he calls "flashforwards": Moments he lives through which he feels like he remembers from before - on some occasions in situations he definitely did not see before. Is there any hard evidence on this or a name for the phenomenon? Is this some elaborate kind of self-deception?

Déjà vu seems to match what you describe.
There are various possible explanations though they are a bit difficult to test since you can't readily activate the feeling in a lab setting. One of them is the idea that in the process of encoding a memory of the event it is simultaneously and erroneously "recalled".


Can we increase our higher order thinking (HOT) skills by practicing inductive reasoning? I previously asked about the conceptual links between higher order thinking and inductive reasoning. This question focuses on the potential for improving higher order thinking through practicing inductive reasoning tasks.

For instances, in order to become a good dancer, one must exercise leg muscles, improve coordination, learn how to breathe and so on. Is their an analogy with acquiring higher order thinking skills?

If so, where can one find the main literature on how this process works?

This is more of a comment than an answer. In fact it's more of an advice.

Higher-order thinking and inductive reasoning have rather vague definitions, in my mind. They seem to also come from different backgrounds. If you don't mind, I think it's easier to approach your situation rather than your question. You might find it refreshing to think of higher-order thinking as a phenomena that occurs under certain conditions; in addition to thinking of it as a muscle (which is implied by your question). Specifically, if you look at higher-order thinking, as you call it, as a state to be entered into, some of the greater facilitators are ability to relax and to change perspectives effectively with emphasis on relaxation. This is within the scope of neurolinguistics, if you'd prefer a contemporary approach; if you don't mind going old school with this, more or less any meditation, should lead to noticeable improvements or autogenic training might float your boat.

I hope this is helpful. I regret not providing any references. Edits are welcome.


How to determine nerve conduction velocity? Can anyone suggest good sources or papers to understand about experimental setup and procedure for measuring nerve conduction velocity for various types of neurons?
I wish to learn how such experiments are done and get insight on how they were able to classify neurons based on conduction velocities as (alpha beta gamma) or I / II / III grade neurons especially for neurons that have small distances between axon and dendrites for it might be difficult to insert probes at cell body and measure signal at the synapse of that neuron to measure time elapsed in signal conduction or they measure for few neurons in chain and average out the time taken for conduction velocity.

I think there are many ways to accomplish this in terms of technical detail, but they will all boil down to measuring the arrival of an action potential along the axon on at least two points with known distance from each other on the axon. From these two arrival times the latency can be deducted. Then, by dividing the distance between the elektrodes by the latency (i.e., the time it took the action potential from going from electrode 1 to number 2), the conduction speed can be estimated. In a paper by DeMaegd et al. (2017) they use extracellular electrodes and the figure in their paper is quite informative (Fig.1 ).

Fig. 1. Measuring axon conduction velocity by recording action potentials. source: DeMaegd et al. (2017)
Reference
- DeMaegd et al., Bio Protocol (2017); 7(5)


When does the brain stem appear in humans? When does the brain stem appear in humans?

The following article states:

  Once the neural tube closes, at around week 6 or week 7 of pregnancy,
  it curves and bulges into three sections, commonly known as the
  forebrain, midbrain and hindbrain. Just to the rear of the hindbrain
  sits the part that will soon turn into your baby's spinal cord. Soon,
  these areas bubble into those five different regions of the brain that
  we're most familiar with: the cerebrum, cerebellum, brain stem,
  pituitary gland and the hypothalamus.

How "soon" after 6 - 7 weeks is this soon the article talks about? When does the brain stem appear in humans?

Fetal Brain Development

I'm not sure this question is answerable at that specificity. There isn't a discrete point in time where the cells are definitively a brain stem rather than a precursor structure such the bulge mentioned above. One could identify a set of a cells in earlier structures that eventually are located in the adult area we call the brain stem, but that doesn't mean at the point those cells are identifiable that they are IN the brain stem during development.


What is the linguistic equivalent of functional fixedness? Recently, I saw a crossword clue: (5 letters) "They help you after a crash." After going through the list of EMTs, firemen, police officers, etc. I realized that the answer was "IT Guy." This seems to me, to be analogous to the phenomenon of functional fixedness, and I was wondering if there is some linguistic equivalent to functional fixedness?

I'm not sure whether this can explain your crossword experience, but perseveration is a fairly well-studied phenomenon in word production. Individuals with aphasia (a neurogenic language disorder) often exhibit perseveration errors in tasks like picture naming. For example, imagine trial N is a picture of a dog and the participant responds "dog" (correct) and trial N+1 is a picture of a car and the participant again responds "dog" (perseveration error). Stark (2007) provides a good historical review of theories of perseveration in aphasia, which generally propose either failure to inhibit the representation of the previous response or failure to sufficiently activate the representation of the new stimulus (and it is possible that both can happen: Fischer-Baum & Rapp, 2012). Like other speech errors, perseveration errors are also produced by typical (non-aphasic) adults, just much less frequently than in aphasia.

More general kinds of perseveration - inability to stop focusing on a particular topic - are associated with deficits of executive function (possibly related to frontal lobe dysfunction or damage) and a variety of psychopathologies, such as depression.

References:

Fischer-Baum, S., & Rapp, B. (2012). Underlying cause(s) of letter perseveration errors. Neuropsychologia, 50(2), 305–318. doi:10.1016/j.neuropsychologia.2011.12.001

Stark, J. (2007). A review of classical accounts of verbal perseveration and their modern‐day relevance. Aphasiology, 21(10-11), 928–959. doi:10.1080/02687030701198239


Clarification on the definition of sublimation? I'm reading the wikipedia article on sublimation. The article says:

  In psychology, sublimation is a mature type of defense mechanism where socially unacceptable impulses or idealizations are consciously transformed into socially acceptable actions or behavior, possibly resulting in a long-term conversion of the initial impulse.

But it's not clear to me how these impulses are transformed. Are these impulses transformed inside the mind of the one who do them or are they transformed in a social level (via persuasion)?

Rephrasing the question: Does him argue with himself and make himself believe that the unacceptable behavior is actually a good thing or succeeds to persuade others to believe that behavior is a good thing?

Sublimation is a term from psychoanalytic theory. In short, the internatlized norms - the so-called Super-Ego - directs the drives to outlets that are free of guilt or shame. The whole process takes place inside the individual, and in fact the norms that individual has internalized (in his childhood) need not be identical to the norms that the adult person is surrounded by.


Is it really impossible for a hypnotist to make a participant do something against their will? Is there any evidence of a hypnotist making someone do something against their will while in a hypnotic state?

I know there are many sites by practicioners that state it is impossible, but they have a vested interest in making their potential patients feel safe.

This question cannot be answered empirically.

  Thus, a refusal to carry out antisocial actions can be ascribed to insufficient depth of hypnosis (or inadequate hypnotic technique), while the behavior of S[ubject]s who comply can be explained by asserting that the action merely represents what they would have done anyway. (Orne, 1972)

Sources:

Orne, M. T. (1972). Can a hypnotized subject be compelled to carry out otherwise unacceptable behavior? A discussion. International Journal of Clinical and Experimental Hypnosis, 20(2), 101-117.


Is hypnosis really concentration/focus? It's widely claimed that hypnosis is a state of highly focused attention.

But I've also seen many claims that the hypnotic state is about accessing the subconscious mind directly, essentially "bypassing" consciousness.

However there lies a dissonance; all the material I ever read about focus (mostly from Daniel Goleman and Leonard Mlodinow) indicates that focus is a conscious phenomenon.

Can anyone please clarify?

The answer lies in what is known of the conscious, unconscious and the presconscious parts of the mind, with preconscious is the scientific name for the subconscious, however, for the purposes of this answer and because of how the theory of hypnosis is put together, I will refer to the preconscious as the subconscious.

When I was learning about the basis of hypnosis in formal training, I was taught to visualise the mind as the following diagram

Image: CCF diagram from my training notes - the "memories and belief system" part of the diagram is the subconscious part of the mind.  The CCF (the orange part of the diagram) is the filter between the conscious and subconscious parts of the brain. It compares a new situation with our memories, belief system and morals.

Formation of our beliefs and morals

Internal and external influences form our belief system which is stored in our subconscious mind.  External influences involve things within our environment.  Internal influences involve things we ‘know’ to be true.  I said ‘know’ because what we believe to be true and what is actually true, correlates with the things we have learnt during our lives.  Our belief systems are built from the moment we are born.  Our external influences such as what we have seen, touched, tasted, smelt and heard, help us to learn things whilst a baby.  Listening to words and speech patterns from our parents help us to learn our language including names for objects.

As we get older and start to be able to wander around and explore our environment our parents tell us things such as “Don’t touch that it’s hot” or “Don’t eat that or you will be ill”.  We were told that the grass is green and the sky is blue.  Cultural influences start playing a role too such as the idea that pink is a girls colour and blue is for boys, Barbie dolls are for girls and action men are for boys.  We took those ideas on as literal truth.

As we got older, experiences begin to confirm some of those ideas.  Some got hurt by the heat of a cup of tea.  Some got ill from trying the berries we were told not to eat. In these ways we had a model of the world confirmed and constructed.

Some of those beliefs were absolutely correct, we tested the ideas and had them confirmed by outside sources. Some beliefs may have been left untested but nevertheless all the beliefs in turn developed what many call the, Conscious Critical Faculty (CCF) (Watts, n.d.).

The CCF (the orange part of the diagram) is the filter between the conscious and subconscious parts of the brain. It compares a new situation with our memories and belief system and morals.  Everything stored in the subconscious is essential for your survival.  If the CCF encounters something which goes against the belief systems or morals, stored in the subconscious, it throws the idea out and the belief systems remains intact and life can continue.

But what if there are falsehoods stored in the belief system?  Phobias can develop and other damaging effects can take place.  This part of the belief system can be built by other people who are unfortunately basing their information on their own belief systems.  These in turn were given to them by people who formed their own belief systems.  What can we do about this?

Take a situation where comments from adults, taught someone when they are a child, that they are selfish, unattractive or lacking intelligence.  Once these ideas have taken hold it is very difficult to try and change these beliefs at a conscious level and remove them from the subconscious mind as the CCF will take over and reject opposing beliefs.  This can be damaging to the confidence and opportunities in that persons adult life.  This is why it’s so easy to give advice but so difficult for some others to take it even when you know it is correct.  For a more effective way of doing this, we need to bypass the Conscious Critical Faculty in order for the correct belief system to be accepted.

There are a number of ways that new information can be pushed past the CCF. (Burns, 2009)

They include:

Repetition
Shock
Hypnosis

Repetition

Selfishness and altruism, attractiveness and unattractiveness, intelligence and lack of intelligence etc. taught as a child or later instilled in adult life is often a result of repetitive comments.  The same goes for trust and distrust in certain people or animals.  How this happens is for example:-

A belief that no man can be trusted is put to you on a repetitive basis
This is usually backed up by other people’s actions.  Maybe a man disappointed you in the past
The concept or belief becomes part of your belief system because no one in your circle of friends can give you an opposing concept or belief to compare it to
This in turn affects the way you act towards men
This then causes some men to react in a way which can be perceived to reinforce your belief

Repetitive affirmations and confirmations over time can rectify falsehoods in belief systems.

Shock

Shock that someone may experience as a result of a traffic accident for example, can induce unhesitating acceptance of thoughts and beliefs. (Burns, 2009)  If the thought is given where someone says “that looks bad, I bet that hurts” then of course they will become extremely aware of the pain and in turn may develop a severe aversion to getting into a car again.  Other traumas can have similar effects.

If you look at someone suffering from the trauma of war, rape or sexual assault, this trauma will lodge the memory of what happened straight in the subconscious and develop either conflicting belief systems which cause more problems, or immediately alter the belief system completely.  Counselling sessions can dredge up those painful memories and the resulting shock induced can open the client to opposing thoughts and beliefs which can help to correct the faulty belief system.

Hypnosis

Hypnosis is a natural state of mind where acceptable selective thinking is established, concentration is enhanced and the Conscious Critical Factor is bypassed, opening the subconscious mind to suggestion.  With the subconscious mind open to suggestion without interference by the CCF, therapy will be able to work more quickly (Watts, n.d.) by installing correcting belief systems.

The hypnotic state can be induced by reading, carrying out a repetitive task or listening to a hypnotherapist’s hypnotic induction routine.  Watching television can induce a hypnotic state which helps to explain how effective on-screen advertising can be.

References

Burns, J., 2009. Beating the barriers to making life changes. [Online]
Available at: http://www.somersethypnotherapy.com/articles-by-John-Burns/beating-barriers-to-change.pdf

Watts, T., n.d. *The Conscious Critical Faculty. [Online]
Available at: http://www.selfhypnosis.com/the-conscious-critical-faculty


Is it common for OCD sufferers to experience schizophrenic episodes So I was sleeping on a road trip and I had to wake up to go to the restroom at a gas station we stopped at. I walked in like a zombie and the cashier sheepishly said hello to me. I took it that he was nervous and then my brain started coming up with some scenario that he was being held hostage by someone, told not to call the police and was somewhere in the store. As I was going to the restroom I sort of convinced myself that this was actually happening and I started to get kind of nervous. Later I realized that the only reason the cashier seemed nervous was because I walked in like I had just risen from the dead. Which got me worried again thinking I'm starting to develop some form of schizophrenia. I'm 16 years old and have been diagnosed with OCD in the past. I know this is a better question for a professional but I figured this would give me a quick reassurance for concern or if that was just an ocd sort of thing. I will be talking to a doctor and my parents afterward I just trust stack exchange's opinion for now. Thank you

As someone who has had OCD since the age of 12, I can assure that this sounds very much like an OCD symptom. It is likely that you walked into the store "like a zombie", and at the time, did not consider your personal appearance, assuming only that the store owner was acting strange. However, if you had been aware of the way you were acting, you would have likely picked up on this instantly and dismissed it. Unless we are salient to our own features, we are unaware of how others are perceiving us. Your ability to gauge your salience was likely decreased due to just waking up from your nap.

As an OCD sufferer, I've definitely had bouts where I was concerned I was developing schizophrenia, only to realize later that I was hyper-aware of every little "sign" that pointed in that direction. If this is an ongoing worry of yours, confirmation bias will likely amplify the most ambiguous of symptoms related to losing your mind.

Let's get a little further into schizophrenia, however. The Diagnostic and Statistical Manual - IV (yes, the old one, though the symptoms have not changed much) states:

  Characteristic symptoms:

  Two or more of the following, each present for much of the time during a one->month period (or less, if symptoms remitted with treatment).

  Delusions
  Hallucinations
  Disorganized speech, which is a manifestation of formal thought disorder
  Grossly disorganized behavior (e.g. dressing inappropriately, crying
  frequently) or catatonic behavior

  Negative symptoms:

  Blunted affect (lack or decline in emotional response)
  Alogia (lack or decline in speech)
  Avolition (lack or decline in motivation)
  Imapaired communication (due to hearing voices)
  Social or occupational dysfunction: one or more major areas of functioning, work, interpersonal relations, self-care, are markedly below the level achieved prior to the onset.

  Significant duration: Continuous signs of the disturbance persist for at least six months. This six-month period must include at least one month of symptoms (or less, if symptoms remitted with treatment).

  If signs of disturbance are present for more than a month but less than six months, the diagnosis of schizophreniform disorder is applied. Psychotic symptoms lasting less than a month may be diagnosed as brief psychotic disorder, and various conditions may be classed as psychotic disorder not otherwise specified.

First and foremost hallucinations and delusions are NOT something that you are able to identify. Schizophrenia leaves the sufferer out of touch with reality. The sufferer believes in their hallucinations and delusions with every fibre of their body, they don't simply think that they are hallucination or becoming deluded. That being said, no, you are not developing schizophrenia. If you were, you wouldn't know it, and once you found out that you had it, you'd be the last one to know.

Note "positive" and "negative" symptoms, are not "good" and "bad". Think of a positive symptom as an addition to one's life (the addition of delusions), and a negative symptom as something that's being taken away from one's life (motivation). If you read further down the DSM criteria, you will see that "one-off" events like this do not substantiate a diagnosis of schizophrenia. However, a brief psychotic episode is still possible, possible, but extremely highly unlikely based on the fact that you have a great amount of insight (self-knowledge) of what was going on with you in the store.


What explains the characteristics of the receptive fields of simple cells in V1? Here is a YouTube video of a Hubel & Wiesel experiment from 1965 in the visual cortex. The video shows the experimenters outlining the receptive field of a simple cell in the first part of the video using symbols. Crosses are used for excitatory responses, and triangles for inhibitory responses.

As shown in the video, neuron firing rate increased when the edge of a bar of light touched the crosses present on the top left. It is not just the orientation and location of light bar, but it seems that the light bar's edge is defining the firing rate, and thus determines the receptive field. So, the oriented receptive field of the cell seems to be defined w.r.t to the stimulus edges, rather than the bright and dark regions stimulating the on-center and off-surround parts of the receptive field. It seems that the simple cell was getting triggered when the edge of the light bar touched the three lines made by cross marks and triangles in that particular orientation. So, the cell under consideration was responding to edges at three separate locations.

Is my understanding correct ? Please help me in understanding how oriented receptive fields made up with center-surround concept explain the excitation at the edge observed. Perhaps it can be seen as the derivative of a box-like receptive field, or an oriented receptive field.

The retinal ganglion cells (RGCs) and the neurons in the upstream lateral geniculate nucleus (LGN) both have relatively simple receptive fields that are organized in in a center-surround fashion (Fig. 1).

Fig. 1. Center-surround receptive field in a retinal ganglion cell. source: Pinterest

In the primary visual cortex, the simple cells receive inputs from multiple LGN neurons (Fig. 2). By combining these inputs and aligning them with multiple ON-centers and OFF-surrounds in series (or vice versa) orientation-selectivity is accomplished in V1. The video you linked corresponds to Fig. 2C:

Multiple ON-centers are linearly aligned and
The ON-centers are sandwiched between linear arrays of OFF-surrounds.

This means that

The simple cell will respond maximally when the ON-centers are illuminated and the OFF-surrounds are not (first minute video clip);
The cell will not respond when the OFF surrounds are illuminated (1:20 point in clip), regardless whether the ON-centers are illuminated or not; the stimulation of the entire ON-center and OFF-center area results in zero activity (2:30 in clip).
A stimulus oriented obliquely to the RF also results in zero-activity, because the ON and OFF parts are both stimulated (1:50).

Fig. 2. Diagrams of simple cell receptive fields in primary visual cortex. source: Stanford


How are autistic savants able to perform certain mathematical computations so quickly? How do autistic savants (or other people with these abilities) compute equations like $81^{100}$ in 2.5 minutes?
Which algorithms do they use? Is it an efficient one, or do they just have a lot of memory?
Can non-autistic savants use these algorithms to solve equations just as quickly?

Here's the Wikipedia page on that:

  Savant syndrome is poorly understood. No widely accepted cognitive theory explains the combination of talent and deficit found in savants.
  It has been suggested that individuals with autism are biased towards detail-focused processing and that this cognitive style predisposes both individuals with and without autism to savant talents.

  Another hypothesis is that hyper-systemizing predisposes people to show talent, where hyper-systemizing is an extreme state in the empathizing–systemizing theory that classifies people based on their skills in empathizing with others versus systemizing facts about the external world, and that the attention to detail shown by many savants is a consequence of enhanced perception or sensory hypersensitivity in individuals with autism.

  It has also been suggested that savants operate by directly accessing low-level, less-processed information that exists in all human brains but is normally not available to conscious awareness.


A psychological theory that explains why people remember only the outcome? I've read somewhere about a psychological theory that people often remember the end results or the outcome of a certain situation/discussion/conversation/etc, but not the details of it.

In other words, the theory postulates that people often forget about things like who invented the solution, or how this happened, or who should be doing this task. Rather, people tend to just remember what the solution was, what happened, and what task had to be done.

I don't remember exactly in what context I read about this theory. It could have been part of some other theory.

Does such a theory exist? If so, what is the name of that theory?

I'm not sure about the problem-solution context, but there is the fairly well-studied "peak-end" phenomenon in which people appear most sensitive to the strongest and/or the final levels of positive or negative experiences in an episode. Daniel Kahneman has done a lot of work on this phenomenon, you can find a list of his papers on his website. A fairly simple demonstration is in this article:

Kahneman, D., Fredrickson, D.L., Schreiber , C.A. , & Redelemeier, D.A. (1993). When more pain is preferred to less: Adding a better end. Psychological Science, 4(6), 401-405.


Can General Assessment of Functioning (GAF) be used to measure recovery etc. from all mental health problems? Can General Assessment of Functioning (GAF) be used to measure recovery etc. from all mental health problems?

I know it's used with 'schizophrenia', but what about things like personality disorders, Dissociative Identity Disorder, etc.?

Yes, the General Assessment of Functioning (GAF) score can be used for all psychiatric disorders.

The GAF is not commonly used now as the DSM V has opted for the WHODAS 2.0 instead of GAF. There were fundamental problems with GAF including poor reliability with people who were less trained, cross-cultural variations and symptom severity tended to influence symptom scoring instead of functional impairment (Gold, 2014). The DSM V also commented on their concerns -

  We do not believe that a single score from a global assessment, such as the GAF,
  conveys information to adequately assess each of these components, which are likely to vary independently over time. Further, we are concerned about evidence that the GAF requires specific training for proper use, and that good reliability and prediction of outcomes in routine clinical practice may depend on such training
  (APA, 2013).

References:

American Psychiatric Association. (2013). Insurance Implications of DSM 5. In Diagnostic and statistical manual of mental disorders (5th ed.).

Gold, L. H. (2014). DSM-5 and the Assessment of Functioning: The World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0). Journal of the American Academy of Psychiatry and the Law Online, 42(2), 173–181.


Is the Neanderthal Theory of Autistic brain a reasonable scientific theory? I've recently learned about The Neanderthal Theory, that explains autistic (and especially Asperger's) brain functioning as the effect of genetical similarity with Neanderthals.

The author gives a great number of examples of differences between modern and Neanderthal human, that in the same fact are strongly correlated to differences between neurotypical and autistic brain. Most of them greatly applies to me, which biases me towards accepting that theory:

Neanderthals have less developed social life, so their social skills were less developed too, so are the social skills of autistic people
most primates avoid eye contact as the sign of aggression, modern humans (neurotypicals) are the exception, both Neanderthals and autists are not
Neanderthals have bigger brains, and the proportion of brain size to body size was bigger, that could mean they were more intelligent, people with Asperger Syndrom are typically more intelligent than neurotypicals
by Neanderthals women were dominating and were taking sexual initiative, autistic people find it especially difficult to adapt to sexual model of neurotypicals, where males are sexually dominant, increased tendency to behaviours such as exhibitiosm can also be explained by neanderthal genes, since among Neanderthals such behaviours were actually accepted as normal and dominant
Neanderthals were meat-eaters (for me meat is the best diet)
Neanderthals prefer cold to heat (I like when it's cold and hate when it's hot)

This all makes sense, however, I'm aware, that it's quite easy to find a theory that will exactly match the known facts, so each theory must be proven by new facts and experiments. So I ask for any facts and scientific articles that would either support or reject that theory.

I don't know if it's a reasonable scientific theory, but here's some more info:

Autism: The Eusocial Hominid Hypothesis

ASDs (autism spectrum disorders) are hypothesized as one of many adaptive human cognitive variations that have been maintained in modern populations via multiple genetic and epigenetic mechanisms. Introgression from "archaic" hominids (adapted for less demanding social environments) is conjectured as the source of initial intraspecific heterogeneity because strict inclusive fitness does not adequately model the evolution of distinct, copy-number sensitive phenotypes within a freely reproducing population.

Evidence is given of divergent encephalization and brain organization in the Neanderthal (including a ~1520 cc cranial capacity, larger than that of modern humans) to explain the origin of the autism subgroup characterized by abnormal brain growth.

Autism and immune dysfunction are frequently comorbid. This supports an admixture model in light of the recent discovery that MHC alleles (genes linked to immune function, mate selection, neuronal "pruning," etc.) found in most modern human populations come from "archaic" hominids.

Mitochondrial dysfunction, differential fetal androgen exposure, lung abnormalities, and hypomethylation/CNV due to hybridization are also presented as evidence.

A short video introduction


Is Behaviorism a type of Functionalism? Behaviorism separates itself from other psychological views in that it doesn't care about the psyche.  Rather, it focuses on how the mind behaves, how outside factors can manipulate it, and so on.

Given this, I'm led to believe it is a form of functionalism.  Both don't seem to care about what the mind really is deep down, and they focus more on the practical results that can be achieved.  Is this correct?

If take a look at the Wikipedia article @Fizz provided in the comments, it does say that Functionalism is different to Behaviourism

  because it is only concerned with the effective functions of the brain, through its organization or its "software programs".

The full explanation of why it is different is that Behaviourism is

  a systematic approach to understanding the behavior of humans and other animals. It assumes that all behaviors are either reflexes produced by a response to certain stimuli in the environment, or a consequence of that individual's history, including especially reinforcement and punishment, together with the individual's current motivational state and controlling stimuli.

In other words it looks at how people's current and past experiences affect the person's mood and behaviours.

Functionalism states that

  mental states (beliefs, desires, being in pain, etc.) are constituted solely by their functional role – that is, they have causal relations to other mental states, numerous sensory inputs, and behavioral outputs.

Comparing the human brain to the computer whilst trying to explain this philosophy, the Wikipedia article points out that

  brains are physical devices with neural substrate that perform computations on inputs which produce behaviors.

Where Behaviourism just looks at the initial stimuli and resulting behaviours, Functionalism looks at the brain functions and tries to explain how behaviours manifest themselves in reaction to the information the brain receives.


How does fever affect time perception? Many of my friends and I have noticed that at certain stages of fever, time is often perceived as being longer than usual. I'd like to know if this is caused by the disease itself, an immune reaction, or high body temperature.

Fun fact: a lot of gamers I know have told me that their performance in first person shooter games increases while they have fever. I also noticed that works for me and as far as a ill person's judgment goes, I think that fever disrupts prolonged concentration on a single task, which makes it easier to interchange current objectives (like from "going there" to "defending from that guy out of nowhere" almost instantly). I'd like to know if it's true and if it is related to fever at all.

Experiments reported in the article "Feeling the heat: body temperature and the rate of subjective time, revisited." (Weardon and Penton-Voak, 1995) observed that in many cases the rate of subjective time increased with increased body temperature.  They suggest that a possible mechanism being that body temperature change also results in a change in arousal state.


Why can't we learn what we don't like? The school system as we know it, is & has been shaping students to fit the system which they live in and throughout this process, the students are forced to learn(mostly memorize) subjects which they do not have any interest in whatsoever and because of this they can't score high in school. It is as if our brains are trying to avoid information, which is out of interest, as much as possible. But when there's something in interest it is damn easy to collect and comprehend that information.

Let's assume that you are a programmer and you are greatly amazed by that, you love solving problems and develop software, you read lots of documentations and contribute on other peoples projects without even having to worry about "remembering" what you're reading, everything is easily understood and there's no issue with that. But when you have to learn about politics and how the system works, it appears as cancer to your eyes because you have no interest in it, there's no will to collect that information and therefore you score low in that subject.

now my question is: Why can't we learn what we don't like? (what we're not interested in?)

1
There is some relation between what we are interested in and what we are good at. If people are bad at something, they usually lose interest in it and turn to other things. If you are good at something, you enjoy doing it and are interested in it.
Interest, therefore, is a preditor of ability, and you are better at learning things that you can do, than you are at learning things that you cannot learn to do.
2
Learning requires time, attention, and effort. If you are interested in something, you will (want to) spend more time, attention, and effort on it. If you aren't interested in something, you'll find every minute of it unpleasant, so you will limit the time you spend with it, not be as attentive, and not labour as hard.
You will also not think about it while you are not learning, you won't connect it to other interests and activities, and so on. In short, you won't elaborate.
There is a psychological theory, the elaboration likelihood model, that says that the processing of information will be more superficial when the motivation to process the information is low.
3
Doing something interesting is pleasurable, and everything in your mind and body works better if you are in a good mood. Hormones such as oxytocin, whose levels are higher when you are "happy" (and free of negative stress), have a positive effect on memory formation and retention.


Problems with parameterizing neuronal simulation on a limited number of datasets I'm hoping to contribute to the OpenWorm project by helping their efforts to parameterize the neurons in CElegans so the model elicits biologically realistic behavior.

The problem is I've got only five activity series datasets for all neurons in CE and I fear whatever model is trained on these datasets won't be an accurate model of the full space of neural activity in CElegans.

Can you give some ideas as to how the field works around this and where I can read about what methods are used to resolve this issue?

Because of variation between organisms, cells in the same organism, or even the same cell separated by a few days, can have different parameter set. However, I think this is where parameter fitting becomes useful. As suggested in the comments knowing how parameters change between cells or over time can be very insightful. Parameter Estimation is very important because it allows us gather more information about the parameter set from less experimental data and thus allowing more complex experiments.

Philosophy aside, here are some tips for getting into the field. I'd suggest reading this open access article by Van Giet et al. here and I'll give a brief review of their article.

General Model
First one needs a general framework to work within,

What is your type of neuron model going to be?  a integrate and fire neuron(discontinuous reset) or is electrophysilogical model (continuous).
What are the currents/channels/gates in it (Sodium, Potassium, Chlorine, Calcium)?
what form do the differential equations take?
What are the known/unknown parameters?

The  more  you can answer these questions the easier the parameter fitting process will be, but beware, a one size fits all approach rarely works in biology because of cell to cell variation.

Error Function
Next one needs what is called an error function, or a way to tell if the model output voltage trace is similar to the actual voltage trace. The most classical (but in my honest opinion the worst one)  is the $\mathcal{L}_2$ norm on the voltages. The  $\mathcal{L}_2$ is simply

$$\sqrt{\sum^{N}_i (V_{model}(i)-V_{data}(i))^2}$$

To see why this is so bad I attached a sample (simulated trace from the Hodgkin-Huxley model).

The Blue Trace is from a Neuron with slightly less injected current then the yellow Trace one. As you can see yellow has a faster frequency than blue, and as a result the  $\mathcal{L}_2$ norm is massive  for each misaligned spike. However the spike trains are intuitively very close as seen not only in where the spikes line up but where the spikes so one would like a measure that defines misaligned phase and frequency.

Van Geit et al's. insight is that the  $\mathcal{L}_2$ is the wrong norm to compare voltage distance in. What they do is make a parametric plot of voltage verses voltage's derivative. The then compare distance between the curves like in the below plot.

.

We see that the voltage traces are indeed very similar, but to calculate distance between these curves, we must disregard time data. We can imagine subdividing phase space into a grid of equally sized boxes. Then count up the number of data points and model points in the boxes. In math notation this amounts to

$$
\sqrt{\sum^{N_x,N_y}_{i,j} (V_{model}(i,j)-V_{data}(i,j))}
$$

we have lost information about phase of the spike. It is also important to note that this is highly dependent on the size of the boxes, if they are too small the error will be high, too big the error will be to low.  While there method may not be the only proposed solution it does better than the $\mathcal{L}_2$

Here is both methods side by side for comparison. The black dot is the true solution. Blue is $\mathcal{L}_2$ and Yellow is Van Geit's method. You'll note that both are ``noisy" but there is a better trend in Van Geit's method than the $\mathcal{L}_2$ norm, thus optimization is easier. For the $\mathcal{L}_2$ method notice how the function is flat far away from a very steep and narrow valley. This is hard for optimization algorithms to hit. Van Geit's method is better because it has more of a downward slope that can be followed to a better global minima.

Also  Note that this noise is not from random variation (although that makes it worse) but rather from discretization of the data and model. (remember everything stored in a computer has a sample rate no matter how small).

Optimization Algorithm
Now Once has an appropriate error function one needs to use a optimization algorithm too find the local minimum of said error function. In my example here, I am using injected current as my parameter, but in every neuron model has many parameters that one needs to optimize over so direct visualization like is usually impossible.

Another caveat is the ``noise". these local valleys can make optimization algorithms get stuck in the local minima. Stochastic (random) optimization algorithms like simulated annealing  can help with getting stuck in these valleys, as they have a chance to jump past them.

Good Initial guesses
As far as not responding the "full space'' of solutions, the more of the possible inputs one has the better chance of being able to predict a different input. Also defining the computational behavior of your neuron is a good start.  Having a general model that acts qualitatively correctly but not quantitatively is often a good start to parameter fitting, This means one doesn't start with a neuron that doesn't respond to inputs, or something else physically unrealistic.

Anyway hope this gives a background to things to consider, this field is far from solved, and in need of creative solutions.


How do I change my tiredness patterns? All of you probably know what the human 'circadian cycle' is, and depending on your personality, you would either be a night-owl or a morning-lark.

I am interested in understanding the patterns of alertness and tiredness throughout the entire day, between waking up and sleeping.

Personally, my alertness gears up in the morning until 12.30 pm, after which I will, consciously or not, begin to feel very very drowsy. This happens even in the absence of lunch (lunch makes people feel tired because the body works to break down the carbohydrates). I will continue feeling tired and exhausted throughout the entire afternoon before I become alert again from 5 pm onwards. And then of course, in the night I am quite alert.

Here are my questions:

Has research been conducted on this?
Are there strategies to alter the patterns?
Does the tiredness have to do with eating patterns?
What are the relationships between tiredness and our circadian cycles?

To answer your questions (as to inspire you to do your own research and to avoid writing a book):

Yes, there is a TON of research on circadian rhythms... There are also many ongoing research projects. I might suggest doing a google scholar search. You might also try getting access to academic peer reviewed journals through your local library, university/college, schools, etc.
There are certainly strategies to alter the patterns. For example, amount of exposure to sunlight and time of day, amount of exercise and time of day, eating patterns,  etc. have all been shown to have a correlational effect on wakefulness vs. tiredness. If you do research on what effects our circadian rhythms, you will have an idea of how to alter them. There was an interesting study done on the circadian rhythms of nurses who worked shifts of varying lengths and their work productivity/effectiveness due to their circadian rhythms. You might want to try to find articles like that.
Yes, tiredness can certainly have to do with eating patterns. This is why many schools are implementing breakfast programs for children. Simply, food provides calories which provide energy. Without energy (and energy of the right type) we cannot function to our fullest ability. Different types of food would also effect one's circadian rhythm. You might wish to do some research on ghrelin and the circadian system. There is ongoing research looking into the effect of one's diet on their circadian rhythm.
At this point, the full extent of relationships between tiredness and circadian rhythms are unknown. However, there is strong correlational data which suggests that REM sleep patterns, circadian rhythms and tiredness vs. wakefulness is highly related. You might also wish to look up specific neural circuitry which effects one's circadian rhythms.

I wasn't sure how complex of an answer you wanted or your understanding of neural circuitry, so I haven't typed out the answers for you. Looking up various neurotransmitters would probably be a great place to start if you're interested.


How does listening to music decrease stress? I'm interested in how listening to different types of music (such as jazz, classical, etc.) can help some people calm down.

More specifically, how does the brain form a link between music heard and processed to the stress system? Is it some cortical association area or a direct circuit?

This may be happening due to beat entrainment. Different music genres have different beat and rhythm patterns. The ones that are calming will generally have a lower beat and rhythm frequencies. The lower beat and rhythm frequencies are similar to the frequency of heartbeat and breathing when a person is feeling calm and/or relaxed. Through the process of entrainment, the person's breathing and heartbeat may synchronize with the music, thus calming the person. The mechanism could be working by counter-acting the effects of shallow breathing.


What is the upper bound on rate of learning in young adults? I was wondering how a normal adult in their 20s could best structure their life to make best use of their capacity to learn. I am no expert in cognitive science, so I assume just a really common definition of "learn" here. We might measure this by, for example, hours of sustained, intense study per 24 hrs. I realize my question might be a major oversimplification, leaving out factors like stress.

If there is some upper bound on how quickly learning occurs, then there may be little point in studying more than, say, 6 hours per day.  Does anyone know of any research which shows some general, asymptotic upper bound for learning in adults (20-30)?

Anectodal examples might also be useful. What are some examples of how highly accomplished adults structure their days?

Karl Ericsson, on whose work Malcolm Gladwell based much of his popular Outliers, has expressed on a number of occasions that the optimal amount of practice time a day is around 3-5 hours, depending on domain.

There is a great deal of research in the expertise literature, but Ericsson, Krampe, Tesch-Römer (1993) is a seminal (if not uncontroversial) paper in the field which provides a very solid introduction. They reported evidence for the idea that practicing more than four to five hours a day was not associated with higher achievement within a domain. To support this claim, among others, they drew on a number of sources, including:

Literature review

  A number of training studies in real life have compared the efficiency of practice durations ranging from 1-8 hr per day.These studie sshow essentially no benefit from durations exceeding 4 hr per day and reduced benefits from practice
  exceeding 2 hr (Welford, 1968; Woodworth & Schlosberg, 1954). Many studies of the acquisition of typing skill (Baddeley & Longman, 1978; Dvorak et al., 1936) and other perceptual-motor skills (Henshaw & Holman, 1930) indicate that the effective duration of deliberate practice may be closer to 1hr per day. Pirolli and J. R. Anderson (1985) found no increased learning from doubling the number of training trials per session in their extended training study.

Retrospective estimates from expert violin players

  When the duration of all music-related activities was summed across the diary week, the average number of hours per week was 50.6, and no reliable differences between the groups were found. Of the eight activities judged to be highly relevant to improvement of violin performance, only two had an average duration across all three groups exceeding 5 hr per week. These two activities were practice alone (19.3 hr per week) and sleep (58.2 hr per week).

Biographies of accomplished scientists and intellectuals

  Biographies report that famous scientists such as C. Darwin, (E Darwin, 1888), Pavlov (Babkin, 1949), Hans Selye (Selye, 1964), and Skinner (Skinner, 1983) adhered to a rigid daily schedule where the first major activity of each morning
  involved writing for a couple of hours. In a large questionnaire study of science and engineering faculty, Kellogg (1986) found that writing on articles occurred most frequently before lunch and that limiting writing sessions to a duration of 1-2 hr was related to higher reported productivity. [...]

  In this regard, it is particularly interesting to examine the way in which famous authors allocate their time. [...] Almost without exception, they tend to schedule 3-4 hr of writing every morning and to spend the rest of the day on walking, correspondence, napping, and other less demanding activities (Cowley, 1959; Plimpton, 1977).

However, many questions remain regarding the generalizability of deliberate practice. More recent research has suggested that Ericsson's theory may not be equally adequate for all domains, and nearly irrelevant to some. For a more critical review of Ericsson's work, please see my related answer on, "Do 10.000 hours of practice make you an expert?".

References

Ericsson, K. A., Krampe, R. T., & Tesch-Römer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100, 363–406. doi:10.1037/0033-295X.100.3.363


Why I dont like music? I'm not sure, if I'm alone, but I never liked music, any kind of music. It never made me happy or sad. Actually it never ever had any effects on me right from my childhood days. My iPod(received as a gift) is filled with audio version of movies and dramas, but never songs.

Is it some kind of mental illness?

I wouldn't call it a disorder, unless it significantly affects your life. Not enjoying music or not being able to produce music is known as "amusia". It probably has to do with differences in perceiving pitch [1]. It can also occur in people with recently fitted hearing aids or cochlear implants [2].

If you are interested in this, there is a chapter about cases of amusia in Oliver Sack's book Musicophilia [3].

References:
[1] Liu F, Patel AD, Fourcin A, Stewart L. (2010). Intonation processing in congenital amusia: discrimination, identification and imitation. Brain. 133(Pt 6):1682-93. doi:10.1093/brain/awq089
[2] Cooper, W., Tobey, E., & Loizou, P. (2008). Music Perception by Cochlear Implant and Normal Hearing Listeners as Measured by the Montreal Battery for Evaluation of Amusia. Ear and Hearing, 29(4), 618. doi:10.1097/AUD.0b013e318174e787
[3] http://www.oliversacks.com/books-by-oliver-sacks/musicophilia/


What are threshold symptoms and sub-threshold symptoms? I've come across these terminologies—threshold symptoms and sub-threshold symptoms—in one of the papers in psychology where delayed reactions are introduced:

  Empirical studies that have mapped PTSD symptoms over time in fact observed what appear to be delayed elevations in the direction of threshold symptoms...

However, I don't have any ideas what those words are all about.

I believe that the concept of 'subthreashold symptoms' refers to a situation where a client clearly presents with symptoms of a given condition but, crucially, they present with too few symptoms to meet the diagnostic criteria.

This link, which hopefully also satisfies Seanny123's request for a document, states:

  Although DSM-IV acknowledged the clinical significance of some subthreshold forms of unipolar depression, such as minor depression (MinD) and recurrent brief depression (RBD), clinicians continued to struggle with the concept of "subthreshold" depression. A substantial number of patients continued to present with depressive symptoms that still did not satisfy any DSM-IV diagnosis. Generally, these patients failed to complain of anhedonia and depressed mood, a criterion that DSM-IV mandates for any diagnosis of depression.


How would synapses behave if resting potential was zero? Assuming that the resting potential is zero and the other mechanisms were exactly the same, how would it affect the generation of spikes in terms of excitatory and inhibitory postsynaptic potentials(EPSP and IPSP). Trying to understand the reason behind negative resting potential, not how it is maintained, but why so. Does it mean EPSP is inherently suppressed by design?

There are two very different questions here. The first question is simple (although it could be interpreted a few different ways). The second question is very tricky and I am actually not certain we know the answer.

1. What do PSPs look like if the resting membrane potential is 0 mV?

If a cell is being held at 0 mV, its voltage-gated conductances are essentially broken and it is not actually able to fire an action potential. But let's put that aside and focus on synaptic events. Let's also assume that the reversal potentials for each ion are 'normal'.

The short story is that most excitatory receptors have a reversal potential near 0 mV, so EPSPs would have little direct effect on the membrane potential (remember this rule: current passing through an ion channel can only push the membrane potential toward the reversal potential of that channel). Inhibitory receptors tend to reverse around -75 mV, so they would have a large driving force and would strongly polarize the cell.

The slightly-longer story is that EPSPS would still have some effect--when ion channels open, ions flow in the direction of their electrochemical gradient. For excitatory receptors, this means that sodium flows into the cell, potassium flows out, and calcium flows in. The net electrical current would be roughly zero, but there would be an exchange of ions, and an opportunity for those ions to activate secondary signaling pathways.

Another effect of opening ion channels is a reduction in the resistance of the cell membrane. Thus at 0 mV, excitatory synapses can actually shunt IPSPs.

2. What is the reason for having a negative resting potential at all?

The first thing to recognize is that neurons store a large amount of energy in their chemical gradients. Potassium is pumped into the cell while sodium, chloride, and calcium are pumped out. Running these pumps is metabolically expensive (your brain takes up 20% of your metabolism at rest!), and the chemical energy burned in the process (ATP) becomes potential energy in the chemical gradient. Another way of saying this is that each of these ions prefers to be on the other side of the membrane, but the pumps keep them where they are.

Ions are generally pumped in such a way as to maintain charge balance--for every positive charge pumped in, one positive charge goes out. Now if you happen to have channels that admit only a single type of ion (we do), then opening that channel will result in an immediate flow of ions. But wait! Unlike the pumps, this ion flow is not charge-neutral, so after a very short time, the membrane becomes charged, and that charge imbalance (voltage) counteracts the chemical gradient (if ions dislike being on the wrong side of a chemical gradient, they absolutely hate being on the wrong side of an electrical gradient).

So what we have now is a huge energy store in the form of chemical gradients, and a means for the neuron to rapidly convert that energy into electrical potential. If the neuron wants to depolarize, it needs only open sodium or calcium channels. If it wants to repolarize, it opens potassium or chloride channels. You can think of it like a balloon connected by hose to two tanks: one high pressure, the other a vacuum. Open one valve and the balloon fills, open the other and it empties.

Ok, that was long but I am finally ready to talk about resting potential. The how is easy: neuronal membranes are more permeable to potassium than sodium. One of the valves is always open a little bit, and this drags the membrane potential negative, away from zero. Which is to say that the resting membrane potential is not at all the "driving force" for neuronal activity. Rather, it is almost just a side-effect of the real powerhouse--the chemical gradients.

I mentioned that neurons spend a lot of energy maintaining their chemical gradients. Why then, would the cell allow its potassium gradient to simply leak away? This is not an easy question! The lazy answer is "because all the voltage-sensitive channels operate in the range from -70 to 0 mV". I call this lazy because if there really was no benefit to having the cell rest at -70 mV, then evolution would find a way to conserve all that energy wasted by leaking potassium. So there must be a better reason. I've turned this into its own question here: Why do neurons have a negative resting potential?


What is an effective metric of complexity for an Artificial Neural Network? After asking the question What is the most complex neural network... I realized I don't really have a good metric of "complexity" in a general sense. The simplest measure would likely be count of neurons or number of synapses, but that fails to take into account the structure of the network.

A couple measures of complexity are discussed in the paper Complexity of Predictive Neural Networks
 but they are very specific to a single task. One is the amount of work needed to learn a certain thing, and the other is how many neurons are needed to approximate a certain function.

Rough, animal based measures are often employees for the sake of grabbing headlines; such as the incorrect claims that The Blue Brain Project had emulated a neural network "as complex as" a cat's brain. C. elegans is a common and seemingly attainable level of complexity for an artificial neural network.

Animal based measures are relateable to the layman but seem questionable, especially when comparing a neural network to that of an animal who's neural network has not been completely mapped (as C. elegans has).

What is a meaningful measure by which artificial neural networks can be measured? How are such networks currently compared? Can any such metric appropriately measure complexity of such a system?

The standard complexity metric in theoretical computer science and machine learning, in particular in statistical learning theory, is the Vapnik–Chervonenkis (VC) dimension. It is of interest because it gives us a very good tool to measure the learning ability of a neural network (or any other statistical learner, in general).

A good introduction to the use of VC dimension for studying neural nets is:

Eduardo D. Sontag [1998] "VC dimension of neural networks" [pdf].

There, the author shows (for instance) that a network with one hidden layer, $n$ inputs, and $\tanh$ neurons has VC dimension of $n + 1$. He also explain some basic technique for how to upper-bound the VC dimension, and for how to use it for dynamic neural nets.


Ignoring minority while generalizing about a group, any theoretical reference? In conversation, we might define a particular group by the characteristics that the majority of that group holds even if a minority in that group doesn’t possess those characteristics.

Some possible examples:

Human being eats meats (even though ~3-5% of human are total vegetarians)
Russians like vodka (many don’t drink there)
Asians are brown (though there are many who are white)
(Ignore the figures or classification it’s just for explaining purpose)

The point is, why are we programmed to make generalizations this way, i.e., disregard the small or even significant but minority of a group while taking it as a whole, this is understood by common sense, but, I was wondering is there a scientific basis for this, perhaps some kind of theory presented by someone or a research that established this rule?

I think the exceptions are implied. If someone says, "All Russians like vodka" then we understand that there are no exceptions to the rule. People get frustrated when you're overly specific about the percent of Russians who like vodka. Instead it's safer to just say Russians like vodka. And bears.

Influence: The Psychology of Persuasion talks about why we operate based on generalizations. We would freeze if we analysed all the details of every situation before we act, so we make generalizations.

Thinking, Fast and Slow is an excellent book talking about the latest research in human biases from one of the foremost experts in the field.


What's the percentage of people that are mental calculator prodigies? I want to reply to this comment:

What's the percentage of people that are mental calculator prodigies?
How do they spread over the different parts of the world?

There are two common ways someone can become a mental calculator via high iq or by savant ability. In exceptional cases someone may develop this ability while having only a average IQ but the level of dedication to such abilities is pathological interfering with normal development on the order of OCD.

Assuming the mental calculator abilities are the function of a savant ability. 62 out of every 10,000 are autistic and 10% of all autistic person have a savant ability finally half of all savants are autistic so multiply the number of autistic savants by two. Which gives you 12/10,000 as a maximum amount of mathematical savants.

About 1/1,000 people are geniuses with iq of 145 but i suspect it takes an Exceptionally Gifted person with an iq above 160 1/10,000 to have the capacity to become mental calculators.

So by my high estimations between 1 and 5 people out of 10,000 are capable of being mental calculators. Because savantism, autism and iq occur semi randomly (due as best we know to genetics) you should expect their to be an equal distribution among all populaces.


Are all dendrites targeted by an axon, or are there a lot of "empty" dendrites? As far as I understand, one neuron can have up to 200 000 dendrites (e.g. purkinje cells). As for axons, there can be only one per neuron, which can divide into thousands (but not hundreds of thousands) of branches at the end.

I assume that each dendrite has one input terminal and each axon branch has one output terminal. I also assume that only dendrites can have input terminals and that only axons' branches can have output terminals. So we can have up to 200 000 input terminals and up to thousands of output terminals per one neuron. So it seems to me like in the whole brain we have more input terminals than output terminals available.

Are my assumptions correct?

If yes, does that mean that there are a lot of redundant dendritic input terminals available?

Short answer
Axonal outputs are coupled to dendrites or other effector tissues, such as muscular fibers or glandular tissue. There are no redundant axonal outputs, or redundant dendritic inputs. There is a tight coupling between the two both during developmental formation of synapses and during the maintenance of the two.

Background
Neurons can have extensive dendritic trees (e.g., Purkinje cells in the cerebellar cortex, Fig. 1) and also elaborate arborated axon terminals (*e.g., in the neuromuscular junction, Fig. 2).

In the cases shown below, the functions can be defined as simple logical operators, namely integration (Purkinje cell) and amplification (neuromuscular junction). The Purkinje cells receive and integrate input from the brainstem. The motoneurons innervating muscle use multiple axon terminals to target a larger area of the muscle so that stronger, synchronous muscle contractions can be achieved.

The development and maintenance of dendrite-axon connections are tightly coupled (e.g., Shen & Lowan, 2010). Generally, when either input to the dendrite is diminished (axonal regression), or output of the axon is cancelled (dendritic regression), the plasticity of the neural tissue will lead to degeneration or re-directing of the axon, or regression or re-innervation of the dendrite, respectively (e.g. Marc et al., 2003).

As regarding to your math; be aware axons can branch, axon arborations can target a single dendritic tree, axons can terminate on other tissues, such as glands and muscles (no dendrites there!). In other words, your mathematical example is an oversimplification. Further; cells with elaborate dendritic trees as shown in Fig. 1 are common in cortical layers, but are not the norm. The ratios of the cell types have to be taken into account as well.

Lastly, there can be the textbook connections between neurons, namely axo-dendritic connections, but also axo-axonal (Schmitz et al, 2001), dendrodendritic (Shepherd, 2009), and even axosomatic synapses between neurons (Fig. 3).

Fig. 1. Dendritic tree (Wundt, 1904)

Fig. 2. Axonal terminals in a neuromuscular junction. source: Farrel (2017)

Fig. 3. Different kinds of synapses. source: Modesto Junior College

References
- Marc et al., Prog Retin Eye Res (2003); 22(5):607-55
- Shen & Kowan, Cold Spring Harb Perspect Biol (2010); 2(4): a001842
- Shepherd, Ann N Y Acad Sci (2009); 1170; 1-11
- Schmitz et al., Neuron (2001); 31(5): 831-40
- Wundt, Principles of Physiological Psychology (1904)


What do we know about schizophrenia and mathematics? Schizophrenia is usually associated with intellectual problems. I don't think that cognitive deficits are only associated with vulnerability to schizophrenia, though there is the much cited

  Russell et al (1997) recently proposed that intellectual decline in
  schizophrenia was a nothing more than a ‘myth’. They followed up
  patients who had received an intelligence test as a child, who then
  developed schizophrenia, and had their intelligence re-tested some 19
  years later. There were no differences between the child and adult
  IQs. However, others have criticised this study on the grounds that
  the sample was unrepresentative in that the individuals had presented
  to child psychiatry units and were far more intellectually impaired
  than subjects in other studies of children who subsequently developed
  schizophrenia.

From my research prior to this question, it seems that there is a loss of ability, but likely not chronic decline over the course of the illness, one before or during the transition to psychosis. Another well known meta review claims this, that there's

  no support for hypothesizing a degenerative
  process in schizophrenia once positive symptoms appear... a static encephalopathy rather than a degenerative process

I've seen it said that it is centered on mathematical ability.

What do we know about mathematical ability pre and post psychosis, in schizophrenia? e.g., was John Nash a worse mathematician after he went mad?

References

Russell, A. J., et al. (1997) Schizophrenia and the myth of intellectual decline. American Journal of Psychiatry, 154(5), pp 635–639.
DOI: 10.1176/ajp.154.5.635 PMID: 9137118 WOS: A1997WX13000009

I spent times of the order of five to eight months in hospitals in New
  Jersey, always on an involuntary basis and always attempting a legal
  argument for release. And it did happen that when I had been long
  enough hospitalized that I would finally renounce my delusional
  hypotheses and revert to thinking of myself as a human of more
  conventional circumstances and return to mathematical research. In
  these interludes of, as it were, enforced rationality, I did succeed
  in doing some respectable mathematical research.

Seems like he himself is saying his research suffered while unwell and not staying in institutions.

However, the standard deficit in IQ, of it seems around 10 points, may be inconsequential in someone like Nash. Even if the executive function and memory impairments are more significant.


Is there a correlation between online and offline vandalism? I did some searching but I was not able to find anything substantial on this topic either for or against. I am mainly trying to figure out whether online trolling is a way of redirecting otherwise destructive offline behavior.

So, is there a correlation between online vandalism (trolling) and offline vandalism (damaging/defacing public property)?

According to this study, there really is a correlation:
http://www.slate.com/articles/health_and_science/climate_desk/2014/02/internet_troll_personality_study_machiavellianism_narcissism_psychopathy.html

  The research, conducted by Erin Buckels of the University of Manitoba
  and two colleagues, sought to directly investigate whether people who
  engage in trolling are characterized by personality traits that fall
  in the so-called Dark Tetrad: Machiavellianism (willingness to
  manipulate and deceive others), narcissism (egotism and
  self-obsession), psychopathy (the lack of remorse and empathy), and
  sadism (pleasure in the suffering of others).

  It is hard to overplay the results: The study found correlations,
  sometimes quite significant, between these traits and trolling
  behavior. What’s more, it also found a relationship between all Dark
  Tetrad traits (except for narcissism) and the overall time that an
  individual spent, per day, commenting on the Internet.

The research document itself can be found here:
http://www.sciencedirect.com/science/article/pii/S0191886914000324