What is the optimal length of a training session?

Principles of optimal practice duration from the expertise literature

The expertise literature and its discussion of deliberate practice provides substantial guidance on the question of optimal practice duration.
As Ericsson et al (2006) summarised:

  elite performers search continuously for optimal training
  activities, with the most effective duration and intensity, that will
  appropriately strain the targeted physiological system to induce
  further adaptation without causing overuse and injury.

With regards to optimal practice length, Ericsson et al (2006) stated (with key points bolded by me) that:

  Although the detailed nature of deliberate practice will differ across
  domains and as a function of attained skill, there appear to be limits
  on the daily duration of deliberate practice, and this limit seems to
  generalize across domains of expertise. Expert performers from many
  domains engage in practice without rest for only around an hour, and
  they prefer to practice early in the morning when their minds are
  fresh (Ericsson et al., 1993 ). Elite musicians (Ericsson, 2002) and
  athletes (Ericsson, 2001, 2003 c) report that the factor that limits
  their deliberate practice is primarily an inability to sustain the
  level of concentration that is necessary. Even more interestingly,
  elite performers in many diverse domains have been found to practice,
  on the average, roughly the same amount every day, including
  weekends, and the amount of practice never consistently exceeds five
  hours per day (Ericsson, 1996; Ericsson et al., 1993 ). The limit of
  four to five hours of daily deliberate practice or similarly
  demanding activities holds true for a wide range of elite performers
  in different domains, such as writing by famous authors (Cowley, 195
  9; Plimpton, 1977), as does their increased tendency to take
  recuperative naps. Furthermore, unless the daily levels of practice
  are restricted, such that subsequent rest and nighttime sleep
  allow the individuals to restore their equilibrium, individuals
  often encounter overtraining injuries and, eventually, incapacitating
  “burnout.” In some domains of sports, such as gymnastics, sprinting,
  and weight lifting, the max- imal effort necessary for representative
  performance is so great that the amount of daily deliberate practice
  is even further limited by factors constraining the duration of
  produc- tion of maximal power and strength.

Implications for the specifics of your question

Thus, based on the expertise literature,  four or five one-hour sessions of deliberate practice in a day with plenty of rest between and at night would be optimal if the aim is to maximise learning on the focal task in the shortest period of time.

In general, I wouldn't define optimal duration of practice in terms of amount of the task learnt.

Also, in the real-world, the optimality criterion can vary between people. The expertise literature assumes that the goal is to maximise learning on the focal skill. However, in the real-world, a person may be learning a number of things, and also need to accomplish tangible outcomes at the same time.

References

Cowley, M. (Ed.) (195 9). Writers at work: The
Paris review interviews. New York: Viking.
Ericsson, K. A. (1996). The acquisition of expert performance: An introduction to some of the issues. In K. A. Ericsson (Ed.), The road to excellence: The acquisition of expert performance in the arts and sciences, sports, and games (pp. 1–5 0). Mahwah, NJ: Erlbaum.
Ericsson, K. A. (2001). The path to expert
performance: Insights from the masters on how
to improve performance by deliberate practice.
In P. Thomas (Ed.), Optimizing performance in
golf (pp. 1–5 7). Brisbane, Australia: Australian
Academic Press.
Ericsson, K. A. (2002). Attaining excellence through deliberate practice: Insights from the study of expert performance. In M. Ferrari (Ed.), The pursuit of excellence in education
(pp. 21–5 5 ). Hillsdale, NJ: Erlbaum.
Ericsson, K. A. (2003c). The development of elite performance and deliberate practice: An
update from the perspective of the expert-performance approach. In J. Starkes & K. A.
Ericsson (Eds.), Expert performance in sport: Recent advances in research on sport exper-
tise (pp. 49–81). Champaign, IL: Human Kinetics.
Ericsson, K. A., Krampe, R. Th., & Tesch-Romer, C. (1993 ). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100, 3 63 –406. PDF
Ericsson, K. et al. (2006). The influence of experience and deliberate
practice on the development of superior expert performance. The
Cambridge handbook of expertise and expert performance, 10(3):683-703. PDF
Plimpton, G. (Ed.) (1977). Writers at work: The Paris review. Interviews, Second Series. New York: Penguin.


How is gender variance classified in the cognitive sciences?

So far, I've found that the American Psychiatric Association's DSM 5 has made it abundantly clear they no longer consider gender variance itself a disorder, to the point of a 2012 position statement on access to care, a 2012 "Position Statement on Discrimination Against Transgender and Gender Variant Individuals", and updated language in the DSM.

It also looks like ICD-11's beta now uses "Gender Incongruence", versus the various "gender identity disorders" under the F64 code in ICD-10.  Link when I have the reputation to post it.


link between top-down (bottom-up) processing and cortex layers

It is generally thought that thalamic input comes in layer 4, feed back from higher areas come through layer 1 to layer 2/3 and feed forward is sent from the deeper layers.

see Canonical Microcircuits for Predictive Coding
Andre Bastos, W. Martin Usrey, Rick Adams, George Mangun, Pascal Fries, and Karl Friston
http://psych.nyu.edu/clash/poeppellab/JournalClubPapers/BastosFristonNeuron12.pdf

who cite Douglas, R.J., and Martin, K.A. (1991). A functional microcircuit for cat visual cortex. J. Physiol. 440, 735–769.


Not aware of any studies on this topic.
I think this is a tricky question because of the nature of sleeping.

Hypersomnia does not fit in with physiological nor psychological dependence because of the following (from the proposed DSM-V revision, but similar enough to the DSM-IV-TR) symptom:

"The sleep periods are non-restorative (unrefreshing) or so prolonged in length that this causes clinically significant distress or impairment in social, occupational, or other important areas of functioning."

Now, sleep would not fit in with the class of substance-related disorders. I cannot see one having impaired control over or compulsive use of sleep. Can one really derive that much pleasure, and thus, a reward response from sleep? Would one have a tendency to keep increasing the dose, to chase "a high"? Abrupt cessation of sleep after excessive "use" may trigger negative feelings but if one were to, say, give the sleep-craving individual stimulant medication, I doubt serious withdrawal effects will take place.

The only proposed behavioral addiction for the DSM-V (at least I think at this point) is Gambling Disorder, or pathological gambling. The proposed criteria are as follows.

A.    Persistent and recurrent maladaptive gambling behavior as indicated by five (or more) of the following:

is preoccupied with gambling (e.g., preoccupied with reliving past gambling experiences, handicapping or planning the next venture, or thinking of ways to get money with which to gamble
needs to gamble with increasing amounts of money in order to achieve the desired excitement
has repeated unsuccessful efforts to control, cut back, or stop gambling
is restless or irritable when attempting to cut down or stop gambling
gambles as a way of escaping from problems or of relieving a dysphoric mood (e.g., feelings of helplessness, guilt, anxiety, depression)
[Not relevant.]
lies to family members, therapist, or others to conceal the extent of involvement with gambling
has jeopardized or lost a significant relationship, job, or educational or career opportunity because of gambling
[Not relevant.]

Can a psychological dependence on sleep fit in with the above criteria if one were to mold it to pertain to "pathological" sleeping?

I could not think of analogous "Sleep Addiction" criteria to match that of Gambling Addiction's A-6/A-9 symptom points, but from the above, it appears that a psychological dependence /can/ apply to a dependence on sleep(ing). From this loose argument alone.

Preoccupied with sleep. [Sure.]
Needs get an increasing amount of hours of sleep to achieve the same response. [Eh. I was thinking "resorts to increasing doses of sedatives to achieve longer periods of sleep" but felt that ventured into substance abuse territory.]
Has repeated unsuccessful efforts to control, cut back, or stop (ha) [excessive] sleep. [Sure, why not.]
Is restless or irritable when attempting to cut down on sleep. [Can see this happening.]
Sleeps as a way of avoiding problems or of relieving dysphoric mood. [Most definitely, this symptom reminds me of some subtypes of Major Depressive Disorder. But I digress.]
Lies to family members, others, to conceal the extent of excessive sleep. [Why not.]
Has jeopardized or lost a significant relationship, job, or educational or career opportunity because of excessive sleep. [Can easily see this.]

If I can interject my own opinion on the matter, I just cannot see anyone developing a physical need for sleep. Our basic biological or evolutionary make-up does not allow for that, I feel. But I know little about, say, narcolepsy - but to my knowledge they find their excessive sleepiness unwanted and detrimental. Nor can I see potential for one to become psychologically dependent or addicted to sleep. I just can't see someone deriving pleasure from more and more sleep.


It is a biological/chemical response. Once in a stressful situation, you're not supposed to act smart or able to solve a rubik cube, but punch whatever is getting you angry and/or getting the hell out of the place.
The adrenaline, and other stuff, discharge are responsible for
increased blood pressure, heart rate and what-not (Nordqvist, 2013):

Anger is not just a mental state of mind. It triggers an increase in heart rate, blood pressure and levels of adrenaline and noradrenaline. Anger has survival benefits, and forms part of our fight or flight brain response to a perceived threat or harm.
When a human or animal decides to take action to stop or confront a threat, anger usually becomes the predominant feeling and takes over our behavior, cognition and physiology.

Actually, we do get more acute cognitive abilities... though at the expense of others :

The brain shunts blood away from the gut and towards the muscles, in preparation for physical exertion. Heart rate, blood pressure and respiration increase, the body temperature rises and the skin perspires. The mind is sharpened and focused.

Blood is shifted AWAY from the frontal cortex, responsible for nice thoughts (Hanscom, 2014):

When the real or perceived threat persists we feel or are trapped. This, of course, leads to frustration and anger, which causes adrenaline levels to really skyrocket. The result is that your blood supply is shifted largely to the skeletal muscles, which enables you to flee danger. Other effects include:
Decreased blood flow to your brain – especially to the frontal cortex where most thinking occurs.

Spektor, Treister, et al (2011) states in their study that observing anger in others increases analytical problem solving whilst hindering creative problem solving (not really related):

Studies 1 and 2 supported two of our predictions: Observing
another person’s anger influenced observers’ thinking processes,
and the way anger is expressed shaped this effect. Observing anger
hindered the solving of creative problems and enhanced the solv-
ing of analytic problems.


How to calculate IQ from bhatia battery test?

I hadn't heard of the Bhatia measure before. A little research (see page 42 of Sharma and Sharma) explains that it is a performance based measure of ability for children in India. In general, you should obtain the test manual to learn about the recommended scoring procedure. A quick Google suggests it might be available from here: http://www.npcindia.com/

Reference

Experimental Psychology  By Ram Nath Sharma, Rachana Sharma


Is learning and memory formation mostly comprised of new synapses forming, or already-existent synapses strengthening?

Formation of a synapse does not automatically mean learning. It is the strength of the synapse that makes it a "skill". Hebb's rule for learning states that if a Neuron A repeatedly takes part in firing Neuron B, then the synapse from A to B is strengthened. We should also consider the fact that a neuron can be either excitatory or inhibitory to another neuron. If it is excitatory, the mental habit or skill improves, and otherwise it deteriorates.

Memory formation can be modeled as recurrent neural networks, where outputs continue to occur even after input to network has ceased.


How exactly are socionics and MBTI different?

Both socionics and MBTI are a try to dig deeper on the path of Carl Gustav Jung, who observed empirically (both from his work as a psychiatrist and from his travels across the globe) that all human brains displayed common cognitive descriptions, which Jung described by two energy-attitudes, two perception functions and two judgment functions.

  About Jung (about 100 years ago - his milestone book about cognitive types
  was published in 1921)

  The energy attitudes are introverted - the energy flows outward from the
  inside stimulation; and extraverted - the energy flows inward from the
  outside stimulation.

  The perception functions are intuition - a misnomer, with intuition you
  take information from a 3,000 ft view and make connections from this - and
  sensation - you take information from your senses and like to get into
  details, like with a magnifier glass.

  The judging functions are thinking - you make your decisions based on
  logic - and feeling - a slight misnomer, you make your decisions based on
  your subjective set of values (N.B. objective and subjective are commonly-used
  words in C G Jung's books).

  Following Jung, we all have a piece of everything in us, but we also have a
  preference for each dimension - energy management, taking information,
  making a decision.

  Jung described a set of 2x2+2x2=8 cognitive functions: introverted thinking,
  introverted feeling, extraverted thinking, extraverted feeling, introverted
  intuition, introverted sensation, extraverted intuition and extraverted
  sensation - also known as Ti, Fi, Te, Fe, Ni, Si, Ne and Se. Yes, N stands
  for iNtuition, as i stands for Introverted.

As mentioned in the comments, the MBTI was developed in the US - Katharine Briggs met Jung in Switzerland and her daughter Isabel Myers-Briggs was raised in a family/friends/colleagues environment that talked about cognitive types and she followed her own path, about 35-to-50 years after Jung.

  About Briggs and Myers (about 50 years ago)

  They described the structure of the preferences of the cognitive functions:
  sixteen combinations rephrase Jung's preferences, with the three axis from
  Jung (energy orientation of the dominant function, perception function,
  judgment function) and with a fourth axis, describing whether the
  extraverted function among the main two functions used by a profile
  is either a perception function or a judgment function.

  This descriptions fits into four letters (E or I, S or N, T or F, J or P)
  that describes the preference of a cognitive profile for two Jungian functions.

  Every profile has an inward function and an outward function, every profile
  has a perception function and a judgment function. With a main (dominant) and
  an auxiliary (auxiliary) function, this makes 16 combinations of letters,
  and 16 archetypes to describe common traits of a profile.

  The Myers-Briggs Type Indicator (or MBTI) is a questionnaire that tries to
  figure out whether your preference is E or I, S or N, T or F, J or P. Its
  main weakness is that this way of typing is not accurate at all - though it
  had a huge success in business. This was a weakness from the science viewpoint,
  as the MBTI never improved upon itself, by trying to describe with better
  accuracy the nature of our cognitive functions (which was Jung's goal).

Now, we turn to the former USSR, where other people followed the path of Jung,
too. They founded socionics, which is an extrapolation of Jung's work to describe
how the 16 profiles communicate and interact with one another.

  About socionics (about 50 years ago - USSR)

  Socionics also developed a fourth axis beyond Jung's three axis, but do not
  be misunderstood about it, as it is not the same fourth axis as in MBTI.
  In socionics, the fourth letter describes whether the dominant function of
  a profile is a perception function (p) or a judgment function (j).

  However, while MBTI focused on typing with four letters, socionics kept
  working both on the four-letter code and on the description of the Jungian
  functions. For the four-letter code, socionics described one-letter
  archetypes like in MBTI, but also two-letter and three-letter archetypes.

  About the Jungian functions, socionics described how a given Jungian function
  (e.g. Introverted Thinking) could be described by a slightly different archetype
  depending on its rank within the eight functions - while MBTI described
  mostly the first two or the first four functions of a profile, socionics
  tried to describe the eight functions of a profile, by decreasing order of preference.

Trying to describe a cognitive profile by an order of functions leads us to
figuring out how stress states may alter our use of our preferred functions.

This topic was mentioned by Jung (through the concept of Shadow), it is hardly
described in MBTI (not much developed either is the topic of mastering our
functions as we grow older - there are a few life stages when we care
differently for our preferred cognitive functions), while socionics described
a stress model called Model-A (this is a first step on our journey).

  Wrapping things up - until you ask for more?

  When MBTI and Socionics speak (about) the same with a different vocabulary:
  MBTI  -  Socionics  -  Jungian functions (descending order)
  INTP  -  INTj       -  Ti Ne Si Fe Te Ni Se Fi
  ENTP  -  ENTp       -  Ne Ti Fe Si Ni Te Fi Se
  INFP  -  INFj       -  Fi Ne Si Te Fe Ni Se Ti
  ENFP  -  ENFp       -  Ne Fi Te Si Ni Fe Ti Se
  ISTP  -  ISTj       -  Ti Se Ni Fe Te Si Ne Fi
  ESTP  -  ESTp       -  Se Ti Fe Ni Si Te Fi Ne
  ISFP  -  ISFj       -  Fi Se Ni Te Fe Si Ne Ti
  ESFP  -  ESFp       -  Se Fi Te Ni Si Fe Ti Ne
  ENTJ  -  ENTj       -  Te Ni Se Fi Ti Ne Si Fe
  INTJ  -  INTp       -  Ni Te Fi Se Ne Ti Fe Si
  ENFJ  -  ENFj       -  Fe Ni Se Ti Fi Ne Si Te
  INFJ  -  INFp       -  Ni Fe Ti Se Ne Fi Te Si
  ESTJ  -  ESTj       -  Te Si Ne Fi Ti Se Ni Fe
  ISTJ  -  ISTp       -  Si Te Fi Ne Se Ti Fe Ni
  ESFJ  -  ESFj       -  Fe Si Ne Ti Fi Se Ni Te
  ISFJ  -  ISFp       -  Si Fe Ti Ne Se Fi Te Ni

I hope this helps!


Applications and Limitations of EEG Electrode Pooling - Averaging across time series

This seems to be a rather painful terminology issue.

"Pooling" is used in statistics to describe combining data / different sources of information in a single model. It's of particular interest in hierarchical modelling approaches (e.g. mixed-effects modelling), and partial pooling -- broadly, the sharing of information between groups in a model without discarding the structure of the groups -- is perhaps one of the great innovations of 20th Century regression techniques. For more on this topic, see e.g. Gelman and Hill (2007).

In this sense, the use of regions of interest (ROIs) instead of individual electrodes as a categorical variable can be seen as a form of pooling -- you're combining data sources to gain more information, but losing some structure along the way. Because of the limited spatial resolution of EEG and the high correlation between adjacent electrodes, averaging across a ROI (and this is implicitly what's happening when we use ROI as a factor in ANOVA or regression models -- this is where the term "regression to the mean" comes from), may enhance our ability to see and detect the signal in the noise (i.e. increase statistical power). The coarsening of spatial (more specifically topographic) resolution is perhaps not tragic, because we are currently not able to make precise spatial predictions. Maris (2004) suggests an alternative way of dealing with topography.

This appears to be the sense that BrainVision Analyser uses the word "pooling". You're combining multiple data channels (electrodes) into a single one (ROI) via averaging. This is one of those places where you see that "channel" and "electrode" are not completely synonymous.

Incidentally, there are other ways you can combine information from electrodes. EEG measures voltage, which is per definition potential difference. The question, of course, is "difference to what?" In traditional recording setups, you have a single reference electrode (or perhaps a few linked electrodes as in linked mastoids) and you measure the difference in the electric field between the measurement electrode and the reference -- this is called "common reference". Sometimes, a pair of electrodes is measured relative to each other as "bipolar electrodes". This seems to be more common with the electrooculogram and has the advantage there that it makes eye movements more apparent. It has the disadvantage that you have effectively made one channel from two and cannot distinguish between the two original electrodes! A further disadvantage is that techniques like independent component analysis (ICA) depend on a common reference to do their magic, and as such, bipolar electrodes are problematic for ICA. A more advanced variant of common reference is "average reference", where the voltage is measured to the average voltage of all common reference electrodes. This seems weird at first, but it has its uses and emphasizes how the electrodes differ from each other (topography). Any common reference can be computed from any other via a relatively straight forward linear transformation. For more on this, see Luck (2005, 2014).

All of this stuff with referencing is important because it is possible to compute bipolar channels offline -- they are simply the difference of two common-reference electrodes. (Depending on which electrode you substract from which, you will get a different sign.) ERPLAB allows you to combine channels in fairly arbitrary ways to get new ones. If you're doing linear combinations of channels, it's fairly straightforward to compute what the statistics of the combined channel will look like compared to the statistics of the originals, but for arbitrary combinations, this can get confusing quite fast. Incidentally, the construction of ROIs or "pooling" in the BrainVision Analyser sense can be viewed as a special case of this -- you're adding a number of channels together and dividing by a constant (i.e. calculating the mean), which is a linear transformation.

Finally, you could also use existing channels to simulate missing or bad channels -- this is called interpolation. Good interpolation takes things like the curvature of the scalp and the electric field into account and is thus computationally more complex, often using techniques like splines. A simpler interpolation method is simply taking the average of adjacent electrodes (in some sense constructing a mini-ROI!), but this is not just less accurate numerically but also fails to take into account issues with the way electric fields sum together (see also: equivalent dipoles). Despite Scott Makeig's protests, I suspect that linear interpolation for a single electrode would work quite well in a high density setup. But then again, in a high density setup, you can generally afford to leave one electrode out of your analysis!

In each of the cases above -- construction of ROIs, arbitrary combination of channels, interpolation -- you are in some sense "pooling" the data you have. You are not gaining any information that was not there (e.g. an interpolated electrode does not really add much if any statistical power to your analysis), but you may be using the information that you had more efficiently. And that's what pooling is all about in statistics.

EDIT (2015-07-07 05:51 UTC): ICA and common vs. bipolar reference

As stated in the comments, ICA is actually based on relatively general assumptions that are generally indifferent to the choice of reference. In signal terms, the key assumption is that each measured channel is the linear combination (sums and constant multiples) of a number of components, which are typically taken to represent different (neueral) generators or (EEG) sources. In other words, ICA is a type of Blind Source Separation (BSS), which can be used to decompose a set of (directly) measured signals into a set of contributing sources, based on some additional assumptions. There are many different BSS techniques, each with different assumptions / goals, and thus each answering slightly different questions. For example, Principal Component Analysis (PCA) requires that components are orthogonal, while ICA require that components are independent. Somewhat simplified, PCA tries to separate the signal in terms of successive, "maximal" trends, which ICA tries to separate the signal into a series of distinct contributions.

This can be best seen in the following figure:

(Image reproduced from Jung et al (2001).)

The first component produced by PCA is a larger diagonal one explaining the general trend of increasing $y$ for increasing $x$, while the second component is a measure of "drift" or a correction to the general trend. Importantly, the components are at right angles (orthogonal) to each other. Combining each component in different proportions (i.e. weights), you arrive at the original two measurement series. In ICA, the components are  not required to be at right angles to each other, and the result in this example is a component for each of the visually obvious  groups.

Applying this to EEG data, we can view the choice of reference as some sort of builtin "offset" for measurement channel. This will change the weights in the recovered components, but ultimately not the components themselves. It's fairly trivial to transform the data from one common reference to another, and it's also fairly trivial to change transform the component weights from one common reference to another.

Now, when the channels have a mix of references, things get a little more interesting. Bipolar (measurement) channels are still linear combinations of EEG sources, but they have unknown offsets.[1,2] This is not a problem for ICA in and of itself -- as @mmh pointed out in the comments -- and thus the decomposition into sources / components works. The bigger issue is that the offset messes with the weights a bit and thus the back-projection; i.e. the generation of scalp maps becomes somewhat more difficult and the resulting scalp maps may be not be interpretable and cannot be source localized.[1] (Moreover, bipolar channels effectively pack the signal change from two discrete spacial locations into one and thus lose some of the topography information, which is also important for things like scalp maps.)

This is ultimately why the official advice from the EEGLAB Wiki is to use common reference for all channels, including the eye channels, because you can always create bipolar channels from unipolar channels, but not vice vera:

  We advise recording eye channels (conventionally four channels, two for vertical eye movement detection and two for horizontal eye movement detection) using the same reference  as other channels, instead of using bipolar montages. One can always recover the bipolar montage activity by subtracting the activities of the electrode pairs.[2]

For the work I do, ICA is really only interesting if you can generate scalp maps or perform source localization. It is still possible to identify (some types of) problematic components and remove them (e.g. a single noisy electrode, but then again, you can often identify that without ICA), but if the scalp maps are not interpretable, then I would have serious doubts about removing components that depend on electrodes from multiple references -- removing components is effectively substracting the component-associated scalp map from the measurement-associated scalp maps and my intuition is that the resultant difference would not necessarily be the correction you're looking for.

Or more succinctly, Arnaud Delorme, one of the key figures in the development and application of ICA to EEG data, states:

  ICA on bipolar montage will not be informative. ICA will attempt to model each channel reference so that common sources may be projected to all channels in a linear fashion. [3]

ICA will work with a mixture of bipolar and common references, but it will be answering a a different question than the one we would like answered.


Descriptive models of different types of consciousness

Studies examining unconscious perception usually rely on the experimental logic known as the dissociation paradigm (Reingold & Merikle, 1990), whereby the presence of subliminal perception is supported by a dissociation between two measures of perception. One measure is assumed to provide an index of subliminal perception whereas the other is assumed to index conscious awareness. The presence of subliminal processing is supported when changes in a critical stimulus effect the measure of subliminal processing, but the observer is unaware of either the presence or the changes in the critical stimulus.

For example, in the widely used masked priming paradigm, a lower case word is briefly presented (40 miliseconds) and replaced by a target word in capitals. Although the first word is rarely consciously perceived (measure of consciousness), recognition of the second word is faster when the two words are identical (e.g., star -> STAR), compared to when they are different (cope -> STAR). This pattern of results suggests that the first word is processed subliminally, and that this processing produces savings in how long it takes to process the target word.

Measures of conscious awareness are divided broadly into subjective and objective measures. Subjective measures are typically verbal reports of the observers' perceptual awareness during or after the task. Subjective reports can either be obtained with a direct question, or through a series of graded questions that gradually probe more specific aspects of an observers awareness. An experimenter might ask participants at the end of an experiment whether they were aware of any briefly presented stimuli, whether they noticed any patterns in the stimuli, or whether they developed particular strategies throughout the task. Objective measures are obtained through tasks and provide a numerical estimate of whether an observer was aware of a stimulus or implicit structure of a task. For example, observers might be asked to make a forced choice decision about a briefly presented stimulus to assess how visible the materials are.

Subjective measures are generally regarded to be unreliable, as participants may indicate that they are aware of a stimulus only when they are highly confident. This means that participants may neglect to mention instances where awareness was only partial. Another problem faced with subjective measures is that direct questioning during an experiment may draw participants attention toward the subliminally presented materials. Alternatively, participants may forget that they were aware of the critical stimulus if consciousness is assessed at the end of the testing session.

Although seen as more reliable, objective measures are associated with a number of limitations. Reingold and Merikle (1990) argue that a good measure of consciousness should be both exhaustive and exclusive. That is, the measure should index all components of conscious awareness (exhaustive), and should not index unconscious processes (exclusive). It is unclear whether objective measures are able to satisfy both of these criteria, as objective measures may only index a subset of the contents of consciousness (depending on the task instructions), and may also tap into unconscious processing. Another practical issue concerns how a lack of consciousness is estimated. Support for a lack of consciousness is obtained by showing that objective performance is at chance (e.g., guessing). This criterion is undesirable as this involves accepting the null hypothesis that participants were not aware, instead of rejecting the null hypothesis that participants were aware. Moreover, it cannot be guaranteed that participants will maintain motivation during a difficult task that consists mostly of guessing. In these cases participants may 'give up' and simply press buttons without considering the stimuli.

References
E. Reingold, P. Merikle. (1990). Using direct and indirect measures to study perception without awareness, Perception & Psychophysics, 44, pp. 563–575


Are we able to simulate pain through the brain?

Short Answer

It appears that stimulation of the thalamus would invoke feeling of pain:

  Direct deep brain stimulation (DBS) in the VP thalamus from patients without pain typically evoked nonpainful, paraesthetic sensation. DBS at the core and posterior inferior region of the VP thalamus can evoke pain sensation without specific topographic distribution. However, warm sensation was more frequently evoked in the posterior than in the core region. Intensity of sensation was dependent on current and frequency of microstimulation. (Yen and Lu, 2013)

The trouble is that deep brain stimulation (DBS) is a surgical procedure, so it would not be viable for any sort of virtual reality gaming, however it seems that Trans-cranial Magnetic Stimulation (TMS) could possibly be used if it could be developed and proven to be safe enough for this purpose.

It would have to be proven to target the specific parts of the brain required.  It would have to be proved not to be stimulating other areas that could cause unwanted and possibly dangerous consequences.

Long Answer

As I have very small amounts of knowledge on what happens in the brain neurologically compared to some people here, I have had to do a lot of reading to start with and I believe I have a basic idea of how this possibly could be done.

First of all we need to look at how pain is registered in the brain.

Nerves as pain sensors

A nociceptor is a type of sensory receptor at the end of a sensory neuron's axon that responds to damaging or potentially damaging stimuli by sending signals of pain to the spinal cord and brain. This process is called nociception.

The peripheral terminal of the mature nociceptor is where the noxious stimuli are detected and transduced into electrical energy. (Fein, 2012)  When the electrical energy reaches a threshold value, an action potential is induced and driven towards the central nervous system (CNS). This leads to the train of events that allows for the conscious awareness of pain.

Message transfer to the brain

Afferent nociceptive fibers (those that send information to, rather than from the brain) travel back to the spinal cord where they form synapses in its dorsal horn — the posterior grey column of the spinal cord.

After reaching the specific lamina within the spinal cord, the first order nociceptive project to second order neurons. The second order neurons then send their information via two pathways to the thalamus at the centre of the brain: the dorsal column medial-lemniscal system and the spinothalamic tract (or otherwise known as the anterolateral system). The first is reserved more for regular non-painful sensation, while the lateral is reserved for pain sensation.

Reaction from the thalamus

The sensory information is relayed from the thalamus upward to layer IV of the primary somatosensory cortex (S1) of the postcentral gyrus.

Initially, Brodmann areas (BA) 1, 2 and 3a and 3b (Brodmann, 1909/1994; Vogt, 1919; Kaas, et al., 1979) of the Cerebral Cortex were considered to make up the primary somatosensory cortex of the human brain, however, BA 3b is now conceived as the primary somatosensory cortex because:

it receives dense inputs from the NP nucleus of the thalamus;
its neurons are highly responsive to somatosensory stimuli, but not other stimuli;
lesions here impair somatic sensation; and
electrical stimulation evokes somatic sensory experience. BA 3a also receives dense input from the thalamus; however, this area is concerned with proprioception.

Reaction from other parts of the brain

The primary somatosensory cortex contains cells that project to the secondary somatosensory cortex (S2).  This is divided into several "areas". An area at the entrance to the lateral sulcus, adjoining the primary somatosensory cortex (S1), is called the parietal ventral (PV) area.

Area S2 is interconnected with BA 1 and densely so with BA 3b, and projects to BA 7b, insular cortex, amygdala and hippocampus.

The insular cortex, which is in both hemesperes of the brain, are believed to be involved in consciousness and play a role in diverse functions usually linked to emotion or the regulation of the body's homeostasis. These functions include perception, motor control, self-awareness, cognitive functioning, and interpersonal experience.

One thing I knew before the research is that it is the amygdala and hyppocampus which initiates the 5F response (fright/flight/fight/freeze/fawn response) to threats.

References

Brodmann, K. (1909/1994). Localisation in the Cerebral Cortex, Translated by Laurence J. Garey (New York, NY:Springer Science): pp 106—110 ISBN-13: 978-0387269177
Free PDF available from http://www.appliedneuroscience.com/Brodmann.pdf

Fein, A. (2012). Nociceptors and the perception of pain (Farmington, CT:University of Connecticut Health Center)Free PDF available from http://cell.uchc.edu/pdf/fein/nociceptors_fein_2012.pdf

Kaas, J. H., Nelson, R. J., Sur, M., Lin, C. S., and Merzenich, M. M. (1979). Multiple representations of the body within the primary somatosensory cortex of primates, In: Science 204(4392): pp 521—523 DOI: 10.1126/science.107591 PMID: 107591

Vogt, C., and Vogt, O. (1919). Allgemeinere Ergebnisse unserer Hirnforschung, In: Journal of Psychology and Neurology (Leipzig), 25: pp 279–461. OCLC: 671560835 Google Books: BJcXAAAAYAAJ

Yen, C., and Lu, P. (2013). Thalamus and pain, In: Acta Anaesthesiologica Taiwanica 51(2): pp 73—80. DOI: 10.1016/j.aat.2013.06.011
Free PDF on Creative Commons Attribution – NonCommercial – NoDerivs (CC BY-NC-ND 4.0) at http://www.e-aat.com/article/S1875-4597(13)00066-0/pdf


correction for multiple comparison over many ROIs

You have one p-values for each ROI timecourse (for the largest cluster) indicating whether your conditions are exchangeable. If you want to correct for the 4 ROIs you could use any adequate multiple comparison correction, from classical Bonferroni (which might be too conservative as the tests are likely not completly independent) to Benjamini-Hochberg style FDR correction (but applied to the cluster permutation test p-values).

This leaves us with the question which p-values count, one per ROI (the largest cluster, i.e. smallest p-value) or the p-values for all supra cluster-threshold clusters. I would think the former is more appropriate, as you already corrected for the multiple clusters.

That is, for the Bonferroni correction you would multiply your p-values by 4, (or identically, divide your critical alpha by 4).

This solution is incomplete, as I do not know how to get corrected p-values for the second largest cluster with FDR or Holm-Bonferroni.


How long does it take to decide for an multiple choice option with increasing number of choices?

A starting point is Hick's Law:
As noted in the URL, the visual complexity of the choice space may be important independent of the informational complexity of the question options


When I got aware of some ability, I couldn't do it that well anymore

It makes sense that you should either be good at something or not, but in fact our abilities vary a lot under different conditions.
It sounds like what you are experiencing is loss of automaticity. There are things we do best without the interference of the conscious mind, like playing sports or driving or any skill that we have practiced a lot of times. When we pay attention to what we are doing, we may not be able to do the action as quickly or as well.
It might also have something to do with "choking" under pressure to do things well. There was no pressure before you decided you are good at it, then it became harder to do it well after that.
There's an older paper that explores these ideas. Shiffrin, R.M., & Schneider, W. (1977). Controlled and automatic human information processing. II. Perceptual learning, automatic attending and a general theory. Psychological Review, 84(2), 127-190.


How to measure precision in classical test theory framework?

'Precision' in classical test theory
Most accounts of classical test theory do not have a notion of precision as such, but occasionally, reliability may be called precision instead. The relationship is probably most concisely illustrated with the standard dartboards. This is also explained on the Wikipedia Item Response Theory page, but as you can see, in CTT, precision is to reliability what accuracy is to validity.

(Wikipedia Reliability article juxtaposed with a Tufts University guide.
Origin of 'precision' in classical test theory
Cronbach (1951) suggested Coombs (1950) as the origin of the reliability/precision confusion.

Coombs (6) offers the somewhat more satisfactory name "coefficient of precision" for this index which reports the absolute minimum error to be found if the same instrument is applied twice independently to the same subject. A coefficient of stability can be obtained by making the two observations with any desired interval between. A rigorous definition of the coefficient of precision, then, is that it is the limit of the coefficient of stability, as the time between testings becomes infinitesimal.

I'm not entirely sure if I'm interpreting the secondary question right, but IRT precision is a measure of precision under IRT, and ICC is a measure of reliability under CTT. The main difference is that CTT expresses reliability as a single value, while IRT expresses precision for different values of the underlying trait. This isn't specific to absolute agreement, though, so maybe I'm misunderstanding.
References

Coombs, C. H. (1950). The Concepts of Reliability and Homogeneity. Educational and Psychological Measurement, 10(1), 43-56.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. psychometrika, 16(3), 297-334.


Why is it easier to neglect one's self than others?

It seems that what you are describing is Empathy-Altruism.

Debate over whether other-helping behavior is motivated by self- or other interest has raged over the last 20 or so years. The prime people involved in this debate are Daniel Batson arguing for empathy-altruism, Robert Cialdini arguing for self-interest and the works of John Thibaut, Harold Kelley, Caryl Rusbult, and George Homans on Social Exchange Theory

Social Exchange Theory states that human relationships are formed by the use of a subjective cost-benefit analysis and the comparison of alternatives.  The basis is that that altruism does not exist unless benefits to the helper outweigh the costs.

By contrast, C. Daniel Batson holds that people help others in need out of genuine concern for the well-being of the other person.

  The key ingredient to helping is "empathic concern". According to [Batson's] 'empathy-altruism hypothesis', if someone feels empathy towards another person, they will help them, regardless of what they can gain from it.


Are there any introductory books about the relationship between art and psychology/cognition?

Oliver Sacks has an excellent and very approachable book on the topic (psychology/cognition + music in particular, less art in general): Musicophilia.


Problems with using personal feedback to motivate participation in an online psychological experiment?

Ethics of Feedback:

The APA's code of ethics (2010) as well as the Advisory Group on Conducting Research on the Internet (AGCRI) report (2004) summarize ethical issues related to conducting offline and online psychological research.  Feedback is normal in psychological experiments, and researchers are encouraged to debrief participants, before, immediately after, or as soon as the research conducted reasonably allows without risking an effect on results.

Research proposals should undergo an Institutional Review Board (IRB) review prior to initiation.  A consideration with respect to feedback is if it might reasonably be construed by participants as being on a positive-negative dimension (ie , the feedback could be considered negative), then you may want to reconsider providing it, whereas if the feedback is on a neutral dimension (an example would be a personality trait such as placement on an introvert-extrovert dimension), then there is unlikely to be any concern.

Effect of Motivation:

Of course, feedback provided after task completion cannot affect task performance.  Presumably however, the promise or expectation of feedback at the end of a task may have an effect.  Without knowing the nature of the research, the general findings on the effect of incentives on results are that they are negligible if any.  For example, Mason and Watts (2009) find that "Accuracy ... is not reliably different for
different wages," and similarly, a review of online studies conducted on Mechanical Turk (2011) reports that "most workers are not motivated primarily by the financial returns and genuinely care about the quality of their work," and result validity is quite high after some basic spam filtering is applied.

Nonetheless, I would recommend testing the effect of your chosen incentive if at all possible.  This can be done either by comparing results from unincentivized participants to those of incentivized participants, or through validity checks - for example in surveys common practice is to include multiple questions with similar meanings but different wordings to check that they all get similar responses as a way of confirming that answers are legitimate and not just trying to get through the survey as fast as possible.

Completion Rates:

The effect of incentives on task completion in general is very mixed.  Online studies do consistently see greater participation for higher paid experiments, but for non-monetary incentives the results are more complex.  The overjustification effect is an example where incentives may actually reduce task completion rates or performance quality, though this effect is not very robust in practice.      Houmanfar and Hayes (1998) report that "the results indicated no effects of either private feedback or public feedback on task completion," Conrad et al (2010) find that "feedback can improve their experience though not necessarily their completion rates."

The difference between a simple score at the end of the experiment, and more typical notions of gamification may be considerable however.  Gamification in general does have an overall positive impact.    Gamification typically involves a variety of interactive features that come into play throughout the task.  So if at all possible, I would recommend incorporating say, a progress indicator, badge system, storyline, or any other gamification feature that can reasonably be added.  Note that gamification features are not uniformly successful, so some experimentation may be necessary to determine what works best in your particular situation.

Non-contingent Incentives:

One final note: You didn't mention if the feedback would be contingent on completion of the experiment.  While the idea of providing incentives only on task completion may seem intuitively sound, there is substantial evidence that non-contingent incentives are generally more effective.  For example, if you promise to provide a score only on task completion, then fewer people might attempt the task than if you promise to provide a score regardless, and even if completion rates are much lower you might get higher participation overall.  Say only 10 people attempt the task for a contingent incentive, and have a 50% completion rate, then you get 5 results.  On the other hand if 100 people attempt the task for a non-contingent incentive, and have a much lower 10% completion rate, then you get 10 results - twice as many.  Worth considering I'd say.


Is there evidence of a mechanism for transmission of instinct?

http://www.theguardian.com/world/2007/dec/12/japan.justinmccurry
Here they talk about scientist who shut down fear of cat in mice behavior. After genetic engineering the mouse isn't afraid of the cat smell. The conclusion of this study is that fear (at least in this case) is not learned through experience, but a consequence of genetic evolution. In the end, they even explain that mice are still afraid by the sound of the cat. So it's seems to be possible to modify a really precise reaction and not just a large class of behaviors.

Also, all the complex chemicals activities in our brain are coded by dna, so it's not surprising that our instincts are inherited.
For the 99% of dna in common with Chimpanzee, I have to say that 1% is still a big number of genes, and can make a huge difference. Also they might be some part of the dna that are not used anymore in the 99% (they are just relics of evolution).

Actually I found information (one from Carl Sagan) saying that big parts (sometimes 80% or 97%) of our dna are unused. I'm not sure about those numbers thought, and one has to be careful because the sources don't seems to be always reliable to me. (The best might be non-coding dna on wikipedia)

References

Kobayakawa, K., Kobayakawa, R., Matsumoto, H., Oka, Y., Imai, T., Ikawa, M., ... & Mori, K. (2007). Innate versus learned odour processing in the mouse olfactory bulb. Nature, 450(7169), 503. DOI: 10.1038/nature06281 PMID: 17989651 PDF: http://www.academia.edu/download/45075404/Innate_versus_learned_odour_processing_i20160425-21574-dycs42.pdf


How do clinicians control for their own mental disorders?

Clinical Supervision (see these articles on effectiveness) is standard practice and required in codes of practice for registered counsellors, psychotherapists, psychologists, psychiatrists, etc. and those in training.

Note: This is separate and completely different to line-management but necessary for effective line-management

There is no one way to do clinical supervision, but there are a few principles…

clinical supervision allows a person to focus on particular aspects of their clinical practice in a way that they would not normally do
it is characterised by reflection on previous action and its implications for future action
a clinical supervisor will often challenge the supervisee to think outside of their current ways of working
the clinical supervisor will offer support and advice
the supervisee tends to learn alternative ways of working and specific skills
the clinical supervisor will be interested in the quality of the supervisees performance and wellbeing; and will offer constructive feedback

Assuming that all therapists follow the code of practice, all clinicians will be monitored for mental health conditions and other problems which would affect their ability to perform their work effectively.

Clinical supervisors have a duty of care, not only to the supervisee (the therapist), but also the supervisee's clients, and if the supervisor feels that abuse of power is occurring they must refer it to the governing bodies to remove their licence to practice.

If they feel there are any mental health issues preventing the supervisee from acting effectively, then the supervisor will refer the supervisee for therapy.  If necessary, they may also take further action to prevent the therapist from causing harm to their clients whilst undergoing therapy.


Can repetitive sports-related head injuries make a person senile many years later?

yes, here is a nice paper which shows evidence : http://www.nature.com/srep/2013/131017/srep02972/full/srep02972.html

from the paper :
" a report commissioned by the National Football League (NFL), showed that retired players between the ages of 30–49 were 20 times more likely, at a rate of 1.9%, to receive a diagnosis of dementia, Alzheimer's disease (AD), or other memory-related impairments11. Over the age of 50, the proportion diagnosed with one of the above rose to 6.1%, compared with only 1.2% In the general population11. Overall, neurodegenerative mortality of NFL alumni is 3 times greater than that of the general population, with AD and amyotrophic lateral sclerosis (ALS) estimated at 4 times as high '


In an experiment with animated stimuli, should I accept answers during Animation Time and count it into the Response Time?

You could solve this problem telling your participant that they have to answer as soon as they spot the right answer or if you do not want them to answer before the end of the stimuli you can disable answers before the end of the stimuli (normally you write what you expect in the experiment introduction screen).
If you let (want) your participant to answer as soon as they spot the right answer then you should consider as time response the time they took to answer. In concrete:
if the stimuli are presented at time 0 and last 200ms and your participant answer at time 50ms you should record them as answer time 50ms.
As far as I understood you are interested in seeing how long it takes for your participants to spot the right answer. So if you wait till the end of the stimuli for recording their answer you might just see how fast they are in pressing the bottom and not how fast they spot the right answer.


Are behaviourist practices and/or principles still valid and useful?

Turf war mixed with artificial distinctions. Behaviorism can hardly be considered outdated when the most popular therapies are behavioral: CBT, DBT, ACT. Even modern implementations of mindfulness are behavioral. Behaviorism is also popular in performance management and organizational psychology, addiction, instructional design, etc.


What psychophysical research published its data?

It's not exactly what you're after, but the Newcastle Cognition Lab has a data repository. It includes a number of learning curve datasets and other studies that measured response time to various simple cognitive tasks.


Does a recent general review of recurrent neural networks exist?

There may not be a single paper that reviews all models, but I have listed some articles and books below that may meet your needs.

Asakawa, Shinichi. (2003). Psychological applicability of simple recurrent neural networks. Japanese Psychological Review, 46(2), 274-287.

De Mulder, W., Bethard, S., & Moens, M. F. (2015). A survey on the application of recurrent neural networks to statistical language modeling. Computer Speech & Language, 30(1), 61-98.

Jacobsson, H. (2005). Rule extraction from recurrent neural networks: A taxonomy and review. Neural Computation, 17(6), 1223-1263.

Rojas, R. (2013). Neural networks: a systematic introduction. Springer Science & Business Media.

Subathra, B., & Radhakrishnan, T. K. (2012). Recurrent neuro fuzzy and fuzzy neural hybrid networks: a review. Instrumentation Science & Technology, 40(1), 29-50.

Suykens, J. A., Vandewalle, J. P., & de Moor, B. L. (2012). Artificial neural networks for modelling and control of non-linear systems. Springer Science & Business Media.

Zhang, H., Wang, Z., & Liu, D. (2014). A comprehensive review of stability analysis of continuous-time recurrent neural networks. Neural Networks and Learning Systems, IEEE Transactions on, 25(7), 1229-1262.


Empty the small jug.
Fill the large jug.
Use the large jug to fill the small jug. This leaves 2L in the large jug and 3L in the small jug.
Empty the small jug.
Use the large jug to fill the small jug. This leaves 0L in the large jug and 2L in the small jug.
Fill the large jug.
Use the large jug to fill the small jug. This leaves 4L in the large jug and 3L in the small jug.


Statistics books for educational psychologists?

Cross Validated has a long list of answers to, "What book would you recommend for non-statistician scientists?" including an answer from our own @JeromyAnglim regarding SPSS for psychologists. Jeromy has also listed a number of good recommendations in response to The current recommended text for statistics in behavioural sciences, and @Mike suggested one for R users such as myself. I hesitate to recreate their content here because their original wording seems appropriate to preserve, and I'd rather have you read their answers and upvote them than try to take any credit myself.

I'd offer additional recommendations of my own if I had any good ones, but my stats textbooks were pretty deficient in retrospect, and I've had to overwrite a great deal of my formal education in psychological statistics through more diffuse study of sources other than textbooks. My standards for "a firm grip" on statistical research methods are probably more stringent than is truly necessary though, so my experience shouldn't concern you necessarily.

Also, FWIW, I had good but limited experiences with the textbooks that were assigned to me in my graduate stats classes for all areas of doctoral study in psychology (which excluded ed psych at my alma mater). My experiences with these were limited because I borrowed from colleagues instead of buying to save money. I will provide references to these books below. They were assigned by two psychometricians whose professional opinions I hold in high regard, one of whom is the primary author, Bob Rosenthal.

References

Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Routledge.

Rosenthal, R., & Rosnow, R. L. (2007). Essentials of behavioral research: Methods and data analysis (3rd ed.). New York: McGraw-Hill. Presently available used from \$1.11.


How much red/orange is needed to stimulate hunger?

I tried to find a source to back up the claim that 'red' stimulates hunger. I couldn't, and in fact I found a study that suggests the exact opposite: the color red reduces food intake, because it acts like a stop signal (Genschow et al., 2012).

This also reminded me of a study by Brian Wansink and colleagues at Cornell, who had study participants consume Pringles in which every 7th chip was dyed red. They found that these people actually consumed fewer chips than controls (where none of the chips were dyed red). This may be due to the color of the chip, but another likely hypothesis is that  changing colors gave participants an implicit signal of how many chips were eaten. (i.e., if all chips were red, their intake would be the same as controls)

If red/orange does stimulate hunger, it is likely a very weak effect, and highly context-specific. Therefore, asking "how much red" might not be the appropriate question to ask.

  Genschow, O., Reutner, L., & Wänke, M. (2012). The color red reduces
  snack food and soft drink intake. Appetite. LINK

  Geier, A., Wansink, B., & Rozin, P. (2012). Red potato chips:
  Segmentation cues can substantially decrease food intake. Health
  Psychology, forthcoming. PDF


What do brains do when processing information, that Von Neumann machines cannot (yet?) imitate?

I'm taking your question to be equivalent to "how does the human brain differ from a computer?".  Indeed, it's well-established that humans outperform computers in a large number of contexts, but it's difficult to pinpoint exactly why this is.  The best answer you'll get is one that outlines how the two computational systems differ.
Let me start with three obvious differences, which IMHO are the most important:

Brains are analog machines, whereas computers are digital.  This means that brains can apply any number of continuous, non-linear transforms to solve problems.  If you're mathematically or programmatically inclined, here's a wonderful paper that demonstrates how a brain can elegantly and efficiently discriminate between two stimulus frequencies (supplementary materials here if you want to mess with the code yourself).

Brains are good at fuzzy-logic and uncertainty.  Contrary to computers, brain activity can "evoke" or "activate to varying degrees" similar representations.  Intuitively, you can think of this as local activation spreading to adjacent areas (although this is a gross oversimplification).  On a more cognitive level, this enables things such as semantic priming to be implemented quite naturally, whereas this is horrifyingly complex with digital computers.

Synaptic connections are much, much, much, much, much more complex than logic gates.  Synaptic connections can be reinforced and inhibited on either end of the cleft (presynaptic or post-synaptic).  Moreover, the dynamic nature of synaptic connections allows for some interesting emergent properties such as mutual inhibition, or the formation of multiple iso/nullclines in firing rates via more complex interactions (see the Machens et al. paper I linked to in point 1).

With this having been said, let me reiterate the point I made in my previous comment.  Human brains have cognition, in the true sense.  This alone makes them able to solve problems that other systems can't.  To use your own words, humans have conceptual reasoning, whereas computers do not... which is to say the answer was in your question to begin with.
EDIT:
To expand on what is admittedly a not-very-useful last paragraph, it seems as though you are conflating concept and representation.  A concept implies conceptual knowledge, which is simply non-applicable to a non-cognizant system.  As to how the representations differ, this is where point 2 is relevant.  In this case, the representation of a face evokes activation corresponding to various related representations (e.g. on the semantic level).  Importantly, this "spillover" occurs by the very nature of the system -- it's not something that's artificially tacked on.
It's the relationship between your representation, other representations, and the sensorimotor system ("self") that arguably constitute a concept.

References:
Fletcher, P. C., Shallice, T., Frith, C. D., Frackowiak, R. S. J., & Dolan, R. J. (1996). Brain activity during memory retrieval The influence of imagery and semantic cueing. Brain, 119(5), 1587-1596.
Machens, C. K., Romo, R., & Brody, C. D. (2005). Flexible control of mutual inhibition: a neural model of two-interval discrimination. Science, 307(5712), 1121-1124.


Are the human cerebral hemispheres only connected via the corpus callosum?

The corpus callosum is a massive horizontal white matter tract (commissure) that connects the two hemispheres and it is considered the most important route of communication between the hemispheres.

However, there are five additional commissures that cross the midline, namely:

Anterior commissure, connecting the two olfactory bulbs and the temporal cortices;
Hippocampal commissure (psalterium), connecting the two hippocampal formations;
Habenular commissure, connecting the habenular nuclei;
Posterior commissure, connecting the pretectal nuclei, mediating the consensual pupillary light reflex;
Supraoptic commissures (a. Gudden's commissure, or ventral supraoptic decussation connecting the medial geniculate bodies and b. Meynert's commissure, connecting the two suprachiasmatic nuclei*).

Below figure shows the corpus callosum and the anterios commissure:

Saggital section through the human brain showing the corpus callosum and anterior commissure. Source: Brain Atlas.

*The exact connection of Meynert's commissure I am unsure of. This is the best I could do.


Starting academic textbook/survey article for the field of persuasive communication?

I would like to suggest the classic and pioneer book in the field of communication and pursuasion by Daniel H. Pink.
To Sell Is Human: The Surprising Truth About Moving Others
The book not only contains the basics of pursuasions but also explains in detail, why and how things work. Its a master piece!
Hope you would enjoy it.


The hypothesis

The idea that

  Ted Bundy went into trance like states during his killing sprees

is an anecdotal observation which can be true or it may be false.  If we are to be considering it to be true, you could say that what is being described is a severe pathological form of dissociation or compartmentalisation.

I covered the idea of compartmentalisation in a totally unrelated question whereby;

  Compartmentalisation is often employed, for example, by people within the emergency services (fire officers, paramedics, police officers, coastguard etc.) in order for them to concentrate on the immediate task whilst temporarily isolating themselves from their emotions.

Compartmentalisation is a form of dissociation in a sense because dissociation is a psychological defence mechanism (Cardeña, 1994) which helps the person to get through the situation with as little harm as possible. The difference between compartmentalisation and dissociation is that when you are compartmentalising, you are very much aware of what you are doing.

So in conclusion

What is being described fits the description of dissociation but it would have to be a severe pathological form of dissociation.

If Ted Bundy did have real empathy, dissociation would have helped him to disconnect from conscious reasoning and empathy with what he was doing.  During the state of dissociation, you can appear to be in a trance because you are "throwing a switch on conscious awareness" so that you cannot connect with the event alone at any time after the event.

References

Cardeña, E. (1994) The domain of dissociation. In: Dissociation: Clinical and theoretical aspects, Edited by: Lynn, S. J. and Rhue, J. W. 5–31. New York, NY: Guildford Press.


Reference request for creator of heuristic for processing fMRI data (T.Nichols)

I know very little about fmri, but as @strongbad points out, surely it is Professor Thomas Nichols at Warwick.

I'm not sure what the authoritative reference is, but Luo and Nichols (2003) might be worth a look. They state:

  We construct a histogram based on all non-tail data (10th to 90th percentile) and use the location of the minimum bin as the antimode estimate.

Luo, W. L., & Nichols, T. E. (2003). Diagnosis and exploration of massively univariate neuroimaging models. NeuroImage, 19(3), 1014-1032. http://www-personal.umich.edu/~nichols/Docs/fMRIvis.pdf


ANOVA and linear regression are inappropriate when your outcome is a percentage of correct trials, especially so if numbers are near the boundaries 0% or 100%.

Mixed effects logistic regression may be appropriate.

More detailed answers would require more details about your experiment.


How does the brain encode order of information in sentences/stories?

Similar to your other question, this one reduces to "what are the neural mechanisms behind language?", which is very much a work in progress.

The only neural model of language that I currently know of is the Semantic Pointer Architecture (SPA), which is largely theoretical and only has some super basic examples.

Basically, the SPA represents language as vector manipulation. The vectors are represented in neurons using the Neural Engineering Framework.

For more details on how this is done, check out "How to Build a Brain" by Chris Eliasmith and the work by Peter Blouw who is trying to solve part of this problem with his PhD thesis.


Calculate criterion values for each confidence level (within SDT)

There's actually a very simple answer to this question: calculate criterion of confidence level = 3 by counting as hits only those trials where the answer was correct (and the target was there), and confidence was equal or higher than 3.

This is also what Rahnev et al did in the following paper:
Rahnev, D., Koizumi, A., McCurdy, L. Y., D’Esposito, M., & Lau, H. (2015). Confidence Leak in Perceptual Decision Making. Psychological Science, 0956797615595037. http://doi.org/10.1177/0956797615595037


Does monism imply that computers can have consciousness?

Note: While "The Basic Theory of the Mind" may potentially be well researched and possibly accurate, it is (as far as I know) a self-published discourse by a non-researcher, that is not peer-reviewed.  As such, I will not address it specifically.

Monism, the view that the brain and mind are one entity, is often associated with a family of philosophy of mind viewpoints called functionalism - the idea that mental states are defined solely by their functional role.  A related approach is computationalism - the idea that mental states are defined by their information processing function.

Thus, computationalism's answer to the hard problem of consciousness (the question of how the brain gives rise to the mind under monism), is that the mind is an emergent phenomenon due to information processing in the brain.  A well-known theory that supports this particular view with evidence is Integrated Information Theory (IIT).  While this is a popular view, it is not the only one, and hence it is not fair to say that monism implies computationalism.

A list of monistic alternatives to computationalism can be found on Wikipedia.  A couple of interesting examples:

Physicalism: The physical properties of the brain also matter (ie, not just its information processing properties).  This implies that a brain made of silicon, performing the exact same information processing as a brain made of carbon, may not share the same conscious experience, because they are physically different.

Eliminative materialism: Conscious experience does not exist.  That is, people's common-sense understanding of the mind is incorrect, and the mind is essentially reducible to the biological properties of the brain.

Wikipedia also mentions functionalism, behaviourism, type physicalism, and emergentism.  Other alternatives worth mentioning:

Representationalism: The mind is an internal representation of the brain - ie, not a physical phenomenon, but an interpretation of physical phenomena.

Philosophical zombies: The conceivability of a zombie, physically indistinguishable from a human being, but having no conscious experience (no mind), suggests that computationalism is incorrect.

Idealism: We are making a mistake trying to determine how the mind arises from the brain, because it is the other way around - the mind is the fundamental reality from which all else arises.

Cognitive Closure: We simply lack the intellectual capacity to understand the brain-mind relationship.


What forms of the travelling salesman problem are difficult for humans to solve?

I just quickly looked this up on Google Scholar and found the following interesting reference :

JN Macgregor, T Ormerod. "Human performance on the traveling salesman problem." Perception & Psychophysics Volume 58, Issue 4, pp 527-539 (June 1996)

This paper claims that "complexity of TSPs is a function of number of nonboundary points, not total number of points." They define a nonboundary point as a point inside the convex hull that encompasses all points in the problem. This paper also makes some interesting observations about perceptual space for humans in this task, claiming that the problem appears to be solved by humans in a 2D problem space that matches the 2D perceptual space. Finally, the references cited by this paper indicate that at least some research has gone into the question of human performance on the TSP as far back as the late 1960s.

It looks like you might also get some useful pointers by following the citation graph from this paper forward in time : http://scholar.google.com/scholar?cites=9195299723226128892


Name of a cognitive test assessing whether a child can think independently

The first one is a test if a child has understood conservation of matter. It is an example of a conservation task. These belong to the tests used in the framework of Piaget to test what stage of development a child is in.
Here is a video demonstration of the cookie task. Here is another question on this site pertaining to a different conservation task.

The second one is an example of a false-belief task test for the Theory of Mind. See here for some criticism of the false-belief task, questioning if it truly tests what it aims to test.

I don't think it's appropriate to say either of these is used to test if children are "thinking on their own" for what it's worth. They're about developmental stages.


How to transform data to a frequency spectrum?

In the cited paper their methodology is explained in the Materials and Methods section on  p.209, where it says:

  Fig. 4 shows the norm of the CoP during the experiment [...] which are represented by spikes in the norm of the CoP [...] In order to characterize the movement properties of the CoP, we have computed the corresponding spectra over the experiment stages [...]. Fig. 5 shows the spectra of the norm of the CoP [...].

Spectra, or more appropriately called frequency spectra or spectrograms, are typically generated by Fast Fourier Transformation (FFT). FFT essentially decomposes a signal into a collection of sine waves. The x-axis of a spectrogram (like Fig. 5 in the article) represents the frequency of each sine wave, the y-axis the magnitude (amplitude or more aptly the 'power') of each sine wave in the frequency spectrum.


How is the signal-to-noise ratio of an event-related-potential measured?

Based on your comments I interpret your question as:

"(1) What is the definition of the signal-to-noise-ratio (SNR) and (2) how do I determine the SNR for event-related potential (ERP) amplitudes in an EEG signal?".

(1) Signal-to-noise-ratio (SNR) is a term often encountered in electrophysiology (e.g. EEG) and signal processing and can be loosely defined as the ratio of the relevant signal divided by the noise level. The signal in this example is the ERP amplitude, while the noise is the remaining background activity in the EEG that distorts the ERP (unwanted noise). Noise includes hardware noise, movement artifacts by the subjects, random synchronized brain activity and so on. So SNR = signal/noise.

(2) In case of ERP amplitude being the signal you are after, than the noise is the amplitude of the background EEG (SNRERP_amplitude = ERPamplitude / NOISEamplitude). The ERP amplitude can be defined by determining peak amplitude (e.g. relative to baseline). A straightforward (and widely accepted method) to characterize noise amplitude is determining the standard deviation (SD) of the entire EEG epoch (e.g., 500 ms) in which the ERP was recorded (Hu et al., 2010). Then, the SNR becomes ERPamplitude / SDEEGepoch.

PS: your comment

  If the variance approaches to zero, then theory tells me that SNR goes to infinity (a really good signal), but the signal that I will have is useless.

is incorrect. The signal is always part of the EEG epoch. Assuming there is a measurable ERP on a flatline background EEG (amplitude=0), than the signal will be the only thing that adds to the noise component. This is counter intuitive, but note that when noise amplitude is defined as, e.g., the SD, than this SD will be very small as it is determined across the entire EEG epoch. Hence, the peak-amplitude of the ERP will be much larger than the SD. In this ideal ERP recording the SNR will be large, but it will never become infinitely large.

Reference
- Hu et al., NeuroImage (2010); 50(1): 99-111


How to interpret intelligence test scores for an individual who has taken a test multiple times in quick succession?

General points about practice effects

Intelligence tests differ in how much they are subject to practice effects.

Practice effects can also be distinguished:

Time between taking the test: The shorter the timeframe the more likely you will see practice related improvement.
General practice on similar tests and similar items versus practice on the same set of items. In general, practice effects will be greater where the items are identical between test sessions. Adaptive testing where items change each time should show fewer practice effects.
Whether feedback is present. In general participants do not get feedback on what was or was not the right answer, but if they do receive such feedback, then practice effects will be much greater, especially for item specific transfer.

Test-retest variation

Another general point is that intelligence tests have a level of reliability such that a score on a test is only an estimate of an individual's true standing on the latent trait being measured. So obviously, some variation between administrations would be expected purely based on the standard error of measurement.

That said, the general model of test-retest reliability assumes reasonably controlled testing conditions and a participant that is applying reasonable effort.
When these conditions are not met, you could see much more variation:

If a test taker applies minimal effort or is distracted, they may get a much lower score than their true level.
If a test taker cheats in some way they may get a much higher score than their true level.

Issues of administration are more likely in an online environment particularly where there is either (a) no consequences for not applying full effort, or (b) an incentive to cheat.

Interpreting scores of someone who has taken a test multiple times

In general, if you are trying to measure intelligence, you should administer the test once and that first measure would be the measure of their intelligence.

Test administrations that follow immediately afterwards would be contaminated by practice effects. Unless you have a very good understanding of how practice effects operate and how they can be controlled for, then it would be difficult to incorporate information from these subsequent administrations.

That said, if you had additional information that said that on the first administration the participant was not concentrating or fundamentally failed to understand the test, then you may wish to tentatively rely on the score from a different administration.

In addition, a pattern of scores that differ by three standard deviations (e.g., 100, 115, 145) may suggest either that the test has reliability issues or that something strange is happening for that particular individual that you want to look into.


I think, I have found an answer, more or less. There is a person called Sam Vaknin, who published a book called "Malignant self-love". Even though Vaknin is not an academic himself, the book does contain references to more recent studies.


Do the Jungian Cognitive Functions/ Processes really exist?

The research done by Dardio Nardi (the researcher you're referring to) clearly shows that something is there. Although, he would have no way of knowing as to whether his samples were of the particular type, or if what's being demonstrated really demonstrates use of that particular cognitive function. E.g doing something logical doesn't necessarily mean you're 'using' Ti.

I do believe we have innate, instinctive preferences and can classify them into types as such, but I truly doubt that Jung's work would be 100% accurate. Even Jung was hesitant to be exacting in his understanding of the psyche - which lead him to leave a lot of holes in his model.

Myers and Briggs filled those holes with many assumptions - which is why the functions are a far better application to finding somebody's 'type'.

So yes, I would say that they do exist. But probably not exactly in the way they were described by Jung. Hopefully people begin to think critically about this, then maybe we can actually see some results.


Are there specific game mechanics that correlate with addictions?

This article identifies the key gameplay elements (of Candy Crush Saga) that keep players engaged and excited for the next level. A few key quotes are:

  Players experience Beginner’s Luck when they start the early levels, which allow them to easily get three stars for matching candies and crushing them.

This is essentially enticing a user with a quick reward (e.g. an easy to earn badge) to quickly get them hooked on the idea of earning more.

  This is the Free Lunch that makes them feel like they are getting bonuses due in part to their performance.

These could be rewards unlocked as they progress (e.g access to moderator tools on SE).

  a Leaderboard which includes where you rank amongst your friends.

Relatively self-explanatory, but being compared to other users (particularly friends) can be a major motivator to maintain bragging rights.

  Last Mile Drive where the player keeps on playing because they're so close to the goal and they've already invested too much time and energy in the game to quit.

This is an important one in terms of addiction; once you've drawn a user in with other methods, it can get to the point where they have to keep going or else feel they have wasted their time. Of course, with gamification there isn't an end level; you want your application to be used indefinitely.

With all the above said, I think the important thing is not what you implement, but rather, how you implement it. Try to avoid badges such as 200 consecutive logins, and use analytics to watch out for any addictive behaviour.


Psychology behind dumb child doing good in academics

Most people confuse shyness with introversion, and the difference is that shy people do it out of fear, while introverted people do it out of the urge to be alone.

Being shy is a bad thing.

Being an introvert is NOT a bad thing.

People also confuse Dumbness with Gullibility.

Gullibility is a failure of social intelligence, which is again a clear sign of high introversion, and they do that because they're a better judge of character.

Simply put "Intelligent people are more likely to trust others, while those who score lower on measures of intelligence are less likely to do so"

I couldn't do better than this.

source:

https://www.sciencedaily.com/releases/2014/03/140316133840.htm


Short answer
V1 can be recruited for visual imagery, but it is not strictly needed for imagery to occur, and it is not sufficient in itself to allow for visual imagery.

Background
Visual imagery is a complex and broad topic of research. It's in fact a big pain in visual prosthetic research. In this area of research it's often nice to show those fancy pics of deafferented visual areas in the brain to light up after having been deprived of visual activation for years. Then you find those seemingly strikingly activated visual regions by your awesome visual prosthetic, to be shot to pieces later by critical referees that believe it may just as well be that your subjects have been imagining stuff.

Anyway, visual imagery depends on much of the same structures in the visual system as seeing by itself. The retina, being considered part of the central nervous system, and the end organ of the visual system is not involved as it only delivers input by sensing light. Hence the optic nerve is not involved either. After that we have the brain stem and strikingly, already the LGN in the brain stem has been shown to be activated by imagery. And not surprisingly then, V1, being the output location of the LGN, is activated too (Chen et al., 1998).

However, activation of these regions does not mean they are necessary for imagery to occur. Because imagery follows the visual neural path pretty much in reverse, it is the higher association areas in the brain that are most crucial for this process to occur. Indeed, visual imagery has been shown to occur in people with large trauma-related defects in V1 nearly obliterating the occipital cortex (Bridge et al. (2012).

Meta analyses of various studies has delivered a potential reconciliation of these opposing findings. V1 recruitment may depend on the specific type of imagery, and specifically that detailed imagery is more dependent on V1 (Ganis, 2012).

References
- Bridge et al., J Neurol (2012) 259: 1062–70
- Chen et al., Neuroreport (1998); 16(16): 3669-74
- Ganis, Visual Mental Imagery, Springer Link (2012)
- Urbanski et al. Frontiers Integr Neurosci (2014); 8:74

Fig. 1. Visual system. source: Urbanski et al. (2014)


Do unequal step sizes in staircase procedure affect the convergence?

It is going to mean bad things. If you can only create stimuli with a predefined non uniformly sampled set of "levels" then the the corresponding percent correct that the staircase will track will depend on the threshold of an individual observer. For example, if you can create stimuli with levels of 0, 1, 2, 3, ..., 100, 110, 130, 170, 250, 410, where for small levels the up and down step sizes are equal, but for large levels the up step size is twice the down step size. This means the percent correct point is going to be different depending on the threshold of the subject. You wouldn't have to worry about it if you use something like the method of constant stimuli.


What is the difference between implicit and explicit attitudes?

Although implicit and explicit attitudes are not the "same" they frequently overlap (e.g. people that are explicitly racist are usually implicitly racist).  Both are a positive or negative feeling towards an object.  The primary difference between the two is found in conscious awareness of a particular attitude and how the attitude is expressed.  Implicit attitudes are unconscious while explicit attitudes are conscious.  Explicit attitudes are tempered by things like social desirability.  Work with implicit attitudes tests like the IAT have shown implicit biases against things like race, age and sex.  Most people do not explicitly subscribe to these biases but still unconsciously harbor latent preferences.

Check out Project Implicit to take a variety of IAT's and learn more:
https://implicit.harvard.edu/implicit/


Negative thoughts as cause or consequence of depression

Short answer
The cause of depression is thought to be one of neurochemistry, resulting in depressive thoughts.

Background
I think the general consensus is that depression is a psychological disorder with neurochemical causes. In particular, the serotonin hypothesis of depression has received much attention, basically due to the success of the serotonin-specific reuptake inhibitors (SSRIs) that increase overall serotonin levels in the brain. The serotonin hypothesis basically states that depression is the result of a lack of serotonin and its metabolites in the brain (e.g., Nemeroff (1994)). However, the story is of course more complicated that that. For example, other monoamine systems in the nervous system may also be affected.

The general idea is that the consequences of that monoamine imbalance in the brain include depressive thoughts, among other (more physical) effects, such as a loss of weight. The DSM-V criteria for depression include:

  Depressed mood most of the day.
  Diminished interest or pleasure in all or most activities.
  Feelings of worthlessness or excessive guilt.
  Recurrent thoughts of death (APA, 2000, p. 356).

Reference
- Nemeroff, Clin Chemistry (1994); 40(2): 288-95


Is the concept of conservation fundamental to understanding fairness and capacity in "love"?

There are a number of ways to interpret the statement and your question.

One problem is what the age of children being discussed is. There are lots of developmental studies showing abstract thinking not really kicking in until about 5 or 6, but most of them are on physical abstraction. You can look up anything on Piaget's stages of development for this. Abstraction in general id acquired relatively early.

The word "understand" is a problematic bit. Children understand fairness, equal division, etc. at a very young age. I don't even see that as particularly abstract. On the other hand, some people spend their whole lives trying to understand the nuances of what love means. Children have some concept of love at a pretty young.

As near as I can tell, the statement you heard is vacuous without context and intent.


How sexual activity influences a woman's sex drive

The inverse of your first question might hold generally true: that desired sexual frequency could influence a woman's actual sexual frequency.

Willoughby and Vitas (2012) conducted a study focusing on the sexual desired discrepancy between male and females. They make reference to sexual desire discrepancy (SDD) - difference between one's desired frequency of sexual intercourse and actual frequency of sexual intercourse.

  High SDD may then lead some females to put more resources into the
  relationship in order to work toward future sexual contact and
  increase the intimacy and closeness in their relationship. In this
  way, SDD may serve among female partners as a motivator to enhance and
  support the relationship as it progresses toward higher sexual
  frequency.

It mainly would depend on the quality and satisfaction of the sexual intercourse that would determine whether a woman's desire for greater sexual frequency would increase or not. Assuming that quality and satisfaction of sexual intercourse is high for the woman, I would say that this would increase a woman's future desire to have sex. Processes on positive expectancies give rise to higher perceived quality of the sexual relationship (McNulty & Fisher, 2008) and thus, in my opinion, if the woman expects sexual intercourse to be as good as a prior experience, they're more likely to desire it more.

So, perhaps deprivation or excess of sexual intercourse and expectancies of quality of sexual intercourse plays a major role in moulding sexual desire for women. Another thing: while the frequency of sex is predicated on the physical rewards of it for men, this may not be necessarily true for women.

References

Willoughby, B.J. & Vitas, J. (2012). Sexual desire frequency: The effect of individual differences in desired and actual sexual frequency on dating couples. Archive of Sexual Behavior, 41, 477-486.
McNulty, J.K. & Fisher, T.D. (2008). Gender differences in response to sexual expectancies and changes in sexual frequency: A short-term longitudinal study of sexual satisfaction in newly married couples. Archive of Sexual Behavior, 37, 229-240.


Is psychotherapy more effective when examining free association speech than writing?

Free association is an integral part of depth psychological therapy (such as psychoanalysis), which is still prevalent around the world (e.g. in Germany depth psychological therapy and cognitive behavioral therapy are the only two therapies paid for by health insurance).

The problem with writing would be that it slows down the interactive process between therapist and client. It has been suggested and there is anecdotal evidence that outside of a therapy, free association writing can be a useful tool for self-knowledge. Within a therapy free association is only one part of the methods and its usefulness is dependent on other processes such as transference and countertransference, which need the presence of a therapist.

To my knowledge, there have been no attempts at purely written (e.g. online) depth psychological psychotherapy. I believe such an impersonal setting and slowed down communication would hinder the interpersonal processes and actually the spontaneous workings of the subconscious needed for depth psychological psychotherapy to work.


Short answer
Given the fact that literature on hypoxia consistently report euphoria as a symptom, my conclusion is that the two are correlated strongly and is not confined to a small subset of susceptible people.
Background
Personally I know only of the effects of oxygen on the central nervous system under conditions of increased oxygen pressure, as for example encountered by scuba divers at depths greater than standard recreational diving. In that case it is called oxygen intoxication or oxygen toxicity (e.g., Chawla & Lavania, 2001), characterized by e.g.:

visual changes
tinnitus
irritability, anxiety, confusion
vertigo.

Hypoxia (Asmaro, Mayall & Ferguson, 2013) can indeed lead to

Euphoria and feelings of well-being
Acute anxiety, irritability & confusion
confusion, loss of consciousness.

The authors however only qualitatively analyzed their group of test subjects on these subjective mind states and describe quantitative statistics only on psychophysical tests. The latter were indeed significant, showing that hypoxia leads to changes in performance on a variety of tasks in most, and probably all subjects.
To proceed to your question - hard numbers on the prevalence of feelings of euphoria are difficult to find, yet credible reports that mention it as a symptom are abundant. For example, the self-asphyxial risk-taking behavior (SARTB) you mention is known to lead to euphoria and is thought to be one of the motivations behind the 'game' (Griffiths, 2015; Busse et al., 2015).
The fact that hypoxia is a general term for a range of blood oxygenation levels, and the complexity of the cerebral cortex, variability in susceptibility is to be expected. For example, hyperoxic effects depend strongly on the altitude (i.e., partial oxygen pressure) Chawla & Lavania, 2001).
References
- Asmaro, Mayall & Ferguson, 2013
- Busse et al., Arch Dis Child (2015); 100(12): 1106–14
- Chawla & Lavania, Med J Armed Forces India (2001); 57(2): 131–3
- Griffiths, Education and Health (2015); 33(3): 54-6


Psychology of betting against a desired outcome as “compensation”

This is related to the concept of utility of outcomes, as well as the idea of hedging in gambling. When you have a favorite sports team that you want to win, it's very similar to implicitly placing an emotional "bet" - if your team wins, you gain positive utility, while if they lose, you get negative utility. By betting against your desired outcome, you are hedging the bet, which is a way of betting on both outcomes such that you can guarantee a profit, or at least minimize your losses.
By betting for your favorite team, you have an all-or-nothing outcome - you'll either be happy with the outcome and win cash (both good), or be unhappy with the outcome and lose cash (both bad). By betting against your favorite team and hedging your bet, you'll have a more moderate outcome no matter what - you'll either be unhappy but win cash, or be happy and lose cash. Whether hedging a bet is worthwhile will come down to your level of risk aversion, as well as the utility you assign to the cash, a win, or a loss.


How happy are people relative to neutral (as measured by experience sampling)?

I just finished reading this article (2018) by Michael Plant, a PhD student at Oxford University.  Given that it is not a peer-reviewed paper, it would be worth checking his references, but this is what he says about the neutral point:

  Life satisfaction surveys don’t ask people to specify what point on
  the 0 to 10 scale they would consider equivalent to not being alive. 0
  is labelled not at all’ and 10 ‘completely satisfied’. ... How could
  we settle where the neutral point is? Two strategies seem possible.
  First, we could find out at what LS scores individuals report their
  lives are neutral on experience measures of SWB. Second, we could poll
  people to ask at what LS score out of 10 they would be indifferent
  between living with that score for the rest of their life or dying. I
  am unaware of any analysis which has been conducted along either
  lines. Thus, for the moment, this unfortunately remains a point of
  armchair conjecture.

Note: LS = Life Satisfaction; SWB = Subjective Well-Being.


What is, formally speaking, major depressive disorder?

The ICD and DSM definitions can be a bit opaque, but there are several criteria that are usually considered necessary for diagnosis. Different practitioners may diagnose more conservatively or more pervasively, but those differences are based on their professional experience, and they are all meant to interpret from similar guidelines. Because there are different severities of depression, as with any illness, diagnosis relies also on the subjective judgement of a doctor or other mental health practitioner.

Generally, if one experiences a persistently low mood and low energy for a period of longer than two weeks, they may be diagnosed with so-called "clinical" depression. Usually this entails disruption to one or more aspects of daily living, e.g. food, sleep, interpersonal relationships, work or hobbies. This type of disruption is sometimes termed "clinically significant distress", a fairly common criterion for mental illness.

Prevalence is difficult to accurately assess. The NIMH reports 6.7% 12-month prevalence in the US. The CDC has a map of US states showing statistics for current depression, ranging from under 5% to as high as 15%. Other statistics exist in other countries. These data may reflect the best methodology available, but they are still fallible. Epidemiology of mental illness is a difficult field of study.

The inventory you cite is one of several commonly used ones. It's also important to remember that a psychiatrist will not rely on self-report questionnaires for diagnosis. A doctor would conduct a thorough intake interview which takes into account many other factors. A fifteen or twenty question survey is not sufficient to definitively diagnose anyone.


Full list of the capabilities of human brain

The length of your question and it's tags make it quite confusing, however what you mentioned about the brain processing tasks sequentially and then hitting an efficiency bottle-neck when using conflicting resources reminds me of the research of Neils Taatgen.

He uses a cognitive model called ACT-R to do computer simulations to predict what efficiency bottle-necks a person might experience. His research might help clarify some theories you have.


Can an axon connect to dendrites of multiple other neurons?

Sure, look at the connectome of C. elegans for example: URB (circled in red) has synaptic connections to IL1, RIC and also to CEP (which also synapses back to URB, showing that cycles in the connectome are possible). Likewise RIS (circled in blue) has synaptic connections to at least 4 different neurons (in this map) and a couple more off-map.

(click to enlarge)