How to estimate IQ for public figures? Background: I read a question on Quora that asked how intelligent is Barack Obama. A wide range of arguments were presented. The tone of the answers was not neutral because of the political context of the question. Furthermore, over the while I've read estimates of intelligence of various famous people from history (e.g., scientists, presidents, etc.). Issues were also raised about how intelligence is defined (e.g., cognitive, social, emotional or physical; achievement versus latent ability, etc.)
Despite these issues, I find the topic interesting.

Questions:

If you cannot administer a standardised intelligence test to someone, to what extent can you obtain a good estimate of their IQ from the kinds of information available about public figures?
What is considered scientific best-practice in this regard?
How accurate is best practice? Do any studies provide validity estimates (e.g., correlating estimates with actual IQ test scores)?

In relation to public figures, a wide range of information is often available: e.g., demographics, educational attainments, career achievement, writing samples, personal achievements, samples of public speaking, and so on. Sometimes, information such as school and university grades will be available. Of course, a lot of this information will be non-standardised. I wonder what would be a good way to collect and synthesise this information to generate a prediction.

Entry into the literature

As a starting point, Simonton (2009) provides an excellent introduction to the field of historiometric assessment of intelligence. To quote the abstract:

  Running parallel to mainstream research on the psychometric assessment
  of intelligence is another tradition of research on the historiometric
  assessment of intelligence and closely affiliated variables.
  Historiometric assessment is based on four data sources: (a)
  personality sketches (e.g., Intellectual Brilliance), (b) developmental histories (e.g., IQ), (c) content analyses (e.g., integrative
  complexity), and (d) expert surveys (e.g., Openness to Experience).
  The first two represent major lines of intelligence research that
  involved key figures in the development of corresponding psychometric
  methods (e.g., Galton, Terman, and Thorndike), whereas the last two
  constitute independent research paradigms that later intersected with
  the first two. The literature on U.S. presidents then provides an
  integrated illustration of the four historiometric approaches and how
  they converge on the same broad conclusions. Significantly,
  historiometric investigations on the relation between broadly defined
  intelligence and adulthood achievement obtain about the same effect
  size as that found in psychometric research (i.e., $r$ or $\beta$ .25 $\pm$
  .10). Because historiometric and psychometric studies have rather
  distinctive methodological advantages and disadvantages, this
  consistent outcome provides corrobora- tive support for both sets of
  empirical findings.

The review summarises various studies aiming to assess intelligence of royalty, U.S. politicians, and eminent figures.

Critical thoughts

For current and recent public figures substantial additional information would be available. In particular, many powerful predictors of IQ would often be available including university grades, scores on standardised assessments, SAT scores and so on. Furthermore, the existing literature on IQ correlates is huge and provides substantial information that could inform predictive models of IQ prediction. In contrast where such models are applied to the past, the predictive power of such models may be wrong.

I'd also be extremely wary of estimates of intelligence that yield estimates like 200 (i.e., around 7+ standard deviations above the mean). E.g.,

  After comparing the chronological age in which .. achievements
  appeared with the mental age that they represented, Terman decided
  that Galton’s IQ must have been close to 200. (Simonton, 2009, p. 319)

The expertise literature has highlighted the importance of not confusing eminence with IQ. Eminence is substantially influenced by years of practice, training, focus, opportunity, and luck. IQ is useful, but the correlation between IQ and eminence is insufficient to yield the kind of certainty in prediction to result in IQ predictions above something like 3 or perhaps 4 standard deviations above the mean (i.e., 145 to 160).

References

Simonton, D.K. (2009) The “other IQ”: Historiometric assessments of intelligence and related constructs. Review of General Psychology, 13, 315.


Fitting a psychometric function when data does not lend itself to a sigmoidal fit I'm fitting a psychometric function to a range of data. The majority of this data lends itself to a sigmoidal fit (i.e. participants can do the task), but some individuals are absolutely unable to do the task. I'm planning to compare the slopes obtained from different conditions, but I've hit a wall with the unable-to-do-the-task data.

Fitting a function to this data, the slope should be nearly flat, right? However, the data is really noisy and some weird fitting is occurring - I end up getting erroneously high slopes. I'm using pypsignifit, the parameters I'm using can be seen below. Any idea how to stop this happening?

num_of_block  = 7
num_of_trials = 20

stimulus_intensities=[3, 7, 13, 20, 27, 32, 39] # stimulus levels
percent_correct=[.38, .75, .6, .43, .7, .65, .43]     # percent correct sessions 1-3
num_observations     = [num_of_trials] * num_of_block      # observations per block
data= np.c_[stimulus_intensities, percent_correct, num_observations]
nafc = 1
constraints = ('unconstrained', 'unconstrained', 'unconstrained', 'Beta(2,20)' )
boot = psi.BootstrapInference ( data, core='ab', sigmoid='gauss', priors=constraints, nafc=nafc )
boot.sample(2000)
print 'pse', boot.getThres(0.5)
print 'slope', boot.getSlope()
print 'jnd', (boot.getThres(0.75)-boot.getThres(0.25))

What you are looking for is called Hierarchical, Multi-level or Random-effects model. In your particular case the solution is a hierarchical logistic regression.

Assume $y_{st} \in \{0,1\}$ is the response of subject $s$ on trial $t$ and $x$ is the dependent variable then a simple hierarchical model that solves your problem is:

$y_{st}\sim \mathrm{Bernoulli}(\mathrm{logit}(\alpha_s+\beta_s x))$

$\beta_s \sim \mathcal{N}(\mu,\sigma)$

where $\mu$ is the population value of the slope and $\beta_s$ is the subject level estimate. Roughly, $\mu$ is a weighted average of all $\beta_s$ where the weight of each $\beta_s$ is inversely proportional to the variance of the estimate of $\beta_s$. For more details on hierarchical logistic regression and for extensions of the simple model, that I have suggested above, refer to Chapter 14 in Gelman & Hill (2006).

  Fitting a function to this data, the slope should be nearly flat, right?

No. The slope should be uncertain. Flat slope looks differently, say $(10,0.61), (20,0.59),(30,0.6),(40,0.58),(50,0.6)$. The corresponding estimate of $\beta$ should show wide interval such that you can't conclude that $\beta>0$ or $\beta<0$ or  $\beta=0$ (as you suggested).

How will a hierarchical model handle such uncertain $\beta_s$? This $\beta_s$ will contribute little to the estimate of $\mu$. Instead $\beta_s$ for this particular subject will be pulled towards $\mu$. The hierarchical model will effectively tell you that if your data is inconclusive, it will just assume that the subject is a typical member of the population (that is if $\mu$ had been estimated reliably) and discard the erratic data.

Literature:
Gelman, A., & Hill, J. (2006). Data analysis using regression and multilevel/hierarchical models. Cambridge University Press.


Why does the summer holiday go so quickly? Take 6 weeks at school or work and it'll feel like an eternity, If your out with your mates or on holiday, time flies! Why do we feel like this considering everyday contains 24 hours.

Please check the answer to this question, Why do some days feel fast and others feel slow?, think that is the answer you are looking for.


Terminology for introvert's frustration after excessive social exposure Does anyone know if there is a phrase or term that describes the frustration an introvert experiences when they have had too much social exposure and need to be alone?

As an analogy, I recently heard the phrase "hangry" used to describe the state of anger/irritability that some people suffer when they are hungry, and find it infinitely useful to instantly convey that state of emotion with a single phrase.

Having a similar phrase so that others know that a person isn't upset with them, but just needs to be alone would save me, and probably many other people, a lot of frustration.

This does not constitute a definitive answer, so I invite criticism and feedback.

I don't believe there is a specific term for this state, as energy management and the introversion/extroversion scale seem to be a somewhat recent area of focus. However, it seems reasonable to think that the feelings experienced by an over socialized introvert may be similar to experience of decision fatigue, which is when the quality of ones decisions worsen the more decisions they need to make.

Since socialization for introverts often requires more deliberate internal calculations than extroverts, decision fatigue and the experience you're seeking a name for might be cousins. As such, perhaps 'social fatigue' is a useful term.


Correlation between anorexia and mass media stereotypes I know anorexia is a complex phenomenon.
I've been reading on Wikipedia that:

  Sociocultural studies have highlighted the role of cultural factors,
  such as the promotion of thinness as the ideal female form in Western
  industrialized nations, particularly through the media. There is a
  necessary connection between anorexia nervosa and culture; culture may
  be a cause, a trigger, or merely a kind of social address or envelope
  which determines in which segments of society or in which cultures
  anorexia nervosa will appear. The strong thesis of this connection is
  that culture acts as a cause by providing a blueprint for anorexia
  nervosa. A moderate thesis is that a specific cultural factors trigger
  the illness which is determined by many factors including family
  interactions, individual psychology, or biological predisposition.
  Culture change can trigger the emergence of anorexia in adolescent
  girls from immigrant families living in highly industrialized Western
  Societies.[89] People in professions where there is a particular
  social pressure to be thin (such as models and dancers) were much more
  likely to develop anorexia during the course of their career,[90] and
  further research has suggested that those with anorexia have much
  higher contact with cultural sources that promote weight-loss.

Source: Sociological section of Wikipedia on anorexia nervosa

It seems that the mass media can contribute in the diffusion of anorexia.
But I wonder if statistics suggest that this disease has got a boom of cases of in the last years.

Source: Media effects section of Wikipedia on anorexia nervosa

Short answer
According to a study dating 6 years back, the incidence rate of anorexia nervosa was stable over several decades.

Background
According to a review paper published in 2012, the overall incidence rate of eating disorders, including anorexia, was stable over the previous decades.  However, there was an increase found in the high risk-group of 15–19 year old girls, but that might have been due to earlier detection of anorexia nervosa cases or an earlier age at onset (Smink et al., 2012).

Given that the tendency nowadays is a moving away from the stereotypical barbie-sized waistlines I reckon above study is a valid source of information, as I do not expect the number of anorectic people to be soaring.

Interestingly, while there are hosts of studies linking mass media and stereotyped ideal bodily proportions, a review study puts these findings in a different spot light. While the authors recognize mass media and eating disorders are linked, they question the size of the impact mass media has on these disorders. They did this by studying the correlation between social media versus negative body image and disordered eating in females (Levine & Murnen, 2009).

References
- Levine & Murnen, J Soc Clin Psychol (2009); 28: 9-42
- Smink et al., Curr Psychiatry Rep (2012); 14(4): 406–14


Is it possible to objectively measure the amount of pleasure a person is experiencing? I'd like to know if it's possible to quantify somebody's "fun meter". Maybe by measuring the amount of endorphin produced. Because every person is unique, I don't expect that amount to make another person feel exactly as much satisfaction, but I'm ready to be proven wrong.

Are there any existing methods to objectively measure pleasure?

This is a very general answer to your question. And let me say upfront that I don't know about any measurement instruments for pleasure. However, I would like to emphasize that pleasure, just as about any psychological phenomenon, has to be considered a latent construct. What this means is that it cannot be measured directly, but only indirectly and imperfectly through a bunch of indicators. It is actually important to have more than one indicator in order to estimate how reliable the measurement is. Since you asked wether it is possible to measure pleasure or not, my answer is yes.

The question then becomes what the indicators are, that allow one to measure the amount of pleasure someone is experienceing. They should be derived from a theory about what pleasure is. In the reference that @GregMcNulty gives in the comments, for instance, the amount of pleasure is measured predominantly by activity in the prefrontal cortex. But it is also stated that "From a biological perspective, pleasure is not a unitary experience in the brain. It’s not just one region that is activated when we find pleasure in something or someone." That's speaking to the notion of having more than one indicator.

Whatever way you do it, though, you will have to come up with a good theory on what pleasure is and then find indicators. And with a construct as complex as pleasure, it is important to keep in mind that you will always have measurement error.


Why is it hard to simulate a neuron? I read a NY Times article about the European effort to simulate a human brain and the criticism regarding the (non-)feasibility of such an endeavor (not to mention the astronomical costs).

In this article, there's mention of the current inability to simulate the 302 neurons in a nematode brain, so my (layman's) question is simple:

why is it so hard to simulate a neuron?

Complexity.  That is, the fundamental laws governing the behavior isn't terribly difficult to comprehend or model.  However, putting it all together and hoping it reproduces the correct behavior is a great challenge.

Once you develop a model that has the appropriate underlying mechanisms in it's components, you still have to put them all together and choose the right parameters and hope you didn't miss anything in terms of modulators that would actively adjust those parameters.  So even if the functional mathematical form of your model is correct, you still have 5-10 parameters for each neuron in the network that you have to get to the right value, including the parameters describing the strength and dynamics of the coupling between neurons.  Just being off by values as small as .001 can sometimes mean the difference between a working model and a failing model.  Now you have 5-10 parameters for 300 neurons... that's 1500-3000 parameters that all need to be "correct" at the same time.

That being said, it's not like we are exceedingly accurate in our models of even single neurons.  We make simplifications and take averages.  There's lots of second messenger and genetic processes involved in neuron function that many models neglect.  This isn't meant to disparage modeling.  It implies that no complex mathematical model will probably ever be able to generalize the neuron for all cases.  Instead, we make models focused on asking specific questions.  We investigate two or three mechanisms at a time and hold all the other considerations constant in order to isolate those mechanisms we're interested in.  So a model I develop to study the effects of the diversity of calcium channels on neuron excitability will have many differences (in parameters selection) from the same model used by somebody studying diversity of potassium channels.  And in some cases, we may even simplify less relevant aspects of the model, e.g., I may only have one potassium channel in my neuron to generalize and average all potassium channels so that I can focus only on calcium diversity and not fuss with more parameters.


How to help relieve test-anxiety in others I teach, as a layman, young adult students who mostly try to get a degree part-time whilst juggling full-time jobs and small crumbs of left-overs of a  private life.

As it is hard for them to do rock-solid preparation, there is often a serious amount of test-anxiety close to the exams and up to the point where they forget something they definitely had down before. I want to educate myself on techniques to relieve test-anxiety in others as a teacher. Google gives innumerable hits for relieving that form of stress yourself, but not from the educator's viewpoint. Any help would be appreciated.

Being a layman, you can only give advice to the students. When their test anxiety is serious, the best advice you can give them is - seek professional help.

There are, as you say, numerous ways to relieve 'normal' anxiety. A good web source is WebMD, that gives the following tips, which may aid your students too:

Learn your students to study efficiently; your institution may offer dedicated study-skill courses to the students;
You can learn them test-taking strategies;
Students feel more relaxed if they study systematically and practice the material that will be on a test. Establish a consistent pretest routine. That way they'll learn what works best for them, which eases stress levels;
Teach them relaxation techniques. There are a multitude of them, applicable to either right before the test, or during the test to help them stay calm, e.g., breathing techniques, muscle relaxing strategies, closing the eyes and imagining a positive outcome, or meditation techniques;
Remind them to eat and drink. Their brain needs fuel to function. They should eat a meal before the test and drink plenty of water. However, sugary drinks such as soda pops can cause the blood sugar to peak and then steeply drop. Also, caffeine may not be wise as it can increase anxiety;
Let them exercise. Regular aerobic exercise, and exercising on exam day, can release tension;
Urge them to get plenty of sleep. Sleep is directly related to academic performance. Preteens and teenagers especially need to get regular, solid sleep;
Make sure your students can openly discuss anxiety issues with you;
A student may have a learning disability that requires professional help. Test anxiety may improve by addressing the underlying condition that interferes with the ability to learn, focus or concentrate — for example, attention-deficit/hyperactivity disorder (ADHD) or dyslexia. If a student has been diagnosed with a learning disability you can provide them with assistance with test taking, such as extra time to complete a test or having questions read aloud;
And again - urge them to seek professional help, if necessary. Talk therapy (psychotherapy) with a psychologist or other mental health provider can help them to work through their feelings, thoughts and behaviors that may cause or worsen anxiety. You can ask around at your institution if it has a counseling service in-house, otherwise you can advise your students to seek professional help outside the school's setting.


In psychophysics, why are log luminance rather than absolute luminance values reported? Are there any papers which justify converting into log luminance? For example papers showing humans being sensitive to changes in log luminance rather than luminance per se?

In general, subjective sensation increases linearly with the the log of physical intensity, which is described by Fechner's law.

We are sensitive to small variations when light is dim, but we need large differences in intensity under conditions of high luminance (Weber's law). This is a linear relation, but taken together with Fechner these findings are described as the widely-known Weber-Fechner's law, justifying the log scales used.

Another well-known example is the decibel scale in hearing, which is also a log scale.

Any basic textbook on perception or psychophysics will explain this and a reference is added below.

Reference
- Masin et al., J History Behav Sci (2009); 45(1): 56–65


How to define "current" in artificial neural network? How do neuroscientists define current/current densities in artificial neural networks?

Assume I have some deep network and I would like to study its dynamic/evolution in time during the training session what kind of model are there to study the flow?

Maybe there is some information I can extract from the PDE's of back-propagation? or some evolution of the Graph $G=(V,E)$ in time.

Short answer
In artificial neural networks currents are not involved, other than those flowing in silico in your pc. Instead, those currents are represented by weighted mathematical functions.

Background
Artificial neural networks as applied in machine learning (e.g., deep learning) perform stuff like automatic feature extraction from raw data, also called feature learning. These models are algorithms that have little to do with the basic physiology of neurons. Hence, current/current density is not a matter of interest. It's the coupling between elements that matters, namely which cells couple to which cells and how strong that interaction is (Fig. 1).

  A given node [(Fig. 1)] takes the weighted sum of its inputs, and
  passes it through a non-linear activation function. This is the output
  of the node, which then becomes the input of another node in the next
  layer. The signal flows from left to right, and the final output is
  calculated by performing this procedure for all the nodes. Training
  this deep neural network means learning the weights associated with
  all the edges.

source: Towards Science

In other words, there is no current involved, only weighted functions.

Artificial neural network. source: Towards Science


Where to find historical dream activity data? Is it just me, or are we dreaming less? Maybe it's the computer screens in our face all day. Maybe that's just what happens when we get older.

I'm wondering if there's a resource of some kind to determine historical dream activity. Might it be possible to use Google Trends to determine dream activity (similar to how Google Flu tracks illness via search queries).

Or is Google too novel a tool, and are dreamers searching too randomly to track any meaningful delta in dream activity? If so, is there another resource that might provide meaningful dream data?

I think you need to distinguish dream activity and dream recall. I thought that everyone dreams every night. However, many factors influence whether we recall the dreams.

Thus, I think a more productive search would be to focus on the factors that influence dream recall, and perhaps the prominence of dreams in peoples lives.

I found one older article by Cohen (1973) which summarises research on the frequency of dream recall. He states that

  Frequency of dream recall is affected by physiological, methodological, and psychological factors.

Beaulieu-Prevost and Zadra (2005) writes

  Schonbar (1965) suggested that people who remember many dreams are
  generally interested in dreams, in trying to understand them, in
  increasing their dream recall frequency, and tend to have an overall
  positive attitude towards dreams.

Beaulieu-Prevost and Zadra (2005) then go on to cite numerous such studies.

Thus, the next question would be whether the factors that influence dream recall have changed over recent history.  Palagini et al (2011) might provide a useful starting point as they review historical perspectives of dreaming.

References

Beaulieu-Prévost, D., & Zadra, A. (2005). Dream recall frequency and attitude towards dreams: a reinterpretation of the relation. Personality and individual differences, 38(4), 919-927.
Cohen, D. B. (1969). Frequency of dream recall estimated by three methods and related to defense preference and anxiety. Journal of Consulting and Clinical Psychology, 33(6), 661.
Palagini, L., & Rosenlicht, N. (2011). Sleep, dreaming, and mental health: A review of historical and neurobiological perspectives. Sleep medicine reviews, 15(3), 179-186.


Which characteristics of neural activity patterns underlie conscious experience? Which specific characteristics of neural activity patterns are unique for the cortex and neocortex as the presumed "seat of consciousness" and can only be observed there? Activity patterns having these characteristics would be candidates for "neural correlates of consciousness" and so to speak are responsible for or underlie conscious experience. Furthermore, it would be "explained" why neural activity in other parts of the brain don't (directly) affect conscious experience.

I especially wonder on which level of description and observation and on which spatio-temporal scales these activity patterns (and their characteristics) would be found. It could be

on a subneuronal level
on the level of single neurons
on the level of small groups of neurons, e.g. cortical columns
on a voxel level
on a ROI level

With "characteristic" I mean something like

"reentrant signaling states in some specific forms" source
some forms of synchrony, resonance, or general structuredness

but it would have to be defined in a specific way such that it is unique and characteristic for the cortex and would not be found in other areas of the brain.

Are there at least some preliminary and not too abstract answers around? Known neural-based explanations of consciousness I am aware of (and that are summarized for example here or here) don't give explicit answers to my question but often remain rather abstract and often don't explicitly argue that the processes they describe only do and can occur in the cortex - let alone what is "really characteristic" for them as spatio-temporal processes.

If experts here would say that this question in this form is unanswerable or otherwise ill-posed it would be great to know. Thanks a lot in advance.

As discussed previously in this thread, information (specifically, information that exists in the neural circuits), is probably the physical quantity that correlates perfectly with consciousness and, I would like to add, qualia. This is because information can have the same complexity, dynamicity, and content as consciousness and qualia do.

Now, what is the specific neural activity that is or contains information among neural circuits. When a neural circuit is functioning, there are many activities going on in and around that neural circuit: signal processing activities, metabolic activities, structural maintaining (of membranes, organelles, cytoskeletons, etc.) activities, circuit modifying (of synapses, dendrites, axons) activities, changes in supplying blood circulation, oxygen, and other blood constituents, changes in its physical constitutions (temperature, mass, entropy, etc.), etc. But the only activity that has the complexity, dynamicity, content containing capacity as the information does is the signal processing activity. Moreover, it’s the only activity that can communicate locally and extensively with its counterparts in other neural circuits.

So, from current evidence, it is to be concluded that neural processing activities, with its correct spatio-temproal and other profiles, underly the brain’s information-related functions, including consciousness and qualia. Clinical and experimental evidence strongly supports this concept. Anything (such as a certain disease or drug, brain electrical stimulation, or transcranial magnetic stimulation) that mainly affects neural transmissions and significantly interferes with the signal processing activities but does not significantly interfere with other activities significantly interferes the brain’s information-related functions, such as consciousness and qualia. Moreover, the change that occurs in the signal processing activity and that in the brain’s information-related functions (such as consciousness and qualia) occur simultaneously! For more detailed discussion about this matter, please read ref 1 and ref 2.

Now, why do some signal processing activities have qualia or consciousness, why some don’t? There are different explanations for this from some existing theories. The Integrated Information Theory [IIT][3-6] asserts that a conscious experience is a maximally irreducible conceptual structure (MICS), which corresponds to a local maximum of integrated conceptual information (or a local maximum of Φ or Φmax) and provides mathematical formulations to calculate Φ. So, according to this theory, for any signal processing activity to be conscious, it must be complex in a certain way enough for its Φ to reach Φmax there. For example, from its calculations, there is no consciousness during sleeps, generalized seizures, or in the cerebellum – which are all true – even if, in the last two examples, active and complex processing activities are going on. It also calculates that processing activities in computers or robots, no matter how complex, can’t become conscious because they function from fixed software, which isn’t really complex in the IIT way.

According to The Basic Theory of the Mind [1,2], not all signal processing activities can be qualia or consciousness. To be qualia or consciousness, the signals from signal processing activities not only must be accessible by the consciousness neural process but also must be in some specific forms that mean qualia or mean consciousness in the nervous system language, that is, the signals must be in some specific forms that, when processed by neural circuits in the nervous system, will be interpreted to be qualia or consciousness. The theory called this kind of signals “Special signaling pattern” and “Special signaling state”. This is like why all words, except the word is this specific form “consciousness”, do not mean consciousness in English. However, although the theory gives some preliminary characteristics of these special signaling forms, it admits that the complete characteristics of these special signaling forms are not known at present but predicts that these specific forms exist and can be found by investigations.

According to the Adaptive Resonance Theory (ART)[7,8], “all conscious states are resonant states, but not all resonant states are conscious states”. The resonance states must be accessible to consciousness to be conscious. “Indeed, some resonant states, such as the storage of a sequence of events in working memory before rehearsal occurs, or the entorhinal–hippocampal resonances that may dynamically stabilize the learning of entorhinal grid cells and hippocampal place cells, are not accessible to consciousness.” So, they are not conscious. Also, the resonance states must be in some forms to be conscious – they must involve the processes of learning, expectation, and attention. For example, “What sort of resonance supports a conscious percept of surface brightness or color? As noted above, I have predicted that such a consciously visible percept is supported by a surface shroud resonance between visual cortical areas and the parietal cortex that is predicted to play a role in learning invariant object categories (Section17).This prediction illustrates how ART clarifies mechanistic relationships between the CLEARS processes of consciousness, learning, expectation, attention, resonance, and synchrony.”

I think these are some preliminary answers that I can gather from some existing theories. They are certainly not the widely-accepted, standard answers. And there are other theories that I’m not familiar with, such as ref 9-11, which may have the answers you’re looking for. So, if you are intereseted and have time, please examine them.

References:

Ukachoke C. Chapter 5 – Theorem IV: A Quale is a Special Kind of Signaling Pattern In: The Basic Theory of the Mind. 1st ed. Bangkok, Thailand; Charansanitwong Printing Co. 2018.
Ukachoke C. Chapter 6 – Theorem V: Consciousness is a Special Kind of Reentrant Signaling State In: The Basic Theory of the Mind. 1st ed. Bangkok, Thailand; Charansanitwong Printing Co. 2018.
Tononi G. An information integration theory of consciousness. BMC Neurosci 2004,5:42. DOI: 10.1186/1471-2202-5-42.
Tononi G. Integrated information theory of consciousness: An updated account. Arch Ital Biol. 2012 Jun-Sep;150(2-3):56-90. DOI: 10.4449/aib.v149i5.1388.
Oizumi M, Albantakis L, Tononi G. From the phenomenology to the mechanisms of consciousness: Integrated Information Theory 3.0. PLoS Comput Biol. 2014 May;10(5):e1003588. DOI: 10.1371/journal.pcbi.1003588.
Tononi G, Koch C. Consciousness: Here, there and everywhere? Philos Trans R Soc Lond B Biol Sci. 2015 May 19;370(1668):20140167. DOI: 10.1098/rstb.2014.0167.
Grossberg S. Adaptive Resonance Theory: How a brain learns to consciously attend, learn, and recognize a changing world. Neural Netw. 2013 Jan;37:1-47. DOI: 10.1016/j.neunet.2012.09.017.
Grossberg S. Towards solving the hard problem of consciousness: The varieties of brain resonances and the conscious experiences that they support. Neural Netw. 2017 Mar;87:38-95. DOI: 10.1016/j.neunet.2016.11.003.
McFadden J. The CEMI Field. Theory gestalt information and the meaning of meaning. J Conscious Stud. 2013;20(3-4):3-4.
Sevush S. Single-neuron Theory of Consciousness. Journal of Theoretical Biology. 2005.
Hameroff S, Penrose R. Consciousness in the universe: A review of the 'Orch OR' theory. Phys Life Rev. 2014 Mar;11(1):39-78. doi: 10.1016/j.plrev.2013.08.002.


Is performance reducible to brain activity in an unambiguous way? As a preface, let me assume that the entirety of mental states and their corresponding behaviors in a person are entirely reducible to the physical activity of neurons sending a variety of chemicals across synaptic clefts at appointed times. There's no extra-logical, metaphysical sense of being that guides our actions e.g. spirits, soul stuff, etc.

Beyond this provision, which is obvious, is the overarching question of how particular networks in the brain control various structural and behavioral faculties in the mind. For example, if we place a person in an MRI and ask them to count to three, we expect to find activation in a portion of the parietal lobe. Just how fine-grained is this activation? If we ask the same person to do the same counting at a different time, will a different network in the same area of the brain be used?

The first question has a corollary to it; a kind of role reversal: given a sufficiently detailed picture of a person's brain, is it possible to more or less describe what the person is doing or thinking?

If we stick them in an MRI, the activation will not be very fine-grained. There are roughly 630,000 neurons in a 3x3x3 mm voxel recorded during fMRI. However even this coarse detail is sufficient to perform many impressive mind-reading tasks (e.g. Mitchell et al., 2008)

But what if we were able to record every single neuron in the brain simultaneously, could we then find a unique 1-to-1 mapping between neuronal firing and behavior? Not really. Consider what happens when you count to three-- and let's ignore everything going on in your brain that's not contributing towards this task (e.g. autonomic functions, mind wandering, etc.) Do your tongue, jaw, and lips move in exactly the same way every time? Does the acoustic signal sound the same every time? No; there is some variability in neuronal firing that causes behavioral variability.

OK, well what if your muscles did move in exactly the same pattern. Then, would the neuronal signature be identical between trials? Not necessarily. Let's assume there are 100 billion neurons in the human brain. We can't observe that many degrees of freedom in our behavior. It's likely that if we removed a single neuron, our behavior might remain 'identical'. There's a massive amount of dimension reduction to go from an array from 100 billion neurons to human behavior. But overall, the answer to your question depends on how you characterize 'performance'. If you define performance to be sufficiently complex such that performance is equivalent to the pattern of neuronal firing, then the question becomes a tautology.

The answer to the reverse question is slightly different. It is likely that if we observe the exact same pattern of neuronal firing twice, then the behavior will be exactly the same. However, even then, there is the possibility of noise in the peripheral nervous system once signals leave our brain that leads to some variability.

In a broader sense, cognitive neuroscience is aimed at answering this exact question: How does the activity of the brain correspond with our cognition and behavior? I like to think we've made some decent progress in this area, but we're still nowhere near a complete answer to this question.

  Mitchell, T. M., Shinkareva, S. V., Carlson, A., Chang, K. M., Malave,
  V. L., Mason, R. A., & Just, M. A. (2008). Predicting human brain
  activity associated with the meanings of nouns. Science, 320(5880),
  1191-1195. PDF


What is the relationship between fear and desire? Are fear and desire located on the opposite sides of a spectrum or are they more like filters/lenses through which one can look simultaneously?

The Atlas of personality, emotion and behaviour (Mobbs, 2020) is able to visualise emotions in two dimensions: affiliation and dominance.  Fear is considered submissive and disaffiliative.  Desire is more dominant and intrapersonal, that is, in itself neither affiliative or disaffiliative.

Reference
Mobbs AED (2020) An atlas of personality, emotion and behaviour. PLOS ONE 15(1): e0227877. https://doi.org/10.1371/journal.pone.0227877
Declared interest
I am the author of the atlas paper.


Handedness bias in Raven's Matrices A few years ago I tried a Raven's Matrices IQ test on the Internet. In every test the bottom right element had to be deduced and this could always be done by scanning the first two rows to determine the pattern. It may also have always have been possible to deduce the solution by scanning the first two columns, although I am not sure that the test designer had this in mind.

It occurred to me that there could be a built-in bias favouring right-handed people or people who first learned to read horizontally from left to right.

It should be fairly simple to devise experiments to test for such bias but an (admittedly rather cursory) Internet search found nothing relevant.

Has there been any such research?

There isn't much of a difference in IQ tests between left and right-handed people. I don't know if this is (more) significant on a sub-test like Raven's.

On the other hand there's  some correlation between both handedness and first-language script direction and the phenomenon of mirror writing. So the native script direction may be relevant to a test like Raven's.  I don't know if they adjust for it (e.g. by rotating the matrix) when it's "translated" to Hebrew or Japanese.


What are the cognitive elements of dangerous behaviors? I am looking for theories or articles that focused on cognitive elements contributing to risk-taking behaviors. For example it is known that response inhibition is linked to impulsive behaviors.
I am looking for any neurocognitive parameters that meet criteria of antisocial personality disorder in DSM-5, especially including impairments in self-functioning such as:

  Self-direction: Goal-setting based on personal gratification; absence of prosocial internal standards associated with failure to conform to lawful or culturally normative ethical behavior.

There are correlations betweeen risk behaviours and temperament traits. According to Strelau's theory of temperament (1998) people are devided into those who have low and high demand for stimulation. The second one will probably do risk behaviours more often. There are also anothar temperament traits which can influence sb's behaviour.

You can read more there:
Strelau (1998) Temperament: A Psychological Perspective

And some other scientific articles with research results:
http://www.sciencedirect.com/science/article/pii/S0376871603003570
http://psycnet.apa.org/journals/psp/73/5/1052/


Why does a person feel sad without knowing the reason? I have known people to behave in a way they despise, and they don't know why.

Modern theories of emotion suggest that like many aspects of self-knowledge, emotion is "inferred" rather than "introspected".

This is exemplified by a classic experiment in which men were surveyed by an attractive female interviewer while on a bridge.  Some of the men were on a "fear-arousing" suspension bridge, while other men were on a "non-fear-arousing" solid bridge.  Men surveyed on the suspension bridge were more likely to include sexual content in their answers, and more likely to call the interviewer later.  Presumably the men on the suspension bridge were more aroused than the ones on the solid bridge, and misattributed their arousal to the attractiveness of the interviewer.

Similar research supports the idea that physiological inputs (eg, the effects of hormones in our system) are combined with a process of inference to produce emotion.

Imagine having a low level of serotonin in your brain.  This may cause a negative effect on your mood - sadness.  Now you want to know why.  So you search for possible reasons: Maybe a conversation you had recently didn't go well, maybe your bank account is low on funds, maybe you notice that you haven't spent time with friends lately...  Successful attribution typically requires a plausible cause-and-effect relationship - that is, the most likely explanation is probably the correct one.

Put another way, people in general sense physiological states (such as sadness) without knowing why.  They then (unconsciously) "guess" why through inference.  Sometimes they get it right, and sometimes they get it wrong.  If you've ever had a girlfriend on her period blame her feelings on the way you treat her, then you know what I mean.  So the reality is that people who feel sad and don't know why, are ... accurate.  The only difference between feeling sad and knowing why, and feeling sad and not knowing why, is successful attribution - coming up with a plausible guess.


Are there any modern mechanistic theories of motivation? I remember hearing about the old 'drive' theory of motivation in Psych 101, and despite continuing my cognitive science education for another 4 years, that's the last theory of motivation I've heard about.

Are there any modern theories of motivation at mechanistic level of explanation?

The only stuff on motivation I find these days are along the lines of Pink's book "Drive", which talks of "purpose" and "mastery" as motivators, but doesn't discuss the actual mechanisms underlying them.

Motivation is a massive topic, and it's difficult for me to know what would count as a 'theory' of motivation as it's currently construed.  For instance, at one level, we might consider motivation to be the processing of incentive salience on perceived stimuli: you see a cheeseburger, something makes you want it, and so you pursue it.  One way of talking about what it means to want this cheeseburger is called incentive salience; see Berridge 1998 for a great review on this topic with a focus on the contentious role of dopamine, and some pretty amazing experiments that pry apart wanting from liking.

Coming from the opposite direction, Carver and Scheier's cybernetic model has proved quite influential in describing motivation, and its hedonic consequences, in terms of progress during goal pursuit.  This goal-centrality dovetails with some of the achievement goal theoretic constructs, one of which (mastery) you mentioned with regard to Pink's book; Andrew Elliot did a nice review here.  For an even more meta computational formulation, Juergen Schmidhuber has for years been proposing an  all-encompassing model that might be grand enough for your tastes, although it is woefully untested by empirical work and, from what I can tell, seems to be considered kind of fringe.

I could go on, but suffice it to say that theories of motivations -- or pieces of theories -- are nearly as numerous as the stars.  The real trick is in unifying them in a coherent system that makes sense at multiple levels of abstraction and isn't just some hodgepodge collection.


Does dream recall alter the dreaming process? I've encountered the following phenomenon : within a single night of starting a dream journal again, my dreams became more numerous, recall improved and I'm waking up after each sleep cycle except the 1st one with more recall.

In particular, I scribble down my dreams on paper immediately upon awakening from a dream. This happens 5-6 times a night.

This makes me ask- does activating dream recall mechanism in the middle of the night alter brain chemistry or dream process, facilitating more recall?

Your experience with more dream following dream recall can be explained in this paper, Effect of encouragement on dream recall (Halliday, 1992). People experience lighter sleep when they recall dream upon awakening (Shapiro, Goodenough, & Gryler, 1963), Armitage (1992) reported that males had more dream recall in low stress days while females showed the opposite.

Armitage, R. (1992). Gender differences and the effect of stress on dream recall: A 30-day diary report. Dreaming, 2(3), 137. http://dx.doi.org/10.1037/h0094354

Halliday, G. (1992). Effect of encouragement on dream recall. Dreaming, 2(1), 39.http://dx.doi.org/10.1037/h0094346

Shapiro, A., Goodenough, D. R., & Gryler, R. B. (1963). Dream recall as a function of method of awakening. Psychosomatic medicine, 25(2), 174-180.


Depression Causing Body Dysmorphic Disorder (BDD) Whilst trying to think of non-chemical/hormonal causes of low self-esteem when reading Is low self-esteem, a brain chemical imbalance problem, rather than a personality defect, and can't be fixed by any amount of counselling/self-help?, I have been considering Body Dysmorphia Disorder (BDD).

Whilst it is a mental disorder in its own right, I have been thinking that BDD can cause depression due to the constant upset caused by the feelings concerning the body, but not the other way round; yet the UK mental health charity, Mind, states.

  No one knows exactly what causes BDD. However, recent research suggests that there are a number of different risk factors that could mean you are more likely to experience BDD, such as:

  abuse or bullying
  low self-esteem
  fear of being alone or isolated
  perfectionism or competing with others
  genetics
  depression or anxiety

I am asking here specifically about depression because for the other reasons in MINDs list such as perfectionism or bullying, anxiety could cause BDD in my thinking.

With risk not necessarily meaning cause, in order for the risk to be quantified, there needs to be indication from studies and past clients that depression led to BDD rather than the other way round, and yet I am not convinced of this.

What studies are available which indicate that depression can cause BDD rather than the other way round?

TLDR version: it appears depression-as-a-risk-factor-for-BDD hasn't actually been studied, so the quoted UK NGO claims might stem from a blurring of risk factors and comorbidity.

Let's start by recalling what risk factor actually means (it does not mean cause):

  Risk factors are characteristics at the biological, psychological, family, community, or cultural level that precede and are associated with a higher likelihood of negative outcomes.

So support the quoted passage in your question, one would only have to show that depression (from whatever cause) can happen before BDD in some individuals. If someone is predisposed to "go off the deep end" because of their body, they could possibly do that for any other perceived insufficiency in themselves (like thinking they're not being smart enough). The criteria to BDD are extremely specific, only a preoccupation with physical appearance counts; if someone ruminates or obsesses or over their (perceived) lack of intelligence, that doesn't qualify for BDD. With this in mind, depression being a risk factor for BDD doesn't so improbable.

Alas, I came up empty for an actual longitudinal study where depression got worse before BDD... but I did find one close enough:

  We found several significant longitudinal associations between BDD and the comorbid disorders we examined. The association was strongest for depression. Time-varying associations showed that improvement in BDD and major depression were closely linked in time, with significant associations in both directions: improvement in major depression predicted BDD remission, and improvement in BDD predicted major depression remission. This finding suggests that the same etiologic processes contribute to both BDD and major depression in some subjects.

The reason they could only talk of improvements (and not deterioration) is that this study had a treatment-based time frame. So there's wasn't much in the way of naturalistic observation sans treatment. That would probably require a much longer time scale... and I'm not convinced someone could get funding for that... especially since it raises ethics questions like observing depression getting worse in some patients but not doing anything about it, just so BDD aggravation could be observed.

On the other hand, the common sense logic (that you had) that depression might usually come after BDD, turns out to be supported by this study (well, again based on remission):

  in our sample depression may be largely secondary to BDD for many subjects, as a substantial proportion remitted from major depression following BDD remission. Conversely, after remission of depression, BDD tended to improve but less markedly. Our findings additionally suggest that BDD is not simply a symptom of depression. If it were, BDD would be expected to remit around the time of depression remission and during subsequent months.

Frankly, I suspect that the NGO page in question might have simply confused (or amalgamated) risk factors with comorbidity. I'm saying this because a 2015 research paper notes that very little is know about risk factors for BDD. According to that paper, the only things which have been investigated as risk factors for BDD being:

"perceived teasing about general appearance"
"emotional, physical, or sexual abuse or neglect resulting in poor
attachment and body shame"
"a genetic predisposition for a need for symmetry or order"
"being excessively self-conscious about appearance changes during adolescence"

So, my conclusion from all this: it sounds somewhat plausible that depression is a risk factor for BDD (based on the common etiology [in some people] hypothesis), although it doesn't seem to have been formally/directly investigated, and the reverse occurence of events (BDD first, then depression) sounds a bit more common/likely.


Where do spatial dimensions enter in single compartment neuronal models? I am trying to understand how the length and diameter of a compartment are specified. For example, in the Hodgkin–Huxley model, we only have conductances specified in $\rm mS/cm^2$. How do you specify that a compartment is say $100 \mu\rm m$ long?

In a single-compartment model, you do not have spatial dimensions. Sometimes this is not a problem, for example in the stomatogastric ganglion of C. borealis, in which the neurons have a mechanism to scale the signal with distance by modifying the "effective reversal potential" (Otopalik et al., 2017). In the case of one of these models, it would be sensible to either make an approximation of the cell surface area (Liu et al., 1998 for example) or to use parameters which are normalized by the surface area, to whose explicit numerical value we remain agnostic. One would do this by using a membrane capacitance in microfarads per centimeter squared for instance (typically about unity) and then use maximal conductances in millisiemens per centimeter squared.

This way, the natural units for current divided by capacitance are mV * mS/cm^2 * cm^2/uF, or equivalent to mV/ms.

If you wanted to model multiple neurons with a decay factor, you could either use the cable equation and explicitly input the current into the descending neuron following that, or make a neuron with multiple compartments.


Identify kind of descriptive role playing game for self-discovery There's a comic book called "Knights of the Dinner Table" about a bunch of rpg players.
In one issue, the only girl at the table GM's some kind of self-discovery game she learnt in her psychology class. She describes some situations and asks for details from the players, giving an example herself.
At one point, for example, she says:

Ok, so you continue your journey down your own personal path. Soon you come to a large bear! What do you do? My bear turns out to be very tame and I'm able to hand feed it and befriend it! He decides to accompany me on my journey.

At the end, she explains what each thing symbolizes:

The bear represents adversity and how you deal with it

Supposedly this is (loosely) based on a real exercise for self discovery. I would like to know more about the real exercise in which this is based, but I don't know how to start.
Any idea how this exercise is called, or how can I find more information about something similar?
Thanks.

I finally found it, apparently it's called The Forest Test

Hindrances and annoyances that take away our happiness, entrenched
fears, values that govern our choices and behavior. The forest test
tries to clarify and interpret many of these issues based on the
approach from which it was designed: relational psychoanalysis.
According to this theory, our psychological suffering is rooted in
underlying issues that we must bring to light in order to heal the
hurts and move forward.
For those who have not heard about this relational test, we should
first say that it isn’t in any way conventional. The forest test
doesn’t have enough reliability and validity to be part of normal
clinical practice. However, we cannot rule out its relevance within
the context and the theoretical framework from which it was created.
It is, without a doubt, worth taking into account.
The forest test is a projective test which can reveal the fears, hindrances and deepest interests of each patient.


What is the name of the phenomenon whereby someone steps-up and others follow? Example: In class, when a teacher proposes some unreasonable assignment, students hesitate to express their objection until someone steps-up and then others find courage to talk.

I've tried searching for the term for this phenomenon but I don't know what I'm looking for exactly.

Your example of no student willing to object until one objects is analagous to Asch's conformity experiments. To quote the Wikipedia article:

  In a control group, with no pressure to conform to an erroneous view,
  only one participant out of 35 ever gave an incorrect answer. Solomon
  Asch hypothesized that the majority of participants would not conform
  to something obviously wrong; however, when surrounded by individuals
  all voicing an incorrect answer, participants provided incorrect
  responses on a high proportion of the questions (32%). Seventy-five
  percent of the participants gave an incorrect answer to at least one
  question.
  ...

  The unanimity of the confederates has also been varied. When the
  confederates are not unanimous in their judgment, even if only one
  confederate voices a different opinion, participants are much more
  likely to resist the urge to conform (only 5–10% conform) than when
  the confederates all agree.


Blocking out unwanted sound sources Suppose you are in a room with two other persons, both of them talking. If you want to hear one of them, you are able to block out the other even though he is talking (although not very loud). How our brain does this as if the other person is not talking, even though the sound waves from both the persons are entering your ears?

You're not really blocking them out. It's more that you're processing the language of the person you're focusing on.

You could do exactly what you describe at reasonably high volume levels.

Though the level is not equal for all people. Young children and people with attention difficulties
Why it's Difficult to Listen to two People


Is there visual focus during a saccade? Has anyone succeeded in measuring where the focus is between saccades? Through some kind of nonintrusive brainscan perhaps? I would like to be able to draw with my thought :) (Something similar would be okay, like the position or shape I am thinking of overlayed on what I see)

Short answer
The retinal image cannot be refocused on an intermediate target during a saccade.

Background
Psychophysical experiments have shown that during a saccade, attention is aimed at the target location. Instructing the subject to make a saccade from location A to C, while focusing on another point B proved impossible.

The authors conclude that:

  [A] saccade executed to a peripheral location in the visual field
  involves the orienting of attention to that location, prior to the
  actual execution of the saccade. The inability to orient attention to
  one location and simultaneously execute a saccade to another location
  suggests that orienting of attention may be an essential component of
  preparing and/or executing saccades.

In other words, a saccade is meant to shift the point of focus, and attention cannot be paid to another point during a saccade.

Reference
- Hoffman & Baskaran, Perception & Psychophysics (1995); 57(6), 787-95


How important is eye contact for hypnotism? We had the funny situation where an ambiguous question was asked and then edited to go two ways. Thus, I've reposted the edited version of the question that was not retained, particularly so that the answer that was posted there by @what will have a more natural home here.

How important is eye contact for hypnotism? What is the optimal eye locking duration between 2 persons for inducing hypnotism?

There are different kinds of hypnosis. In therapeutic settings traditional, or classic, hypnosis is differentiated from modern, Ericksonian hypnosis.

Traditional hypnosis, as it has been used from Mesmer to Freud, is based on direct commands. The hypnotist usually acts in a dominant manner and uses eye contact, pendulums, fixation of the index finger etc. to induce the trance. Advantages of traditional hypnosis are quick induction of trance and often a quick deepening of trance. Disadvantages are that not everybody is susceptible to this kind of hypnosis. Show hypnotists use traditional hypnosis, but they preselect their subjects to work with those susceptible to direct commands. Direct induction is also popular in the context of NLP.

James Braid explains the eye fixation method of trance induction in Neurypnology (1843):

  Take any bright object (I generally use my lancet case) between the
  thumb and fore and middle fingers of the left hand; hold it from about
  eight to fifteen inches from the eyes, at such position above the
  forehead as may be necessary to produce the greatest possible strain
  upon the eyes and eyelids, and enable the patient to maintain a steady
  fixed stare at the object.

  The patient must be made to understand that he is to keep the eyes
  steadily fixed on the object, and the mind riveted on the idea of that
  one object. (p. 27)

James Braid inducing a trance with the eye fixation method

Ambroise-Auguste Liébeault, founder of the Nancy school of hypnosis in the 19th century (distinguished from the Paris school around Charcot at the Salpêtrière), used eye contact to induce a hypnotic trance in his patients. (Kossak, 2004, Hypnose: Lehrbuch für Psychotherapeuten und Ärzte, Weinheim: Beltz, p. 22)

Modern or Ericksonian hypnosis, developed during the 20th century, mainly by Milton H. Erickson, does not use any auxiliary means. Trance is induced indirectly during conversation. The client falls into trance slowly and without noticing. Advantages are a pleasant feeling during trance and a better acceptance than during traditional hynosis. Also, a dialogue with the unconscious is easier in modern hypnosis. A disadvantage is that the trance is usually not very deep (usually a medium depth).

Therapists often use a combination of both methods to utilize the advantages of both methods.

To answer your question, while eye contact is unnecessary – Milton H. Erickson, in Hypnotic Realities, says that "often the therapist does not even look at the patient's face" –, it is one of several methods for inducing quick and deep trances in suitable subjects.

I don't know that there is an "optimal eye locking duration", as the time to fall into trance – and thus the time of fixation, if the eye fixation method is used – varies with the "hypnotizability" of the subject. James Braid (Neurypnology, 1943, p. 27) describes that "[a]fter ten or fifteen seconds have elapsed, by gently elevating the arms and legs, it will be found that the patient has a disposition to retain them in the situation in which they have been placed, if he is intensely affected", but then continues to describe how to proceed if the subject has not fallen into a trance after that period of time.


What is the meaning of "little efferent input" to retina? Gollisch & Meister (2010) state that "the retina receives little efferent input from the brain" (p. 157). Could anyone describe what exactly this "little efferent input" (where it originates, whether it is present in primates, its function ...) is or point me to the relevant literature?

Here is the paper in question:

Gollisch, T., & Meister, M. (2010). Eye smarter than scientists believed: neural computations in circuits of the retina. Neuron, 65, 150–64.

Interesting question!

The paper you read should have inserted an appropriate citation. Moreover, "little input" is a subjective statement and doesn't make much sense in the context, as it can mean that there are few efferent axons (which may still have large effects on retinal functioning), or that the efferent input is relatively unimportant when compared to the afferent visual projections (which may indeed be so). In fact, I think what the authors actually try to say is that there is not much data available on efferent retinal input.

To answer your question: The efferent projections from the brain back to the retina, referred to as centrifugal projections, are indeed not extensively studied. The studies done were mainly performed in avian species. However, centrifugal projections have been shown to exist in monkeys and humans. In the macaque, they originate in the brain in the hypothalamus, and constitute histaminergic neurons which are thought to be involved in regulating blood flow in the inner plexiform layer of the retina. They may also be involved in regulating retinal dopaminergic amacrine cells, at least in mice and other species. Specifically, dopaminergic amacrine cells in the retina may be receiving centrifugal input from the suprachiasmatic nucleus (SCN, situated in the hypothalamus) where circadian rythms are initiated from melanopsin containing ganglion cells. The dopaminergic amacrine cells in the retina target photoreceptors, horizontal cells and amacrine cells and thereby regulate the retina depending on the state of the circadian clock. Most studies are histological in nature and functional data remains scant.

Reference:
Webvision - Feedback Loops (by Helga Kolb)


Why does splitting attention between a primary task and another task appear to improve performance on the primary task? I've been thinking about my performance at various tasks and where my focus is at during them and something's really got me confused.

It makes sense that devoting all my focus to a task while I'm doing it would yield the best results that I'm capable of. In my case, however, the opposite seems true.

If I'm trying my best to accomplish something and it's not working to my satisfaction (bugs in my program code that don't appear to have a reasonable cause for example) - and this only happens when I'm really focusing on the task - I get irritated with my apparent inability to come to the desired result and my performance declines, which irritates me more.

On the other hand, if I have my focus split (i.e. playing a movie or tv series while I'm busy with the task), I stay a lot calmer and generally my performance at said task stays pretty high.

It's very clear to me that I don't perform well under pressure, but in a lot of cases, there's no pressure aside from what I put on myself.

So my question is this: how is it that when I'm just absent-mindedly doing something, it generally turns out better than it would if I focused on it and tried my hardest?

Dual Task research

In general, I think a lot depends on what is the secondary task and how it relates to the primary task (see human multitasking).
In general, secondary tasks tend to lower performance on the primary task.

A classic combinations where there may be facilitation is music with gross motor tasks, where the music is often experienced as motivating.
In other cases, music can serve to block out other external distractions, such as in a noisy office.

However, in general, it would be unusual for task performance to be improved by simultaneously watching television while doing the task. It might make the task more enjoyable, but it would be rare for it to improve productivity. The intrusive way that TV impinges on your attention would generally interfere with flow and focus on the primary task, especially where the primary task involves cognitive control.

Incubation

That said, there is a literature on the benefits of breaks and incubation on problem solving. So, in general, taking a break after working on a task intensely and getting stuck, can be a useful way of breaking the impasse. In particular, a good night sleep can be particularly helpful.

Motivation

Another way of framing your question is in terms of the effect of a secondary task on motivation and persistence. Making the task more enjoyable might have an effect on your persistence.

However, drawing on the expertise literature, I'd say it's often better to work in a focussed and concentrated way for a shorter period of time, than to do a task in a half hearted way for a longer period of time. If you've truly lost the ability to concentrate, then it may be time to rest and recuperate, both in terms of good sleep and time off task.


How to build a high sensitivity EEG headset for continual monitoring? After having a conversation with a couple of the more popular "consumer" level EEG makers such as Versus, I have found that their monitoring abilities are either limited or altogether absent.  The devices utility, while cool from a 3rd party controlled training standpoint, is neutered when it comes to just getting raw data and plotting it out in a manner that allows one to make their own interpretations and calls.

I would like to build my own device that can monitor from the very low < 0.5 hz all the way up to at least 200 hz.  My goal is to feed that into my own software in order to keep a running graph for analysis, etc.

How would one go about building an EEG that has this level of sensitivity?

There are a few commercial EEG makers that do allow monitoring of raw EEG data. For instance, I know the Muse headband and OpenBCI allow you to do this with little trouble. These both support sampling rates up to 250 Hz. (The OpenBCI in principle could have a higher sampling rate, but i don't know anyone who has done this.)

The Emotiv EPOC also has an option to get raw EEG data. You have to pay more for the research version of the SDK to get the data officially. However, someone has reverse engineered their protocol, so you can access the raw data that way. This has a sampling rate of up to 128 Hz.

That said, if you still want to build your own EEG, OpenBCI has documented all of their plans, so a good start would be to replicate their product.

There is also the older, but still useful, OpenEEG project, which also has open plans for an EEG device.


Are emoji smiles also contagious? It is fairly common knowledge that smiles are contagious is this also true when people are exposed to ascii/emoji smiles? ie. :) , ☺ ,

By contagious I mean making a person feel happier and more likely to smile themselves.

Yes. Emoji smiles are contagious just like real human smiles.

As this study suggest the brain activity observed when people look at emojis is the same when we look at real faces, and subsequently mimicry and emotion contagion follows.

  We presented 20 participants with images of upright and inverted
  faces, emoticons and meaningless strings of characters. Emoticons
  showed a large amplitude N170 when upright and a decrease in amplitude
  when inverted, the opposite pattern to that shown by faces. This
  indicates that when upright, emoticons are processed in
  occipitotemporal sites similarly to faces due to their familiar
  configuration.

Also, a more general study for on-line expressed emotions demostrated emotion contagion similar to face to face comunication.

  We show, via a massive (N = 689,003) experiment on Facebook, that
  emotional states can be transferred to others via emotional contagion,
  leading people to experience the same emotions without their
  awareness. We provide experimental evidence that emotional contagion
  occurs without direct interaction between people (exposure to a friend
  expressing an emotion is sufficient), and in the complete absence of
  nonverbal cues.


What is it about the nature of slow-wave sleep that makes it difficult to awaken the sleeper? In humans, delta wave sleep ("slow wave" sleep, stages III and IV by AASM criteria) is more common in children and becomes only a small percentage of total sleep time in adults.

Cortical EEG waves have notably low frequencies (sometimes as low as 1Hz) during these stages.  I've always modeled this in my own understanding as the brain "polling" the environment at a lower rate, but why do stimuli that coincide directly with the peaks of the cortical waves still not seem to arouse or awaken the person sleeping?  Clearly there are some physiological "shunts" occurring in the brainstem and cortex to dampen the effects of external stimuli, but why see any activity at all, then?

Slow EEG waves reflect a slow oscillation in cortical neurons, between a depolarized state (UP-State) and hyper polarized state (DOWN-state; Steriade et al., 1993a, 1993b). During the down-state, neurons are disfacilitated (they can't really be activated by external stimuli or depolarized; Contreras et al., 1996). As the brain progress into deep sleep (lots of large-amplitude slow waves), not only cortical but also thalamic neurons becomes more and more hyper polarized (Amzica & Steriade, 2001). Steriade (2006) proposed that this progressive hyper polarization that is occurring during deep sleep might protect the brain from interference from the external world and facilitate memory consolidation, because the brain becomes "non-responsive" to the external environment. Indeed, this thalamo-cortical hyper polarization occuring during the down-state might "gate" the brain from external influence.

Recent neuroimaging studies in humans (Schabus et al., 2012) indeed showed that during the DOWN state, there was no cortical response to auditory stimuli in fMRI.  Thus we think that those waves, either in N2 (K-Complex) or N3 (SW), protect the sleep brain from external influence.

Sources :

Steriade M, Nuñez A, Amzica F. A novel slow (< 1 Hz) oscillation of neocortical neurons in vivo: depolarizing and hyperpolarizing components. Journal of Neuroscience. 1993;13(8):3252–3265.
Steriade M, Contreras D, Curró Dossi R, Nuñez A. The slow (< 1 Hz) oscillation in reticular thalamic and thalamocortical neurons: scenario of sleep rhythm generation in interacting thalamic and neocortical networks. J Neurosci. 1993;13(8):3284–3299.
Contreras D, Timofeev I, Steriade M. Mechanisms of long-lasting hyperpolarizations underlying slow sleep oscillations in cat corticothalamic networks. J Physiol (Lond). 1996;494 ( Pt 1):251–264.
Amzica F, Steriade M. Electrophysiological correlates of sleep delta waves. Electroencephalography and Clinical Neurophysiology. 1998;107(2):69–83. doi:10.1016/S0013-4694(98)00051-0.
Steriade M. Grouping of brain rhythms in corticothalamic systems. Neuroscience. 2006;137(4):1087–1106. doi:10.1016/j.neuroscience.2005.10.029.
Schabus M, Dang Vu TT, Heib DPJ, et al. The Fate of Incoming Stimuli during NREM Sleep is Determined by Spindles and the Phase of the Slow Oscillation. Front Neurol. 2012;3:40. doi:10.3389/fneur.2012.00040.


Can we really motivate ourselves "on-demand"? There are so many articles online and books selling on the idea that we should motivate ourselves daily, as motivation doesn't last long. Many cite numerous experiments and advise on techniques you can supposedly use, because some experiment showed positive results.

From all the popular psychology and life coaching books on Motivation, all I can gather is that motivation is something a person should think about constantly and regulate on their own, on a daily basis.(10 proven ways to motivate yourself,...and similar titles).

Can you really talk yourself into feeling motivated? Or is motivation something that just happens subconsciously? Is popular psychology really onto something or their claims too big?

Edit: My question is not answered with the suggested answer in the comment section. I'm not interested in obstacles to motivation, I'm interested in whether one can consciously spark motivation within oneself, regardless of existing obstacles.

There is not much possibility to talk yourself into being motivated. However, personal narratives can help us redirect our motivations or manage them more productively. To take this more abstractly, consider a person who just ate a large meal. If they are not hungry, could they talk themselves into being hungry? (Rarely.) However, if a person is craving a certain type of food, they could notice that and consciously decide to redirect that interest into a different type of food, and then that intention might lead to actual behavior. This could also apply to longer-term goals, such as pursuing more education; but that process is only possible to the extent that other, existing motivations are borrowed to a new target. See https://en.wikipedia.org/wiki/Self-determination_theory for a popular theory of overall social motivations.

Motivation is not just subconscious, to the extent that we can have sensations around desire and goal states, e.g., be aware of urges and drives. All cognition includes subconscious processes: absolutely.

Popular psychology is wildly profitable but often quite unrelated to the latest empirical science. The incentive is to be convincing and be shared, not to be accurate. 'The Secret' is a good example: super popular and entirely inconsistent with physics. Finally, the note "...nobody can claim anything" is a bit vague.


Classical test theory: Covariance of two variables I'm stuck with the definition of the Covariance in the classical test theory (CTT) framework:
In CTT it is assumed that for two items:
$X = \tau_x + \epsilon_x$
$E(X) = \tau_x$

$Y = \tau_y + \epsilon_y$
$E(Y) = \tau_y$

From these assumptions it follows that:
$Cov(X,Y) = E[(\tau_x+\epsilon_x)*(\tau_y+\epsilon_y)] - E(\tau_x+\epsilon_x)*E(\tau_y+\epsilon_y)$
$= E(\tau_x\tau_y) - E(\tau_x)E(\tau_y) $
$= Cov(\tau_x,\tau_y)$

I tried to come to the same conclusion using a slightly different approach:
$Cov(X,Y) = E((X-E(X))(Y-E(Y))$
$=E((\tau_x+\epsilon_x-\tau_x)*(\tau_y+\epsilon_y-\tau_y))$
$=E(\epsilon_x*\epsilon_y)$

As $E(\epsilon_x) = 0$ the following terms should be equivalent:

$E(\epsilon_x*\epsilon_y) = E[(\epsilon_x - E(\epsilon_x))*(\epsilon_y - E(\epsilon_y))] = Cov(\epsilon_x, \epsilon_y)$

As the conclusion drawn from my approach contradicts with the first conclusion I assume that there is a flaw in my math. Unfortunately I seem to be unable to identify my mistake. Can someone point me to it?

I do not myself use classical test theory, but from a statistical point of view the answer to this should be straightforward. The answer is that you are right, and that the first solution is wrong.

An early indication that the first formula is incorrect is that a :
$$
Cov(\tau_{x},\tau_{y}) = 0
$$
because $\tau_{x}$ and $\tau_{y}$ are constants (I assume $\tau_{x}$ and $\tau_{y}$ are constant in your question because your equations state that they are expected values, which are always constant). The formula above holds because constants can't covary with one another.

To show you are the one who is correct, we need to dig a little bit deeper. One basic property of covariance is, for $X$, $Y$ random variables and $a$, $b$ constants:
$$
Cov(X+a, Y+b) = Cov(X,Y)
$$
Intuitively, adding a constant to a random variable doesn't affect its linear relationship with another random variable.

In your particular example, if I understand correctly, $\epsilon_{x}$, $\epsilon_{y}$ are random variables, and $\tau_{x}$, $\tau_{y}$ are fixed constants. Plugging these into the above formula,
$$
Cov(\epsilon_{x} + \tau_{x}, \epsilon_{y} + \tau_{y}) = Cov(\epsilon_{x}, \epsilon_{y})
$$
And of course, using the notation in your question, $X$ = $\tau_{x}$ + $\epsilon_{x}$= $\epsilon_{x}$ + $\tau_{x}$ and $Y$ = $\tau_{y}$ + $\epsilon_{y}$= $\epsilon_{y}$ + $\tau_{y}$. Therefore, using the variables from your question,
$$
Cov(X,Y) = Cov(\epsilon_{x}, \epsilon_{y})
$$


Which neurotransmitters can be measured in a living human brain? I'm interested in learning more about the modern techniques that are used for scientific studies of neurotransmitters in the living human brain. As far as I know, there are 4 neuromodulator systems within the human brain.

They are:

Noradrenaline system

Dopamine system

Serotonin system

Cholinergic system

As far as I understand, some of biosynthesis pathways of these systems are interconnected, with the level of one neurotransmitter affecting levels of others further down the line.

Can anyone comment on which ones of these neurotransmitter levels can the modern science (as of 2012) measure or at least estimate in the living human brain?

How close is modern science to understanding the cascading effects that these neurotransmitter systems may have on each other?

Update: The other similar question deals with the imaging techniques of neurotransmitters, and this paper describes the process that might be used in the future, after tests and approvals. Structure-Guided Directed Evolution of Highly Selective P450-Based Magnetic Resonance Imaging Sensors for Dopamine and Serotonin

What is not very clear to me from the other answer if all 4 neurotransmitter systems listed above can be measured in a living brain, or if some of them are out of reach of modern science. Can we measure Noradrenaline, Dopamine,Serotonin and Choline/Acetylcholine levels in a living brain using modern methods?

Thank you for your input!

There are many, many more neuromodulators in the brain than that.  Essentially anything that binds to G-protein coupled receptors could be considered a neuromodulator.  Even "classic" fast neurotransmitters like GABA and glutamate have "neuromodulatory" receptors (GABA-B receptors for GABA, 3 different families of "metabotropic glutamate receptors").  Peptides (e.g., endogenous opioids, orexin, oxytocin...) also commonly bind to G-protein coupled receptors.

There are even "orphan receptors" that exist, but we haven't identified the chemical that naturally binds to them.

As you get deeper into pharmacology, you'll learn that each of the common neurotransmitters has MANY kinds of receptors that are located in different places and do different things.  On the other hand, G-protein coupled receptors can be be classified according to which G proteins they bind to.  "Second messengers" would be a good thing to search for to learn more about this (cAMP, phospholipase C.....).

To answer your question, though, we can measure the release of some neurotransmitters using PET.  The idea is that you pick a drug that binds to a particular receptor for that neurotransmitter (e.g., dopamine).  Then, you manufacture some of that drug such that one of the atoms in the drug is radioactive (i.e., the drug is made with a radio-isotope of carbon, fluorine, etc.).  The PET scanner will pick up the radioactivity released by the drug, which will be localized to places that contain that type of receptor (e.g., D2 receptors).  Drugs don't stick to receptors perfectly, though.  The natural ligands for the receptors ALSO bind to the receptors.

You can take advantage of this by having two conditions in your experiment.  In one, subjects do some control task while you measure the level of radioactivity in various parts of the brain.  In the other, they do the task you're interested in.  If that task is associated with an increase in dopamine release, you should see a DECREASE in the amount of radioactivity, since some of the receptors will now be occupied by normal, nonradioactive dopamine instead of the drug.  The more dopamine release, the less radioactivity.

Neurotransmitter levels can also be measured directly using a technique called "microdialysis".  The idea is that you've got an animal implanted with a probe that ends in a particular brain region you're interested in.  The end of the probe is a "semi-permeable membrane", and you've got liquid flowing through the probe.  At regular intervals, you take some of the liquid and use a chemistry technique called high performance liquid chromatography (HPLC) to measure the levels of various things that dissolved into the probe.  In rare cases, you can do microdialysis experiments in humans (patients with severe epilepsy).

Another way of measuring the release of particular neurochemicals, with better time resolution than microdialysis, is fast scan cyclic voltammetry (sp?).  I'm not really familiar with it, but it exists.

In terms of interactions among different neurotransmitter systems, there are many ways this can happen.  Cells that release transmitter A might be excited or inhibited by transmitter B.  Transmitters A and B might act on different G proteins in the same cell, with opposite effects on some downstream system ("Gi coupled receptors" and "Gs coupled receptors" have opposite effects on cAMP, for example).  Receptors for two different transmitters may be physically right next to each other and affect each other's functioning (D2 receptors and adenosine A2A receptors, for example).  Neurotransmitters may bind to each other's receptors or use each other's uptake proteins (cortical dopamine is taken up by norepinephrine transporters; there are norepinephrine receptors in the striatum despite the absence of norepinephrine terminals, presumably because they can be activated by dopamine).  Single neurons may release more than one transmitter at a time (glutamate and dopamine can be released from the same cell).  The downstream effects of one receptor may cause a second receptor to be phosphorylated, affecting its function in some way.  Downstream effects could also change gene expression.

My suggestion would be to start searching PubMed for review papers related to things you're interested in.  At least some of them should be available without a university library.


How to convince subjects that the computer is playing fairly We are planning an experiment using the odds-and-evens game. The rules of the game are simple: player A selects either "1" or "2"; player B selects simultaneously either "1" or "2"; if both select the same number, player A wins \$1 and B wins nothing; if they select different numbers, player B wins \$1 and A wins nothing.

In our experiment, player A is a human subject and player B is a computer program (the computer is programmed to play randomly - select "1" or "2" with equal probability each time). Our concern is: how to convince the human that this is really what's going on? The problem is that, the human reveals his choice by clicking a button, before the computer reveals its choice. So in theory, we could have programmed the computer to always choose a number different than the choice of the human. Indeed, we have an incentive to do so because it will reduce the amount of money that we will have to pay to the subjects!

How can we convince the human subjects that the computer makes its choice simultaneously and does not "cheat"?

As computer scientists, the first option that came to our mind is to use a cryptographic commitment scheme. But, this might be too complicated for the subjects to understand. Are there simpler solutions?

I'm imagining a system that chooses the computer's response not in a stochastic manner, but chaotically. Suppose you have some chaotic mapping function from the [0,1] interval to the {heads, tails} set. Choosing any real number in the set will get you some deterministic mapping to heads or tails. This mapping equation should be quite complex, but made visible to the user. Have them choose a number in [0, 1], and you'll get an output that appears random, but could be computed if the user chose to take the time. You just need to make the mapping function complex enough that it's not easily computable to rig the game, and also such that it maps 50% to heads and 50% to tails.


Is there anything comparable to the IPIP for IO psychology, work psychology and the like? The International Personality Item Pool is a public domain collection of over 3000 items and 250 scales.

Is there anything comparable for work psychology and the like?

I'm not aware of any such initiatives. But it would be great to see.

In general, I think I/O psychology has been a bit less proactive in engaging with the open science approach than some disciplines of psychology. More generally, many researchers are silent on the issue of licences for their scales. Thus, it can be ambiguous about what you are allowed to do with a scale, say, that you find in a published journal article. Furthermore, many scales in organisational psychology are explicitly free to use for research purposes are not free for commercial purposes.


Is love from families a necessity for children to form nornal relationship? Some human skills need specific input during childhood to develop, such as language skills. Is the ability to love one of them? I.e., does the formulation of intimate relationship with partner (or any other relationship, like with kids or friends) require the input of love from family members during childhood?

Related research can be, like, can victims of domestic violence form normal and long-lasting relationships when they grow up? Or any dataset/survey/study on similar focus?

not being an expert in developmental psychology i cant give precise information but i have recently been listen several of "the great courses" on human development and personality.

i think the consensus of modern (and a large extent of more "vintage" research) would support the idea that we need affection and the security that having a relationship with caregiver provides. (bowlbys monkeys etc). any diusruption to this kind of input will have an affect on development. i did read an interesting study (i think it was an Italian university) on the development of psychopathic traits in abused children, so i think its probably safe to say that the trend certainly lies in the direction that says forming relationships needs some reciprocal affection.

i wouldnt go as far as to say that authoritarian parents  = less love-capable offspring, people are to complex for such a basic interpretation. there is also the issue of CBT and other treatments in helping to develop these bonds. i think most parents would probably agree that they didnt really know as much about love as they thought until they had children to care for.


Why does it seems in similar cases sometimes classic conditioning happens and in others habituation? I'm slightly confused and was hoping you guys could correct me.

In classic conditioning as with Pavlov's dogs if we ring a bell just before a dog is given food, the bell will give the same response for the dog as the food alone would have, such as an excess of saliva. On a cellular level when two cells fire at a similar time one can cause the other cell to fire.

What I don't understand is why this doesn't happen in cases of habituation. So we already have the connection fattening foods taste good and when we eat a burger it should strengthen the connection between this is a fattening food, you like fattening foods you like this burger, but this doesn't happen if we had burgers everyday we get bored of it.

So guys where am I going wrong here? One a cellular level whats going on?

The Wikipedia article on Habituation explains it fairly well:

  The habituation process is a form of adaptive behavior (or neuroplasticity) that is classified as nonassociative learning. Nonassociative learning is a change in a response to a stimulus that does not involve associating the presented stimulus with another stimulus or event such as reward or punishment.[4] (Examples of associative learning include classical conditioning and operant conditioning). Habituation is the decrease of a response to a repeated eliciting stimulus that is not due to sensory adaption or motor fatigue.

Classical Conditioning strengthens associations and elicits a response because the stimulus is associated with something. The bell means food, pay attention to it. Habituation happens when there's no association; why keep getting worked up by the church bells ringing when you know it doesn't mean anything important (as opposed to a tornado siren).

To generalize "classical conditioning" further into just "associative learning", they're two sides of the same coin; if something is important, connections in your mind strengthen; you remember and a response is illicited. If something isn't important, you stop caring about it and might fail to notice the stimulus at all. This is why excessive fire drills (and worse, false alarms) can be a bad thing; many college students end up being habituated against fire alarms rather than being classically conditioned to know "loud noise" -> "get the heck out".


How many thalamocortical relay cells synapse onto each spiny stellate cell in neocortex? I am curious about how many different thalamocortical relay cells synapse onto each layer IV spiny stellate cell, on average? The answer is likely to be different per region and species, of course. I understand the topographic mapping that occurs, but how narrow or wide is the final projection?

From Shepherd's Synaptic Organization of the Brain (5th ed, pg 513):

  In the cat visual cortex, the terminal arbors of each individual
  thalamic afferent may extend over 1-5 mm of the cortical surface (Fig. 12.11)
  so that each point in layer 4 is covered by the arbors of at least 1000
  separate thalamic relay cells. Thus, the dendritic tree
  of an average layer 4 neuron, which extends for 200-300 micron, could
  receive input from many more thalamic afferents. However, the
  connections are not made randomly between the geniculate afferents
  and the cortical neurons. Selectivity is expressed in several ways.
  For example, there is a high degree of precision in the visuotopic map
  recorded in the first-order cortical neurons in the input layer, i.e.,
  those receiving mono-synaptic activation by the thalamic afferents.
  This clustering is made according to the eye preference of the arbors.
  The afferents of those thalamic relay neurons that are driven by the
  right eye cluster together in regions about 0.5 mm in diameter and are
  partially segregated from the afferents that are driven by the left
  eye. This segregation forms the basis of ocular dominance columns.

There are, of course, many other factors in the specificity of thalamocortical projections.
Point here being that thalamocortical projections are not necessarily limited to cortical neurons with a shared receptive field in visual space, but may be limited in other ways.

Interestingly, the corticothalamic feedback projection is also not limited to shared spatial receptive fields (Shepherd, p. 321ff.):

  Thus, for the lateral geniculate nucleus, this cortical pathway comes
  from visual cortex (mostly areas 17, 18, and 19), and likewise,
  somatosensory and auditory cortex project back, re- spectively, to the
  ventral posterior lateral and medial geniculate nuclei. One
  implication of this reciprocity is that the corticothalamic pathway
  faithfully ad- heres to the map established in the thalamic nucleus.
  For instance, the corticogenicu- late pathway conforms to the
  retinotopic map in the lateral geniculate nucleus. However, there is
  some question as to the extent to which the maps match at the cellular
  level. This is based on evidence that, in the cat (Murphy and Sillito,
  1996), the spread of an individual corticogeniculate axon arbor can be
  quite extensive, reaching well beyond the region within which
  receptive fields that match those of the cortical axon can be
  recorded. The corticogeniculate terminals have a maximal extent of 1.5
  mm compared with the spread of a typical retinogeniculate arbor of
  only about 0.2-0.4 mm (Bowling and Michael, 1984; Sur et al., 1987).
  The retinogeniculate arbor's expanse roughly corresponds to the size
  of a geniculate receptive field, implying that the corticogeniculate
  axonal arbor can contribute to subtle effects on relay responses
  beyond the "clas- sic" receptive field. However, the majority of the
  corticothalamic terminals lie in a central core that roughly
  corresponds to the classical receptive field.


To what extent does the awarness of the presence of others affect brain function and cognitive state? This scope pertains to non-life threatening interactions and the awareness of the presence of a single or multiple individuals - (not direct conversation, not group mentality) just the presence.

To what extent does the presence of others affect brain function, emotion and cognitive state?

What are the differences within the host that cause certain individuals to evoke stronger cognitive changes vs. those that evoke weaker changes?

What are the changes in state when one is completely sure nobody is around?

Are there any studies that measure this or show what a reasonable standard deviation would be for this phenomenon?

In addition, what are the factors that allow the host to completely block any changes in cognition regardless of the presence of others? (i.e. - higher serotonin, larger frontal cortex, etc?)

I recently came across an article (1) examining the effect of an observer on cognitive task performance. The meta-analysis showed an overall negative effect associated with the presence of others leading to a poorer cognitive performance.

I am not aware of an article investigating such an observer effect using brain imaging techniques. It didn't stop researchers (2) to speculate on a cognitive/neuropsychological model of social inhibition. They stated that "the presence of others places high demands on the frontal and executive systems, leaving less available processing capacity to dedicate to performing tasks that require executive and frontal processing. The presence of others may, in turn, facilitate performance on tasks that rely less on frontal and executive processing".

I leave them the final sentence of this post:

"there is clearly potential for more collaboration between social psychologists
and those working in cognitive psychology and neuroscience"

(1) Eastvold et al. (2012). Does a Third Party Observer Affect Neuropsychological Test Performance? It Depends. The Clinical Neuropsychologist, 26(3).

(2) Wagstaff et al. (2008). Some cognitive and neuropsychological aspects of social inhibition and facilitation. European Journal of Cognitive Psychology, 20(4).


Interpretation & Actual Result of "10% of your brain" Myth It is well known that the common myth that an individual  only ever uses 10% of their brain is.. well, a myth. I had a question about a possible interpretation of this idea, and a follow-up question about the result of that interpretation.

After spending a small amount of time with computational neural networks, it seems that at any given time, a small percentage of neurons are actually firing. All neurons have the potential to be firing, and at some point in execution likely will fire, but due to efficiency, only very few are needed for a particular function. This is my interpretation of what I have seen so far.. is this interpretation valid for the activity of neurons in the brain?

If this is valid, what would happen if 90-100% of neurons were firing at all times? I'm assuming this would be a huge disadvantage to whoever this happened to. Epilepsy? Overheating? Would the body be overworked and go into shock?

It is correct that only a small percentage of neurons increase their activities  relative to their baseline level in response to   new stimuli or to more abstract thoughts. There are many computational advantages to this. For instance, in deep learning, sparse coding is a class of unsupervised methods for learning sets of over-complete bases to represent data efficiently. Basically you have more combinations to store patterns if you activate a few cells than if you either activate too few or too many.