# Question
Title: Hobbies / interests correlated with Big 5 scores?
Are there any established treatments (I'm going to leave the exact terms a little bit vague because my understanding is vague) of which hobbies and interests are most likely to be attractive to someone with XYZ score on an OCEAN / Big 5 test?

TIA,

# Answer
> 3 votes
Yes. One example is that people high in Openness to New Experiences are interested in aesthetic experiences including museums and being in nature, and novel experiences as you'd expect from the name. https://psycnet.apa.org/record/1997-08808-031

Treatment is a bit misleading here to mean 'study', because in psychology it usually means 'intervention'.

# Answer
> 0 votes
Holland's RIASEC is probably the most studied such personality-based model of vocational choice. Note however that's not quite Big Five based though. See https://doi.org/10.1016/B978-0-12-804674-6.00025-9 for the details. It's way too much to get into the details here, but a teaser quote:

> vocational interests are markedly more stable than the Big Five personality traits in adolescence and young adulthood (Low et al., 2005). Although the stability of both constructs increases during these life phases, the stability of interests becomes stronger, and vocational interests remain more stable than the Big Five personality traits for ages 22 to 29. From ages 30 to 39, the stability coefficients of the Big Five and vocational interests converge. However, even though vocational interests tend to be remarkably stable, there is still room for change.
>
> \[...\]
>
> The approach of viewing vocational interests as personality traits is based on personality models (e.g., the Neo-Socioanalytic Model of Personality; Roberts & Wood, 2006; McAdams & Pals, 2006) that distinguish between personality traits and motivations and consider interests and personality traits to be equivalent or regard interests explicitly as personality characteristics (e.g., Kandler, Zimmermann, & McAdams, 2014). By contrast, several other models of personality view interests as outcomes of personality traits (e.g., McCrae & Costa, 2008).
>
> \[...\] Holland himself stated that vocational interests are “an important aspect of personality” (Holland, 1997, p. 8), and he defined the six interest types as “personality types” (Holland, 1997).

See also a review on the correlation of choice of academic major and Big Five personality (that's got some mainstream press coverage.)

> Consistent findings across studies were that students of arts/humanities and psychology scored high on Neuroticism and Openness; students of political sc. scored high on Openness; students of economics, law, political sc., and medicine scored high on Extraversion; students of medicine, psychology, arts/humanities, and sciences scored high on Agreeableness; and students of arts/humanities scored low on Conscientiousness. \[...\] For all Big Five personality traits medium effect sizes were found frequently, and for Openness even large effect sizes were found regularly.

(Some will surely turn on the MBTI-style cliché/stereotype generator based on that.)

I'm not sure if there's that level of research depth for just "hobbies and \[non-professional\] interests" as opposed to vocational/academic-major choice, but probably there are some papers on the less professional interests. I'm not sure there's a unifying (attempt at) theory for just any interests, but one can surely find somewhat amusing/disparate papers like:

> Collectors with an investment motive tend to have above-average education and financial means. High Openness and low Agreeableness significantly characterize their personality.

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Tags: cognitive-modeling, behavior, io-psychology, big-five
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# Question
Title: How to confirm that a more frequently labelled object is a better instance of the label
I have some data from a study where humans are shown an object and asked to select all words from a list that apply to the object. What I am trying to do is use the data to confirm that a particular object, $o\_{1}$, is a better fit of a particular word, $w$ , than another object, $o\_{2}$. I am trying to use hypothesis testing to confirm this, with a null hypothesis that $o\_{2}$ is an equivalent or better fit than $o\_{1}$ i.e. the probability of labelling $o\_{2}$ with $w$ is greater than or equal to the probability of labelling $o\_{1}$ with $w$.

There are $n\_{1}$ annotations for $o\_{1}$, in which the object is labelled $x\_{1}$ times with $w$. Similarly $o\_{2}$ is labelled $x\_{2}$ times in $n\_{2}$ annotations.

To calculate the p-value I am working out the probability of observing the difference in the proportion of times $o\_{1}$ and $o\_{2}$ are labelled with $w$, $P(x\_{1}/n\_{1}-x\_{2}/n\_{2}\geq d)$, where d is the observed difference. This gives quite a long function, which relies on the actual underlying probability, $p\_{1}$, of labelling $o\_{1}$ with $w$, so now I suppose I have to find $p\_{1}$ which maximises this function?

I feel uncertain that I'm tackling this in the right way, does this seem correct?

# Answer
Fishers's exact test exists for this purpose which calculates the p-value from a contingency table. In this case the null hypothesis is that $o\_{1}$ and $o\_{2}$ are equally likely to be labelled with the word. As noted by @Bryan it may also be possible to use a two-proportion z-test, but this would require a larger dataset.
> 0 votes

# Answer
You could possibly use a two-proportion z-test to test against the null hypothesis that $(x\_{1}/n\_{1}-x\_{2}/n\_{2})==0$, though there may be better methods that consider the overall distribution of words chosen and accounting for differences in raters in terms of how many words they choose (your situation does not fit the assumptions of the test but may be 'close enough' for certain purposes).
> 0 votes

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Tags: statistics, data, experiment-design, linguistics
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# Question
Title: What percentage of the population have the brain anomaly associated with the inability to exhibit empathy?
According to an article on livescience.com, *"Narcissists' Lack of Empathy Detected in Brain Scans"*, research seems to indicate that a low volume of grey matter in the left anterior insula is associated with an inability to exhibit empathy.

> Researchers used magnetic resonance imaging to scan the brains of 34 people, including 17 individuals who suffer from narcissistic personality disorder, and found that pathological narcissists have less gray matter in a part of the cerebral cortex called the left anterior insula.

What percentage of the population have this particular condition?

# Answer
In short, the question cannot be answered as-is. I will explain why, and then answer a broader question that you may find useful instead.

**Reverse Inference:**

As background, consider the common problem of reverse inference: Suppose we identify subjects with relatively low grey-matter volumes (GMV) in the left anterior insula (LAI). Can we conclude that these subjects have low empathy? Well, the source paper for the referenced article already says ... not really:

> GM volume of the left anterior insula was marginally, positively correlated with emotional empathy (... p\<.10 ...).

What about NPD, can we conclude that they have NPD? Well, subjects with low LAI GMV might have NPD, or they might just be good singers! Or maybe they are just good at learning new languages! In fact, low LAI GMV is associated with some cognitive advantages, as well as many mental disorders. See, one of the problems with reverse inference is that psychological constructs simply do not line up well with gross neuroanatomical features - that is, brain regions do multiple things.

**Anatomical Abnormality:**

A second issue is with the concept of an abnormality. Although the source paper discusses "structural abnormalities in fronto-paralimbic brain regions of patients with NPD," it does not define this abnormality. Consider this figure from the paper:

Here, the vertical (Y) axis represents LAI GMV. It does appear that NPD patients (green) have lower LAI GMV than healthy controls (yellow). However, where is the abnormality? What volume difference constitutes an identifiable condition?

**Normal Distribution:**

Technically, we should also be concerned with the low power of this paper (only 17 subjects in each group). For example, an earlier study (with 11 subjects in each group) found differences in the right anterior insula rather than the left. Hmmm... Replication crisis anyone? But let's put that aside for a minute, and consider the question at hand.

Suppose for a minute that low LAI GMV did indicate something about empathy (though it probably does not), and that there was a definable abnormality of LAI GMV (though there probably is not), what percentage of the general population would have such an abnormality?

Well, it's reasonable to use a normal distribution to estimate this. For this, we need average and standard deviation values for LAI GMV. I am not aware of a meta-analysis looking at this, but some individual studies report such values. For example, this study of 39 subjects reports LAI GMV (corrected for total brain size) mean = 2209mm3 and std = 214.2mm3. Supposing that this is representative of the general population (I wouldn't assume that, but it's a start), a normal distribution might look like this:

For this example, I just went with the cut-off being the mean for clinical patients in the study (2124mm3), resulting in about 35% of the population below the cut-off, but you can construct your own graph with whatever cut-off you deem useful for your purposes.
> 6 votes

# Answer
Kent Kiehl's work may be the closest means of determining this. According to an interview, he states "psychopaths have 5 to 10 percent reduced gray matter density in and around the limbic regions \[a network deep in the brain that's important for emotional processing\]." If his source(s) can be examined for 1. what percent of psychopaths exhibit such reduced gray matter like all or most or some and 2. compared to what data regarding the general population.

For the former, it could be twisted into finding your answer by simply combining that and the fact (which multiple sources have reported) that psychopaths make up 1% of the population (Note!: almost all sources that report this do so based on behavior, which is sampled and attempted to be detected, not based on anatomy and brain structure).

It is in the latter where more details on this condition can be found for the general population, if Kiehl source(s) does happen to have it.

If anything, enough brain scans of the general population to best ascertain this have not been conducted.
> 1 votes

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Tags: moral-psychology
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# Question
Title: If it takes multiple action-potentials to cause one action-potential in another neuron, why don't brain signals dissipate almost immediately
I just got into neuroscience like a couple of months ago, but I can't, for the life of me, figure this out. Wouldn't it take a humongous amount of action-potentials in, for example, the thalamus for a small number of neurons to fire at the opposite end of the brain in the frontal cortex? Also, usually, signals travel from the cortex back to the thalamus, so is it possible for signals to get boosted in some way? It just seems there wouldn't be enough action-potentials for there to be any circuitry in the brain.

Edit: My thought process is very mathematical, and I didn't think about temporal summation when thinking about this, but let's say, for example, that it takes 4 APs to fire a single neuron. That would mean that y = x/4, with y being the amount of output APs and x being the amount of input APs. Let's say that 100 million neurons need to fire to reach the end of the frontal cortex. That would mean you'd need 400 million input APs in total to reach the end of the frontal cortex. That seems like a lot, but while typing this, I feel like my grasp of some of the more basic aspects of neuroscience isn't really that great. I'm self-teaching so maybe that has something to do with it.

# Answer
> 3 votes
This answer is a bit below my normal referencing standards, but hopefully helps you with some things you're missing and motivates further reading...

1. Thalamus (at least parts of it) projects directly to frontal cortex (and everywhere in neocortex). Just one synapse from thalamic cell to cortical cell. Neurons send long projections (axons) from region to region. So, with your assumption of 4 presynaptic neurons per cell (which is probably on the low side, but see 2 and 3 below) that would mean just 4 cells in thalamus, rather than 400 million.
2. In the CNS, especially in the brain and even more especially in neocortex, connections are one-to-many (divergence) and also many-to-one (convergence). When one cell fires, it influences many other downstream cells (for order of magnitude you can assume "thousands"). The strengths vary: some cells get larger inputs than others from the same cell.
3. Most connectivity is local, and the entire brain is constantly active. For typical neocortical cells, you might see a *minimum* firing frequency of around 1 Hz in normal *in vivo* conditions. There are billions of cells each connected to thousands of others, so any one cell is receiving many many inputs at any one time. Other inputs arrive on this background of activity.

I'd recommend starting with a basic neuroscience textbook; Purves' Neuroscience is a good one as is Kandel's Principles of Neural Science. If you're coming from a more computational background, Dayan and Abbott's Theoretical Neuroscience is also a good book, but I'd suggest pairing it with something more rooted in biology as well.

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Tags: brain
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# Question
Title: What Field of Behaviorial Psychology Deals with Technology? How the Application of Pyschology can Improve Something Like Computers
My real question is where can I find people to discuss topics in this area of study - the application of behavioral psychology on technology and computers. For example, can we use what we know about the physiology of the brain and the psychology of humans to make better software?

I know that behavioral psychology is starting to be applied to the areas of economics. Is it being applied in other areas like technology? How would I be able to form discussion groups with people interested in this topic?

Thank you for any guidance that you can provide.

# Answer
> 1 votes
What you are looking for is not so much a 'sub-field', as they are cross-disciplinary fields of researchers who borrow from different fields, including computer science and psychology.

Human factors:

> Human factors and ergonomics (commonly referred to as human factors) is the **application of psychological and physiological principles** to the engineering and design of products, processes, and systems. The goal of human factors is to reduce human error, increase productivity, and enhance safety and comfort with a specific focus on the interaction between the human and the thing of interest.

Human-Computer Interaction (HCI):

> Human–computer interaction (HCI) studies the design and use of computer technology, focused on the interfaces between people (users) and computers. Researchers in the field of HCI observe the ways in which humans interact with computers and design technologies that let humans interact with computers in novel ways. As a field of research, human–computer interaction is situated at the intersection of computer science, **behavioural sciences**, design, media studies, and several other fields of study.

We have a tag on this site.

Information science:

> Practitioners within and outside the field study application and usage of knowledge in organizations along with the interaction between people, organizations, and any existing information systems with the aim of creating, replacing, improving, or understanding information systems. Historically, information science is associated with computer science, **psychology**, technology and intelligence agencies.

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Tags: brain-computer-interface
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# Question
Title: Is there any formal understanding of how humans perceive humanity/vitality in other entities?
When humans watch animations which contain human-like characters in them, we seem to imagine that the animated individuals, whether they be photorealistic or mere stick figures, are human, or at least living, in some way. If I see a stick figure get his or her heart broken, I feel for them as if I were watching a character in a movie get their heart broken.

There is obvious nuance in that my emotions will likely be different in response to watching two situations which ceteris parabus only differ in that one has stick figure characters while the other has high-qualtiy photorealistic ones. However, there still seems to be something going on where the mind imbues entities with a perception of humanity, or at the very least of vitality.

So, **my question is** first and foremost whether or not there has been any research done our perception of other things as human/alive (this seems like something that would at least happen in child developmental fields), and if so, is there a particular region of the brain and/or pathway/mechanism that we know is involved with this behavior?

# Answer
Yes, there's a lot of work on this! Still a ton of open questions though, and plenty of smart people working in quite disconnected paradigms.

A classic study in this space is Heider F. & Simmel M. (1944). An Experimental Study of Apparent Behavior, The American Journal of Psychology, 57 (2) 243. DOI: 10.2307/1416950

But note the date! 1944! I think what you're really looking for is the community that is still citing this today.

One recent example might be people interested in Bayesian Theory of mind, eg: Baker CL, Jara-Ettinger J, Saxe R, & Tenenbaum JB (2017). Rational quantitative attribution of beliefs, desires and percepts in human mentalizing. Nature Human Behaviour

Also, 'agency' is one of the areas identified/investigated as part of core developmental knowledge by Spelke and collaborators, see for example Spelke, E. S., & Kinzler, K. D. (2007). Core knowledge. Developmental science, 10(1), 89-96.

This answer doesn't really do justice to the breadth of this literature, there's a lot of it! But hopefully the citations and cited-by links from these will throw up the kind of thing you're looking for.
> 2 votes

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Tags: cognitive-psychology, social-psychology, perception, cognitive-modeling, developmental-psychology
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# Question
Title: How can motivation be increased by improving brain chemistry with nutrition and activities?
I'm reading some material about motivation and brain chemistry. One of the interesting articles is "7 Ways to Increase Motivation by Improving your Brain Chemistry". I'm interested in a more scientific treatment of the topic. Thus,

* How can motivation be increased by improving brain chemistry with nutrition or various activities (sport, exercise, relationships etc.)?
* What scientific articles exist on this topic?

It would be great if there was some article targeting this exact topic with references.

# Answer
The best thing you can do is avoid nutritional deficiencies and exercise. In general, it's the same as for the rest of the body. Many people have subtle nutritional deficiencies that they may never know about their whole life just based on eating habits. As Chuck Sherrington said, neurotransmitter-based treatments are subject to homeostatic compensation, but if you have a deficiency, it may be more complicated.

**Nutrition**

Particularly, the same things that increase pulmonary/circulatory health are going to increase brain health\[1,\]. A large contribution to health in the developing fetal brain comes from the mother's diet. There are lots of diseases associated with maternal nutrtional defecits\[,\].

**Exercise**

Running and other physical activities increases neurogenesis \[5,\]. But does it do it "intelligently"? I don't know. More neurons isn't automatically more motivation or intelligence. But it is a stress-relief technique, and too much stress can certainly kill motivation.

**Behavior**

You didn't ask, but behavioral practice is probably another strong factor. For example, breaking jobs into smaller tasks: getting the first small task done can give a motivational boost towards getting the second done (and so on). They've actually found a correlation between paying smaller loans off first (even though not mathematically more efficient in terms of costs) is more likely to lead to loans being paid off all the way because of the human element\[9\]
> 4 votes

# Answer
Low / loss of motivation is associated with several Disorders of Diminished Motivation (DDM) (eg, akinetic mutism, abulia, apathy) that occur frequently in individuals with traumatic brain injury or other underlying neurological disorder, as well as avolition, and is a prominent symptom of dysthymia, motivational anhedonia, schizophrenia, and others.

There is not much research on treatment of motivation in these disorders with nutrition, possibly because of the underlying neurological causes, the complexity of studying nutrition, and low incidence rates. For a reasonably useful answer, I will instead review the effect of nutrition on motivation in depression, where much more research is available, and this would hopefully extend to low motivation in general.

**Personalized Nutrition:**

There are several reasons why it may be impossible to find clear answers on nutritional treatments for motivation. For one, known nutrient deficiencies rarely manifest in isolated cognitive symptoms such as low motivation - but rather with acute physical disease symptoms.

Another important factor is that nutrient deficiencies may have as much to do with individual characteristics as general dietary ones - that is, a dietary prescription may not work the same for everyone. Unfortunately, nutritional genomics as a field is currently in its infancy - see Ordovas et al (2018) for a recent review.

There are also many unknowns remaining regarding the role of the gut microbiome in depression, and the placebo effect of treatment - ie, seeing a nutritionist may well be as important as the prescription they provide. And ironically, some research suggests that fasting may be effective with depression - implying the opposite of a nutrient deficiency!

**Healthy Diet:**

Rigidly set dietary prescriptions can have advantages even when not personalized. For example, they take the onus off patients to make healthy diet choices, and may be more likely to be followed.

However, research on a variety of diets demonstrate that healthy diets have positive effects on depression (Molendijk et al, 2018; Opie et al, 2015; Firth et al, 2019). The general recommendation therefore is well known: Reduce sugar and processed foods, increase fruits and vegetables. This has the added bonus of not just improving motivation, but also improving overall physical and mental health!

So, the below recommendations are fine to follow, but just note that any healthy diet is fine too.

**Dietary Prescriptions:**

Several recent reviews of current findings containing specific dietary prescriptions are listed below, with relevant extracts. I encourage reading the papers for specific tests of nutritional interventions and their results, as recommendations may or may not be applicable.

Sathyanarayana et al (2008): Understanding nutrition, depression and mental illnesses

> The dietary intake ... are often deficient in many nutrients, especially essential vitamins, minerals, and omega-3 fatty acids.

Khanna, Chattu, & Aeri (2019): Nutritional Aspects of Depression in Adolescents - A Systemic Review

> ... several healthy foods such as olive oil, fish, nuts, legumes, dairy products, fruits, and vegetables have been inversely associated with the risk of depression and might also improve symptoms.

WebMD: Depression and Diet

> ... while certain eating plans or foods may not ease your symptoms or put you instantly in a better mood, a healthy diet may help as part of your overall treatment.

Brown (2012): Nutritional Brain Energy Enhancement for Reducing Mental Fatigue and Improving Mood and Cognition

> The enhancement of brain energy metabolism with nutritional factors such as creatine, acetyl-l-carnitine, multivitamins and polyphenol rich diets may be a novel strategy for reducing mental fatigue and improving mood and cognition ...
> 1 votes

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Tags: neuroscience, reference-request, motivation, neurology
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# Question
Title: to electrophysiologists, where is your electrode?
how do you know where is your electrode in the brain? Whether you're in the soma, axon, its terminal, dendrites - wouldn't it change your signal (and how)?

What happens if you are recording from a neuropil region? There are just so many possibilities when you stick up an electrode - how do you control this and keep your sanity?

# Answer
I don't really have an answer to your question, but I can give you some starting points. First regarding whether you are in the soma the answer is "very unlikely". Keep in mind your typical acute recording electrode will be ~100um in diameter, at least ~50um and up to ~250um for linear probes. Chronic recording electrodes (e.g. Utah arrays) can be much smaller but never smaller than ~10um. The body size of neurons vary within the range 10-50um. So if you poke the soma of a neuron with your electrode you will pretty much kill it instantly (unless you use patch-clamping, e.g. https://www.nature.com/articles/nmeth.1993/).

Now dendritic electrical potentials are small (few mV). Only after being non-linearly summed up will they reach the threshold that will trigger a spike (https://www.annualreviews.org/doi/pdf/10.1146/annurev.neuro.28.061604.135703). Spikes is what you are able to record, it is unlikely that dendritic potentials will be high enough for you to detect above background noise. Even if, it means your electrode is close enough to the soma and your recording will most likely be dominated by the neuron spikes, which will have a much higher Signal-to-Noise Ratio.

The trickiest part of your question is whether you are recording from an actual neuron or its axon. I see no reason why you wouldn't be able to record from an axon. Statistically I do not know how likely it is, considering that axons are far smaller, but much longer than the soma. I can provide 2 thoughts: (1) does it matter? Axons within gray matter most likely come from local neurons. As a physiologist your goal is to know when/what/how the neurons within the vicinity of your electrode are spiking. So does it matter that you are recording from the soma itself or its axon few hundreds of um away? (2) When you lower you electrode too much and reach white matter you start seeing strange spikes, usually I see "double-spikes" that look like an "M". Based on the depth of the electrode, background noise and that this doesn't look a regular spike, it is quite clear that this waveform comes from an axon. I've personally never seen similar waveform within gray matter. But of course I cannot be 100% sure that I've never recorded from an axon either.

As for how to keep your sanity, as always in science you draw conclusions based on what is most likely. Physiology is very hard, so as long as you made the best possible job targeting the correct recording area, isolated good-looking waveforms, did a rigorous spike-sorting and found meaningful effects related to your stimulus/task. Then is it more likely that you recorded mostly from proper neurons, with possibly few artifacts here and there, or that your recorded mostly from dendrites or axons from far-away neurons (that is things that are not related to computations actually being carried within the area your are recording from), and that all your effects are just an artifact? You'll never be able to completely eliminate uncertainty, but you can reduce it to levels that make you quite confident what you are reporting is true. Asking this question is a good start though.
> 2 votes

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Tags: neuroscience, electrophysiology
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# Question
Title: Definitions of the alpha wave in the revised glossary by Clinical Neurophysiology Practice?
I am a novice in EEG, and also not a native speaker of English.

I am reading through the article A revised glossary of terms most commonly used by clinical electroencephalographers and updated proposal for the report format of the EEG findings. Revision 2017 in Clinical Neurophysiology Practice. There it distinguishes the *alpha rhythm* and *rhythms of alpha frequency*. In the definition of alpha rhythm:

> Rhythm at 8–13 Hz inclusive occurring during wakefulness over the posterior regions of the head, generally with maximum amplitudes over the occipital areas.

Which, I read, refers to that alpha wave we also know as the PDR (posterior dominant rhythm). Notably,

> “\[others in this frequency band\]... should either have specific appellations ... or should be referred to as rhythms of alpha frequency or alpha activity.”

Ok. Then, I expected *alpha wave* to be generic, defined as waves in 8–13 Hz. However it read:

> Alpha wave: Wave with duration of 1/8–1/13 s (77–125 ms).

As I understand, duration of a wave (as in physics) is different from its period. A period is the inverse of frequency, while duration is either the time the wave continues, or the time of single up and down which doesn't cycle. The glossary itself has an entry for duration:

> Duration: (1) The interval from beginning to end of an individual wave or complex. Comment: the duration of the cycle of individual components of a sequence of regularly repeating waves or complexes is referred to as the period of the wave or complex. (2) The time that a sequence of waves or complexes or any other distinguishable feature lasts in an EEG record.

So it seems to me that it's either (1) The glossary is inconsistent in its wording, or (2) alpha wave as defined here is for single complex (similar to *spike* or *sharp wave*) that is characterised by its length in time. Either isn't very convincing for me: (1) They took their trouble ommiting the word frequency and using 1/8-1/13 instead of 8-13, would they use confusing wording? (2) From what I have gathered, this definition is used by a distinct minority (if any).

My question is:

* Is the glossary inconsistent? Can I understand the alpha wave **defined there** as Wave with *frequency* of 8–13 Hz?
* If not, can I understand this alpha wave as a name for non-cyclic activity? How widely is this definition used? Any other usuage of *alpha wave* I encountered simply refers to a continuous oscillation with frequency of 8–13 Hz.

# Answer
> 1 votes
I personally don't see the contradiction. It seems very contrived from your end to establish that there is one. I think it's very clear from the definition of the alpha wave that 'duration' is synonymous with 'period' in that case. In the 4th quote, defining 'duration', it even says this outright, "The duration of the cycle of individual components of a sequence of regularly repeating waves or complexes is referred to as the period of the wave".

Basically, looking at the definition of alpha wave where duration in that specific case equals period, solves everything. It's the most intuitive answer. Would it have been better if they had written 'period' instead? Probably. But to pick up on that definitional ambiguity, not see their definition of duration also includes that of period, and somehow claim that this implies people are defining alpha waves for non-cyclic activity is an enormous stretch.

The glossary's definition is correct and you can understand the definition of an alpha wave as a wave in the 8-13 Hz band / a wave with a period of 1/8 - 1/13 seconds.

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Tags: terminology, eeg, electrophysiology
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# Question
Title: Can Someone Explain How Fluid and Crystallized Intelligence was Discovered?
What is the difference between fluid and crystallized intelligence? How did Raymond Cattell deduce that our intelligence operates in these two different ways?

# Answer
> 4 votes
This is actually a fairly obscure topic in the history of psychology. According to a recent paper (starting with its conclusion), in the early 1940s Cattell mostly reforumulated an idea of Hebb, which the latter obtained by observing the differential effect (on verbal vs non-verbal abilities) of some brain injuries (lobotomies of various kinds actually). After a 20-year hiatus, Cattell published on this again (together with his student Horn) but this time with focus on the fluid intelligence as being "culture-fair".

> “Cattell's” theory of fluid and crystallized intelligence is Hebb's theory of Intelligence A and Intelligence B, given another name and popularized by Cattell. Cattell's theory was Hebb's idea. \[...\]
>
> In his 1943 paper, Cattell (1943, p. 179) stated that:
>
> > Hebb (1941c, 1942) has independently stated very clearly what constitutes two thirds of the present theory, for he says that “intellectual power may be needed for the first appearance of the qualitatively superior response, but not necessarily for its persistence” (Hebb, 1942), and “in any test performance there are two factors involved, whose relative importance varies with test: one factor being the lasting changes of perceptual organization and behavior induced by the first factor during the period of growth.”
>
> \[...\]
>
> Hebb's presentation (Hebb, 1941c) discussed the differences in effects of brain injury on adults and children and the finding that “certain kinds of abilities are less affected by late than by early injury.” While I do not have a copy of Cattell's (1941) APA presentation, I do have the typed version of Hebb's (1941c) in which he presented his ideas on Intelligence A and Intelligence B as follows:
>
> > It may be proposed that intellectual development includes two distinct things: (A) direct intellectual power, by neural maturation, and (B) the development of qualitative modifications of perception and behavior. The first factor is what reaches a peak somewhere around the beginning of adolescence, declining slowly thereafter; the second is the product of the first factor. \[Hebb, 1941c, p. 5\]
>
> \[...\]
>
> Hebb (1942, p. 287) \[...\] concluded by saying “The contrast is not between intelligence and knowledge, but between capacity to develop new patterns of response and the functioning of those already developed.”
>
> \[...\]
>
> The two pages that Cattell sent to Hebb for his comments include the definition of fluid and crystallized intelligence as follows:
>
> > Adult mental ability is of two kinds, which may contingently be called ‘fluid’ and ‘crystallized.’ ‘Fluid’ ability is a truly general ability to discriminate and perceive relations between any fundaments, new or old. Crystallized ability consists of discriminatory response habits built up in a particular field, through the original operation of ‘fluid’ ability, but no longer requiring a true insightful perception for their successful functioning. Intelligence tests test, at all ages, the combined action of fluid and crystallized ability, recording the level of whichever is higher.
>
> He continued to say that: “the level of the ‘crystallized’ abilities has been largely determined by the original level of the all-round, ‘fluid’ ability. ‘Crystallized’ ability is thus a dead coral formation revealing by its outlines the limits of the original living process. Loss of any system of discriminatory habits, e.g., through brain injury, is now likely to remain more localized, i.e., to affect general ability less, and to be less remediable. For as the tide of ‘fluid’ ability recedes after adolescence the ‘crystallized’ discriminatory powers persist at a level above that at which the fluid ability is capable of rebuilding them.” (Hebb, 1941-1942, R.B. Cattell to Hebb, September 22, 1941)
>
> \[...\]
>
> Hebb showed Cattell's letter to his Head of Department, George Humphrey, and Humphrey then wrote to Cattell that “I do not think however that you should present this as your own hypothesis. It is in essence the theory on which Hebb has been experimenting all the year.” He continued to say that “Some hundreds of A.P.A. members heard Hebb put out the theory at the Evanston meeting, and I hope you will forgive me if I say that I am sure you would do your scientific reputation harm by publishing the paper in the form in which I have seen it, i.e., without giving him credit.” (Hebb, 1941-1942, G. Humphrey to R. B. Cattell, September 24, 1941)
>
> \[...\] Cattell also replied to Humphrey to explain how he developed his theory. He said that “I made what seemed to me a tenable, though possible premature, generalization on his data differentiating the adult abilities which do and do not deteriorate and asked in my last letter if he approved of the passage in which I described this as implicit in his writings.” Cattell went on to say that “The further theories are however quite independent, and to the best of my knowledge were neither in Hebb's paper nor in our after dinner conversation. My views were based on two pieces of evidence not in Hebb's field of research, and I had already discussed them with Thurstone and with Miles. Hebb's third source of evidence fitted in beautifully with these and completed the picture, but two thirds of the picture was already there. Naturally Hebb and I in discussion gained clarifications, but this would have happened if I had discussed the same matter with any other man of Hebb's intelligence and liking for the subject.” (Hebb, 1941-1942, R.B. Cattell to G. Humphrey, September 26, 1941)
>
> \[...\]
>
> Finally, Cattell agreed to credit Hebb, but suggested that he was being generous in doing so: “However, I trust that the revised statement which I have sent to Hebb will be agreeable to both of us, though I confess that on re-reading it I think it goes further in acknowledging priority of parts of the theory to Hebb than my reason alone indicates that it should.” (Hebb, 1941-1942, R.B. Cattell to G. Humphrey, September 26, 1941).
>
> \[...\]
>
> As noted by Horn (1966, p. 554), Cattell did not do any follow-up research on the theory of fluid and crystallized intelligence, but “left it on the shelf” until 1963, when he showed that two general ability factors could be derived from factoring culturally embedded and culture fair intelligence test results from a sample of 277 children in the 7th and 8th grades (Cattell, 1963). In this paper he concluded that one of these factors “fits the crystallized ability factor measured in traditional intelligence tests and the other a fluid general ability measured in culture-fair intelligence tests” (p. 20). Cattell's student John Horn continued to develop the theory of crystallized and fluid intelligence (Horn and Cattell, 1966, 1967).

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Tags: cognitive-psychology, intelligence, history-of-psychology
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# Question
Title: Rat between two walls viewed as a product in a category
I'm reading the book "A New Foundation for Representation in Cognitive Brain Science - Category Theory and the Hippocampus" by Jaime Gómez-Ramirez (a terrible book, if you ask me).

On p. 164 the author introduces the product of two objects in a category. I.e. the product of two objects $A$ and $B$ in a category $\mathcal C$ is another object $P$ equipped with two morphisms $p\_1: P\rightarrow A$ and $p\_2: P\rightarrow B$ such that for any pair of morphisms $x\_1: X\rightarrow A$ and $x\_2: X\rightarrow B$ there is a unique morphism $h$ making the figure commute.

The author goes on to say that the main characteristic of a product is that the constituents are retrievable via the projections. The following example is given: Let $W\_A$ and $W\_B$ be two walls that the delimit the maze a rat is moving in. After reaching both walls, the rat would develop the concept of a middle point $P$. This middle point $P$ corresponds to the categorial product $P=W\_A \times W\_B$.

I struggle to make sense of this. If the walls, or more generally, any location in the maze, are objects in a category, then what are the arrows (morphisms)? My first guess is: paths. Translated into the maze-world: There is a "concept" $W\_A \times W\_B$ that gives me paths from each wall to the middle $P$. And given any point $X$ in the maze there is a unique path $X\rightarrow P$ from $X$ to $P$. This interpretation doesn't make sense at all.

The second guess is that the walls $W\_A, W\_B$ are not actual locations in space, but the rat's concepts of these walls. But it is still unclear, what the arrows between concepts are supposed to be.

**Is there a way to make sense of this? Specifically, what exactly is this "maze-category"?** Because to me, so far, this is just half-baked, abstract nonsense jibber jabber.

Any pointers to more substantial literature would be greatly appreciated!

# Answer
> 1 votes
According to the author, in this maze-category the objects are memories (or mental objects).

The author references to chapter 3, when discussing the maze-category. Chapter 3 of the book, gives an application to Memory Evolutive Neuronal Systems (MENS). There, a morphism represents a way of relating mental objects. This is a general description.

The author gives as examples for the maze-category:

* travel time
* number of steps needed to go from one mental object to another.

The product $P$ of two memories is two memories at once. The concept of a middle point requires that the agent has the memories of both memories. One wall only requires one memory.

$X$ can potentially represent any of the points between the two walls.

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Tags: cognitive-modeling, mathematical-psychology
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# Question
Title: Satisfaction from music due to correct prediction of a sound
Ive randomly thought about a vague idea that perhaps the satisfaction I experience when listening to music is due to my brain correctly predicting a next sound in a sequence.

Do you think that has any theoretical truth to it? If so, what do you think an evolutionary reason to feel satisfaction after predicting a sound?

Another observation is that listening to unfamiliar music, for example a classical music sequence, is not satisfying to me. I'm not sure if I can appreciate its beauty that so many people see. What about that?

I'm not sure if that's the right place bu I just wanted to share my thoughts. Is there any interesting writing on that? I'm also not sure which tags to use-please feel free to categorise my question or point me to another forum for discussion. Thanks!

# Answer
> 3 votes
That's pretty much the core argument of "On the joys of perceiving: Affect as feedback for perceptual predictions" (2015) Chetverikov & Kristjánsson. It's a fun read, I think you might enjoy it.

Obviously music and other arts pull a bunch of other affect levers as well, not just this one. And "correct predictions" might not be the best way to characterize this particular lever: maybe the pleasure comes from being *predictive* rather then *predictable* cf. Braem, Senne, and Trapp (2019) "Humans show a higher preference for stimuli that are predictive relative to those that are predictable." Familiarity with a music style confounds the two, they both go up as you get a feel for the style. There's obviously *something* going on with curiosity/exploration/novelty also being pleasurable, but I don't think it's clear yet if you get that 'for free' with the predictive account or if an intrinsic reward for exploration should be its own thing.

Anyway, long story short there's some literature that looks a lot like your 'random vague idea', it's incomplete ongoing work, but it sure looks like it might be going somewhere interesting. Enjoy!

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Tags: neuroscience, brain
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# Question
Title: Extra-classical receptive fields are surprising, but retinal ganglion receptive fields are not. Why?
Rao and Ballard (1999) start their paper by stating that extra-classical receptive fields, which exhibit the phenomenon of end-stopping are difficult to explain. They show that in an idealized predictive coding model trained on natural images, the "neurons" at a higher level in the model have a receptive field that exhibits end-stopping; therefore, if neurons in the brain are implementing predictive coding, they would exhibit this phenomenon.

What I don't understand is this - why is it difficult to explain extra-classical receptive fields? After all, retinal ganglion neurons that are on-center will also exhibit "end-stopping" if a stimulus extends outside of the center, and the explanation for that receptive field is straightforward: the photoreceptors at the periphery hyperpolarize the ganglion cell, whereas those at the center depolarize it. Why can't a similar story be told about cortical neurons? Why was the predictive coding framework needed to explain end-stopping?

# Answer
> 0 votes
The difference is that ganglion neurons are responding directly to phenomena *in* their receptive field. That is, the on-center, off-surround ganglion cells are directly connected to the photoreceptors at the center and in the surround. The explanation for off-surround is that photoreceptors at the periphery will directly hyperpolarize the ganglion cell.

Extraclassical receptive field effects are about explaining how a neuron (e.g., in V1) responds to phenomena *outside* its receptive field. That is, it is possible to map the entire portion of the visual field that it is hooked up to, e.g., by passing a stimulus across the visual field and noting all regions where spike trains are evoked by the stimulus. This portion of the visual field is known as the classical receptive field. It turns out that V1 neurons can be influenced by stimuli *outside* their classical receptive field. Unlike "end-stopping" in retinal ganglion neurons, this cannot be explained by hyperpolarizing input at the periphery of the receptive field, because the stimulus causing the end stopping is *not* in its receptive field in the first place.

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Tags: neuroscience, theoretical-neuroscience, computational-modeling
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# Question
Title: What is actually happening with neuron during refractory period?
Sorry for a very rookie question. I've got an interest in spiking neural networks and therefore I started learning about different neuron models like Leaky integrate-and-fire, Izhikevich, etc. But then I became interested in the biological nature of all the processes happening "under the hood".

What I really don't get at this point in time, is what is happening with the neuron while it is in its refractory state? Most of the sources say something like `during the refractory period, a neuron is unable to produce new spikes`. Yes, I get it. But what happens internally? I.e. how the incoming impulses are handled during this time?

I mean, a neuron is constantly receiving impulses (spikes) from other neurons it's bound with via synapses. So hundreds (or even thousands) of presynaptic neurons will keep sending impulses to our post-synaptic neuron, while it's refracted. What will happen to all these impulses? Will they just become "discarded" somehow? Or will they be still somehow accumulated within the post-synaptic neuron and their influence will be considered later, after neuron comes back to the resting state, in order to produce an action potential?

Because, if the incoming signals are discarded, then we are losing the "data" in some sense, which I don't believe is happening in reality. If these signals are accumulated somewhere, what's the maximum capacity of this "somewhere"? What happens in case of overflow? And anyway it would mean that the transfer of the signal within the network gets delayed, and that's quite confusing...

# Answer
**Prelude**

You are thinking far too much about biological neurons as CPUs or some similar electronic equivalent; they are not, they are biological machines and much of the fidelity of biological signal processing comes from massively parallel probabilistic networks with a lot of simultaneous redundancy, rather than serial processing of a stack. Neurons encode information in space (which neurons are firing) and time (when do those neurons fire). There is no biological mechanism for encoding the strength of a signal beyond the maximum firing rate of an individual neuron without considering the ability of a group of neurons to fire together.

If you are interested in biological neurons, I would strongly suggest starting from a basic neuroscience textbook. You will get a lot further learning bottom-up rather than trying to reverse engineer what you know about artificial neural networks and network models in thinking about biology. Two books I typically suggest (any edition of either is probably fine) are **Neuroscience by Dale Purves, and Principles of Neural Science by Eric Kandel**. You can consider either of those books as references for the rest of this answer, which is all very basic in the context of a first-semester neuroscience course.

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**Neurons in space**

Neurons are not single-compartments (whereas most artificial neural network units are); they extend across non-isoelectric space, so events occurring at the soma/axon hillock are filtered before affecting the dendrites (where inputs tend to arrive). Therefore, "what happens during the refractory period" depends very much on *where you are* in the cell. This is addressed a bit in this Q&A: Does an action potential abolish an excitatory postsynaptic potential?

When neurotransmitters bind ligand-gated ion channels, a conductance is opened with some reversal potential. What happens to the membrane next depends on other parameters, in particular the magnitude of other open conductances (or the inverse, the input resistance) and the membrane voltage. Excitatory conductances tend to have reversal potentials near 0 mV, so the closer the cell is to 0 mV the smaller the evoked current will be. During action potentials (at least near the soma, and possibly propagated into the dendrites), the cell is depolarized and has low input resistance due to open voltage-gated channels. Inputs that arrive in that context are indeed going to be blunted if not entirely "wiped out".

**Absolute refractory period**

There are two relevant refractory periods to consider. One called the "absolute" refractory period refers to the period of time during and immediately after an action potential. Action potentials occur due to a positive feedback loop of opening voltage-gated (typically sodium) channels. After opening, these channels *inactivate* and cannot be reopened for some time. This inactivation is necessary for an efficient repolarization of the cell back near rest after an AP is fired. These channels need to recover sufficiently from inactivation in order to fire again.

**Relative refractory period**

After the absolute refractory period, there is an additional interval in which a cell is more hyperpolarized than normal. This state is caused by the voltage-gated potassium channels that are crucial for repolarizing the cell quickly, with the trade-off that the cell is further from threshold for a brief time. The relative refractory period can be overcome with a sufficiently large stimulus, whereas the absolute refractory period cannot.
> 2 votes

# Answer
Here you are confounding the function of a neuron with its implementation (you might want to read about David Marr's 3 levels of analysis). Functionally you can describe neurons and neural networks using information theory, bayesian modelling, causal networks or any other framework makes sense in what you are studying. However keep in mind that a neuron is a biological object.

There are 2 kinds of refractory periods caused by 2 separate mechanisms (see image from physiologyweb.com). Firstly because the potassium channels are slower than the sodium channels, there is a time after the spike where the cell is hyperpolarized. The electrical potential of the neuron is lower than its resting potential. This is the relative refractory period where it is harder to make a neuron spike (because you need a higher depolarization to reach spiking threshold). This is well describe by the Hodgkin-Huxley model. On top of that the sodium channels themselves have a refractory period. After being activated they remain inactive until the cell become hyperpolarized. This is the absolute refractory period.

To go back to this idea of level of analysis, a model is always a simplification of the world. If you wanted to have an exact model of a neuron you would need to model the ions themselves. Instead if you are interested in the flow of ions you can simply model the gates and their dynamics. If you are interested in the electrical potential you can ignore the gates and use the Hodgkin-Huxley model. If you are interested in the spikes you can simplify it even further and use an intergrate-and-fire model. You can even model only the mean firing rate and so on and so forth. From the point of view of the neuron, or the ions being pumped in and out the neuron, there is no "data" to be processed. All you can say is that it functionally behaves as if it was implementing whatever function you are studying. But keep in mind it will always be imperfect as it is a biological object.
> 3 votes

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Tags: neuroscience
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# Question
Title: If babies were isolated, would they develop their own language?
Let’s say that two or more babies/infants from the age of 0 were put in an environment without the affection of adults to teach them how to speak. Would the babies after 13 or so years develop their own language?

Let's assume that someone or something would take care of the babies, giving them food and water and so on, but never speak to them.

# Answer
This question would require an experiment that cannot ethically be conducted, but it is interesting.

Wikipedia has an article on historical attempts at language deprivation experiments:

> An experiment allegedly carried out by Holy Roman Emperor Frederick II in the 13th century saw young infants raised without human interaction in an attempt to determine if there was a natural language ... "foster-mothers and nurses to suckle and bathe and wash the children, but in no ways to prattle or speak with them ... But he laboured in vain, for the children could not live without clappings of the hands, and gestures, and gladness of countenance, and blandishments." ... James IV of Scotland was said to have sent two children to be raised by a mute woman isolated on the island of Inchkeith, to determine if language was learned or innate. The children were reported to have spoken good Hebrew ...

While these experiments had the advantage of a lax ethical environment, they also had a major disadvantage of poor methodology, and the accuracy of their documentation is very questionable.

There are quite a few documented cases of feral children, but none that I'm aware of who were raised together so as to have had an opportunity to develop language.

The most compelling case for the innateness of language development that I'm aware of is the Nicaraguan sign language (ISN):

> ... a sign language that was largely spontaneously developed by deaf children in a number of schools in western Nicaragua in the 1970s and 1980s. It is of particular interest to the linguists who study it, because it offers a unique opportunity to study what they believe to be the birth of a new language.

These children were in fact raised as normal children, but were language isolated, with no contact with other deaf children until school age. Some variables not well controlled for here include that they were exposed to the concept of language, were aware that other people communicated with each other, and already had a proto-language (mimicas). Nonetheless, they appeared to develop a proper structured language fairly quickly upon being introduced to each other, without any apparent support or encouragement from adults, who were entirely unfamiliar with any sign language.

There are similar examples of isolated sign-language development, such as ABSL and MVSL, but the problem with all of them is that the actual level of language isolation is not well controlled for, and hence not clear.
> 58 votes

# Answer
While no cases of complete isolation of a group of children seem to exist, idioglossia (language invented and spoken by only one person or very few people) in twins is well documented and appears to be amplified by social isolation, as the sad cases of June and Jennifer Gibbons aka "Silent Twins" and the "San Diego twins" Poto and Cabengo illustrate. The effect appears to be bidirectional though, i.e. a sort of positive feedback effect is causing a cycle in which more isolation leads to more reliance on idioglossia which in turn fosters more isolation from the rest of society. (For the latter see Hayashi et al. for instance.)

Of course, in the case of twin idioglossia the children do not truly invent the very notion of language. Note however that the same can be said about child-developed sign languages like the Nicaguan Sign Language (NSL): adults still occasionally communicate with such children in a more primitive, ad-hoc sign language, and surely that happens before such children met each other in school etc., so the very idea of a sign language cannot be said to have been invented by these deaf children on their own, but they surely developed a much more sophisticated (and unique) sign language on their own. A qualitative difference between NSL and twin idioglossia is that in the NSL case the adults' (sign) language is more primitive. In this respect however, the parallel is not that different from the distinction between creole and pidgin. The latter is more primitive language of the parents, while the former is a more grammatically sophisticated version usually evolved by their children and later descendants.

In general, languages spoken by few people like twin languages and even those more widely spoken like Pirahã (and this includes sign languages of this kind like NSL) have one sure thing in common: there are bitter disagreements between linguists as to their features. The Wikipedia articles on Pirahã or document NSL those controversies well enough. For twin ideoglossic languages, while some researchers like Bakker have claimed high prevalence and gone to some lengths to describe their features, other researchers like Dodd and McEvoy have argued that such languages basically don't even exist (or if they do are extremely rare), being mostly phonological disorders that make them hard for us to comprehend, but that twins sharing the same genes share the same disorder, so they learn to undestand each other, while we can't do it that easliy.

So (insofar) not much in the way of firm conclusions can be inferred from these with respect to the development of languages that most people speak. And probably not that much can be inferred from them with respect to what would happen in a group of children in total isolation either...
> 8 votes

# Answer
Christine Kenneally asks a number of famous linguists this question and gives all their answers side by side at the end of her book "The first word" (2007). There's not really much consensus! Some say yes, some say no, and there's quite a bit of variety in the justification for each. Plus also some interesting intermediate answers that are something like "yes, but a linguist arriving on the island would immediately notice features of the language suggesting it had a short history".

This question is the last chapter for good reason, the rest of the book gives the context for why the answers are so varied.
> 2 votes

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Tags: learning, developmental-psychology, language, nature-nurture
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# Question
Title: Is Jordan Peterson correct when he states that "as societies become more egalitarian, personality differences across genders maximize"?
There are many videos (for example, here, here, and here) where Jordan Peterson claims that **as societies become more egalitarian, personality differences across genders increase**. He is often stating that these results have been replicated over and over and published in the most leading scientific journals (such as Science) and claiming that this is an established fact.

On a quick search, I was not able to find any Science articles that debate this specific topic (only in other journals whose quality (as an outsider) I cannot judge (e.g. here)). Also, since in my own profession (economics) many famous professors tend to overstate that their view is the established one, how debated are these claims within the academic (not political or media!) landscape today?

# Answer
> 11 votes
Searching the first three pages of "personality gender egalitarianism" on Google Scholar, I found five studies on this topic. All of them support the view finding of increased gender differences in more egalitarian countries, and I didn't find any that were against. \[Edit: added a Falk 2018 as noted in a comment.\]

Most of the studies analyze the Big Five personality traits. Schmitt 2017 also claims increased differences in "Dark Triad traits, self‐esteem, subjective well‐being, depression and values", and Falk 2018 finds increased differences in "willingness to take risks, patience, altruism, positive and negative reciprocity, and trust". One study, Lippa 2010 argues that the differences in the Big Five are quite small, whereas "gender differences on the people–things dimension of interests are ‘very large’". The study authors agree that this shows some inadequacies in social role theory and is more consistent, attributional, and social comparison theories.

Costa Jr., Paul T.,Terracciano, Antonio,McCrae, Robert R. Journal of Personality and Social Psychology, Vol 81(2), Aug 2001, 322-331. link

> Secondary analyses of Revised NEO Personality inventory data from 26 cultures (N =23,031) suggest that gender differences are small relative to individual variation within genders; differences are replicated across cultures for both college-age and adult samples, and differences are broadly consistent with gender stereotypes: Women reported themselves to be higher in Neuroticism, Agreeableness, Warmth, and Openness to Feelings, whereas men were higher in Assertiveness and Openness to Ideas. Contrary to predictions from evolutionary theory, the magnitude of gender differences varied across cultures. Contrary to predictions from the social role model, gender differences were most pronounced in European and American cultures in which traditional sex roles are minimized. Possible explanations for this surprising finding are discussed, including the attribution of masculine and feminine behaviors to roles rather than traits in traditional cultures.

Schmitt, David P.,Realo, Anu,Voracek, Martin,Allik, Jüri Journal of Personality and Social Psychology, Vol 94(1), Jan 2008, 168-182. link:

> Previous research suggested that sex differences in personality traits are larger in prosperous, healthy, and egalitarian cultures in which women have more opportunities equal with those of men. In this article, the authors report cross-cultural findings in which this unintuitive result was replicated across samples from 55 nations (N = 17,637). On responses to the Big Five Inventory, women reported higher levels of neuroticism, extraversion, agreeableness, and conscientiousness than did men across most nations. These findings converge with previous studies in which different Big Five measures and more limited samples of nations were used. Overall, higher levels of human development--including long and healthy life, equal access to knowledge and education, and economic wealth--were the main nation-level predictors of larger sex differences in personality. Changes in men's personality traits appeared to be the primary cause of sex difference variation across cultures. …

Lippa, R. A. (2010), Gender Differences in Personality and Interests: When, Where, and Why?. Social and Personality Psychology Compass, 4: 1098-1110. doi:10.1111/j.1751-9004.2010.00320.x. link

> How big are gender differences in personality and interests, and how stable are these differences across cultures and over time? To answer these questions, I summarize data from two meta‐analyses and three cross‐cultural studies on gender differences in personality and interests. Results show that gender differences in Big Five personality traits are ‘small’ to ‘moderate,’ with the largest differences occurring for agreeableness and neuroticism (respective ds = 0.40 and 0.34; women higher than men). In contrast, gender differences on the people–things dimension of interests are ‘very large’ (d = 1.18), with women more people‐oriented and less thing‐oriented than men. Gender differences in personality tend to be larger in gender‐egalitarian societies than in gender‐inegalitarian societies, a finding that contradicts social role theory but is consistent with evolutionary, attributional, and social comparison theories. In contrast, gender differences in interests appear to be consistent across cultures and over time, a finding that suggests possible biologic influences.

Schmitt, D. P., Long, A. E., McPhearson, A. , O'Brien, K. , Remmert, B. and Shah, S. H. (2017), Personality and gender differences in global perspective. Int J Psychol, 52: 45-56. doi:10.1002/ijop.12265. link

> … Several large cross‐cultural studies have generated sufficient data for evaluating these global personality predictions. Empirically, evidence suggests gender differences in most aspects of personality—Big Five traits, Dark Triad traits, self‐esteem, subjective well‐being, depression and values—are conspicuously larger in cultures with more egalitarian gender roles, gender socialization and sociopolitical gender equity. Similar patterns are evident when examining objectively measured attributes such as tested cognitive abilities and physical traits such as height and blood pressure. Social role theory appears inadequate for explaining some of the observed cultural variations in men's and women's personalities. Evolutionary theories regarding ecologically‐evoked gender differences are described that may prove more useful in explaining global variation in human personality.

Falk, Armin and Hermle, Johannes (2018), Relationship of gender differences in preferences to economic development and gender equality. *Science*. doi:10.1126/science.aas9899. link

> \[According to the resource hypothesis,\] greater availability of material and social resources removes the gender-neutral goal of subsistence, which creates the scope for gender-specific ambitions and desires. In addition, more gender-equal access to those resources may allow women and men to express preferences independently from each other. As a consequence, one would expect gender differences in preferences to be positively associated with higher levels of economic development and gender equality.
>
> We tested these competing predictions using data on experimentally validated measures of willingness to take risks, patience, altruism, positive and negative reciprocity, and trust for 80,000 individuals in 76 representative country samples. So that the data would be geographically representative, the dataset was chosen so as to include all continents and a broad range of cultures and economic development levels. In total, the data represent about 90% of both the world population and global income.
>
> The data revealed substantial cross-country variation in gender differences in preferences. Gender differences were found to be strongly positively associated with economic development as well as gender equality. These relationships held for each preference separately as well as for a summary index of differences in all preferences jointly. Quantitatively, this summary index exhibited correlations of 0.67 (P \< 0.0001) with log GDP per capita and 0.56 (P \< 0.0001) with a Gender Equality Index (a joint measure of four indices of gender equality), respectively. To isolate the separate impacts of economic development and gender equality, we conducted a conditional analysis, finding a quantitatively large and statistically significant association between gender differences and log GDP per capita conditional on the Gender Equality Index, and vice versa. These findings remained robust in several validation tests, such as accounting for potential culture-specific survey response behavior, aggregation bias, and nonlinear relationships.

Mac Giolla, E. and Kajonius, P. J. (2019), Sex differences in personality are larger in gender equal countries: Replicating and extending a surprising finding. Int J Psychol. doi:10.1002/ijop.12529. link

> Sex differences in personality have been shown to be larger in more gender equal countries. We advance this research by using an extensive personality measure, the IPIP‐NEO‐120, with large country samples (N \> 1000), from 22 countries. Furthermore, to capture the multidimensionality of personality we measure sex differences with a multivariate effect size (Mahalanobis distance D). Results indicate that past research, using univariate measures of effect size, have underestimated the size of between‐country sex differences in personality. Confirming past research, there was a strong correlation (r = .69) between a country's sex differences in personality and their Gender Equality Index. Additional analyses showed that women typically score higher than men on all five trait factors (Neuroticism, Extraversion, Openness, Agreeableness and Conscientiousness), and that these relative differences are larger in more gender equal countries.

# Answer
> 0 votes
This phenomenon was at least alluded to by William Strauss and Neil Howe in their book, "Generations".

America had a relatively egalitarian society in the late 1940s, 1950s, and early 1960s, during the rise of the World War II generation, a so-called "civic" type of generation. That was when politics was played "between the 40 yard lines," that is, around the center, ice cream came in three flavors, there was no political "gender gap" (women were not notably more liberal (or conservative) than men), and houses like those in "Leavittown" were of roughly uniform size and shape "little boxes" made of ticky tacky." It was in such a "uniform" society that gender differences were most pronounced, perhaps as a "counteraction" against the general uniformity.

The "Boom" society that followed was the opposite, with "31 flavors" of ice cream, greater racial and social diversity, rising income inequality, a certain amount of social fragmentation. But the one thing that distinguished the Boomers was the narrowing of gender roles, perhaps as a reaction against the rising differentiation.

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Tags: social-psychology, reference-request, gender, sex-differences
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# Question
Title: What is the motivation model behind StackExchange?
I noticed that I didn't sleep yesterday for no reason and spent the whole night to answer questions in one of the communities in here. Why did I do this? I still come here every hour and check if someone chooses my answer or asks me something. There is a vague feeling. I'm like people who are on Instagram or Snapchat all day. I'm trying to understand what the reasons are behind this.

As far as I know, there are two general types of user here. People who seek help and people who want to help others. The motivation for the first group is obviously urgency of finding an answer for their question. However, the second group doesn't need to bother. They got no problems. What are the psychological factors that make those people help others and contribute to the community?

I know the reputation system has a big impact, but I think giving points and badges are not enough. I believe there are some powerful gamification elements such as unlocking privileges. What actually keeps people here? Is the model of StackExchange, which is depended on reputation points, sustainable? If all reputations were reset today, would people still come here to answer questions? Or there is something more, I don't see?

# Answer
> 8 votes
The short answer is that anyone who gives you a short answer should be treated with suspicion. ;-p

The StackExchange was founded in 2008, and has seen a lot of changes since that time. That has provided the science community with little time to study the phenomenon in much detail. As such, there are many *many* theories, but little consensus, and no comprehensive model in place.

There are several related articles on Wikipedia - one thing I can recommend for now, is to keep an eye on them. Wikipedia tends to be updated with new evidence-based findings over time, so as knowledge progresses, it will likely be featured there:

Speaking of Wikipedia, it is clear that points and badges are not necessary to motivate contributions, as many crowdsourcing systems succeed without them. Presumably, social psychology (eg, recognition, identity) plays a big role, as does intrinsic motivation (eg, ideology, curiosity).

However, what would happen if such extrinsic rewards were removed is a question about a controversial phenomenon called the overjustification effect:

> ... gamification refers to the application of game design elements to non-game contexts ... by providing symbolic rewards such as points, badges, or virtual currency. However, a number of academics and other critics have expressed concern that these rewards may backfire via the overjustification effect. ... these critics of gamification express concerns that gamified contexts ... might provide expected rewards for activities ... and therefore reduce intrinsic interest in those activities.

That is, if this effect is real and applicable to the StackExchange, then there is a danger that initially intrinsically motivated contributors might become dependent on the extrinsic rewards over time. Complicated.

In reality, like any product or service on the market, StackExchange is subject to market forces, corporate decisions may be influenced by motivational models as well as user feedback, but are often made for other reasons, and therefore its sustainability is not easy to predict. It is likely the case that the underlying motivational model is multi-faceted, with each aspect of the system contributing to (or detracting from) its success, interacting in a multitude of different ways with individual user attributes, and changing over time.

# Answer
> 5 votes
**Short answer**
The Stack Exchange model is based on gamification. Gamified environments typically deploy incremental rewards that tap into the brain's reward system, making these applications addictive, in a quite literal sense. In addition, reputation increases come with incremental gain of moderator abilities, which give a sense of power.

**Background**
The Stack Exchange environment is definitely a matter of gamification. But as you already indicate yourself, there's more to it than just reputation increase. It's the privileges and moderation tools that become incrementally available when you are climbing the ladder. These tools give users the ability to exert influence, and eventually they even allow changing the content of the site, without much restrictions.

Gamification is used in a lot of applications. Basically it taps into the **reward system**. The reward of providing a good answer is the incremental increase in reputation and badges. What's even better, more rep comes with step-wise increases in moderator tools on the SE network, which basically corresponds to empowerment on the site. Now all these things are powerful motivators. Neyman (2017) gives a catching account of this phenomenon:

> Closely tied to variable rewards, "gamification" is defined in the tech industry as the process of using game mechanics to reward the completion of tasks. Academically, "gamification" has been defined as "a process of enhancing services with (motivational) affordances in order to invoke gameful experiences and further behavioral outcomes." Experts recommend implementing rewards in small, frequent bits so that the user of an app feels a sense of achievement. They also recommend "sharing loops" that integrate rewards with the users social network by allowing the user to share their accomplishments

Sounds eerily familiar, doesn't it?

The Stack exchange gamified environment does exactly this: the reputation increase is highly incremental. Reputation increase will give you a sense of accomplishment. With that, the reward centers will release dopamine system, as has been associated with gamified paradigms (Janssen *et al*., 2017). Dopamine makes you feel good (see for a review Arias-Carrión *et al*., (2010)). Eventually you want more and more and you might even be craving it (the constant checking out whether you have gained some reputation), akin to addiction. It's know that social media in general, such as the likes on FB comes with shots of dopamine in the reward system. Exactly this mechanism is the reason people becom eaddicted to drugs like cocaine, heroin, meth, which are all powerful dopamine releasing agents (Diana, 2011). But also alcohol, tobacco, gambling and sex release dopamine in the reward center and are therefore potentially addictive. I think that gamified activities fall into the same class of dopamine-releasing activities.

Why am I answering your question right now? Why not another one? Because I want that bounty, and the associated dopamine rush. Why did I just stop revising my paper to answer this question? Procrastination, yes, but even more importantly, it will yield a reward on the *short term*. The reward system is a highly ancient structure, part of our 'lizard brain'. It is highly sensitive to rewards on the short term, bypassing, even short-circuiting our cortical inhibitions that strive to achieve bigger goals that will sustain rewards and happiness on the long run.

Lastly, and already shortly hinted at, also in your post, is that reputation increases come with incremental gain of moderation tools. The ability to downvote and close questions give a sense of power, a sense of you controlling this site. An infamous study showing people's lust for power comes from the **Stanford Experiment**.

In this experiment, an experimental “jail” was set up in the basement of at Stanford University. The prisoners were a group of study subjects, the other half were assigned the role of guards. All subjects were males. The guards tuned from good to evil when the experiment evolved. In the end, they started punishing the prisoners, by denying them food among other quite distressing acts of bruatlity. The prisoners were even (sexually) humiliated and victimized. A lively account is given in the New Scientist (Perry, 2018). What it shows is that people love to be able to exert power over their peers. This in turn, no doubt, will also be fed by the reward system.

**References**
**-** Arias-Carrión *et al*., *Int Arch Med* (2010); **3**: 24
**-** Diana, *Front Psychiatry*, (2011)
**-** Janssen *et al*., *Pediatric Physical Therapy* (2017); **29**(1): 95-99
**-** Neyman, A Survey of Addictive Software Design (2017)

# Answer
> 2 votes
This should be a comment, not an answer. But because of the formatting I put it here.

My speculation: gamification/social acceptance \+ altruism \+ curiosity \+ flow.

* Gamification/social acceptance: you need to prove to folks in this site that you do know stuffs
* Altruism: you once had this question before, so you can related this to yourself. Or you know you have some keywords that help, and you feel that it doesn't take much time to say
* Curiosity: the question is interesting, and you want to see it unfold
* Flow: once you are in a flow, it's hard to break it. Once an idea pops in your mind, you need to finish it.

Except the first one, all the last ones are intrinsic motivations.

Take this very answer as an example. At first it was just a small comment to the question:

> My speculation: gamification + altruism + exploration

Then I felt like "exploration" was not a good word, so I replaced it with "curiosity". Then I added another sentence.

> My speculation: gamification + altruism + curiosity. Except the first one, the last two ones are intrinsic motivations.

But I still felt my answer was incomplete, so I had to elaborate more. So we are here.

# Answer
> 0 votes
I'll try to answer from the second side, wanting to help others. This, as it were, involves a certain amount of "helping oneself."

1) There is a desire to teach, or help others understand what you know. At some level, many people feel the world would be better off, if there were less "ignorance." SE provides a chance for you to educate one, or "many" other people on a topic of your choice.

2) In seeking to help others, I clarify issues/problems for myself. I (hopefully) come away with a better understanding of the question and answer for myself.

3) I get to test my knowledge against that of others with similar interests. Other people will point out things that my answers have overlooked. Queries about my answers from others may force me to "dig deeper" and come to a new level of understanding. And the "reputation" system is a rough measure of how much you have achieved, both in absolute terms, and relative to others.

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Tags: social-psychology, motivation, gamification, prosocial-behavior
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# Question
Title: How can we eliminate the effect of psychiatric medication on neuropsychological research with schizophrenic patients?
It is delicate to conduct studies with **schizophrenic patients**, considering that the results may be altered by the medication factor. What strategies should be used to counteract this effect?

# Answer
As far as I know, this effect cannot be eliminated by any practical means, other than stratifying the subjects into groups according to type of drug, dosage, duration of use *etc*. and use statistical testing to look for any differences between the groups with, *e.g.*, linear mixed modeling.

However, a cursory search on Google Scholar yields multiple studies where unmedicated folks were successfully recruited into the study, *e.g.* Kraguljac *et al.* (2016).

<sub>**Reference**
**-** Kraguljac *et al*., *Schizophrenia Bull* (2016); **42**(4): 1046–55</sub>
> 3 votes

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Tags: methodology, psychopharmacology, schizophrenia, reproducible-research, neuropsychology
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# Question
Title: Why does suicide risk increase just after starting an antidepressant?
There are many ways of treating depression, one of which is administering **antidepressants**. From this site, and several others, I read that **risk of suicide increases** after starting an antidepressant.

> A few people do become more agitated, depressed, and anxious shortly after an antidepressant is started or after the dose is increased. Some people, especially younger children and adolescents, become increasingly suicidal if these symptoms are not detected and rapidly treated. This finding was first reported with SSRIs, but the risk probably does not differ among classes of antidepressants.

My question is, simply, *why* is that? These antidepressants work *long-term*, but cause strong suicidal thoughts when taken *initially*. Does it have something to do with hormones?

# Answer
This comes from talking to a psychiatrist about the issue:

One of the effects of depression is a loss of motivation. In some suicidal individuals, this has the result that they want to die, but can't work up the motivation to do anything about it. Once they start taking antidepressants, however, the lack of motivation goes away before the depression does, creating a short period of increased suicide risk.
> 2 votes

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Tags: depression
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# Question
Title: How are neurotransmitter receptors discovered?
Many neurotransmitter receptors are known, for example 5-HT2a, Mu, NMDA, and so on. How have these receptors been discovered?

# Answer
Each receptor has its own story of discovery. I'll share here the methods used by Lefkowitz that led to the discovery of one of the first neurotransmitter receptors, namely the β2 adrenergic receptor (β2AR) from frog erythrocytes in 1981. With this I mean β2AR was among the first receptors that was identified, purified, and characterized both at the protein and DNA level.

Lefkowitz's team was the first to uncover the charactistics of a neurotransmitter at the protein and DNA level. βARs are involved in regulating cardiovascular function. Lefkowitz was awarded the Noble prize for his early pioneering work on the discovery of these receptors.

His method was based on several steps, namely:

* The development of a novel and specific radioligand binding assay to enable the measurement βAR-binding sites;
* The identification of detergents to successfully solubilize a functional βAR from membrane preparations;
* The synthesis of an affinity resin and photoaffinity ligands to facilitate receptor purification;
* Reconstitution of the purified β2AR into phospholipid vesicles;
* The demonstration that β2AR couples to, and activates the heterotrimeric G protein Gs and subsequent activation of adenylyl cyclase to produce cAMP;
* Purified hamster β2AR was used for peptide sequencing that were subsequently used to synthesize oligonucleotides for cloning studies to isolate β2AR cDNA;

After β1AR, Lefkowitz's lab soon purified β1AR, α1AR, and α2AR.

**References**
**-** Benovic, *Cell* (2012); **151**(6): 1148-50
**-** Lopez-Munoz & Alamo, *Neural Transm* (2009) **116**: 515–33
> 2 votes

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Tags: neuroscience
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# Question
Title: Equalize/balance brightness and saturation of different colors using RGB (across various monitors)
We want to present different colors to participants in an online experiment (in an HTML/CSS-based application, hence we'll use `RGB` values). More in specific, we want to show red and green colors on grey background.

Crucially, we want to do our best to balance all possible factors apart from hue, especially those that might influence emotional (positive/negative) evaluation, so in particular brightness and saturation.

However, different models give different results, and the resulting colors can seem (to us subjectively) very unnatural, i.e. not what we would call a typical green or typical red. For example, selecting a red and green similar in lightness and saturation (`hsl(h*, 100%, 25.1%)`) would mean red `RGB(128,0,0)`(`#800000`) and green `RGB(0,128,0)`(`#008000`), but these seem (on grey background, e.g., `#909090`) neither naturally red and green, nor equal in visibility, see e.g. red here and green here.

Another option is following the CIELCh model, where saturation is calculated as `C*/L*` (Wilms & Oberfeld, 2018), a balanced pair could be: **red** CIE-LCh°(ab) (D65/2°) = 34, 100, 57, `rgb(164, 14, 0)` (`#A40E00`, `hsl(5.1, 100%, 32.2%)`) and **green** CIE-LCh°(ab) (D65/2°) = 34, 100, 150, `rgb(0, 103, 0)` (`#006700`, `hsl(120, 100%, 20.2%)`). But then the lightness from the HSL model is not equal.

Of course there is also the problem that we cannot know the participants' monitor properties (let alone lighting conditions, etc.), which definitely rules out great precision in this matter, but still that seems the lesser problem: in general the same RGB color setting looks fairly similar on all monitors (again, in our subjective experience).

I realize that this can never be perfect, but I'm looking for suggestions for a least problematic solution, something that ensures the least possible influence on emotional impact of the color.

**A definitive answer would include the possibly most optimal *"red"* and *"green"* colors with *RGB* values, along with a clear and convincing explanation (and references) about how it was derived (including software or formula if needed).** An additional *blue* value could also be helpful to generalize the concept (and to further test the necessary color code transformations, if any).

# Answer
> 3 votes
First I should tell you that controlling for color in an online experiment is hopeless. Monitors display quite different colors, people run experiments in environments that have very different illuminations etc. There is no chance you could display equiluminant colors, which is already hard to do in the best of conditions, in an online experiment. However you can still try to minimize as much as possible variations in luminance.

You seem to assume that the RGB value of a pixel is equivalent to luminance. It is not, it is the 8-bits encoding relative to the maximum physical capabilities of the display. The RGB color channels do not have the same luminance. The ratio is roughly respectively 0.3, 0.6 and 0.1. In other words a green value that roughly matches the most luminant red a monitor can display is only half of that value (\[255,0,0\] has roughly the same luminance as \[0,128,0\]). As I said without carefully calibrating your monitor with a photometer there is no way you can display perfectly equiluminant colors online. What you can do is take a RGB space, like the sRGB space, pick 2 colors that have equiluminance in that space, and assume that it is not too far off on people displays. https://en.wikipedia.org/wiki/SRGB

Saturation is even trickier because it is not a physical quantity you can measure (technically luminance is also based on a standard observer but at least you can relate it to radiant energy). Saturation will depend on which color space you pick. CIELuv, or its polar equivalent CIELch is indeed a reasonable choice. Note that CIELuv requires defining a "white point" (in the values you give it seems to be D65), yet another reason why online color experiments are hopeless. Here I think you are making the opposite mistake as for RGB colorspaces, the L coordinate of the Luv/Lch colorspaces is luminance. So 2 colors that have the same L value do have the same luminance (and the uv/ch coordinates indicate chrominance on an equiliminant plane). However you cannot easily transform CIELuv coordinates to RGB values. You'll need to transform colors back to the CIEXYZ colorspace first, and then to RGB.

Finally as the specific hue does not seem to be an issue for you, you can always measure equiluminance experimentally. For example using a alternating red and green drifting bars. Pick a red value, start with a very dark or bright green and increase/decrease that value. When colors are equiluminant you should perceive a clear drop in the speed of the drifting bars (the motion pathway is luminance-based).

All that to say, it is good to try to control for possible confounds, but be aware that you will never be able to perfectly control for it. I would personally not worry about it too much. If it is a critical aspect of your experiment try designing a good control condition instead (switch colors for half the observers, or run a subset of observers with colors that are clearly not equiluminant or something like that).

A very good reference on the topic: http://www.visionlab.harvard.edu/Members/Patrick/PDF.files/2002%20pdfs/equi.pdf

I used this website to convert CIELuv to RGB values. Results are in the figure below. To get equiluminant colors the L value should remain constant (here I used 34 as the paper you cited). To have equisaturation (assuming the colorspace is correct), the uv coordinate should have the same euclidian distance (sqrt(u^2+v^2)=Cst, here I used 100). I absolutely do not guarantee this is correct. I just googled "CIE-Luv converter" and found this website. Checking if it is correct would be quite time consuming.

http://colormine.org/convert/rgb-to-luv

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Tags: perception, measurement, vision, color, emotion-perception
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# Question
Title: Is the Wonderlic invalid if you have previously done other intelligence tests?
Years ago I did a fake wonderlic test on a website getting a bad score mainly because the test server delayed time in between questions but also the questions were harderd and not correctly ordered by difficulty. I did another 2 or 3 tests after then a couple of years later did a real wonderlic test (with different questions) and scored 95th%, im wondering is this score invalid because I did a few practice tests some years before.

Also the real test included instructions not to spend too much time on one question which made a difference i think.

# Answer
> 3 votes
It is assumed that most people taking intelligence tests have been exposed to a wide range of assessments in the past. It is a standard feature of education systems that students will do a wide range of assessments, and some of these are more or less like intelligence tests.

Many tests even have practice questions for the purpose of increasing validity. The rationale is that some people may perform unnecessarily poorly because they're not familiar with the interface or the general test taking strategy.

So, no, doing another intelligence test doesn't invalidate your current intelligence test score.

That said, there is an active literature on practice effects. For example, see this question about practice effects on Raven's.

As a general principle practice effects are generally considered to be small on intelligence tests. The theory of skill transfer says that they will vary on a continuum based on the similarity between what has been practiced and what you are doing now. There also needs to be some capacity for domain-specific learning.

In your case, most free online tests that claim to be modelled on the Wonderlic or another commercial test are likely to be a very rough proxy. More generally, the Wonderlic has a wide range of question types. Thus, I doubt that even taking an alternate form of the Wonderlic would make much difference to subsequent test taking efforts. Also, when you do a test, you typically don't receive feedback on what is the correct answer. So, the capacity for incidental learning is limited.

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Tags: intelligence, cognitive
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# Question
Title: Does the Dunning-Kruger effect still work the same if the incompetent person is aware of this effect?
Is it possible for an incompetent person to reevaluate his abilities (to become more realistic about his abilities) when finding about the Dunning-Kruger effect?

# Answer
One critique of the Dunning-Kruger effect is that it is just regression to the mean. I.e., there is an imperfect correlation between perceived an actual ability. A consequence of this is that people low in ability will overestimate and people high in ability will underestimate. Of course, in some domains, we also see a leniency bias whereby people in general have an inflated sense of their ability. For a discussion of these interpretations see this post by Tal Yarkoni.

But in general, there are ways of increasing the correlation between perceived an actual ability. The basic principle is to provide people with feedback on their performance that is accurate. And presumably, it would help to persuade people that it is trustworthy.
> 3 votes

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Tags: social-psychology
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# Question
Title: Is it possible to convince a group of people that they master something, when they in fact don't?
Is it possible to prove that a bunch of individuals were (or could be) convinced to be good at something (even really difficult), but it was in fact their illusion of knowledge?

Here's a bit more detail: let's take an average class at school. Let's give them a math teacher, whose way of teaching math is extremely mnemonic, still facing hard subjects. They'll be asked exactly what they were told at lesson, without any reworking demanded. The teacher will assign the highest marks to those students who are able to repeat the better. Will some of them eventually get to believe they are good at math, when in fact they can scarcely ever apply what they're studying or explain the ideas behind?

I did not find what I was looking for in the Wikipedia persuasion though.

# Answer
Your question relates a bit to the self-efficacy literature.

Underlying ability is one cause of self-efficacy. And presumably, there are many mechanisms by which people can form an accurate opinion of their ability.

That said, there are various known ways of increasing or decreasing self-efficacy without changing actual efficacy.

For example, there is the big-fish-little-pond effect. Basically, you can increase self-efficacy by putting people in an environment with others who are less capable.

Similarly, giving people feedback that they are good or giving people tasks suited to their ability will increase a sense of self-efficacy. Some of these strategies are considered effective teaching especially if it helps overcome obstacles related to students even trying. But it can also be problematic if people allocate resources based on an inaccurate belief about their strengths and weaknesses.
> 1 votes

# Answer
I would say this is a matter of authority:

> We have the tendency to believe that if an expert says something, then it must be true. People like to listen to those who are knowledgeable and trustworthy, so if you can be those two things, then you are already on your way to getting people to believe and listen to you.
> 0 votes

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Tags: learning, persuasion
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