text:
What sources of randomness does the brain use for sampling?
As an applied mathematician, I have a growing interest in the mechanisms for uncertainty representation and computation in the human brain. In fact, I recently compiled a list of papers on this subject. But, so far I haven't found many papers which answer a fundamental sub-question:

What sources of randomness does the brain use for sampling?

Dan Goodman, a neuroscientist, suggested that I have a look into neuronal noise. The neuronal variability perspective is quite popular among computational neuroscientists and 'Bayesian inference with probabilistic population codes'(2006) is an example of a publication which demonstrates its use:

At first sight, it would seem that the high variability in the
  responses of cortical neurons would make it difficult to implement
  such optimal statistical inference in cortical circuits. We argue
  that, in fact, this variability implies that populations of neurons
  automatically represent probability distributions over the stimulus, a
  type of code we call probabilistic population codes. Moreover, we
  demonstrate that the Poissonlike variability observed in cortex
  reduces a broad class of Bayesian inference to simple linear
  combinations of populations of neural activity. These results hold for
  arbitrary probability distributions over the stimulus, for tuning
  curves of arbitrary shape and for realistic neuronal variability.

However, a recent paper published in 2018 [3] presents compelling counter-arguments against the utility of neuronal noise for sampling in the brain.
In particular, the authors make the following case in their abstract:

Since the precise statistical properties of neural activity are
  important in this context, many models assume an ad-hoc source of
  well-behaved, explicit noise, either on the input or on the output
  side of single neuron dynamics, most often assuming an independent
  Poisson process in either case. However, these assumptions are
  somewhat problematic: neighboring neurons tend to share receptive
  fields, rendering both their input and their output correlated; at the
  same time, neurons are known to behave largely deterministically, as a
  function of their membrane potential and conductance.

While I find the arguments in [3] compelling due to their fundamental nature, this makes me wonder whether there are other fundamental contributions to this problem that I ignore.
Note: Cian O'Donnell recently shared his PhD thesis with me on Twitter [4]. The neural noise vs. no neural noise variant of this question is still very much an open problem.
References:

Wei Ji Ma, J. Beck, P. Latham & A. Pouget. Bayesian inference with probabilistic population codes. Nature Neuroscience. 2006.
Andre Longtin. Neuronal noise. Scholarpedia. 2013.
D. Dold et al. Stochasticity from function - why the Bayesian brain may need no noise. Arxiv. 2018.
R. Cannon , C. O'Donnell , M. Nolan . Stochastic Ion Channel Gating in Dendritic Neurons: Morphology Dependence and Probabilistic Synaptic Activation of Dendritic Spikes. PLOS. 2010.

I kind of think the noise vs no noise people are talking past each other sometimes, though that's more of an opinion than something I can cite. Basically there is enough "other stuff" going on in the brain at any one time, we aren't input output machines the way experiments presume us to be (nor are mice or flies for that matter), so everything else going on at any point in time is "noise."

Not sure if I am getting your question right. You are asking for noise that has an inherently information processing function? I would add an other aspect of noises
Noise as an emerging property

On a large scale, when massive amounts of neurons are
synchronising, then you can detect Noise with Electrodes, like in
the case of EEG. EEG follows an 1/f² or 1/f³ law (brownian
noise, red noise, pink noise, depending on the literature). This
principle can be found anywhere in the world. It states that higher
frequencies / faster oscillating signals have increasingly smaller
amplitudes, similar to smaller and larger waves on the sea and so
on.
In this case is noise a byproduct of other (stochastic) processes.
On a small scale, which would probably be something you would
    measure by using 'clamping'-technique on single neurons.  The
    firing rate of a neuron (a neuron chemically charging, until it
    reaches a threshold, which turns into a all-or-nothing case) also
    follows some 'systematic randomness' on which probabilistic,
    stochastic and noisy properties might be useful to describe these
    processes.
    In this case is noise a property that emerges from natural stochastic single-neuron firing processes.

Noise emerging from signals related to certain anatomic sources

In how far I remember (I do not have a good resource on that) the
    hippocampus, which is highly relevant for memories, has a strong randomization aspect inherently in its functioning.
    This might be my closest guess to your question?!
Another very distinct 'stochastic' process created by the
Thalamus, a largely dominant, pace-giving rhythm within the brain.

Ressource: Buszaki Rhythms of the Brain is a nice read on various of these topics
On noise as an error process
Maybe I got your question a little wrong, but thinking of the brain that in the run of evolution turned out to be highly efficient and energy saving, does not want to have any noise that does not fulfill any purpose. (But as I understand, your question was related to the functional aspect of noise.)


text:
Will acquiring a second language improves the person's general intelligence and reading?
According to this information will acquiring a second language improves the person's general intelligence and reading, even if the individual started learning and have learned it after the age of 18?
How scienctifically and/or empirically accurate is the studies and information?
https://www.bbc.com/news/health-27634990
https://youtu.be/RXeDNkVauh4

source: Stack Exchange

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/

sort: votes


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Do humans really feel that a \$99 price tag is significantly lower than a \$100 one?
Do humans really feel that a \$99 price tag is significantly lower than a \$100 one?
Is there a name for this phenomenon and research supporting it?

This was termed the Left-Digit effect by Thomas & Morwitz (2005).

The Wikipedia page of Psychological Pricing giving this chart:

Why?

Kaushik Basu used game theory in 1997 to argue that rational consumers value their own time and effort at calculation. Such consumers process the price from left to right and tend to mentally replace the last two digits of the price with an estimate of the mean "cent component" of all goods in the marketplace.

Also related on UX Stack Exchange: Is there any advantage in marketing my product for £99.99 instead of £100?

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


text:
Could a failure of condensed inner speech be linked to slowed cognition?
Could a failure of "condensed inner speech" be linked to slowed cognition? It is a type of inner voice, and as conceptualized by Fernyhough it

involves the capacity to think in terms of pure meaning without the
  need to put thoughts into words in order to grasp the meaning of the
  thought.

I'm just wondering whether, either in healthy or psychopathological cognition, condensed inner speech has been shown to be more difficult when thinking is slowed for some reason, such as psychotropic medication. I have read that people tend to use expanded (as opposed to condensed) inner speech when under stress.

I did not find a study trying to test your idea. I suppose your hypothesis could be tested by comparing the results Varieties of Inner Speech Questionnaire (VISQ) on the expanded/condensed dimension of participants with induced slower condition to a control group.
McCarthy-Jones & Fernyhough (2011) studied the correlations between the dimensions and psycho-pathological variables. They found the expanded/condensed dimension was not predictive of psychopathology.
References
McCarthy-Jones, S., & Fernyhough, C. (2011). The varieties of inner speech: Links between quality of inner speech and psychopathological variables in a sample of young adults. Consciousness and Cognition, 20(4), 1586–1593. https://doi.org/10.1016/j.concog.2011.08.005


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How common is it to include unmedicated patients in first episode psychosis (or any type of psychosis) studies?
Is anyone familiar with this open access study?

Radua, J., Borgwardt, S., Crescini, A., Mataix-Cols, D., Meyer-Lindenberg, A., McGuire, P. K., & Fusar-Poli, P. (2012). Multimodal meta-analysis of structural and functional brain changes in first episode psychosis and the effects of antipsychotic medication. Neuroscience & Biobehavioral Reviews, 36(10), 2325-2333. doi: 10.1016/j.neubiorev.2012.07.012

I'm surprised by the included studies. 76% of FEP patients in the structural group (965 patients) received antipsychotics, and only 53% of FEP patients in the functional group (362 patients) received medication. I always assumed studies on FEP using medication-naive patients were almost unheard for ethical concerns. Unless I'm mistaken, that's not the case.
"Forty-three studies met inclusion criteria (Fig. 1). Specifically, in the structural meta-analysis, we included 965 FEP subjects (mean age 24, range 15–35 years; 34% females; 76% receiving antipsychotic treatment), matched with 1040 controls (mean age 26, range 15–35 years; 34% females). The cognitive tasks functional imaging cohort included 362 FEP subjects (mean age 26, range 19–36 years; 31% females; 53% receiving antipsychotic treatment)."


text:
How to recruit participants for fMRI study who do not fall asleep during experiment?
I'm in a psychology lab and we're having trouble getting participants for an fMRI study. We pay $150 per subject and we need to have several hundred healthy controls for one study. For the 20-minute study, the participant has to look at certain words and think about them, like imagining a scenario where "family" or "pride" was important.
We keep finding participants from recruiting around campus who will seem enthusiastic, then fall asleep immediately in the scanner. Our IRB states that we have to let them sleep for the full scan and pay them the full amount. I don't know how to prevent this. We've wasted thousands of dollars and weeks to months of time running studies with garbage data. Has anyone figured out how to recruit better participants?

Change the contract based on paid for viable results. One pays for "work" completed... Otherwise I am worth a fortune....

@SolarMike, for that you need to go back to the IRB, I think.

@Buffy probably, but it was badly written to leave a loophole like that... To make it the equivalent of "sleep in our MRI scanner for an hour and get $150 for the privilege" and that does not even take into account the hourly cost of the scanner...

You could keep your study the same but instead frame it as a study of boredom-induced somnolence. It would be in keeping with a time-honored scientific tradition of trying to make the most of uncooperative subjects, errr, participants :)

I think you need to redesign your task rather than your subject recruitment. It sounds really boring to me. People learning meditation fall asleep all the time, for example. Blaming the participants is probably not the right approach.

I agree with the above comments. Can you include two breaks where they must stand up and do jumping jacks or something?

Do a test first. Unpaid. To weed out the non performers. Do some study with follow on testing. And tell them that falling asleep means losing out in the second gig.

@SolarMike our IRB specifically forbids results-based compensation of any kind.

@Buffy any reasonable solution is going to require an amended ethics approval.

Is it possible that word has gotten around campus that people can take a nap in the scanner and still get the $150?

Tell your participants to think about and memorize the words. Quiz them on the words after they come out of the scanner.

Based on my own experience as a student, the problem is probably not that your participants are lazy... the problem is that, like many university students, they're severely sleep-deprived.
While a student, I once agreed to participate in a friend's (non-MRI) study, which involved listening to sounds and clicking buttons in response. To my embarrassment, despite being enthusiastic about participating, I kept drifting off briefly during the study. I managed to complete it, but I'm sure my results were affected. I'm pretty sure that if I had ever tried to participate in an MRI study, I would have fallen completely asleep.
I don't have experience running MRI studies so I'm not really sure what to suggest to solve this problem, other than to try recruiting from less sleep-deprived populations, or redesigning the study tasks to be more engaging.

Or redesigning the study to account for the phenomenon.

Oh, it also occurs to me that time of day is important -- my guess is that participants are much more likely to fall asleep during an early morning session than a midmorning/afternoon one.

We've analyzed time-of-day results and found no correlation between morning and evening, though subjectively it "feels" like morning subjects have done much better.

Maybe, but my naps come just after lunch. But then, I'm older than the rivers and mountains.

I should also add that we're allowed to offer the subjects coffee, and even pause the study,let them drink coffee, and restart, but no subject has accepted coffee yet in either case. I'm not sure why.

We also can speak over a microphone into the scanner room, and we say "Please keep your eyes open" when we see them start to drift off, but this also hasn't worked.

@rooty play random audio, assuming audio is not part of the results required...

Does your IRB approval allow you to require your subjects to drink coffee? Only half joking.

The notion that students are so sleep-deprived that they couldn't stay awake laying down during a 20 minute study seems insane to me. Even more so if it's true...

The problem is not your participants.  It is your stimuli.  They are too boring.  Change them, or add a task participants must perform.  It could be as simple as "Press a button to continue."
You will need to go through the ethics board again.

I think the lack of any action the participant has to take other than thinking might be part of the problem. Could you add an action at the end of each word display, such as pick the picture that most closely relates to the scenario they imagined? (with IRB approval)

@PatriciaShanahan, If I read it correctly, the problem is with the control group who are not given the words so that the scans of the test group can be compared to a base. Making the control group active might invalidate their use as a control. I think the design issue is fairly deep.

@Buffy The only time I lie down flat with no entertainment, nothing to read, no TV is when I intend to go to sleep. I think even with the sleep opportunities of a retiree, not a student, that design would put me to sleep.

@PatriciaShanahan, yes, and thus it is hard to design the experiment so that you get a valid base line. "Stimulating" the controls just voids the experiment. I don't know the expected MRI difference between sleep and lying down quietly. But it isn't my field.

I thought the experiment was much more practical, such as comparing reactions to different sets of words.


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Taking Control of Your Dream
I experienced a weird situation a while back wherein I was dreaming hut was pretty sure I was in a dream and could control it to my wishes. I even had a break in my sleep and immediately went back to sleep and was again in the same situation. Can someone try to go in this state by planning or is it purely random?

I have been lucid dreaming on and off for more than a decade now and I would recommend the book 'Are you dreaming?' by Daniel Love for a serious introduction to the many techniques involved.

The term for this phenomenon is "lucid dreaming". It is common to have some lucid dreaming experiences, but different people have different occurrence rates of lucid vs non-lucid dreams, and the level of "control" varies as well.
A previous SE Q&A addresses some of the possible influences on lucid dreaming including the potential to learn to have more lucid dreams as a skill.


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Is there a neurological reason why women do not occupy top positions in the chess ranking?
I want to turn arround this question posted on chess exchange where sociological arguments are given to explain why only two of the world's top 100 chess players are women.
Are there neurological evidences to assert, in equal conditions, women would still be worst at chess than men?

I don't think there is anything to add to that question besides what's already there.

@Bryan Krause So the reasons are probably sociological and not any cognitive difference between males and females?

It's not a question that can be separated from the sociology. Training at anything changes the brain. There is no independent neurometric function for "good at chess" or really for anything else except extremely basic psychophysics.


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Neurological explanation for differences in what motivates runners?
I have noticed differences between how my friends and I are motivated with regards to exercise, and would like to better understand what is influencing this difference psychologically.
Personally, I am indifferent to running events.  I have run for its own sake on my own, both at novice and intermediate levels; training myself until I could run 5k or 10k regularly.  I once did a half marathon distance on my own simply as I was curious whether I could do it.  I feel absolutely no motivation to run as part of a group, nor do I feel any motivation to run for the reward of getting a time or rank or medal or what have you.
However, I recognise that this mindset is unusual when compared to my friends.  One friend started running with a "couch to 5k" group, another is keen to train for a half marathon event, another is a semi-professional athlete, etc.  The point is that most people I know who run seem to be motivated differently.
What explains the difference between these types of motivation?  This is not to ask what drives motivation generally, but specifically what is the neurological and thus psychological root cause for individuals being motivated by different sorts of things, in this case about why people run as a form of exercise.

Welcome to Psychology.SE. What have you read in the subject of motivation and what can affect motivation?  There can be a few things psychologically which can cause low motivation and some can be linked to physiological issues.

@ChrisRogers I have read about the relationship between dopamine and motivation, but the question between high and low motivation isn't what is being asked.  This is about what is driving the differences in types of motivation between individuals who are attempting similar tasks, in this case running.  What is the neurological basis for this?

Related: https://psychology.stackexchange.com/q/10410/7001

Your question is really broad and can encompass libraries. However, to add my 2-cents worth regarding

specifically what is the [...] psychological root cause for individuals being motivated by different sorts of things...

I would say that a lot of this has to do with external factors, and specifically external sources promoting exercise to be 'healthy', including peer pressure and multimedia.
To pin this global effect on our way of thinking down to

[the] specific[...] neurological root

is not really feasible in a single answer in the SE framework, as it is just way too complex to grasp on a single web page in a Q&A forum I'm afraid. But the between-subject differences can, at least partly, be explained by environmental differences.
Reference
- Brody & Inoue, Issues Innov Nursing Practice, 218-27

To say the differences are caused mostly by external factors, this suggests the internal neurological basis is effectively the same?  A motivation is a motivation is a motivation; akin to Harris' conclusion that a belief is a belief is a belief.  It seems then possible to conclude fairly concisely that motivation driven by the same neurology regardless of what form that motivation may take, be it social, reward, or otherwise.


text:
Modelling the Human Brain as a directed graph
A mathematician on the MathOverflow, Hans-Peter Stricker, recently(2016) considered the possibility that human brains may be modelled as directed graphs with neurons as nodes and synapses as edges. I think this makes sense as neurons are mostly unidirectional.
Now, what I am curious about is whether there are ever errors in the developmental process such that there are 'collisions' between two neurons. I can imagine this occurring in two ways:

Is it possible for dendrites to connect to other dendrites?
Alternatively, can axon terminals connect to other axon terminals?

If so, are there publications that estimate the natural frequency of such errors in a human brain?
References:

Edward T. Bullmore and Danielle S. Bassett. Brain Graphs: Graphical Models of the Human Brain Connectome. 2011.
Danielle S. Bassett and Edward T. Bullmore. Small-World Brain Networks Revisited. 2017.

This is called brain network topology or connectome topology, and is described in detail in this video series: https://www.youtube.com/watch?v=M0M3srBoTkY.  A related question is: https://psychology.stackexchange.com/q/15272/7001

Axo-axonic synapses and dendrodendritic synapses exist, and are not errors. They are particularly common in invertebrate nervous systems but are also found between particular cells in mammalian brains. I would say they are relatively understudied but not ignored.
True errors of the type you describe seem extremely unlikely to me. Synapses do not simply impinge on other fibers, there is extensive pre- and post-synaptic machinery, and bidirectional communication is necessary for proper synaptogenesis. Synapses are held together by connective proteins that are anchored in each membrane.
However, in terms of thinking of the brain as a "directed graph" one need not consider these uncommon synapses to have bidirectional connectivity: it is entirely possible, if not common, for cells to make traditional axon-dendrite synapses on another neuron that makes a reciprocal axon-dendrite synapse.
Graph theoretical approaches to understanding the brain are quite common, however, and certainly did not arise on StackExchange in 2016, as your own references make clear. There is no need for a directed graph to only have connections in a single direction, either. Any connectivity matrix can be interpreted in terms of graph theory.

Haydon, P. G., & Drapeau, P. (1995). From contact to connection: early events during synaptogenesis. Trends in neurosciences, 18(4), 196-201.
Kawaguchi, Y., & Kubota, Y. (1997). GABAergic cell subtypes and their synaptic connections in rat frontal cortex. Cerebral cortex (New York, NY: 1991), 7(6), 476-486.
Pinault, D., Smith, Y., & Deschênes, M. (1997). Dendrodendritic and axoaxonic synapses in the thalamic reticular nucleus of the adult rat. Journal of Neuroscience, 17(9), 3215-3233.
Somogyi, P. (1977). A specific ‘axo-axonal’interneuron in the visual cortex of the rat. Brain Res, 136(2), 345-350.


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Understanding the 'Wiring Catastrophe'
Introduction:
In 'Wiring optimization in the brain'(2000), Dmitri Chklovskii and Charles Stevens
analyse the dependence of the complexity of cortical circuits on the number of synapses per neuron using virtual perturbations. The authors clarify what they mean by a perturbation in their introduction:

To calculate the optimal wire fraction, we start with a real cortical region containing a fixed
  number of neurons, a mm cube, for example, and imagine perturbing it by adding or subtracting synapses and the axons and dendrites needed to support them. The rules for perturbing the cortical cube require that the existing circuit connections and function remain
  intact (except for what may have been removed in the perturbation), that no holes are created, and that all added (or subtracted) synapses are typical of those present; as wire volume
  is added, the volume of the cube of course increases.

Starting from a reasonable set of physiological relationships approximated as algebraic equations they derive a formula for $\theta$, the ratio of the number of synapses per neuron in the perturbed cortex to that of the real cortex as a function of $\phi$, the volume fraction of the perturbed cortical region made up of wires(synapses + dendrites), and $\lambda$, a constant that multiplies the length of wire associated with each synapse:
\begin{equation}
\theta(\phi) = \frac{1}{\lambda^5} \cdot \Big(\frac{1-\phi}{1-\phi_0}\Big)^{\frac{2}{3}} \cdot \frac{\phi}{\phi_0} \tag{1}
\end{equation}
In the paper, $\lambda$ is assumed to be equal to $1.0$ and I must say that the authors explain the derivation clearly. It doesn't require more than highschool algebra and each assumption is carefully justified. By calculating $\frac{d\theta}{d\phi}$ you may then find that ,if $\lambda =1$, $\theta$ is maximal when $\phi = 0.6$. This much makes sense to me but the authors then try to rationalise this value in a manner that appears to lack careful justification:

Why does complexity reach a maximum value at a particular wire fraction? When wire and
  synapses are added, a series of consequences can lead to a runaway situation we call the
  wiring catastrophe...At this point(phi=0.6), adding wire becomes impossible without decreasing complexity or making
  other changes - like decreasing axon diameters - that alter cortical function. The physical
  cause of the catastrophe is a slow growth of conduction velocity and dendritic cable length
  with diameter combined with the requirement that the conduction times between synapses
  (and dendrite cable lengths) be unchanged in the perturbed cortex.

Question:
The kind of justification that appears necessary to me concerns data on brain development. I understand that significant synaptic pruning occurs during adolescence so $\theta$ should vary and I think this poses a significant challenge to the account given by Chklovskii and Stevens. More precisely, this variation isn't accounted for by variations in $\phi$ in their model so I have doubts concerning the temporal and causal validity of their model.
To quantify the variation in $\theta$ we may use numbers from 'Synaptic Pruning Mechanisms in Learning' by Deborah Sandoval:

At infancy, each neuron averages around 2,500 synapses and at the peak
  of exuberant synaptogenesis (around 2-3 years of age) the number
  increases to around 15,000 (The University of Maine, 2001).

I must add that I have spent some time googling 'Wiring Catastrophe' but this doesn't return anything besides the original paper by D. Chklovskii and C. Stevens.
These observations lead me to the following questions:

If equation (1) is not an exact relationship, how can the extremization(i.e. differentiation) procedure be justified within the context of applied mathematics?
Is there any biological evidence of runaway wiring catastrophes occurring in real brains?

Discussion:
To clarify how synaptic pruning fits into the discussion we may associate a perturbation with a temporal variation in the number of synapses per neuron in the brain as follows:
\begin{equation}
\theta(i \rightarrow f) = \frac{\langle \text{synapses}_{t=f}/\text{neuron}_{t=f} \rangle}{\langle \text{synapses}_{t=i}/\text{neuron}_{t=i} \rangle} \approx \frac{\sum \text{synapses}_{t=f}}{\sum \text{synapses}_{t=i}} \tag{2}
\end{equation}
since the number of neurons in the brain is approximately constant. My argument is essentially that significant variations in $\theta$ aren't explained by the variations in $\phi$ which stands in contrast to the authors' assertion in their introduction that the relation between relative complexity $\theta$ and wire volume fraction $\phi$ is given by equation (1).
Addendum:
I just received a pretty comprehensive reply from Charles Stevens via email. In particular, he advised me to read the final version of their paper: Chklovskii, D.M., Schikorski, T., and Stevens, C.F. (2002) Wiring optimization in cortical circuits. Neuron 34:341-
347. This is on my reading list for the day.
References:

D. Chklovskii, C. Stevens. Wiring optimization in the brain. NIPS. 2000.
Gal Chechik ,Isaac Meilijson. Neuronal Regulation: A Mechanism For Synaptic Pruning
During Brain Maturation. 1999.
Deborah Sandoval. Synaptic Pruning Mechanisms in Learning. 2015.

I'm not really clear what you're asking. They're calculating an optimum for the ratio of wire (axons/dendrites) to non-wire (cell bodies). θ is a relative measure so I don't see how adolescence is relevant. The passage you quote as not careful seems perfectly reasonable to me and follows directly from the part you said is straightforward.

They're just talking about how much of a given volume should be wire. Synaptic pruning doesn't much change the volume of axons and dendrites in the brain. Theta is the ratio of synapses in perturbed vs. unperturbed cortex, an imaginary thought experiment. It's relative, not absolute.

@BryanKrause In their model, Theta is defined in terms of Phi which is a measure of the volume wire fraction. My argument is that due to what is known about synaptic pruning Theta will vary over time but this variation isn't accounted for by variations in Phi in their model so their equation isn't a causal model.

Rereading your question I think you may misunderstand theta. Try to reread the original paper carefully for what the actual meaning of theta is. Ultimately it doesn't matter as much as the optimal value for phi does. In a "pruned" versus "unpruned" brain you would also expect changes in lambda. The whole important result they are describing is just the optimum of phi, it doesn't matter if the other variables change.

@Perhaps I have phrased my question badly. Let me re-word it. I understand that theta refers to the ratio of the number of synapses per neuron.

Theta is not the number of synapses per neuron. It is "The ratio of the number of synapses per neuron in the perturbed cortex to that in the real cortex"

@BryanKrause Thank you for this clarification. I have updated my definition of the variable theta. That said, I have just added a discussion section which explains how my argument is relevant even with this definition.

"My argument is essentially that significant variations in θ aren't explained by the variations in ϕ" They are not interested in calculating theta, only maximizing it for a given lambda. They are only interested in the optimal value of ϕ that maximizes theta and showing that it matches what is found in the brain. That optimum does not depend on the other parameters, only on the cable equation assumptions described in the methods.

@BryanKrause After further reflection I managed to summarise my doubts into a couple questions.

Ok, I'll swing back later and take a stab at an answer if no one beats me to it. It will likely be mostly a synopsis of these comments though. I think you've still missed the point of the paper a bit and are reading things into it that were never claimed or intended.

@BryanKrause Actually I just received a pretty comprehensive reply from Charles Stevens. In particular, he advised me to read the final version of their paper: Chklovskii, D.M., Schikorski, T., and Stevens, C.F. (2002) Wiring optimization in cortical circuits. Neuron 34:341-
347. This is on my reading list for the day.

@AidanRocke You can always try to answer your own question. :)

The role of synaptic pruning and brain development:
In an email I received from Charles Stevens of the Salk Institute, one of the co-authors, he explained that they were trying to make predictions about cortical structure and function in fully developed brains and that they weren't trying to model brain development. This answers my first question.
 Empirical observations of the 'Wiring Catastrophe':
He also advised me to read the final version of his paper [2] which is a lot more thorough and contains a number of predictions based on three different thought experiments. Each thought experiment leads to a function whose extrema correspond to a scenario where the volume of axons and dendrites occupy approximately 60% of a cubic cortical region.
Instead of referring to a 'Wiring Catastrophe' the final paper simply focuses on the predictions of each thought experiment which are backed by the following observation:

We also measured the wire fraction from three mouse cortical regions and find that its actual value is not significantly different from the special value of 3/5.

To be precise, using an electron microscope they analysed cubic cortical regions from the Neocortex, Piriform cortex and Hippocampus of adult mice.
Finally, I must add that the discussion section and experimental methods section contain very insightful caveats.
References:

D. Chklovskii, C. Stevens. Wiring optimization in the brain. NIPS. 2000.
Chklovskii, D.M., Schikorski, T., and Stevens, C.F. (2002) Wiring optimization in cortical circuits. Neuron 34:341- 347


text:
Good neuroscience research blogs
In the field of AI research there are really good research blogs that regularly analyse methods and review papers. Examples that come to mind are:

BAIR blog: The Berkeley AI Research blog
Distill: an AI journal devoted to clear explanations

Might there be something similar for neuroscience? To qualify what I mean by 'good' the blog would have to cover:

methods for experimental, computational and theoretical neuroscience
comprehensive reviews of basic neuroscience research

Three neuroscience blogs that come to mind are:

Harvard Neuro Blog: articles from graduate students and postdocs working on basic research in the neurosciences at Harvard University
Neuwrite West Blog: a blog to make neuroscience accessible to anyone curious about the brain
Niko Kriegeskorte's blog: the blog of the visual scientist Niko Kriegeskorte

So far, I am unaware of an online journal like Distill for neuroscience research.
Note: As per the suggestion of Arnon Weinberg I decided to qualify what exactly I mean by 'good' and provided examples for concreteness.

The Neuroskeptic blog is a nice one.

-1 This seems like a long lists of opinions and not a good fit for the SE model.

@AidanRocke I think just removing the word "Good" from the title would alleviate many fears of opinion-based answers.  Edit the question to specify criteria for "good" instead.

@StrongBad You can join the discussion on meta on whether or not such question are appropriate for this site. The current consensus seems that this particular question is an example of a good 'list' question.

Also check:
https://bitsandbrains.io/
https://www.talyarkoni.org/blog/
calling it a blog is too much but sometimes we share stuff:
kordinglab.com
But also, there is maybe a bit more of a culture of publishing thoughts in papers in the field.

I would also like to plug
Markus Meister’s blog: https://markusmeister.com
Jeremy Borniger’s blog and journal club: https://jeremyborniger.com/new-blog
The Spike on Medium curated by Mark Humphries and curated by others; probably the closest to what you are looking for: https://medium.com/the-spike
Inscopix’s corporate blog: https://media.inscopix.com
Off the Convex Path which features ML and computational neuroscience: https://www.offconvex.org
And Richard Gao’s blog: http://www.rdgao.com/blog/
None of them are “one-stop-shops” like some machine learning blogs but they all offer interesting perspectives and reviews across computational and systems neuroscience.


text:
Is it possible for a "false positive" medical diagnosis to be voided or expunged later?
In general, if a diagnosing clinician makes a grave error in diagnosis, is it possible to later invalidate the diagnosis on the basis of insufficiency, lack of evidence, poor judgment, or other similar reason?
For example, if someone accidentally ended up in a situation where he/she was diagnosed with a mental disorder according to the DSM, but the symptoms according to the DSM do not correspond at all to reality (For example, at least the main symptoms are missing, the study admission was less then the official time needed to diagnose someone with a specific disorder, or a similar reason), can the diagnosis be fully expunged from their medical record upon a sufficient showing of such insufficiency?
I'm not asking about getting a second opinion, refusing treatment, or getting a discharge from treatment - I'm asking about fully eradicating or expunging a diagnosis to the point where it never really "existed" at all in a medical or medicolegal sense. In the practice of law, a legal judgment, order, or document can often be "voided", "vacated", "quashed", "overturned" or "invalidated" by a court if it is shown to have been issued in error. Is there any similar thing in the practice of medicine?
This sort of question is, perhaps, not very interesting or relevant for the majority of patients, but it can be very relevant for persons who must undergo formal "fitness for duty" evaluations or must "pass" medical background checks. For example, someone aspiring to become a pilot who has a history of treatment for schizophrenia, but is currently "ok", must normally undergo a grueling, time consuming, and expensive evaluation process. If such a person could get some sort of medical evaluation stating that they never really "had" schizophrenia to begin with, that could allow them to answer "no" on the applicable medical background check forms and obtain licensure that much more easily. This question may also be relevant to victims of gaslighting - if a person was given a clinical "label" as a result of abuse inflicted upon them, removing the "stigma" of having the "label" may be a valuable form of healing even if the person doesn't have any pressing legal need to have the diagnosis formally removed.

Welcome to Psychology.SE! I am sorry, but for a number of reasons outlined in this meta post we can not, and will not, give advice or potential diagnoses for any specific individual. If you have a question regarding your mental health, you should see a doctor. For further information on how this site is supposed to work, what is on-topic or not, you can take the [tour], visit the [ask] page and [meta].

@Chris I believe this question can be salvaged if it is understood to be asking if, in general, a process exists within the practice of medicine to "invalidate", "void", "vacate", "quash", or "overturn" a prior diagnosis based on procedural issues (or other issues) in the way that a court ruling can.

@Robert Columbia that is exactly what is meant by this question

Thanks! Could you edit your question to say that, and omit the personal details?

probably this is better

This question is very relevant for persons who must undergo "fitness for duty" evaluations or must "pass" medical background checks. The difference between, "Yeah, I was diagnosed with that, but I haven't experienced symptoms or had any treatment since 2012 - I am probably fine now" and "The diagnosis was officially voided in 2012 by the Grand Council of Medical Diagnosis Appeals Professionals on the bases of Lack of Informed Consent, Use of a Non-Evidence-Based Practice, Failure to Take an X-Ray, Improper Billing, and Failure to Post Medical Diploma on Wall of Office" is potentially huge.

I've submitted a suggested edit to your question. Could you take a look and approve it if you feel it is appropriate, with or without changes? It is important to make the question as clear as possible but also make it clear that you are not asking for a personalized professional opinion here on this site, but just asking for general information on how things "work" in a case such as yours.

"I'm not asking about getting a second opinion..." in order to get a clinical diagnosis removed, you are going to have to call on a second opinion, and maybe the opinion from more than a second clinical person.


text:
Can General Assessment of Functioning (GAF) be used to measure recovery etc. from all mental health problems?
Can General Assessment of Functioning (GAF) be used to measure recovery etc. from all mental health problems?
I know it's used with 'schizophrenia', but what about things like personality disorders, Dissociative Identity Disorder, etc.?

I edited out your second question "Does anyone know how each band (0-10, 11-20, etc.) is titled?" since the answer is easily found on Wikipedia. In case you need something different than Wikipedia, please elaborate and explain that in a new separate question.

Furthermore, where did you learn GAF is used with schizophrenia? Adding a citation/link to this initial research you did would improve this question.

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

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

References:
American Psychiatric Association. (2013). Insurance Implications of DSM 5. In Diagnostic and statistical manual of mental disorders (5th ed.).
Gold, L. H. (2014). DSM-5 and the Assessment of Functioning: The World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0). Journal of the American Academy of Psychiatry and the Law Online, 42(2), 173–181.


text:
Constraints on dataset size for AI-assisted connectome reconstruction
From an exchange with Dr. Seung, an expert on connectomics, I learned that one of his former PhD students Viren Jain is leading the Connectomic effort at Google using supervised learning methods. Now, supervised deep learning methods usually require large amounts of data to succeed. (I know this based on experience in industry as well as the deep learning literature.) However, due to the time and effort of human annotation the datasets for circuit reconstruction are really small:

It takes about six months for humans to annotate 1 cubic millimeter of brain volume.
In fact, Dr. Seung informed me that the following dataset from a circuit reconstruction competition in 2016 which is less than five gigabytes in total is basically state of the art.
Given that augmenting training data with synthetic data is frequently used for computer vision problems, I am led to the following questions:

Might it theoretically be possible to augment human-annotated training data with morphologically similar synthetic data?
What methods in the near future might allow us to significantly increase the size of human-annotated training data?

References:

Michał Januszewski, Jörgen Kornfeld, Peter H. Li, Art Pope, Tim Blakely, Larry Lindsey, Jeremy Maitin-Shepard, Mike Tyka, Winfried Denk & Viren Jain. High-precision automated reconstruction of neurons with flood-filling networks. Nature. 2018.
Luis Perez and Jason Wang. The Effectiveness of Data Augmentation in Image Classification using Deep Learning. Arxiv. 2017.
Alberto Bailoni, Constantin Pape, Steffen Wolf, Thorsten Beier, Anna Kreshuk, Fred A. Hamprecht. A Generalized Framework for Agglomerative Clustering of Signed Graphs applied to Instance Segmentation. Arxiv. 2019.
EyeWire: mapping neurons. https://science.eyewire.org/science-mapping-neurons Accessed 21 August 2019.

You might be interested in this work: https://www.biorxiv.org/content/10.1101/548081v1

Improving labeling
Increasing the amount of data that humans can annotate in a reasonable amount of time (your second question), one essentially needs to develop better labeling tools. Typically, this can either involve nicer interfaces or training ML algorithms to propose labels which humans can then more easily confirm or improve.
I recently attended a talk by Moritz Helmstaedter in which he presented work in both these directions. If I remember their approach correctly, they first had people trace axons and dendrites in serial electron microscope sections. Based on these traces, they then found the membrane around these axons/dendrites using an algorithm, which gave them a proposal for the segmentation. For the tracing part, they developed a nicer interface (see this paper): instead of showing only slices along the cardinal directions to their labelers, they developed a "flight mode" in which the labeler can see the data from an ego-centric view in the current direction of the neurite they are tracing. This gave them a 4- to 13-fold speedup.
Synthetic data
Concerning your first question, I'm not aware of any work on synthetic datasets in this area. I imagine generating one would be quite difficult, since cell morphology is complex. In order to generate synthetic EM images, you'd essentially need a detailed description of the cell morphologies in a cube of cortical tissue - and we usually get these descriptions from EM data. Alternatively, you could try to use deep learning (autoencoders or generative adversarial networks) to produce such synthetic data, but this recent review concluded that these will most likely not give you the quality you would need for training, since

the artificial images would likely either fail in subtle ways to be truly
  realistic or would fail to capture the full diversity of real-world data.

For now it seems the field will have to aim for better / faster human annotations instead of synthetic data.


text:
Biologically plausible models for causal inference in the human brain
Introduction:
In ‘Is coding a relevant metaphor for the brain?’(2018) Romain Brette argues that the causal structure of neural codes (linear, atemporal) is incongruent with the causal structure of
the brain (circular, dynamic). While he clearly explains how neural codes are inappropriate theoretical constructs for behavioural neuroscience experiments it's immediately clear what he means by causal structure.

On the 18th page he explains that:

The causal structure of the brain is sketched on Figure 9A. At a
coarse description level, the brain is a dynamical system coupled to
the environment by circular causality. At a finer description level,
the brain is itself made of neurons, which are themselves dynamical
systems coupled together. To a first approximation, the coupling is
mediated by spikes, which are timed events. In a dynamical system,
state variables have a causal role by construction; examples of state
variables in this physical system are membrane potential and the state
of ionic channels. Spikes have causal effect, but being events they
are not state variables; a spike is something that happens, not a
property of the system.

which is incongruent with concept of a neural code since:

Neural codes abstract time away, but temporality is critical to the
operation of a dynamical system.

It's worth noting that Judea Pearl and other computer scientists have developed practical methods for causal inference [2] but no rigorous notion of causality. For this reason, I think evidence of the brain's causal structure would require a practical dynamical model of the brain on which we can perform causal inference to answer questions in behavioural neuroscience.
 Questions:
This leads me to a couple questions:

Are there biologically-plausible dynamical systems models that would qualify? (Might brain network models be sufficient? Ex: [3])
Assuming such models exist, what methods may we use to perform causal inference on these dynamical systems?

After further reflection upon comments due to Bryan Krause I think these two questions may be combined to form a single question:
Are there biologically plausible models for causal inference in the human brain?
 Discussion:
Dynamical Systems that build upon neural coding theory:
Brette's notion of causal structure for the brain appears to be in direct opposition with that of Karl Friston's Free Energy Principle [4] whose formalism builds upon neural coding theory:

Learning under the free-energy principle can be formulated in terms of
optimizing the connection strengths in hierarchical models of the
sensorium. This rests on associative plasticity to encode causal
regularities and appeals to the same synaptic mechanisms as those
underlying cell assembly formation.

However, in [5] Karl Friston argues that a dynamical system like the brain can encode sequences of events via attractors:

...the basic idea is that the environment unfolds as an ordered sequence
of spatio-temporal dynamics, whose equations of motion induce
attractor manifolds that contain sensory trajectories. Critically, the
shape of the manifold generating sensory data is itself changed by
other dynamical systems that could have their own attractors. If we
consider the brain has a generative model of these coupled attractors,
then we would expect to see attractors in neuronal dynamics that are
trying to predict sensory input. In a hierarchical setting, the states
of a high-level attractor enter the equations of motion of a low-level
attractor in a nonlinear way, to change the shape of its manifold.

This is a plausible hypothesis which suggests that a more sophisticated notion of encoding might be used by the brain where state variables emerge from temporal sequences via attractors. Having said that, Brette's critique of the conventional interpretation of neuronal codes by the majority of behavioural neuroscientists still holds.
Causal Inference vs the metaphysics of Causality:
We can't know the brain itself, only models of the brain that we may use to do experiments. To clarify my first question: Brette says that models based on notions of neural coding wouldn't qualify so what are concrete examples of dynamical systems models that do? My questions are very much designed to move the discussion beyond theory and what could be useful to behavioural neuroscientists. Furthermore, I suspect that it's not possible to define causality without going into metaphysics. This is probably why Judea Pearl chose to develop a theory of causal inference and not a theory of causal methods. Using methods from causal inference you can argue that two causal structures are distinct if: (1) there is a method for causal inference that is applicable to struct A but not struct B (2) there is a method for causal inference for which struct A and struct B give different answers.
References:

Romain Brette. Is coding a relevant metaphor for the brain? BioArxiv. 2018.
Robert R. Tucci. Introduction to Judea Pearl's Do-Calculus. 2013.
Christopher W. Lynn & Danielle S. Bassett. The physics of brain network structure, function and control. Nature. 2019.
Karl Friston. The free-energy principle: a unified brain theory? 2010.
Karl Friston and Stefan Kiebel. Predictive coding under the free-energy principle. Phil. Trans. R. Soc. B. 2009.
The Metaphysics of Causation. Stanford Encyclopedia of Philosophy. 2016.

Good question, I'd probably argue against the last point though, I think Brette is just critiquing a causal linear/atemporal view whereas Friston is talking about causality much more abstractly.

@BryanKrause This motivated me to look up Friston's conception of encoding a bit more closely. The issue appears to be a bit more subtle than I realised and I try to clarify this in the discussion section.

In re-reading your question I find it a bit hard to follow what you are actually asking. "it's not entirely clear to me what he means by causal structure" - I'm not sure what's not clear, it's in the diagram. Elements in the brain, lets say neurons, are connected to each other and to the outside world so that the future state of the brain is caused by a combination of the present state and interaction with the outside world. Are you trying to read more into it than that? It might be you are coming at this from what, from my perspective, is too based in math and not on science.

@BryanKrause We can't know the brain itself, only models of the brain that we may use to do experiments. My first question: Brette says that models based on notions of neural coding wouldn't qualify so what are examples of models that do? My questions are very much designed to move the discussion beyond the theory and what could be useful to behavioural neuroscientists. I've added a small remark to clarify this point.

@AidanRocke Right, that's why I'm confused by your confusion, though: Figure 9A depicts an example of such a model. As far as models useful to behavioral neuroscientists, well... there are literally thousands of papers connecting some sort of behavior to some sort of neural model. Doesn't that seem a bit broad to you?

The critique Brette is making is of a linear casual feed-forward network and treating neurons as encoding some experimentally measured or manipulated variable. It's kind of a straw man argument. Brette is just saying that you can't just look at a stimulus and response to understand the brain, you have to understand the context in which the brain processes that stimulus. A neuron that fires when a red square isn't presented shouldn't be understood as a "red square" neuron. That's it.

@BryanKrause I wrote a remark that explains my point in a bit more detail. Brette's constraint is that it would have to be a dynamical systems model that is to some degree biologically-plausible.

From the literature I have found on biologically plausible models for causal inference in the human brain, experimental validation appears to be constrained by a lack of data. In the case of causal inference models for multisensory perception, the authors of [2] say that:

...the specific computations underlying the frontal multisensory
representations, and their specific role in driving behaviour, have
remained elusive.

But, the path to biologically plausible models first starts with cognitive plausibility.
 Cognitively plausible models:
In [1], Kording et al. come up with a time-bounded model and compute-efficient cognitive model for multisensory perception:

Perceptual events derive their significance to an animal from their
meaning about the world, that is from the information they carry about
their causes... The brain should thus be able to efficiently infer the
causes underlying our sensory events. ...We formulate an
ideal-observer model that infers whether two sensory cues originate
from the same location and that also estimates their location(s). This
model accurately predicts the nonlinear integration of cues by human
subjects in two auditory-visual localization tasks. ...By combining
insights from the study of causal inference with the ideal-observer
approach to sensory cue combination, we show that the capacity to
infer causal structure is not limited to conscious, high-level
cognition; it is also performed continually and effortlessly in
perception.

Their causal model may be succinctly described as follows:

One cause may be reponsible for both sensory cues(audio and visual).
Two separate causes may be responsible for each cue.

They then go on to define a Causal Bayesian model which may be described using Bayes rule:
\begin{equation}
P(C|x_v,x_a) = \frac{P(x_v,x_a|C)P(C)}{P(x_v,x_a)}
\end{equation}
where $C$ denotes a type of cause and $x_v, x_a$ represent the visual signals and auditory signals respectively which are modelled as univariate Gaussian variables.
If $C=1$ there is a single cause and if $C=2$ there are distinct causes. Although this model is simple the authors find that the model's predictions actually match the behaviour of the participants in the experiment. This experiment is very useful but the authors recognise:

This leaves the question of what neural processes underlie the causal
inference computations that emerge at the behavioural level as close to
Bayes-optimal.

 Finding a neural description of multisensory causal processes:
Building upon [1], the authors of [2] combined a multivariate analysis approach to MEG data with computational modelling of behaviour, to infer where in the brain and when neural signals predicted by models of sensory fusion and causal inference emerge during multisensory perception. They reasoned that causal inference would rely at least in part on the frontal cortex, a structure that is thought to subserve causal reasoning and sensory conflict resolution.
This is an important step forward as they managed to find a neural description using MEG data that is consistent with their hypotheses and a refinement of Kording et al. causal model:

Using a multisensory rate-categorisation task, we show that flexible
multisensory behaviour is best described by a Bayesian causal
inference model. The neural representations of sensory fusion and
inference unfold hierarchically in time and across distinct brain
regions. This comprises a cascade from early unisensory encoding at
the primary cortical level, to reliability-weighted fusion in the
parietal-temporal cortices, and to causal inference primarily in the
frontal lobe. We found that neural representations within the
dorsomedial and ventrolateral PFC were directly predictive of
categorical choices, and that the vlPFC subserves a particular
behavioural benefit of inferring sensory causes to minimise perceptual
bias in discrepant crossmodal contexts. Our results thereby reconcile previous rival computational models of multisensory integration (Figure 1), by showing that distinct computational strategies are orchestrated in temporal sequence and along a parietal-frontal hierarchy.

Perhaps greater progress can be made modelling the probabilistic behaviour of populations of neurons [3,4]. But, as pointed out by Brette these would have to be neural dynamics models where the method for inferring population codes accounts for temporal dynamics in a biologically plausible manner.
 References:

Konrad P. Körding , Ulrik Beierholm  , Wei Ji Ma , Steven Quartz, Joshua B. Tenenbaum, and Ladan Shams. Causal Inference in Multisensory Perception. PLOS. 2007.
Yinan Cao, Christopher Summerfield,  Hame Park,  Bruno L. Giordano, Christoph Kayser. Causal inference in the multisensory brain. biorxiv. 2018.
Zemel RS, Dayan P, Pouget A. Probabilistic interpretation of population codes. Neural Comput 10: 403–430. 1998.
Pouget A, Dayan P, Zemel RS. Inference and computation with population codes. Annu Rev Neurosci 26: 381–410. 2003.
Karl Friston and Stefan Kiebel. Predictive coding under the free-energy principle. Phil. Trans. R. Soc. B. 2009.


text:
Explanation of "I never thought I'd get this far"
There's a phenomenon where people get to a stage in life they never thought they'd see it and they don't know what to do. Why is that? Why is that when we're faced with a non-foreseeable dilemma we don't know what the right thing is to do? How common is this?
"I Never Thought I'd See the Day!" or "I never thought I'd get this far" from SpongeBob's Plankton T.V. Show are memes.

I'm adding to social psych tag because I've seen related questions in social psych class.

Welcome to psych.SE.  This question seems too broad and opinion-based for this forum...  Perhaps it could be narrowed down to something potentially answerable about pessimism, indecisiveness, future planning, or being overwhelmed?  Please edit the question to something more specific, and then it can be reopened.

This is a good question which cannot really be provided with scientifically proven reasons, so we can only look at possibilities.
From personal experience as a therapist, anecdotally I can say that with some people, the meme would not be complete.  With these people the situation would be

I didn't think I would get this far so quickly

and that could be a key point with many others.
When planning for the future, do you plan for things you know you will reach very soon or do you include those points where you cannot envisage getting to right now?
Forward planning can be different from person to person, and if you haven't planned for a particular eventuality, how do you know what you want to do, let alone how you should do things?
The comment at the bottom of your image:

I have managed to change my name and gender on ALL of my legal documents! So what's next?

can be a comment of surprise, and maybe despair; or it could be:

Good! I have that out of the way, now do I have to do anything else?

The processes involved with identity change can be daunting and therefore some choose to take things a step at a time rather than planning the whole process before carrying it out.
Is the person aware of all the things they need to do?
Can they cope?
Do they have the support of professional organizations to help along the way?
Do they have support from friends and family?
All these things and more will affect how the person will be dealing with the situation.


text:
How the percentage of disability is measured in India in case of autism, ADHD, learning disability etc?
How the "percentage" of disability is measured in India in case of cognitive difficulties such as autism, ADHD, learning disability, intellectual disability etc?


text:
is it possible to be severely autistic yet not being "visibly autistic"?
It is common problem for many "mild" (ASD level-1) autistics to be criticized as "you do not look autistic" or some of its variants. Also sometimes seen in social media that moderate autistics (level-2) (claimingly) facing similar issues to disclose their diagnosis.
By "visible" I mean the publicly considered easily observable disabilities, such as extreme intellectual disabilities, visibly heavily motor nonfunction or totally unable to move, saliva dripping from mouth, complete nonverbality or observably distorted voice and language, disfigurement or birth-defects, inability to hold urine or stool,  etc. Usually the known to be severe (level-3) autistics have at least one of these "publicly perceived as disability" symptoms.
Incidentally, autism is not itself a visible condition at all, and the intellectual disability is not itself autism, its sometimes a co-morbid condition with autism but it is not identical to autism, rather autism is basically the impairment in social cognition. Also some of the symptoms of autism may be actually visible or easily observable but these are commonly mistaken as intentional inappropriate behaviour or lack of morality or as some mental illness instead of cognitive difficulties or social disablilities.
Now my question is; Is it possible that someone has level-3 (severe) autism yet on superficial look or talk the disability does not appear?
Theoretically it seems to be very possible that a severely autistic person may lack all of the publicly believed stereotype on disability, also can lack intellectual disability, moreover can apply sharp observations and observation to mask and fit-in, yet can have tremendous problem in social aspects. In such case a level-3 autistic too may face "you don't look autistic" situations. And probably all the observable symptoms will be imsinterpreted as mood or behaviour issue.
But does that happen in reality? or all of the severe (level-3) ASD have also some publicly believed stereotype of disability?

Note: See also Autism "severity" levels
Screenshot:

Not sure whether it is physically possible to suppress Level 3 according to the definition? Or present a good self for interview without giving off any clues of these issues  - Requiring Very Substantial Support: Severe difficulties in verbal and nonverbal communication. Very limited speech, odd, repetitive behavior; many express their basic needs only.

What you propose

Is it possible that someone has level-3 (severe) autism yet on superficial look or talk the disability does not appear?

is a contradiction in terms by the usual (DSM) definition of autism, which is based on several criteria which are behaviorally defined, i.e. from an observer's standpoint, to start with

a child must have persistent deficits in each of three areas of social communication and interaction (see A.1. through A.3. below) plus at least two of four types of restricted, repetitive behaviors

Nowhere in there is that presupposed to be just "basically the impairment in social cognition" that may not even be manifested.
(Somewhat of an aside here; DSM-5 has tried to be less "atheoretical" than its III/IV predecessors, but in the end the differences in that regard are minor.)

Now if you want a bit of a deep[er] dive here, the DSM-5 acknowledges that some compensatory behaviors exist and should even be considered in assessing the (actual) severity of the diagnosis.
And a bit of digging through recent research finds a controversy in (re)defining (of sorts) "true" autism to mean Theory-of-Mind-deficits instead of [DSM] behavioral-autism... or at least (thus) identifying "camouflaged" or "highly compensated" autism (understood as ToM-deficits). This is quite a complicated discussion because ToM is multidimensional (or at least its measures are--and some correlate better than others with DSM-autism), and so (varied) are compensatory mechanisms for its deficits. The latter are surprisingly used by "normal" people as well, with perhaps only "shallow" compensation strategies specific to autism.
In the realm of personalities, you have prominent researchers on both sides of this dispute, e.g. Happé (responding to) Fombonne's (editorial). (h-index > 100 for both.)
I'm guessing you've read & bought the ToM-deficits view of autism when you say "autism is not itself a visible condition at all" and "is basically the impairment in social cognition". Frankly if you look at Happé's last piece I linked, she (and her group) are cautious not to take that extreme position, although I'm sure it came off like that in some popsci article (the BBC at least has an article on people discovering their "hidden autism" thanks [or at least in relation] to Happé's research.)
As a final (recommended) reading here, which may help put this in context, some piece from Allen Frances who was quite involved with
the previous editions of the DSM on the conflicting views on mental illness diagnosis standards in general (e.g. is clinical impairment needed) is also relevant here.

There is nothing to take as "offence". I have asked a question only.


text:
Do we have a psychological need to talk to people?
Do we have a psychological need to talk to people?
I don't believe it's in Maslow's hierarchy, but surely.

Maslow's needs aren't entirely supported and can be a bit controversial, but one of the levels is love/belonging; it may not include verbal communication explicitly, but it's likely implicitly included for most people. Can you maybe explain a bit more the motivation for your question? That might make it more answerable with specific data..

my motivation is just that i feel the need to communicate but it isn't included in maslow's list of needs @BryanKrause

Have you looked at the isolation and social exclusion literature? That might clarify the need to talk issue

As @BryanKrause asked, please help us to help you and [edit] your question to provide more information on what you have read on this subject, and any problems you are having understanding your research. If you found nothing, what did you Google? This helps to provide an answer which will be more helpful.

i'm not even sure what i would google. i'm looking for a psychological theory that says we have that need (just so that i may read around the topic), not a pop psychology / self help article @ChrisRogers

What have you read about Maslow's hierarchy that makes you conclude "it's not in Maslow's hierarchy"? Would an answer that explains it is encompassed in Maslow's hierarchy answer your question?

It’s worth remembering that Maslow proffered a THEORY with very little experimental evidence to support it. Since then lots of experimental research has been done with a number of primary needs being identified. Primary needs are often those that take place implicitly and/or evoke visceral responses (typically via the amygdala) when threatened or rewarded (there’s more to it than that but just a starter for 10).
A neat summary of those primary needs can be found in David Rock’s Your Brain at Work (2009). The need I believe you’re referring to is RELATEDNESS. Neuroscientific research in this area has found that being excluded from say a conversation or group hurts us more than physical pain. Also have a look at:
The neural bases of feeling understood and not understood
Sylvia A. Morelli,  Jared B. Torre, Naomi I. Eisenberger
Naomi Eisenberger in addition has lots more great research in this area - too much to list here
Hope this helps!


text:
Excluding psychometry and interview methods, is there any physical or molecular method that can confirm mild autism?
ASD is a set of very much heterogeneous symptoms with some common characteristics like lack of eye contact, lack of social guesswork, difficulty in learning unwritten social norms or conventions, missing the sense of personal boundary of other people, lacking or inappropriate gesture, restricted repeatitive and intense interests, etc.
The interview and psychometry methods, sort of, work, still misdiagnosis ain both ways, are common and develop controversies and harasses. Delayed diagnosis is also a fact.
But my question is; do we yet have any "confirmed" and reliable test for ASD particularly those at the "mild" end of the spectrum? Such as a scan-based technique such as MRI/ fMRI/ DTI or say electrophysilology techniques such as EEG or qEEG or molecular tests like DNA blotting or DNA sequencing or Elisa etc does such physical or molecular techniques can characterise ASDs??
Notably, this article says no significant anatomical difference found in a large-scale analysis using ABIDE database.

Related: https://psychology.stackexchange.com/questions/423/what-is-aspergers-syndrome

No.
The key term that will help you look for research about this is the word "biomarker".
There are certainly correlations with autism and some of the measurement techniques, but they aren't specific enough to be used for diagnosis.
Plitt et al 2015 compared fMRI classification to a behavioral scale in high-functioning ASD vs IQ-matched typically developing. Their best imaging classification was about 77% accurate (and that's probably an overestimate due to selecting the 'best'), whereas behavioral classification was 95% accurate. This result is consistent with other studies.
It's possible to use these methods to find biomarkers at better than chance levels, but unless they become equivalent to other diagnostic methods, it is the diagnosis used to evaluate the biomarker rather than the biomarker used to evaluate the diagnosis.

Abraham, A., Milham, M. P., Di Martino, A., Craddock, R. C., Samaras, D., Thirion, B., & Varoquaux, G. (2017). Deriving reproducible biomarkers from multi-site resting-state data: an autism-based example. NeuroImage, 147, 736-745.
Ecker, C., Bookheimer, S. Y., & Murphy, D. G. (2015). Neuroimaging in autism spectrum disorder: brain structure and function across the lifespan. The Lancet Neurology, 14(11), 1121-1134.
Loth, E., Spooren, W., Ham, L. M., Isaac, M. B., Auriche-Benichou, C., Banaschewski, T., ... & Charman, T. (2016). Identification and validation of biomarkers for autism spectrum disorders. Nature Reviews Drug Discovery, 15(1), 70.
Plitt, M., Barnes, K. A., & Martin, A. (2015). Functional connectivity classification of autism identifies highly predictive brain features but falls short of biomarker standards. NeuroImage: Clinical, 7, 359-366.
Uddin, L. Q., Dajani, D. R., Voorhies, W., Bednarz, H., & Kana, R. K. (2017). Progress and roadblocks in the search for brain-based biomarkers of autism and attention-deficit/hyperactivity disorder. Translational psychiatry, 7(8), e1218.


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Is stacking cans really a sign of Asperger's?
Wikipedia says:

People with Asperger syndrome often display restricted or specialized
  interests, such as this boy's interest in stacking cans.

How predictive is this of Asperger's: What percentage of normal boys and boys with Asperger's display this type of behavior, respectively?

What behavior are you referring to? Wikipedia says "restricted or specialized interests" and then gives an example: this particular boy has a restricted or specialized interest in stacking cans. Wikipedia is not saying stacking cans is a sign of an ASD.

@BryanKrause building towers, presumably.

Ok; Wikipedia does not say that building towers is a sign of ASD.

Symptoms of Asperger’s Syndrome

difficulty recognizing social cues
awkward body language
social isolation
aloofness
fixation on certain objects

The picture (and idea) that “stacking cans” is in itself a sign of Asperger’s is misleading at best.
One could just as easily say this child is making “a tower”, a common activity amongst children.
Asperger at Psychotherapy Collective
Stacking objects can be a child development tool.
Childhood development tools

Can you cite any sources that say that building towers is a common activity?

@MaxB added stacking used as a tool

Autism is usually a range or spectrum of co-morbid symptoms that greatly vary from one autistic individual to another. As an only common characteristic we may say that autism is a disability in social cognition.
Even no two aspergers are same (and now the term Asperger has been merged with ASD since there is not a clear distinction of Asperger and other ASD. Initially Aspergers was distinguished from most other types of autism that do not have any speech or language delay (WHO, ICD-10 , DSM-4) though internally it is very same to other forms of autisms.
We may say that arranging objects (such as laundry clips, pen caps, pebbles, blocks, sticks etc) may help recognise autism, but it is not a conclusive by any means. Almost any kids do some amounts of constructive play. If a kid likes to line up toys, no need to panic, it is probably not autism, its probably a very common kid, playing with stuffs. However if there are combination of social difficulties then maybe it is autism and the kid needs support and understanding.
Conversly, someone is autistic does not mean they will obsessively arrange toys in arrays. Some will watch TVs, some will sit still, some will jump or pace up or some will try to socialise but eventually fail. Or some will sit beside the window, or some will not look anything such readily recognisable. ASD is a spectrum of conditions, not one single condition.
Lining up toys that is only one observation on behaviour but there are many more other aspects such as some common characteristics are difficulties comprehending social norms and cues, failing to guesswork on social expectations, lack or inappropriateness in using body language, lack of eye contact, lacking sense of personal boundary, irritability with change of address or routine or  living methods or arrangement of things, hypersensitivity or hyposensitivity (or combination of these 2) towards sound noise, light, smell, tastes, texture, in some cases difficulty with fine motor skills, learning difficulties such as dyscalculia or dyslexia, problems with facial recognition etc. However these symptoms usually occur in a combination and vary greatly within ASD individual.
Yes, punding, patterning and constructive play (and some cases disinterest or difficulty or  inability in pretend play or role play game) is one of the common  feature of ASD, and not necessarily tin cans but these infants may find some other materials, and not only lining up but they may engage in making more type of  arrays and patterns, however only 1 characteristic is not even close to conclusive.

Interesting, do you have references to support your answer?

I will add them later, I will refer to common internet articles including wikipedia articles etc.

Okay, that is no problem!

@HallsofJustice Yes, references would be nice.

Added some links. Will add more later.


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Cingulate cortex vs Limbic lobe are they same or slightly different?
I've read the wikipedia article on Cingulate cortex and the article about limbic lobe. Also did web search but it is not clear to me whether they are synonymous or there are slight differences in the parts they include.
UPDATE:
it seems search terms for "limbic system" and "limbic lobe" giving me a different google search result. There also are wikipedia pages on
1. Cingulate cortex,
2. Limbic Lobe ,
3. Limbic System .
where cingulate cortex (1) is confusingly similar to Limbic lobe (2) but Limbic system (3) seem to be different (but inclusive) terminology from limbic lobe (2).
So I want to know if limbic "lobe" and cingulate cortex are synonymous or they differ in the areas they include.

Updated answer:
The limbic lobe (aka limbic cortex) is made up of the cingulate gyrus and the parahippocampal gyrus (so the cingulate gyrus is only part of the limbic lobe). The limbic lobe is part of the limbic system. There is some disagreement over what the limbic system includes, but some of the other areas contained in the limbic system include the subcallosal gyrus, hippocampus, and amygdala.

If it helps, I use a combination of sources whenever I'm learning about an area. The Human Brain Coloring Book (Collins), Radiopedia.org, and KenHub.com (I just use the free version that you get by registering) are the ones I use the most. It's risky to rely on just one because there are inconsistencies. I only use Wikipedia as a very last resort because it contains far too many errors and too much information, making it hard to understand. I'm sure there are better resources out there so if anyone else has any suggestions, I'd be very keen to hear them.

Wikipedia isn't a great place to learn about neuroanatomy. It is often confusing and misleading. See suggestions for alternatives in the previous comment.

Human brain colouring book??? Seems SOOO exciting, I'll purchase one whenever it will be possible. I just love to learn through pictures and sketches and usually i cannot memorise info about something until and unless i can associate it with distinctive shapes or picture cards.

It's a great book. It contains detailed text as well as diagrams to color. https://www.amazon.com/dp/0064603067/


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Why seemingly all the neuronal membrane-bound receptor are exclusively GPCR or highly homologous to GPCR family?
Nicotinic AchR is known for long to be an ion channel receptor however it has been argued whether it is a GPCR, as well Muscarinic AchR is known to be GPCR.  Seemingly many other nerve cell bound receptors like   Serotonin receptor, Melatonin receptors, Dopamine receptors, Adrenaline and Nor-adrenaline receptors, known to be G-protein coupled receptor (GPCRs). Although GABA receptors are not directly GPCR by functionality, wikipedia tells a subtype of GABA receptor. is probably GPCR.
So I have basically 2 part in this question:

Why GPCR or receptors homologous to GPCR are so common in nerve cells?
Are there neuronal receptors which do not have homology with GPCRs?

I think you're confused about proteins that are GPCRs versus having homology. GABA-B is another that is a GPCR (it is not particularly related to GABA-A). These are also called metabotropic receptors.
Ionotropic receptors are from separate families, many from the Cys-loop family (see Sine & Engel, 2006) with a characteristic 5-subunit composition, or the heterotetrameric structure shared among related glutamate receptors (see Dingledine et al 1999).
Your link for nAChR doesn't seem to argue that it is homologous to GPCRs, instead it describes a possible interaction with that channel with g-proteins.
Additionally, none of this is special for neurons: because all modern proteins evolved from previous ones, there is substantial homology within protein families that can often be traced even between vertebrates and bacteria. Within the GPCR family, many different proteins have evolved different sensitivities and different specific g-protein interactions, but the general concept is conserved: something binds outside the cell, causing an internal conformational change that affects a g-protein. The ionotropic receptors are much different.

Dingledine, R., Borges, K., Bowie, D., & Traynelis, S. F. (1999). The glutamate receptor ion channels. Pharmacological reviews, 51(1), 7-62.
Sine, S. M., & Engel, A. G. (2006). Recent advances in Cys-loop receptor structure and function. Nature, 440(7083), 448.


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Does this Rat psychological developmental mechanism also work in human?
In this epigenetics tutorial by University of Utah (Browser requires to support and allow adobe flash player); it is shown that in rat model those rat kids get little or no maternal care, whenn adult, develops aggression, lack of calmness etc. Whereas the rat kids got more maternal care and nurturing, developed better cope-up at stress, relaxed very quickly after stress. They credit this to hippocampal GR (glucocorticoid receptor protein) gene overexpression in the more nurtured rat kid (and underexpression of GR gene in uncared rat kid) as well as difference in expression in "hundreds of genes". (The adobe flash app even offers a "rat pup licking game"!)

Screenshot of the app.
Does this principle also work on human? There is a common popular belief that stress makes a person more resilient to stress. But at least in the rat example at least partly that popular assumption did not apply. The rat which lacked maternal adore at childhood, developed underexpressed hippocampal GR gene throughout the rest-of-the-life, and though they have specific advantage to specific situation, they could not quckly relief from stress. In contrast, more nurtured rat kid developed overexpression of hippocampal GR gene that helped them fast recover after stress.
My question is; this principle found in rats (which is also at a contrary to a certain popular belief), does also apply on humans? Such as if a human kid get less nurturing and more struggle or stess, will she or he develop less-resilience/ delayed recovery from stress at later life? as well if a human kid get proper maternal care and nurturing then she or he will develop more adaptibility and faster recovery from stress? If yes, is it due to similar set of genes?


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When does a human baby develop a consciousness?
Not to offend anyone or anything, but I've been searching up about abortion lately, and all the debate about it, and it got me wondering, when does a baby develop a consciousness?
Consciousness - the ability to sense the world around you in an independent way. You can think for yourself, and make choices that defy your natural instincts. It is what some say separates us from wild animals. Animals have a survival instinct. They do what they can to survive. Eating colourful packets of soap is not an example of a survival instinct, and therefor proves that we have a consciousness.
Definitions of consciousness
So when does consciousness begin in a baby? And before that time, how does the brain work? Does it just feel the surroundings without any response? Any help would be greatly appreciated. Thanks!

Just curious, is this question too general? What are some ways that I can improve it?

Hi Fuzzy, in my opinion, this question is not answerable. We have neither a good definition of what consciousness is (which may or may not be an answerable question, but in any case, experts in the field disagree; see for example https://psychology.stackexchange.com/questions/987/what-are-current-neuronal-explanations-and-models-of-consciousness ), nor a good definition of what differences there really are between human and non-human consciousness. The only thing that I would be confident in is that there is no particular moment.

"Eating colourful packets of soap is not an example of a survival instinct, and therefor proves that we have a consciousness." is also not a definition of consciousness I have ever heard before. Animals do many things that are not good for their survival, and are also definitely conscious, but the two are unrelated.

@Bryan Really? I thought consciousness could be compared to a survival instinct since consciousness means that we can think for yourself, which is the opposite of what some animals do. Oh, and I provided a link in my question if that could help

Yeah sorry I wasn't clear, I meant definitions biologically of what consciousness is are not known, as in, what can be measured as consciousness. The definitions in your link are helpful but also not very specific, and it leaves open how do you measure for example one from your link "Consciousness is the quality or state of being aware of an external object or something within oneself"

Ah, I see. Sorry about that. I'll try for a more specific question next time

Keep in mind that there is no way to know for sure whether anyone/thing else other than yourself is conscious. All objective measures of consciousness (behavior, EEG, etc...) have an implicit assumption that if something is sufficiently similar to something known to be conscious e.g. me, then it too must be conscious. Questions about a baby's consciousness essentially boil down to 'when is a baby sufficiently similar to a conscious adult human?'

Q: When does a human baby develop a consciousness? … Consciousness - the ability to sense the world around you in an independent way. You can think for yourself, and make choices that defy your natural instincts. It is what some say separates us from wild animals...
A: Consciousness is the term that has various meanings. In the above meaning, it requires the function of certain groups of neural circuits that include the ARAS (ascending reticular activating system), several cortical areas, and the thalamo-cortical loop [1,2]. So, for a fetus to begin to have consciousness, it must have these neural circuits developed to the point that they start functioning, which occurs around gestational week (GW) 24 -26. [3,4]

“Two of the most important pathways in the brain are the ones that transmit sensorimotor information, the thalamocortical (TC) and corticothalamic (CT) pathways. The TC relays sensory and motor information from the receptors in the retina, cochlea, muscle or skin to the sensorimotor regions of the neocortex via the major subcortical sensorimotor relay, the thalamus. The CT pathway completes the feedback loop by transmitting information from cortex back to the thalamus. These essential pathways begin to form in the later part of the second trimester in humans, and are complete by GW 26. [3]”

Studies about sleep-wake cycles in fetuses also find that a fetus has definite sleep-wake cycles with distinguishable REM and non-REM periods between GW 28 – 31 [5,6]. This means that a fetus does already have periods of wakefulness, which are necessary for conscious awareness to occur, instead of being in an unconscious state all the time, during this time. So, consciousness begins to exist in a fetus no later than this time period.
However, consciousness in a fetus is in a very rudimentary form; this can be evident from the fact that even an infant, which has a more mature brain than a fetus, exhibits consciousness only at a low level compared with an adult and that the default mode neural circuit, which is now found to have an important role in consciousness at rest [2], is still incomplete[4]. What’s more, the sense of self or self-recognition begins to appear in some infants only around 15 months of age and in a majority of infants by 24 months of age [7]. So, it’s very very unlikely that an infant has the sense of self and that it can think for/about itself.
In conclusion, it seems that an infant begins to have a rudimentary form of consciousness at around GW 24-26. This may help provide informed decision about legal abortion.

“Assuming that consciousness is mainly localized in the cortex, consciousness cannot emerge before 24 gestational weeks when the thalamocortical connections from the sense organs are established. Thus the limit of legal abortion at 22-24 weeks in many countries makes sense...[4]”

However, these are only indirect evidence. Direct, definite evidence of when exactly a fetus begins to have consciousness is not available yet.
References.

Koch C, Massimini M, Boly M, Tononi G. Neural correlates of consciousness: progress and problems. Nature Reviews Neuroscience. 2016;17: 307-321. The full pdf file can be downloaded from here.
Song X, Tang X. An extended theory of global workspace of consciousness. Progress in Natural Science. 2008 Jul;18(7):789–793.
Stiles J, Jernigan TL.The Basics of Brain DevelopmentNeuropsychol Rev. 2010 Dec; 20(4): 327–348.
Lagercrantz H.The emergence of consciousness: Science and ethics. Semin Fetal Neonatal Med. 2014 Oct;19(5):300-5. doi: 10.1016/j.siny.2014.08.003.
Okai T, Kozuma S, Shinozuka N, Kuwabar Y, Mizuno M. A study on the development of sleep-wakefulness cycle in the human fetus. Early Human Development. 1992 Jun-Jul; 29(1-3): 391-396. https://doi.org/10.1016/0378-3782(92)90198-P
Mirmiran M, Maas YGH, Ariagno RL. Development of fetal and neonatal sleep and circadian rhythms. Sleep Medicine Reviews. 2003; 7(4):321-334.
Anderson JR. The development of self-recognition: A review. Dev Psychobiol. 1984 Jan;17(1):35-49.


text:
Has sharing non peer reviewed sources decreased or increased beliefs in pseudoscience?
I haven't found a detailed study of this, but here would be an example. If people shared a site that talked about the dangers of global warming, but wasn't peer reviewed, does this increase awareness, or does it actually give more credibility to global warming denial sites, since they are on equal footing, both being non peer reviewed? A global warming denialist argument is that a debate still exists (it doesn't), which has been good enough to cause skepticism and lack of action.
I know sites generally have incentives to get their articles or videos shared, so they would rather make their own summaries of scientific results, rather than just link to proper references. But pseudoscience sites can also reference peer reviewed sources, they just give their own interpretations of them. But why should anyone believe one site over another, since the standards for credibility are gone (which all of these sites perpetuate, pseudoscience or not)?
Or is it the case that non peer reviewed sites draw attention to issues in a way peer reviewed sources don't, and while there may be some collateral damage with lowering of standards, people are being swayed by pseudoscience sites either way?
So the main question is, has sharing non peer reviewed sites caused more damage than good in combating pseudoscience (including this site)?

I'm not sure if this can be answered in a strict scientific way, because how could anyone reliably test what influenced a certain person. If you ask me, most people became aware of global warming from the news, not from peer-reviewed articles.

@Jan Yes they probably became initially aware from the news. This question is more how sharing internet sources later influence people one way or another. I would think it would involves studies on groups of people moreso than individuals. Like say social media usage increased in an area, and beliefs in pseudoscience increased. Or maybe a group is taught proper referencing, and belief in pseudoscience decreased, including amongst those connected to them. Controlling for the right things, and finding causation beyond correlation would be challenging I would think.

The only thing I can imagine they can do in research is making surveys, which are sometimes used in collecting data. They would ask people "Where did you hear this?" or "Do you believe this source (peer-reviewed) more than this (non-reviewed)?" The results of such surveys would just give you some statistics about what people believe more, not what is the actual influence of different information sources. I mean, how reliable would be the results of such surveys for you?

@Jan Yes I agree survey data would need to be collected on what people believe, if that's the best way (maybe this information can be garnered by how people vote on certain issues, or on what they buy, etc...). But then these results can be compared to what types of sites are shared on these people's social media accounts. Or something like that. I'm not sure the best way to figure this out, but I would think there should be a way to get a better idea of what the sharing of non peer reviewed sites has done for belief in science or not.

@Jan Maybe there could be a study showing that with the advent of social media in general, belief in pseudoscience has increased. Has the internet made people more informed or more misinformed? Many such questions to ask. I don't really know the answers.


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Why do our brains act in such a evil way sometimes that hurts other people?
I have seen some real evil acts. And I almost lost confidence in humanity.
Why do we become so evil sometimes that hurts other people?
I guess everybody knows the Renaissance novel Les Miserables by Victor Hugo. There in the story, it is depicted how a person from the lowest echelon of the society stole a loaf of bread because his sister's child was hungry and how he was punished for years in hard labor during the industrial revolution.
So evil or injustice reveals itself such sometimes that we are compelled to question why? Why do we have to be so evil when we have this beautiful world just in front of us? Is it because of how our brain chemicals perceive things sometimes?
If a person is envious or jealous or has unjust anger and an MRI could be done right at that instance, would it show why we are evil?

This sounds to me, more like a philosophical, rather than a scientific question. There's no way to quantify Good and evil, and therefore a Good vs Evil person. It's something I Believe Nietzsche covers in his book, "Beyond Good And Evil".

Related: https://psychology.stackexchange.com/q/15610 plus https://psychology.stackexchange.com/q/17650 and https://psychology.stackexchange.com/a/19866

MVR there are many hormones within us that motivate behaviours that served a purpose in previous (phylogenetic) environments that in our modern society may appear to be evil.
Oxytocin for example (the so called love hormone) spikes before conflict, and one of the biggest dopamine hits we can ever experience is by punishing someone.
Sapolsky 2017 - Behave: The Biology of Humans at Our Best and Worst

There's also the work done by psychiatrist Daniel Amen. In his Ted talk [on YouTube] he describes having done about 80000 brain scans. He seriously puts forward the idea that criminality in many cases could be fixed by a brain scan, finding an abnormal growth, and removing or reducing it. He says that all his scans have let him to the opinion that the prison system should do such an assessment of the brain.

Do you have any references to reputable articles covering this?

Not offhand. But his Wikipedia entry does have a list of his publications.