# Question
Title: How does one validate a psychometric instrument
Any science has to be built on the scientific method. While in all fields there are novel phenomena that are not yet understood, an essential step to doing robust science is understanding how one's instruments work, before using them to measure something more complicated.

For example, in physics, we might not yet know what is a Higgs boson, but we understand exactly how magnets and light detectors work. When we make an experiment and gather data, we can select the simplest model which explains all of the observed data, except for the error introduced by those magnets and light detectors, which can be precisely estimated.

Or, for example, in neuroscience, we still have very limited understanding how hippocampal ripples give rise to memory consolidation and what that even means, but the electrophysiological and optogenetic instruments are quite precise, we already sort of understand how single neurons work, and are continuing to iteratively improve instrumentation until we can record a sufficient amount of information from a brain area to fully be able to model what is happening inside of it.

I am trying to understand, where does psychometrics land in this regard. From what I have read, psychometricians use questionnaires as their instruments. I would like to know, how do psychometricians learn what exactly their instrument measure, and how do they estimate the accuracy of the instruments. Here are some naive questions from the top of my head

1. Let's say I want to construct a question that measures whether a person is depressive. Sure, questions like "are you sad often" or "do you find it hard to get out of bed in the morning" sound plausible to me, but how do I test that they measure what I want? How do I even decide what exactly I want to measure? The definition of depression in DCM5 is a bit imprecise...
2. Let's say I know that my question measures depressiveness, but it also is influenced by a whole bunch of other stuff: Is the person honest; Are they generally an optimistic or pessimistic person; What mood are they in today; Do they understand the question; etc. How can I control for these confounds? How can I estimate the uncertainty in my instrument, in order to have an informed decision about the performance of a model I want to fit?
3. Let's say I have gathered a few questions that all measure depressiveness, and have some known uncertainty. I would proceed to fit some model in order to estimate depressiveness. I have heard that common models in modern psychometrics are Rasch models and their extensions. As far as I understand, these models assume that the uncertainty in the questions is caused by random noise, which is independent across questions. I am interested to know whether and how this assumption is typically justified. Naively, I would say that there is no randomness in this process - if asked the same question twice, most people would likely answer the same, if they have the minimal incentive to be honest and precise. Thus, any uncertainty is due to uncontrolled confounding factors. It is certainly plausible that a single confounding factor would affect multiple questions simultaneously. For example, a pessimist would likely write lower numbers for most questions even if they are perfectly healthy. Such confounding would result in correlated noise, and could significantly bias inference. How is this controlled for?

# Answer
I'm not a psychometrician but I use these tools and have some familiarity with the topic so I thought I'd offer some brief thoughts.

**How does one validate a psychometric instrument?**

There are a few steps and this list isn't exhaustive:

* Conceptualise and clearly define a construct (not done particularly well in depression, which has changed definitions over time)
* Develop questions/statements that can adequately identify the construct (see Eiko Fried's paper in my comment on the poor overlap between seven commonly used depression rating scales)
* Establish norms and appropriate cut-offs (for depression, ensuring your criteria do not inappropriately diagnose normal sadness or neurotic/pessimistic dimensions of personality as depression)
* Assess reliability between the individual items/questions (are the questions internally consistent?)
* Assess construct validity (does your instrument correspond to similar instruments that have already been validated?)
* Assess criterion validity (does your instrument correspond to the 'gold standard' for diagnosis?)
* Assess test-retest reliability (does it measure the same thing over time?)
* Use factor analysis to understand if there may be subtypes or dimensions to the construct

Depression, as it's defined in the DSM-5-TR and the ICD-11 (the two most commonly used diagnostic manuals) has modest inter-rater reliability and fairly poor validity, in part because we don't have a robust theoretic model of depression, have no objective tests to identify the presence or absence of depression, and have significant methodological limitations affecting the instruments we use to measure depression (highlighted in your question). Currently, the 'gold standard' by which questionnaires are compared to is the opinion of a psychiatrist, which is subjective and prone to substantial noise.

I don't have good answers to many of the important questions you ask. I hope someone with specific psychometric experience will. I also hope that over time, with respect to depression symptom measurement, we'll move from discrete time point assessment of symptoms (e.g. you visit your doctor and see them again one month later) to ecological momentary assessment, involving multiple repeated measures of mood and behaviour from the same person in real-time to obtain a richer understanding of the emergence of trends and establishment of each individual's baseline.
> 1 votes

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Tags: measurement, survey
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# Question
Title: Can neurons belong to multiple communities?
I've been reading a little about neural networks in the brain, such as this paper.

Most models have a resolution parameter $γ$, and for each value of that parameter a network can be partitioned into communities. Let's say that high values correspond to smaller communities that are more highly correlated, while smaller values allow for larger and less correlated communities.

However, suppose that a group of neurons was a member of several communities. These communities would have a non-empty intersection that is highly correlated (we see it for high values of $γ$), but for lower values of $γ$ we would instead see two separate communities that are similarly correlated with the intersection but less correlated with each other (thus they aren't all a part of one big community).

As we reduce $\gamma$ further, we would still see both of these communities eventually merge into the union of all of them, so this split would only exist in a specific range.

The situation doesn't sound impossible, but neurons are always partitioned when talking about communities as far as I can tell, at least at specific resolutions. Is there a biological or other reason?

# Answer
*Community* means many different things; the answer depends on which of these you're talking about. Community often refers to the graph theory principle community structure, which often *but not always* involves partitioning nodes into discrete communities. Most of these methods do not allow for overlap, but some do; there's nothing in principle against it, these are all analysis techniques so you use or design the technique according to your goals.

"Community" can also refer to abstract measures of weighted graph organization; this sort of community does not actually involve any partitioning or defining community membership per se. For example, one might talk of "small worldedness" which is a feature of graphs where nodes are strongly connected locally but also have a short path between non-local nodes through hubs (nodes with high degree).

There's also the sense of community in terms of groups of neurons co-activated in response to a stimulus or in recollection of a memory. Usually the term used there is "ensemble" rather than "community". Many different ensembles can exist in an overlapping population; a single example . Some examples:

Wilson, M. A., & McNaughton, B. L. (1994). Reactivation of hippocampal ensemble memories during sleep. Science, 265(5172), 676-679.

Bathellier, B., Ushakova, L., & Rumpel, S. (2012). Discrete neocortical dynamics predict behavioral categorization of sounds. Neuron, 76(2), 435-449.

Harris, K. D. (2005). Neural signatures of cell assembly organization. Nature reviews neuroscience, 6(5), 399-407. (In this paper, Harris calls an ensemble an "assembly")
> 1 votes

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Tags: neuroscience, neural-network
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# Question
Title: What are examples of evolutionary benefits of the sharing motive in Tomasello's theory on the origin of human communication?
In "Origins of human communication" (self described by the author as "an empirically based theory of the evolutionary origins of human communication that challenges the dominant Chomskian view" by a "leading expert on evolution and communication"), Tomasello distinguishes 3 motives for communication:

1. requesting,
2. informing and
3. sharing.

What would be examples of communication only involving the sharing motive and what evolutionary benefits would this give to individuals or groups that engage in it?

Is there any work that expands on this question? Tomasello himself does not answer the question, or I didn't get his point.

# Answer
I find it hard to imagine an example of communication which does not "inform", and from the abstract of the book, I am not sure that Tomasello opposes those three purposes in general, and the purposes of "informing" and "sharing" in particular (but I could not access the book to check its text):

> Requesting help in the immediate you-and-me and here-and-now, for example, required very little grammar, but informing and sharing required increasingly complex grammatical devices.

Examples of communication which are informing and sharing (without requesting) are easy to imagine, such as sharing/informing of a danger or of the location of a source of food.
> 0 votes

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Tags: communication, evolutionary-psychology
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title: Pyramidial vs Motor vs Interneurons

text:
# Question
Title: Pyramidial vs Motor vs Interneurons
According to Wikipedia...

> Interneurons are neurons that connect to brain regions, i.e. not direct motor neurons or sensory neurons.

And..

> Approximately 20–30% of the neurons in the neocortex are interneurons, while the remaining neurons are pyramidal neurons.

Is it saying that (A) an interneuron is ANY neuron that is not a motor or a sensory neuron? Or is it just saying that (B) interneurons CONNECT TO neurons that are not motor or sensory neurons(hence saying there are neurons in between that are not inter, motor, or sensory)?

If (A) is correct, the second quote implies that (C) 70-80% of neurons in the neocortex are motor neurons since pyramidal neurons are multipolar and sensory neurons are not multipolar.

So is (C) correct? And are all motor neurons pyramidal?

Also, are there pyramidal neurons that are not motor neurons(perhaps there are pyramidal neurons in other parts of the brain like the hippocampus that are not motor neurons)? Or is (B) correct and are there pyramidal neurons in the neocortex that are not motor neurons?

# Answer
Ah... nevermind. It seems that the two paragraphs from Wikipedia are using "interneurons" in two different ways. First meaning all neurons that are not motor or sensory. The second meaning inhibitory interneurons. So (A) would be correct, and pyramidal neurons are either motor neurons or interneurons in the first sense, while inhibitory neurons are not pyramidal.
> 1 votes

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Tags: neuroscience
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# Question
Title: Do stimulants increase the IQ tests score for everyone?
There is some meta-analytic evidence that stimulants increase the IQ test scores of ADHD children by 2 to 7 points (Jepsen et al., 2009). Although giving stimulants to non-ADHD children may be unethical, I'm still wondering if there is improvement in IQ test score in children (or adults) who do not meet the criteria for an ADHD diagnosis. An additional motivation for asking this is that a study by Tsai et al. (2013) found that the IQ test score improvement from methylphenidate "had no correlation with the decrement of ADHD symptoms."

<sub> Jepsen, J. R. M., Fagerlund, B., & Mortensen, E. L. (2009). Do attention deficits influence IQ assessment in children and adolescents with ADHD?. Journal of Attention Disorders, 12(6), 551-562.
Tsai, C. S., Huang, Y. S., Wu, C. L., Hwang, F. M., Young, K. B., Tsai, M. H., & Chu, S. M. (2013). Long-term effects of stimulants on neurocognitive performance of Taiwanese children with attention-deficit/hyperactivity disorder. BMC psychiatry, 13(1), 330. </sub>

# Answer
IQ in ADHD sufferers indeed increases with the treatment of stimulants, such as methylphenidate (Meyes *et al*., 1994). This is thought to rely on the attention-narrowing effect of stimulants, *i.e.*, they cause the easily distracted ADHD child to focus better on the IQ task (Aman, 1996).

It is an interesting question indeed whether such an effect also plays a role in healthy controls. Indeed it does, at least according to one study, where a control population was subjected to amphetamine.

* Amphetamine improves performance on **spatial working memory**, **Stroop tasks** and enhances **language production** (Barch & Carter, 2005). The authors did, however, not measure performance on full blown IQ tests.

<sub>**References**
**-** Aman, *J Development Phys Disabil* (1996); **8**(4): 347-65
**-** Barch & Karter, *Schizophrenia Res* (2005); **77**(1): 43-58
**-** Meyes *et al*., *DMCN* (1994); **36**(12): 1099–107</sub>
> 8 votes

# Answer
Not about IQ as a whole alas, but I found a 2010 systematic review & meta-analysis "Modafinil and methylphenidate for neuroenhancement in healthy individuals: A systematic review", apparently the only systematic one to date on methylphenidate in healthy subjects:

> The term neuroenhancement refers to improvement in the cognitive, emotional and motivational functions of healthy individuals through, inter alia, the use of drugs. Of known interventions, psychopharmacology provides readily available options, such as methylphenidate and modafinil. Both drugs are presumed to be in widespread use as cognitive enhancers for non-medical reasons. Based on a systematic review and meta-analysis we show that expectations regarding the effectiveness of these drugs exceed their actual effects, as has been demonstrated in single- or double-blind randomised controlled trials. Only studies with sufficient extractable data were included in the statistical analyses. **For methylphenidate an improvement of memory was found, but no consistent evidence for other enhancing effects was uncovered.** Modafinil on the other hand, was found to improve attention for well-rested individuals, while maintaining wakefulness, memory and executive functions to a significantly higher degree in sleep deprived individuals than did a placebo. However, repeated doses of modafinil were unable to prevent deterioration of cognitive performance over a longer period of sleep deprivation though maintaining wakefulness and possibly even inducing overconfidence in a person's own cognitive performance.

Somewhat similarly, there's another more recent (2014) review of methylphenidate "Cognitive effects of methylphenidate in healthy volunteers: a review of single dose studies" (MPH), but its methodology is limited to "effective study percentage" (i.e. not fully meta-analytical):

> The studies reviewed here show that single doses of MPH improve cognitive performance in the healthy population in the domains of working memory (65% of included studies) and speed of processing (48%), and to a lesser extent may also improve verbal learning and memory (31%), attention and vigilance (29%) and reasoning and problem solving (18%), but does not have an effect on visual learning and memory. MPH effects are dose-dependent and the dose–response relationship differs between cognitive domains. MPH use is associated with side effects and other adverse consequences, such as potential abuse. Future studies should focus on MPH specifically to adequately asses its benefits in relation to the risks specific to this drug.

If one is willing to consider modafinil in this class of drugs (some have labelled it "atypical DAT-inhibitor"), then there's a newer 2015 review "Modafinil for cognitive neuroenhancement in healthy non-sleep-deprived subjects: A systematic review":

> We found that whilst most studies employing basic testing paradigms show that modafinil intake enhances executive function, only half show improvements in attention and learning and memory, and a few even report impairments in divergent creative thinking. In contrast, when more complex assessments are used, modafinil appears to consistently engender enhancement of attention, executive functions, and learning.

All reviews primarily point to memory effects (in the short term, laboratory tests), although the last review (modafinil-only) has more mixed results in that regard. The other potential effects of MPH on IQ like speed of processing, are less convincing.

Although I was asking about IQ here, the long-term effects analyzed in the second review raise interesting questions about the mediating mechanism for the broader enhancement effects like learning (these "neuroenhancers" being popular as "study drugs"). There's a different line of research indicating that stimulants may affect motivation even more than mere cognition, even for "healthy" individuals, although apparently only in some sub-groups... which raises other interesting questions (sub-clinical attention problems, personality factors, etc.)

Actually, the authors is this last line of research have conducted their own (2015) meta-analysis of MPH and amphetamine: "Prescription Stimulants' Effects on Healthy Inhibitory Control, Working Memory, and Episodic Memory: A Meta-analysis.":

> The present meta-analysis was conducted to estimate the magnitude of the effects of methylphenidate and amphetamine on cognitive functions central to academic and occupational functioning, including inhibitory control, working memory, short-term episodic memory, and delayed episodic memory. In addition, we examined the evidence for publication bias. Forty-eight studies (total of 1,409 participants) were included in the analyses. **We found evidence for small but significant stimulant enhancement effects on inhibitory control and short-term episodic memory. Small effects on working memory reached significance, based on one of our two analytical approaches. Effects on delayed episodic memory were medium in size. However, because the effects on long-term and working memory were qualified by evidence for publication bias, we conclude that the effect of amphetamine and methylphenidate on the examined facets of healthy cognition is probably modest overall.** In some situations, a small advantage may be valuable, although it is also possible that healthy users resort to stimulants to enhance their energy and motivation more than their cognition.

Its results are mostly in line with previous conclusions (memory being the main aspect improved), however it emphasized that effect size is small (for short-term effects), and it also found publication bias for long-term effects.

After writing that, I found another 2015 review which mostly summarizes what I said by going over those meta-analyses, but emphasizes memory effects and doesn't dig much the motivation explanation.

Finally, I found a 2017 RCT on chess performance (which is reasonably correlated with IQ, at least for non-top players) and psychostimulants. The results of this study are not straightforward:

> This study investigated whether performance in chess – a competitive mind game requiring highly complex cognitive skills – can be enhanced by methylphenidate, modafinil or caffeine. In a phase IV, randomized, double-blind, placebo-controlled trial, 39 male chess players received 2×200 mg modafinil, 2×20 mg methylphenidate, and 2×200 mg caffeine or placebo in a 4×4 crossover design. They played twenty 15-minute games during two sessions against a chess program (Fritz 12; adapted to players’ strength) and completed several neuropsychological tests. Marked substance effects were observed since all three substances significantly increased average reflection time per game compared to placebo resulting in a significantly increased number of games lost on time with all three treatments. Treatment effects on chess performance were not seen if all games (n=3059) were analysed. Only when controlling for game duration as well as when excluding those games lost on time, both modafinil and methylphenidate enhanced chess performance as demonstrated by significantly higher scores in the remaining 2876 games compared to placebo. In conjunction with results from neuropsychological testing we conclude that **modifying effects of stimulants on complex cognitive tasks may in particular result from more reflective decision making processes. When not under time pressure, such effects may result in enhanced performance. Yet, under time constraints more reflective decision making may not improve or even have detrimental effects on complex task performance.**

Quite an interesting conclusion: to me it suggests that modafinil and MPH enhance exploitation rather than exploration.
> 4 votes

# Answer
The study you mentioned that didn’t find a correlation bw improvement in ADHD symptoms and improvement in IQ. BUT they took children off their medication for one week prior to testing them the second time. It’s like suggesting that glasses don’t improve vision after taking somebody’s glasses away. Since they were actually looking to see the impact of long term medication treatment on neurocognitive functioning, this can be somewhat justified by the idea of wanting to see if the brain itself was normalizing/improving. However, it does not allow for the conclusion that there wasn’t a correlation between performance on an IQ test and improvement of ADHD symptoms from medication treatment, since it can be presumed that MOST of the positive impact is related to actively being on the medication. The way the study was presented is deeply concerning, because the fact that children were taken off medication for the second test was really not emphasized up front. I think the assumption is that medication does not cure ADHD, it treats the symptoms while you’re taking it. I imagine that the improvements in ADHD symptoms would have all but disappeared during the week they weren’t taking their medication - when they were tested.
> -1 votes

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Tags: cognitive-neuroscience, intelligence, psychopharmacology, adhd, cognitive-enhancement
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# Question
Title: What is the name of the effect whereby learning past a level increases mastery of that level?
A post in Professor Doom's blog contains the following exchange:

> Pitchman: “What we know for sure is, the students who score high enough for College Algebra usually took courses past College Algebra in high school. The students who don’t quite make it into College Algebra took it in high school, and so on down the line.”
>
> Faculty: “Wait a minute. You mean there’s hard evidence for what we know to be true: that to achieve a goal in learning, you must push past that goal to succeed? Why haven’t these results been published?”

The general idea seems to me to be that if one wants to increase one's comfort with problems at a particular difficulty level, then one should do problems beyond that difficulty level.

Is there a name for this effect? And if so, what are the key findings?

# Answer
I found a paper that contains a graph that shows the loss of algebra knowledge over time:

For those who took courses beyond calculus, the drop was neglible over 50 years.
For those who took only calculus, their knowledge dropped from 90% to 75% over 50 years.
For those who didn't take calculus, their knowledge of algebra dropped below 50% after 50 years.

# Abstract

An analysis of life span memory identifies those variables that affect losses in recall and recognition of the content of high school algebra and geometry courses. Even in the absence of further rehearsal activities, **individuals who take college-level mathematics courses at or above the level of calculus have minimal losses of high school algebra for half a century. Individuals who performed equally well in the high school course but took no college math courses reduce performance to near-chance levels during the same period.** In contrast, the best predictors of test performance (e.g., SAT scores, grades) have trivial effects on the rate of performance decline.

### Citation

Bahrick, H. P., & Hall, L. K. (1991). Lifetime maintenance of high school mathematics content. Journal of Experimental Psychology: General, 120(1), 20–33. https://doi.org/10.1037/0096-3445.120.1.20

Relevant post by Bryan Caplan: https://www.econlib.org/archives/2012/10/does\_high\_schoo.html
> 2 votes

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Tags: educational-psychology
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# Question
Title: Research and theories related to the physical form of Cognitive Fallacies
Is there any research about what physically happens inside our brain anatomically and neurologically when we humans commit cognitive fallacies (especially those fallacies documented in the book of **Thinking Fast and Slow** by *Daniel Kahneman*, the behavioural economics nobel prize winner)?

An example is the subjects when given two options of *(a) terrorism by Muslims* **and** *(b) terrorism by all ethnics*, they ended up assigning higher probability of occurence to (a) than to (b).

This is because (a) feels more sensational to us due to past events and news, but it is a complete bug of our brain because **(b) as a broader case is surely more likely than (a).**

I want to know at physics level and anatomical level what is actually happening with the "circuits" inside our brains (in hope that by studying the physical form of cognitive fallacies we might able to come out with biotech or neurotech that could eradicate such fallacies).

# Answer
This schematic broadly outlines the control processes involved in decision-making, relating to structures of the prefrontal cortex (PFC).

The bias you're referring to is an availability bias. I'm not familiar with fMRI studies investigating the neural substrates of this bias. However, Molenberghs & Louis found the dorsal anterior cingulate cortex, anterior insula, medial PFC, and lateral orbitofrontal cortex play some role in ingroup bias (related to myside bias).

Many of these biases are adaptive and I doubt there is some easily identiable reductive mechanism to be altered (see the diagram below from a recent Nature Neuroscience paper for what I mean by a reductive mechanism).
> 1 votes

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Tags: neuroscience, cognitive-neuroscience, neuroanatomy, psychophysics, behavioral-economics
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# Question
Title: Is it possible to transmit various signal through single nerve fiber?
Imagine a lot of touching, temperature, pain spreading every where on the skin. if every sensory neural required isolated channel it might difficult to repair damaged neural because every neural must reconnect to where it belong. However, if neural act like signal cable. So each neural encode it position to the signal so it can be decoded later. It should be efficient and robust that way. If such a mechanism exist please explain how it works.

# Answer
> 1 votes
No, peripheral nerve fibers transmit just from the receptor they connect to. There is a lot of information to transmit in each of those channels: the firing rate and/or timing of action potentials constantly communicates the state of that receptor, active or not both are informative.

Yes, this means it's difficult to repair neural damage. Think about people with spinal cord injuries that have permanent loss of sensation and/or motor control.

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Tags: nervous-systems
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# Question
Title: Is there any neuroscience research on the emotion of feeling nothing?
When people entering anechoic chambers, logically there is a sensation of silence because relatively speaking, the sound levels are much lower compared to some normal baseline

Likewise, when there is emotional numbness there isn't a feeling of emotions nor there is an awareness that there isn't a feeling of emotion and the person will struggle to describe or comprehend emotion adjectives

Also for some people in anesthetics, they shared about what it is like to feel the consciousness is fading

All of these caused me to become curious on what the literature know about the neuroscience such as brain activity when subjects experience these feelings like feeling numb, feeling empty, feeling consciousness is fading, or all at the same time. Unfortunately neither my neuroscience professors are aware of something similar in the literature, nor intense googling on google scholar found any brain activity studies when people felt numb or something stronger

> What is the technical name for all these seemly neutral emotions and (lack of) sensations?
>
> Any known famous papers or literature that study the neuroactivity when subjects are experiencing these emotions?

# Answer
> 0 votes
Any question about neuroactivity (e.g., changes in firing rates) requires a comparison between two brain states. What would you compare with the absence of something? The question mentioned several states that I assume are qualitatively different. One way to investigate the original question would be to contrast such states with each other. Other low-emotion states could be found in the control condition of many existing studies.

I suggest you look into the default mode network and sleepiness as low-emotion states that have been widely investigated as neural activity.

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Tags: cognitive-neuroscience, emotion, sensation
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# Question
Title: To what degree are discussions and concepts within philosophy of mind relevant in the field of neuroscience?
> Philosophy of mind is a branch of philosophy that deals with the nature of the mind and its relation to the body and the external world.
>
> The mind–body problem is a paradigmatic issue in philosophy of mind, although a number of other issues are addressed, such as the hard problem of consciousness and the nature of particular mental states. Aspects of the mind that are studied include mental events, mental functions, mental properties, consciousness and its neural correlates, the ontology of the mind, the nature of cognition and of thought, and the relationship of the mind to the body.
>
> (source: Philosophy of mind | Wikipedia)

Relevant topics discussed in philosophy of mind include:

Does the field of neuroscience acknowledge any of these and related discussions in philosophy of mind as legitimate issues and topics of inquiry? For instance, does neuroscience recognize the *hard problem of consciousness* as a genuine issue?

Additionally, does the field of neuroscience adopt any philosophical assumptions? For example, is reductive materialism assumed *a priori* to be the case in neuroscience research?

# Answer
> 2 votes
Philosophy of mind and neuroscience are both very broad fields, and their overlap is extensive. This overlap can to a degree be characterized as "neurophilosophy":

> ... the interdisciplinary study of neuroscience and philosophy that explores the relevance of neuroscientific studies to the arguments traditionally categorized as philosophy of mind.

I think a great example of such interdisciplinary study is the neuroscience of free will:

> ... a part of neurophilosophy ... the analysis of how findings from \[neuroscience\] studies may impact the free will debate.

Beginning in the 1980s with the well-known Benjamin Libet experiments, neuroscience has had much to say about free will. The hard problem of consciousness is a more complicated example:

> It has been accepted by some ... cognitive neuroscientists such as Francisco Varela, Giulio Tononi, and Christof Koch. On the other hand, its existence is denied by other ... cognitive neuroscientists such as Stanislas Dehaene, Bernard Baars, Anil Seth, and Antonio Damasio.

The typical neuroscience approach to the hard problem has been through neural correlates of consciousness (NCC):

> A science of consciousness must explain the exact relationship between subjective mental states and brain states, the nature of the relationship between the conscious mind and the electro-chemical interactions in the body (mind–body problem). Progress in neuropsychology and neurophilosophy has come from focusing on the body rather than the mind.

Both neuroscientists who accept and deny the hard problem see NCC as a way forward, and this has been a very active area of research. Note that there are other scientific approaches to the hard problem outside of neuroscience, such as in AI.

Since there isn't agreement about the hard problem amongst neuroscientists, I think it's fair to say that neuroscience does not assume materialism (certainly not the reductive or "type" kind). More generally, there are several competing claims regarding what assumptions (if any) underlie scientific research, such as naturalism, causal closure, coherentism, or even none at all. The matter is not settled.

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Tags: neuroscience, philosophy-of-mind
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# Question
Title: Why can't MEG distinguish EPSPs and IPSPs?
I see this fact stated in many places that discuss the basis of the MEG signal but it's never been made completely clear *why* MEG can't distinguish IPSPs and EPSPs. Please could someone elaborate?

Thanks

# Answer
Two reasons:

First, currents create a magnetic signal that is measured by MEG; from the perspective of the MEG, there isn't any meaning to whether ions are moving into cells or out of them, or whether the ions moving are positive or negative, just that there is some net charge moving a particular direction. Same for EEG. If you can connect a particular waveform to a particular event in the brain through other means, though, you may be able to infer that a given signal is primarily excitatory or inhibitory, but not directly from MEG itself. The Wikipedia article on MEG talks a bit about how this all works and how some level of synchrony is necessary for MEG to work: https://en.wikipedia.org/wiki/Magnetoencephalography Mostly, it works because of the orientation of neurons and flow within dendrites rather than across membranes. Here's a paint-quality diagram:

On the left, positive ions enter a dendrite (black arrows). This causes a net positive flow down the dendrite (red solid arrow). On the right, negative ions enter a dendrite somewhere else (black arrows). This causes a net positive flow in the same direction. MEG is measuring synchronous red solid arrow current flow over many many of these parallel dendrites.

Second, most IPSPs in the brain are shunting inhibition; they don't create much net current or voltage change at all, rather they help to maintain membrane potential near the chloride reversal which is near a typical rest potential.

In any event, the things that MEG or EEG measure are typically rhythmic brain activity, and we know this sort of activity results from a combination of inhibition and excitation anyways. So, while it's true that one can't directly measure EPSPs or IPSPs, that's not at all what these techniques measure. It's sort of like saying that a scale can't tell you how tall you are.
> 0 votes

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Tags: neurophysiology, eeg, meg
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# Question
Title: Can schizoaffective disorder be present with no negative symptomatology
In addition to delusions and hallucinations, schizoaffective disorder involves mood alterations.

Is the presence of negative symptomatology necessary for diagnosing schizoaffective disorder, or is mood alteration sufficient if delusions are present?

# Answer
> 0 votes
According to the DSM-5, negative symptoms is not a diagnostic requisite for schizoaffective disorder. Negative symptomology is included as a specifier only if the patient presents with these symptoms. Further, it is important to note that delusions and mood alterations are not the only diagnostic criteria for this disorder. Patients must meet Criterion A for Schizophrenia that occurs concurrently with a major mood episode (must include depressive and may or may not include manic); and at least 2 weeks of delusions or hallucinations without the presence of a mood episode. Also, symptomatic etiology must not be the result of a substance-induced disorder. Regarding specifiers, clients may present with either Biopolar or depressive type, and may include catatonia. Negative symptoms are remarked in the "Severity specifier" section if present and its severity is rated on a scale of 0 - 4.

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Tags: personality-disorder, schizophrenia
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# Question
Title: ADHD Symptoms Emerging in Adolescence or Young Adulthood
I recently read a fascinating article about the pattern of young women receiving ADHD diagnoses after first displaying symptoms in their late teens or early twenties, typically corresponding to college and post-college years. While very interesting, it was written from an informal, personal perspective. I'd like to know more about the subject from a research perspective.

Has there been much research regarding gender differences in ADHD, specifically about different presentation and age of onset? Within this subject, has there been any research into the effects of estradiol levels on ADHD-like symptoms? I know that consensus is not very common in the research community, especially with a diagnosis as controvertial as ADHD, but I would still like to know whether late-onset in young women is at all commonly accepted.

# Answer
A quick Google Scholar search revealed the following primary article and 2 meta-analytical reviews.

**Primary Article**

Arcia, E., & Conners, C. K. (1998). Gender differences in ADHD? *Journal of Developmental and Behavioral Pediatrics, 19*(2), 77–83. https://doi.org/10.1097/00004703-199804000-00002

Abstract:

> Examined possible gender differences in children and adults (aged 5–60 yrs) with attention deficit hyperactivity disorder (ADHD). Results indicated that adult self-ratings differed significantly by gender. Adult women reported fewer assets and more problems than did male counterparts, but there was no gender difference with respect to age at referral, intelligence quotient, indicators of neuropsychological performance, or parent or teacher ratings of behavior. Referral bias against girls is a possible reason for previously reported gender differences, so the authors interpreted their results in light of the participants' referral patterns. There was a nonsignificant trend for girls with relatively more severe ratings of hyperactivity, conduct disorder, or inattention to be referred earlier than boys. Overall, results suggest no evidence of cognitive or neuropsychological differences by gender in samples that are sensitive to behavioral deviance in girls (as evidenced by early referral), but adult women's self-perception is comparatively poorer than that of adult men.

**1997 Meta-Analysis**

Gaub, M., & Carlson, C. L. (1997). Gender differences in ADHD: A meta-analysis and critical review. *Journal of the American Academy of Child & Adolescent Psychiatry, 36*(8), 1036-1045. https://doi.org/10.1097/00004583-199708000-00011

Abstract:

> Objective
>
> To quantitatively review and critically evaluate literature examining gender differences in attention-deficit hyperactivity disorder (ADHD).
>
> Method
>
> A meta-analysis of relevant research based on 18 studies meeting inclusion criteria was performed. Domains evaluated included primary symptomatology, intellectual and academic functioning, comorbid behavior problems, social behavior, and family variables.
>
> Results
>
> Gender differences were not found in impulsivity, academic performance, social functioning, fine motor skills, parental education, or parental depression. However, compared with ADHD boys, ADHD girls displayed greater intellectual impairment, lower levels of hyperactivity, and lower rates of other externalizing behaviors; it was not possible to evaluate the extent to which referral bias affected these findings. Some gender differences were clearly mediated by the effects of referral source; among children with ADHD identified from nonreferred populations, girls with ADHD displayed lower levels of inattention, internalizing behavior, and peer aggression than boys with ADHD, while girls and boys with ADHD identified from clinic-referred samples displayed similar levels of impairment on these variables.
>
> Conclusions
>
> The need for future research examining gender differences in ADHD is strongly indicated, with attention to methodological limitations of the current literature, including the potential confounding effects of referral bias, comorbidity, developmental patterns, diagnostic procedures, and rater source.

**2002 Meta-analysis**

Gershon, J., & Gershon, J. (2002). A meta-analytic review of gender differences in ADHD. *Journal of attention disorders, 5*(3), 143-154. https://doi.org/10.1177%2F108705470200500302

Abstract:

> The present study examined gender differences in ADHD through a meta-analysis. Effect size estimates for the primary symptoms and correlates of ADHD were calculated in an attempt to replicate and extend a previous meta-analysis on gender differences in the disorder. Relatively lenient inclusion criteria were used in order to maximize the number of studies included in the effect sizes.
>
> The results indicated that in comparison to ADHD boys, ADHD girls had lower ratings on hyperactivity, inattention, impulsivity, and externalizing problems. In addition, ADHD girls had greater intellectual impairments and more internalizing problems than ADHD boys. Overall, the results of the current meta-analysis indicated general agreement with the previous meta-analysis. The clinical implications of these gender differences and future research considerations are discussed.

There is also a **2014 review looking at the implications for psychosocial treatments**.

Rucklidge, J. J. (2008). Gender differences in ADHD: implications for psychosocial treatments. *Expert Review of Neurotherapeutics, 8*(4), 643-655. https://doi.org/10.1586/14737175.8.4.643

Abstract:

> Attention-deficit/hyperactivity disorder (ADHD) has now been recognized to exist in both males and females, albeit the literature supports a higher prevalence in males. However, when girls are diagnosed with ADHD, they are more often diagnosed as predominantly inattentive than boys with ADHD. This paper provides a review of gender differences noted across the lifespan in terms of psychosocial functioning, cognitive abilities and psychiatric comorbidities. Males and females with ADHD are more similar than different, and generally symptoms of ADHD are not sex specific. Small gender differences have been found: adolescent girls with ADHD have lower self-efficacy and poorer coping strategies than adolescent boys with ADHD, but these differences tend to disappear by adulthood; rates of depression and anxiety may be higher (especially in adolescence) while physical aggression and other externalizing behaviors may be lower in girls and women with ADHD, although not all studies support these findings (e.g., non-referred samples show similar rates of coexisting psychiatric disorders between boys and girls with ADHD). However, many studies suffer from small sample sizes, referral biases, differences in diagnostic procedures and possible rater influences. Psychosocial treatments are reviewed and discussed with reference to the reported gender differences in functioning as well as the global deficits noted in all samples. Although the data available so far suggest that psychosocial treatments are likely to be equally effective in males and females, this conclusion is based more on the small number of gender differences noted in overall functioning and less on empirical research on treatment by sex effects and the moderating role of sex, an effect only investigated by the Multi-modal Treatment Study of ADHD group, to date. Future research should include equal representation of both sexes in samples such that treatment analyses by gender can be routinely conducted.
> 1 votes

# Answer
According to the DSM-5, ADHD is more common in males than females (by a 2:1 ratio). It is suggested that gender and cultural differences, as well as adult biases toward stereotypically acceptable gender-role behaviors may be responsible for this difference in prevelence. Regarding onset, ADHD is a neurodevelopmental disorder and thus, symptoms should be noted before the age of 12 for an official diagnosis, with around 4-years-old being the most common age for symptom presentation. As such, clinicians typically seek outside sources to validate adult clients' narrative of having displayed symptoms during childhood, however, this is typically left up to the clinician to ultimately accept clients' autobiography. I have no knowledge of a correlation between ADHD and hormonal levels in female or male patients.
> 0 votes

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Tags: abnormal-psychology, developmental-psychology, adhd, gender
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title: How do I recognize a dog?

text:
# Question
Title: How do I recognize a dog?
I know, neurons take in data from the eyes and pass the data on through synapses to subsequent neurons and synaptic weights from many neurons pass into the subsequent neuron and the neuron adds up all synaptic weights in the axon hillock and if it is strong enough, it decides to send it to the next neuron through the axon terminal.

But if the neurons just keep adding up numbers and sending those numbers to the next neuron, how does the final neuron understand that the image is of a dog? The last neuron just gets a big number, the sum of all the previous neurons' values. It's just a number then, isn't it?

I've learnt about Hebbian learning and stuff, but because the same synapse can allow data about cats, dogs, rats, any other thing to pass through it, how does it realize which data is about a dog to strengthen the connection? It's just a number isn't it, the sum of all those neurons before it?

I am pretty new to this field, and I haven't studied this in school or anything, but I am a programmer and I thought of a pretty cool idea about AI to simulate the brain, so I've been buggin ChatGPT to explain how the brain works. I've got a pretty good idea right now, but I'm stuck on this point and I can't seem to make sense of it at all. Please help me out, thanks in advance.

PS: I don't even know what tags to apply here, sorry

# Answer
For the sake of viewing the brain from an analog computer typology, I will try not comment on the visual-perceptual and cognitive processes at play in our perception of recognizing a dog as a dog, which are of great interpretational significance by the way. However, while there is no easy answer to your question in its pure neurological form, Gestalt's top-down, bottom-up perceptual theory may be of most interest to you. According to Gestalt's theory, neuronal processing of stimuli does not occur concurrently with preconceived ideas of what we are being exposed to, neither do we take in every single characteristic of a dog. Rather we take in the most salient identifying features that have the most 'weight' which allows us to interpret what we are seeing - and discriminate between a dog and a cat at the neuronal level. From this view, all stimuli is data-driven based on the most salient features of incoming stimuli. Interestingly, from this data-driven approach we see that our brains make sense of little bits of incoming information and then fill in the rest based on our interpretation of the data (which is where higher-order cognitive, perceptual, and experiential processes come into play. Gestalt's top-down bottom-up theory is often illustrated by an abstract black and white painting of a dog (which is essentially a smattering of indistinct ink blots). At first glance, we see a dog running through the woods, however, when we take a closer look, huge chunks of the picture are missing and our brains merely fill in the missing data points because we initially received the portions of the picture that featured salient dog data. I am aware that this does not get down to the basic neuronal processes of ionic weight and action potentials; however, Gestalt's theory is a great place to start when examining perception from a data-driven framework.
> 1 votes

# Answer
To understand how we recognize a dog, we need to understand how neural networks work -- because image recognition is what neural networks do. So let's see how they do it.

Imagine you want to teach (to train) a neural network to tell whether there is a dog in a given picture, captcha style. Here is how you might go about it:

1. You show the network a picture, and let it guess if there is a dog in it.
2. Then you give it the correct answer, so it can learn from this experience.
3. Repeat the same the above steps a few million times.

At first, the network has no idea how a dog looks, so it will be guessing at random. But as it learns, it will start forming an singular idea of how-a-dog-looks-on-a-picture. Internally, this idea -- this statistical model -- is a collection of visual patterns that positively correlate with the presence of a dog. With each iteration, the neural network would refine this model, adding new patterns, or adjusting the weights of the existing ones. A few million pictures later, it would form a pretty good idea of how dog looks, and it would know it too (that is it also tracks the level of confidence in its ability to know the dog when it sees one).

And this is exactly what the neural networks in your subconscious mind do -- the learn ideas1 from experience, and they apply those ideas to *guess* what you are looking at (and how you should feel about it). The whole process -- the learning and the application of ideas -- happens automatically entirely under the radar of your conscious awareness. Only the bottom line is communicated up to your conscious mind -- and that's why it feels like a mystery or magic. You don't know how you know that you are looking at a dog, you just do.

1 English philosopher John Locke would refer to those as "simple" ideas -- as opposed to the "complex" ideas of our conscious mind.
> 0 votes

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Tags: neuroscience
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# Question
Title: What would be the evolutionary benefits of Hate?
From an Evolutionary Psychology perspective, what advantages would we get from being able to feel Hate towards another individual, thing, or event? Do we get a personal benefit of holding grudges, or perhaps the population does? This would be related to the question of "How long is it possible to hold grudges?". I haven't researched to what extent it is possible to pass on grudges to future generations, but, maybe, it is some sort of offshoot of passing knowledge from bad experiences?

# Answer
The primary evolutionary advantage of hate is self preservation. Typically, hate is experienced when the target stimulus (i.e., a person, season, ideology, thing, etc.) threatens one's fundamental existence or way of life, conflicts with core beliefs or cognitive schemas, threatens the exposure of weaknesses or defenses, or interferes with goal achievement. Hate is particularly beneficial from an evolutionary perspective because it establishes a long or short-term warning or avoidance against things that are not in themselves particularly threatening (i.e., a spouse, family member, child, etc.). For example, when a stimulus is threatening by nature (i.e., wasp, viper, a contagion, etc.) our evolutionary reaction is fear or disgust which increases our survival chance through fight, flight, or avoidance strategies. However, we are not designed to be threatened by certain things, such as humans, unless their immediate verbal/nonverbal behaviors are perceived as threatening. In this case, hate allows us to protect ourselves from things that do not present as existentially threatening but indeed can cause us psychological, emotional, social, or physical harm. It is worth noting that hate may be most useful for protecting ourselves from threatening information about ourselves, such as breaching our defenses.
> 1 votes

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Tags: evolutionary-psychology
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# Question
Title: Where is data on percentiles of the Big Five Inventory?
I have raw scores (e.g., sums of the relevant question scores for each measure) from the Big Five Inventory (BFI). I would like to convert these into percentiles for interpretation. Where are the data or norms located to accomplish this?

My previous searches have yielded this link: https://www.ocf.berkeley.edu/~johnlab/pdfs/BFI%20Comparison%20Samples%20%28Ages%2021%20-%2060%29.doc

This doesn't align with the scoring of the BFI, though. The scoring of the BFI will yield numbers like 28, not 2.5. Elsewhere, they "transformed the 1-to-5 BFI metric into POMP scores by subtracting 1 and multiplying by 25." It looks like the link gives the average response score, and doesn't use POMP, but the paper uses POMP.

# Answer
The Big Five Inventory is quantified by averaging the score of a dimension (sum of x divided by N). This average will produce a potential range of 1 to 5 for each dimension, with higher scores indicating greater possession of that trait. Quantification instructions and additional information on the BFI can be found in the article: John, O.P., & Srivistava, S. (1999). The Big Five trait taxonomy: History, measurement, and theoretical perspectives. In L.A. Pervin & O.P. John (Eds.), Handbook of Personailty:Theory and Research (pp.102-138). New York: Guilford.
> 0 votes

# Answer
The link you posted contains the only published norms for the BFI. This data is all you need to convert to percentiles and establish where you rank based on these norms. All you need to do is transform these averages - including yours - into percentiles. Note that there is a lot of data on the document so you need to choose your age group to analyze as this will give you the most relevant information. Also, make sure you use the averaged version of these scores, which may indeed be a number such as 2.5, 2.8 and so forth. You can get your percentiles by following these steps for your averaged scores and those in the document within your age group:

To convert the averaged BFI scores into percentiles you will have to (1) determine the frequency of each mean dimension score, (2) calculate the cumulative frequency for each mean score (3) and then convert each cumulative frequency into a percentage \[ c% = cf/N (100%) \]. While it is not essential, creating a cumulative frequency table will keeps things nice and in order. That is, you would create a column for averaged scores (x), a column for frequencies (f), one for cumulative frequencies (cf), and one for cumulative percentages (c%).

Once you have done this for each O.C.E.A.N. dimension, you can see where you rank based on your peers in the published data. Also, note that the document you have also contains the standard deviations for each dimension and age group so that will be useful to know as well. Does this answer your question? If not, let me know and I will see if there is anything else I can come up with. Thanks!
> 0 votes

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Tags: cognitive-psychology, measurement, personality, cognitive-modeling, big-five
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# Question
Title: Is usage of personal pronoun I/me/etc. when writing indicative of self-centeredness?
I have a tendency to use "I" a lot when I write. I think I do this for one of two reasons:

1. the explanation of whatever it is that I'm writing about is easier for me to communicate if I'm explaining it in a "story" mode (for better or for worse)
2. I'm self-centered, and I think everything is about me

In my job I have to write the occasional technical paper or ask the occasional Stack Overflow question, so -- needless to say -- I often have to go back over what I wrote and edit out the "story" part of it. Anyways, with the caveat that I've never taken a psychology course in my life, here's my question, along with a sub-question:

Is using "I" a lot when writing indicative of narcissism? (Maybe "narcissism" isn't the best word as it's loaded -- let's say "self-centeredness. Also, I'm not narcissistic IRL; I'd like to think I'm highly empathetic and compassionate.)

Or is using "I" a lot when writing just a tool that can be used to write more effectively? ("PB&J: First I cut two pieces of bread, then I put peanut butter on one side...")

This idea is starting to bug the heck out of me -- I'm starting to get neurotic about it.

**Is using "I" a lot when writing good/bad/indifferent?**

# Answer
While people with narcistic personalities (who make up less than 6% of the population - Diagnostic & Statistical Manual of Mental Disorders - 5) are self centered and may use "I statements", one's literary style of first-person prose use is not indicative of a narcistic trait or P.D., and given the salience of this literary style (used by more than 93% of the population - Reinhart's Handbook for Writers -7th ed.) this would not be considered within diagnostic criteria or be at all useful in case conceptualization. However, it may be useful to know that professionals suggest the use of first-person prose is so high across the amateur writing board because their writing is mainly introspective, or else they assert their thoughts as merely their opinions, which if anything, suggests they are reluctant to consider themselves as the sole authoritative source on the matter and leave room for others' opinion or correction.
> 1 votes

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Tags: self, writing
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# Question
Title: Is there a word for when thinking of other numbers interferes with working memory retention?
Is there a word for when thinking of other numbers interferes with working memory retention? So suppose you take the digit span test and it's 6178423 and you go to type out 61784 and then forget 23 because you have thought 6 and 7 and go with 6178467. So when completing an e.g. an IQ test your thinking slips to the wrong parts. I don't think it's just focus.

# Answer
**Retroactive Interference**

The scenario of thinking of the numbers 6 and 7 in an attempt to retain a string of digits and mistakenly retrieving the last two numbers as 6 and 7 during recall would be best described as retroactive interference, which is when earlier pieces of information held in working or short-term memory – which in this case would be the last two original digits 2 and 3 – are replaced with newer information (in this case, 6 and 7). While the term retroactive interference may seem to indicate that the last digits should have been the ones most easily recalled (i.e., most recent), the fact that 6 and 7 were being rehearsed makes them the most recent information and the most likely items to be accurately retrieved. As such, focusing on these specific numbers allowed for better encoding, storage, and accurate recall. Further, as 6 and 7 appeared at the beginning of the list, this would indicate that a primacy effect had occurred as the first digits in the serial list were encoded as opposed to the last digits – which would have indicated a recency effect – or the middle chunk.
> 0 votes

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Tags: working-memory
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# Question
Title: What are the effects of antipsychotic medication on brain volume?
I have read numerous different papers each claiming that antipsychotic medication either helps maintain brain volume or causes brain volume reduction in patients with schizophrenia and other psychotic psychiatric disorders. I have to admit that I am confused on this subject. What is the clinically accepted position on brain volume and antipsychotic medication?

# Answer
Yes, there are different results published because it is an open research question. It is a tricky question to figure out due to substantial confounding factors so some results might skew for and some against.

We know that brain volume changes due to natural reasons (age, lifestyle); different antipsychotics have different effects on different brain regions, and so does the illness and the duration of treatment. Usually, in a research study, you need to be able to control for all confounding factors to get (as much as you can) just the two variables you want: antipsychotic and brain volume. But it is challenging to do that in this case and so far, no one has been able to be conclusive about it.

Here's a systemic review of the papers that attempted to find the direction of effect and the answer is mixed results:

Psychological Medicine , Volume 40 , Issue 9 , September 2010 , pp. 1409 - 1422 DOI: https://doi.org/10.1017/S0033291709992297

and then a really nice letter in response that details some of the challenges that I mention above on why we do not know for sure (yet):

*VAN HAREN NEELTJE, KAHN RENÉ. Letter to the Editor: A comment on ‘A systematic review of the effects of antipsychotic drugs on brain volume’ by Moncrieff & Leo (). Psychological Medicine. 2010;40(12):2105-2107. doi:10.1017/S0033291710001686*
> 2 votes

# Answer
Dopamine availability can increase neurogenesis/neuroplasticity in adult brains. Antipsychotic medications, therefore, may have the opposite effect.

Borta, A., & Höglinger, G. U. (2007). Dopamine and adult neurogenesis. Journal of neurochemistry, 100(3), 587–595. https://doi.org/10.1111/j.1471-4159.2006.04241.x

Nitsche, M. A., Kuo, M. F., Grosch, J., Bergner, C., Monte-Silva, K., & Paulus, W. (2009). D1-receptor impact on neuroplasticity in humans. The Journal of neuroscience : the official journal of the Society for Neuroscience, 29(8), 2648–2653. https://doi.org/10.1523/JNEUROSCI.5366-08.2009
> 1 votes

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Tags: neurology, schizophrenia, neuroanatomy, brain-development
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title: Slow-wave EEG artifact removal

text:
# Question
Title: Slow-wave EEG artifact removal
If we want to study a sleep EEG signal in any way (e.g. compute its power spectrum), do we need to remove artifacts from the whole EEG signal, or do we simply need to extract those epochs that correspond to slow-wave sleep and remove artifacts from those?

In other words, can artifacts from regions of the EEG that are not slow-wave sleep have an effect on analyses carried out specifically on slow-wave regions?

I'd appreciate relevant sources. Thanks.

# Answer
It all depends:

* '*...do we need to remove artifacts from the whole EEG signal*' - yes you have to in case you are using the entire EEG trace for spectral analysis *and* if there are artifacts in the first place *and* if the artifacts share at least part of the frequency spectrum with your target band. In case you do not perform spectral analyses and/or you cut out regions of slow-wave sleep that are devoid of artifacts, and/or you use FFT and the artifact features frequencies outside the band of interest, you don't have to bother about artifacts whatsoever.
* '*...or do we simply need to extract those epochs that correspond to slow-wave sleep and remove artifacts from those*' - extracting relevant epochs increases the FFT power because there is less noise from wake EEG. And of course, if you throw away part of the data, you don't have to worry about artifacts in those ditched data, unless the artifacts swamp the EEG so much that slow-wave sleep isn't recognizable in the trace in the first place.
* *...can artifacts from regions of the EEG that are not slow-wave sleep have an effect on analyses carried out specifically on slow-wave regions*' - no, if you extract target epochs and throw away the raw signal outside those epochs, you obviously don't have to worry about the ditched data, but that raises the question why the artifacts would occur only outside your target areas (awake people indeed move more, causing movement artifacts).
> 2 votes

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Tags: neuroscience, eeg, signal-processing
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title: Mistake patterns while learning

text:
# Question
Title: Mistake patterns while learning
About a decade ago, I used to teach programming language in a company specialized in forming new developers. It was common for students to really struggle with very simple coding tasks due to really rookie mistakes unrelated to the technical subject that was being taught. The single most common rookie mistake was when the student simply forgot to save the file before running it. Everything was correct but they just did not hit the save button. And most of these times it required my assistance in solving. I noticed that even more experienced developers enrolled in the classes also made the exact same mistakes and even felt super embarrassed when I spotted the cause.

Today, while studying a new technology, I myself(a 14 years experienced software engineer that used to teach programming languages) made the exact same rookie mistake. It took me 20 minutes of debugging to find out I just forgot to hit the save button. On my day to day activities it does not happen, or if it does I spot it in seconds unless I'm really really tired.

What I mean is, hitting the save button (or cmd + s keyboard shortcut) has become second nature to me even so that sometimes a hit cmd + s on places I shouldn't like while browsing the web. Some devs even have the habit of hitting the button several times. It clearly seems like a second nature to me.

It made me wonder WHY does the human mind, when dealing with a new complex subject, keeps repeating the same mistake patterns unrelated to the matter being studied? Besides that, how does the fact of studying a new subject can affect your 'second nature'?

The human mind truly amazes me.

# Answer
> 0 votes
I think this is mostly a UI/UX problem.

Your brain has a model of the world that you update with new information (something like predictive coding). If nothing in front of you signals that something is unsaved, you can only know whether it has been or not if you have some episodic memory of the situation. Episodic memory is fragmented; we experience too much stuff to remember it all, so most of it is discarded. Events that are emotional or otherwise significant are more likely to be remembered. Pressing a save button, an activity you may do multiple times a day, just isn't that significant. You wouldn't remember where you were the last 10 times you scratched specifically your left eyebrow, either.

The conscious, intentional processing part of your brain is really only dedicated to a few small things that your brain is doing at a time, maybe even just one. You simply can't be attentive to everything your brain is doing at a given moment. It's constantly taking in and filtering information without your awareness. It's maintaining your posture so that you neither fall over in your chair nor have to constantly think "okay I'm leaning to the left a bit, better relax some back muscles and tighten some others". Think of an infant learning to eat: they have trouble even getting the food or utensil to their mouth because they're needing to actively modify the muscle patterns involved in that activity. Similarly, if you've learned to drive, you probably started out by needing to intentionally turn the steering wheel to keep your car within its lane and it would be hard to focus on other things besides staying in that lane, whereas an experienced driver does those tasks effortlessly and instead can focus on looking for unexpected events like a pedestrian moving into the road or participate in a conversation.

Over time, eating, driving, and writing computer code are managed by procedural memory that makes things more automatic. Procedural memory is associated more with the basal ganglia than the neocortex, though it's never quite that simple. Generally, once you learn to do things with procedural memory, those parts of the brain manage the task and the other parts of your brain involved in conscious attention and awareness tune out.

Back to perception and saving... in psychology and neuroscience we talk about the salience of a stimulus; salience is what makes us notice something important and ignore things that are unimportant. If the wrong things are salient, you might have trouble paying attention/focusing (ADHD), focus too much on a stimulus that shouldn't be important (sensory processing disorder/autism), or the brain may even focus on things that aren't really there (e.g., in schizophrenia). If there is nothing in the UI/UX to make it salient that a file is saved or not, there's nothing for your brain to act on. You could try to focus on that cue to make it more salient (sometimes the 'save' icon itself has a different appearance when something is saved versus not), but if you usually save more or less "automatically" as part of your procedural memory pattern for working at the computer, that attempt is usually going to be unneeded and so you won't really learn it.

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Tags: behavior, behavioural-neuroscience
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# Question
Title: Are there any standard tools for neuroscience models programming, like for spiking neural networks?
I come from deep learning environment and there is quite a few standard tools and frameworks that you can use in different occasions. I am trying to build a **spiking neural network** model in Python and I wonder if there are any standard frameworks and tools for visualization that I can leverage.

To give an analogy, there is TensorFlow or Pytorch in deep learning that facilitates building layers of neurons and run experiments. Is there any framework for spiking neural networks? Tools to automate calculatinos per neuron or run iterations?

For visualization I need also another tool that visualizes the spiking neural network and its evolution during learning. Is there any tool that is tailored for visualization of such these networks?

Many thanks!

# Answer
Brian2 is a great tool in python for spiking neural networks: https://brian2.readthedocs.io/en/stable/

NEURON might feel a bit old and clunky but if you want more biophysical detail, it is great: https://nrn.readthedocs.io/en/8.2.4/guide/index.html. It is mainly written in C++ but can be called from python.

Tangential but might be useful: For general differential equation solving using numerical methods, I am in love with Julia's DifferentialEquations package: https://docs.sciml.ai/DiffEqDocs/stable/.
> 3 votes

# Answer
A way into your problem might be to look at the NeuronDB website, which shows models for cell types, genes, transmitters, simulators, and many other search variables. You can then narrow down your search for a Python model.

https://senselab.med.yale.edu/ModelDB/FindByRegionList
> 1 votes

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Tags: neuroscience, computational-modeling, neural-network
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