Why do brains oscillate within specific frequency ranges? Why do brains oscillate within specific frequencies?

I have two specific questions:

What are the physiological mechanisms which generate the oscillations within these very frequencies?
What would go wrong if the frequencies were magically changed? I very strongly assume that this would go badly rather quickly, but I'd like to have a little more detailed information.

What are brain oscillations?

I think it is first important to recognize what brain oscillations refer to: they are small, somewhat localized fluctuations in voltage that are often measured by EEG (electroencephalogram), though they can also be measured inside the skull or inside the brain.

Most of these oscillations are also seen in the membrane potentials of individual neurons. Fast oscillations, like gamma oscillations, can also be seen in membrane potentials but are best associated with spiking activity. The cause of the skull-measured oscillations is the coordinated activity of many many neurons acting in concert.

Why certain frequencies?

Many brain oscillations are created by coupling of excitation and inhibition. The gamma oscillation, for example, is most associated with interactions between excitatory neurons and particular inhibitory neurons called fast-spiking and/or parvalbumin-positive cells. The frequency of the gamma oscillation is due to the time constants and conduction times between the reciprocal circuitry between excitatory cells and fast-spiking cells. If you were to maintain the same activity, but change these time constants, the gamma frequency would change.

Other frequencies may be slower because they involve circuits over a longer distance, such as interactions between thalamus and cortex.

Some of the slowest oscillations, called delta oscillations, come about due to long periods of high and low activity, sometimes called "UP" and "DOWN" states or "ON" and "OFF" periods. Oscillations are often nested within each other, referred to as cross-frequency coupling, or more specifically often phase-amplitude coupling. During the "DOWN" phase of a slow delta oscillation, amplitude in higher frequencies is low because there is little spiking activity; during the "UP" phase the amplitude in higher frequencies increases.

What is the purpose of brain oscillations?

We don't know. There are many theories that certain oscillations are important for certain functions, but most of the evidence for these theories is either theoretical or correlational. In very general terms, slower oscillations tend to be associated with rest whereas higher frequency oscillations are associated with active processing.

For example, gamma oscillations are possibly involved in 'binding' different types of information across different cortical areas: synchronous gamma activity could be the way a brain region primarily processing sounds can associate that information with a brain region primarily processing the visual object producing that sound.

It is also possible that many oscillations are simply epiphenomena: they result from particular types of activity, rather than being the cause of certain functions. Gamma, for example, seems to increase simply whenever overall neuronal activity increases.

The problem is that there is really no way to study an oscillation independent of the rest of the brain activity: anything that would impact an oscillation is necessarily going to be influencing neural activity in other ways.

Probably the best evidence for an actual functional role of brain oscillations is in phase coding in the theta band (and associated gamma oscillations), best-studied in the navigational networks of the hippocampus in rodents. The timing of spikes relative to the phase of an ongoing oscillation can carry more information than the spikes in solitude: the oscillation provides a reference signal.

What happens if brain oscillations were to magically change?

It sort of depends on what the mechanism of the magic is: you could certainly change oscillations by doing extreme things like stopping all neuronal activity: that would go quite badly. Epileptic seizures are a more naturally-occurring but similarly damaging example of oscillations gone wrong. Absence epilepsy is of particular interest since the mechanisms are a bit more complex than grand mal seizures.

However, you can also "magically" change oscillations as simply as closing your eyes: increases in alpha power are well-known to occur when you just briefly close your eyes. Changes in brain oscillations are a normal part of brain function: oscillations are very different during sleep and wake, for example. The amplitude and frequency of certain oscillations can be modulated by how alert or attentive you are. Depending on the specific type, anesthetic agents tend to produce brain oscillations that are at least qualitatively similar to sleep.

There are also correlations between different oscillation patterns and psychological diseases or disorders. People with schizophrenia show different patterns of gamma activity than non-schizophrenics, for example. However, it is unclear if it makes sense to think about oscillation differences as causal versus as a symptom. Autism, for example, is associated with reduced synchrony over long distances in the brain. This reduced synchrony is thought to be due to differences in connectivity. Depending on your perspective, you could highlight the change in synchrony as an important feature, or you could treat it as a symptom of the underlying difference in connectivity.

Summary, Conclusions, and Caution

Brain oscillations are a key window to understanding nervous function, especially in humans where they can be recorded more easily than any other type of neuronal activity. However, we need to be careful about thinking about oscillations as specific entities.

Oscillations in one frequency band could come about by completely different mechanisms in different situations. Changes in oscillations measured outside the skull can reflect changes in synchrony over long distances rather than changes in local oscillatory activity in individual columns. As an analogy, consider ripples in a pond: the amplitude of the ripples might tell you a bit about the size of an object that disrupted the water's surface, but if that's all you have you can't know whether the object came initially from above or below the surface, whether it was a bird, fish, or rock, etc.

Many papers are published that tie oscillations to certain states, conditions, or diseases, and these can be pathways to understanding but they are unlikely to directly identify underlying mechanisms.

For the references below, I've tried to use review articles where possible that are fairly digestible without too much additional information. In particular, I bolded a couple that I think are great starting points.

References:

Bazhenov, M., Timofeev, I., Steriade, M., & Sejnowski, T. J. (2002). Model of thalamocortical slow-wave sleep oscillations and transitions to activated states. Journal of neuroscience, 22(19), 8691-8704.

Buzsáki, G., & Wang, X. J. (2012). Mechanisms of gamma oscillations. Annual review of neuroscience, 35, 203-225.

Cohen, M. X., Elger, C. E., & Fell, J. (2008). Oscillatory activity and phase–amplitude coupling in the human medial frontal cortex during decision making. Journal of cognitive neuroscience, 21(2), 390-402.

Goldman, R. I., Stern, J. M., Engel Jr, J., & Cohen, M. S. (2002). Simultaneous EEG and fMRI of the alpha rhythm. Neuroreport, 13(18), 2487.

Harris, K. D., Henze, D. A., Hirase, H., Leinekugel, X., Dragoi, G., Czurkó, A., & Buzsáki, G. (2002). Spike train dynamics predicts theta-related phase precession in hippocampal pyramidal cells. Nature, 417(6890), 738.

Hasselmo, M. E., Bodelón, C., & Wyble, B. P. (2002). A proposed function for hippocampal theta rhythm: separate phases of encoding and retrieval enhance reversal of prior learning. Neural computation, 14(4), 793-817.

Kwon, J. S., O'donnell, B. F., Wallenstein, G. V., Greene, R. W., Hirayasu, Y., Nestor, P. G., ... & McCarley, R. W. (1999). Gamma frequency–range abnormalities to auditory stimulation in schizophrenia. Archives of general psychiatry, 56(11), 1001-1005.

Lisman, J. E., & Jensen, O. (2013). The theta-gamma neural code. Neuron, 77(6), 1002-1016.

Steriade, M., McCormick, D. A., & Sejnowski, T. J. (1993). Thalamocortical oscillations in the sleeping and aroused brain. Science, 262(5134), 679-685.

Tallon-Baudry, C., & Bertrand, O. (1999). Oscillatory gamma activity in humans and its role in object representation. Trends in cognitive sciences, 3(4), 151-162.

Uhlhaas, P. J., & Singer, W. (2006). Neural synchrony in brain disorders: relevance for cognitive dysfunctions and pathophysiology. Neuron, 52(1), 155-168.


Conceptual representations in brain by distributed groups of neurons It seems generally agreed upon that semantic concepts are distributedly represented by groups and groups of groups of neurons spread over the cortex.

Disregarding the localizations, shapes and connectivity of these groups of neurons, I tried to consider them as sets (in the mathematical sense). Let $S(A)$ be the (probably fuzzy) set corresponding to concept $A$.

The only thing that I would take for granted is that for very similar semantic concepts $A$, $A'$ their corresponding sets of neurons $S(A), S(A')$ do overlap strongly. Otherwise the model of distributed representation would not make much sense to me.

Other answers aren't so obvious:

Does a more general concept $A$ use more neurons than a more specific concept $B \subset A$ - or less? Or does it depend (on what)?
How do the sets of neurons of two concepts $A, B$ with $B \subset A$ overlap? Is maybe one a (fuzzy) subset of the other? More generally: How are semantical or extensional relations between two concepts reflected by set theoretic relations between their corresponding sets of neurons? (My intuitive guess is: $S(A)$ is larger than $S(B)$, and $S(B)$ is contained in $S(A)$, i.e. $S(B)\subset S(A)$. But this may be simply wrong.)
Does a more important concept $A$ (being used more often) use more neurons than a more rarely used.

I wonder if there is any evidence (empircal or theoretical) that sheds some light on these questions.

[If you think, this question is devoid of scientific meaning or otherwise ill-posed, please let me know why.]

You might want to take a look at the work about conceptual spaces by Peter Gärdenfors, e.g. https://www.amazon.com/Conceptual-Spaces-Geometry-Thought-Press/dp/0262572192

Also, the work about semantic pointers might be interesting here: https://www.ncbi.nlm.nih.gov/pubmed/26235459

My opinion with regard to this is, that using set theory to represent concepts is a fruitful approach, but there needs to be a precise definition of the "space" we are talking about as well as if and how it is possible to define some metric on this space or a higher structure, e.g. if it is a vector space. This metric must not only take into account set overlaps but also principal phenomena corresponding to what we know about neurobiology, e.g. classical/operant conditioning etc.

Let's try to build this up systematically (Note, that I do not use a fuzzy set definition here but it might provide some more flexibility and thanks for putting me on that track ;)): We could define the set of all neurons

N = {n_1,n_2,...,n_m}

and the set of all possible states of a neuron (avoiding, for now, a precise definition of what a state is. For example, a state could be a frequency or some pattern of action potentials, e.g. rate/temporal/population code or just a discrete value of the membrane potential)

S={s_1,s_2,...,s_l}

The Cartesian product set N x S will give us the set of all neurons in all possible states C_0:

C_0={n_1(s_1),n_1(s_2),n_2(s_1),n_2(s_2),...,n_m(s_l)}

Then let's define a concept space as a mapping f1 from C_0 to a new set C_1

C_1={{n_1(s_1),n_3(s_3),n_4(s_1),n_5(s_8)},{n_1(s_1),n_2(s_3),n_5(s_9)},...}={c1_1,c1_2,...,c1_x}

For example, an element (c1_x) of C_1 could be a visual representation of a house or some sound or smell or just a point or a line. This is what Thagard & Steward (2014) defined as a semantic pointer and it shares some similarity with Tononi's (e.g. 2016) approach of a qualia space (although approached from a different (set theoretic) angle since Tononi uses information theory). This also is similar to Gardenförs' concept of a conceptual space, although he did not make his definitions mathematically precise. Because strictly, C_1 still has no structure, i.e. is not a vector space or more generally a metric space. There still has to be defined some distance function, which is not easy to be found.

Now, it is possible to generate more and more sets representing more and more complex concepts by consecutive mappings f1 to fn. That is we can generate a new set C_2 consisting of elements of C_1:

C_2={{c1_1,c1_3,c1_5,c1_9},{c1_7,c1_1,c1_8},...}={c2_1,c2_2,...,c2_x}

Imagine the element c2_1 consisting of four lines with coordinates of length l1 to l4 each of them in a specific angle a1 to a4 such that they create a square. Or take c2_2 as three lines with length l1 to l3 and angles a1 to a3 such that they create a triangle.

This process can be repeated to generate more and more abstract concepts. I think it is easy to understand it when considering how letters are combined to words and words form sentences and sentences form even more abstract meanings.

There are now many questions that arise, e.g. are the mappings injective, surjective or bijective? Do inverse mappings exist? What is a suitable metric that is in accord with neurobiological and experimental data? Can a higher structure e.g. vector space be defined?

Finally, I can try to answer your questions:

Based on the above definition one can assume that more general concept e.g. a cube is formed by a set of lines, i.e. a set of semantic pointers forms another set of semantic pointers. For example, a complex movement with the hand was initially learned by combining different simple movements. Or take learning to speak a word for example.
Also based on the definition above, there must not be an overlap between sets at all! Take two very different semantic pointers for example, like barking and the visual representation of a dog. Whereas one set of semantic pointers might represent the sound, the other may represent the visual aspect, but they might not share the same neurons. But all of them together create a concept of a dog. So here again, the definition of similarity seems to be not just a simple set overlap metric (e.g. Szymkiewicz-Simpson coefficient or Jaccard index).
This depends on the definition of important. If you define important as activated more often together, then one could just assume a simple (e.g. Hebbian or STDP) learning rule which strengthens the connection between neurons. But I doubt that more neurons will be included in the concept except when the concept is updated/broadened by new experiences.

Hope this helps a bit! I'm trying to build a more general understanding of conceptual spaced based on set theory for a while and I always welcome discussions, critique or collaborations :).

Sources:

-Thagard, Paul, and Terrence C. Stewart. "Two theories of consciousness: Semantic pointer competition vs. information integration." Consciousness and Cognition 30 (2014): 73-90.

-Tononi, Giulio. "Consciousness as integrated information: a provisional manifesto." The Biological Bulletin (2016).


What are some reasons that make rule-based reasoning about morality more intuitive than utilitarian reasoning? Anecdotally, people are often more into rule-based reasoning. For instance, "honesty is always the right policy" is widely accepted throughout many cultures. It is less often for cultures to naturally adopt a more consequentialist view of morality.
In the English language, saying someone is "principled" is almost synonymous with saying that person is "moral". The same thing is true in Chinese: (saying someone is 有原则的 is the same as saying that person is 好的，正直的，高尚的.)
What are some psychological and cognitive reasons that make rule-based reasoning of morality more intuitive?

I don't know if this really answers your question, but at a high level, rule-based reasoning about anything is more intuitive. By this I mean, rules are heuristics-- and having heuristics makes for more efficient reaction formation, decision-making, action, etc. The time and energy to process a stimulus, including a morally relevant scenario, is reduced when applying a heuristic, like a rule.
Morality is not my area of expertise, But I will add that there's possibly also a component here of some discomfort associated with making moral evaluations. Moral judgements serve as functional guides of behavioral consequences and outcomes (having real impact in people's lives), and typically involve some degree of uncertainty. This may cause discomfort, whereas rule-based reasoning allows for avoidance of careful thought and therefore avoidance of that discomfort ..? Just a thought, no real evidence to back that


How do I handle contradicting study results? A foundation of my psychological work is the body. Simply put, I work on a big part with embodiment to diagnose, as well as to intervene and to integrate.

One illustration, or rather one important reasoning for embodiment seems to be the so called facial feedback test. I have read about this test over and over again in literature.

In 2016, there have been efforts to reproduce this test, and these efforts did fail. See here:

https://www.psychologicalscience.org/news/releases/effect-of-facial-expression-on-emotional-state-not-replicated-in-multilab-study.html

All this is rather new to me, so I don't know how to handle this situation. My intention is to do honest work. I am wondering:

Is it careless to still cite the facial feedback although it cannot be reproduced?
Or is it only careless to still cite if several studies proved it explicitely wrong?
How do I talk to clients about the facial feedback?
Should I simply try it myself and choose to belief what I want?

Please note that I am not asking for opinions. My question finally is:

  As an ethic worker in the field of psychology, how do I handle contradicting study results, based on the example of the facial feedback?

The example of facial feedback implicitely includes a) the contradicting study results and b) the contradiction becomes visible over time.

Short answer
Many individual papers report non-reproducible findings. I would advise you to look for review papers and meta-analysis studies to get the bigger picture. If not available, you can consider to set up a literature study yourself.

Background
Nature puts it down neatly (emphasis mine):

  Science moves forward by corroboration – when researchers verify others’ results. Science advances faster when people waste less time pursuing false leads. No research paper can ever be considered to be the final word, but there are too many that do not stand up to further study

Recently it has appeared that the results of a great many studies cannot be reproduced, leading to what is referred to now as the "Replication crisis".

Many factors may contribute, chief among those are according to Nature:

  the increased levels of scrutiny, complexity of experiments and statistics, and pressures on researchers.

More reliable resources than individual primary research reports are the so-called meta-studies, i.e., review studies that collects as much information there is and where the authors attempt to synthesize the bigger picture to extract solid conclusions from them, as well as confounding factors explaining why some studies may have drawn less correct conclusions.


In NEURON simulator, how do you pan and zoom a plotted graph? How do I zoom in and move around a chart after it has been plotted?

Unintuitive, but it's in the right click > View sub-menu:

Pan/translate:

Right click the chart
View > Translate
Left click drag will pan around the chart

Zoom:

Right click the chart
View > Zoom In/Out
Left click drag horizontally or vertically to zoom the x or y axis

Zoom in on a region:

Right click the chart
View > NewView
Left click on the chart to draw a box
A new window will open, drag the lower-right corner to expand the window


Isolating stable EEG data across all channels in EEGLAB I'm working on some EEG data we collected using the Emotiv Epoc headset using 14 channel sensors.

I need to isolate chunks of data where all 14 channels are stable (non-noisy) for a given length of time (e.g. 5 seconds). I've written a MATLAB script for this, such that I calculate the standard deviation of each channel and pass an analysis window over the data, comparing the difference between maximum and minimum values in the window to this standard deviation (i.e. where maximum - minimum is less than the standard deviation [or 3-5 standard deviations], I treat that window as stable).

Based on this criteria, I am having some success in finding 5 second long segments but am worried this data may not be reliable (or not as stable/artefact free as desired).

Are there any better ways of performing this analysis? Even better, are there any functions built into EEGLAB for this very purpose?

Further info:

I've selected only the relevant channels and can now look through my EEG data files.

I am no neuroscience expert, actually I'm rather new to this sort of analysis, so apologies if this question is overly basic or off-point.

EDIT

We collected our data in a museum environment (very noisy in many ways), with participants sitting as still as possible for 2-minute sessions at a go. For this reason, there is a high likelihood of artefacts being found in the data due to movement, the environment and possibly even inaccuracies from the device itself (since we went through a rather large number of participants, cleaning and charging the headsets in between trials).

From what I've discussed with the team, I've been told that removing artefacts wouldn't solve the issue (though admittedly I'm no expert as to why this would be).

For clarity, the data we've collected looks similar to the plot below.

And we're looking for a minimum of 5 seconds of stable data, closer to the plot below.

Also, I know this data selection can be done manually using pop_eegplot, however since we have close to 300 data files I'm looking to automate this (and hopefully get more reliable selections).

In this conference paper they propose an algorithm that roughly goes as follows (if you can't access it, just add "sci-hub.bz" after ".org" in the url and it redirects you directly to the pdf) :

Divide channels into four groups: 1) frontal, 2) central, 3) temporal and 4) parietal+occipital.
For each group take three signals: 1) the raw signal, 2) the alpha band(8-12Hz, using a 3rd order butterworth band-pass filter) and 3) the beta band(13-35Hz).
For each group and each signal calculate the four metrics: 1) max amplitude, 2) standard deviation, 3) kurtosis and 4) skewness. For the frequency band signals they also take the mean power and the standard deviation of the power.

They then go on and find optimal thresholds for each metric, group, and signal by using a differential evolution algorithm on training data, so unfortunately it's not immediately applicable for you. As I see it, you have at least two options here:

Create 5 seconds long epochs of your data and label a lot of them. Use that data to learn optimal thresholds (unfortunately they don't give any details on how to do that, so you would have to figure that out yourself). This would obviously take a lot of effort but at the end you can be quite confident about your classification.
Just try some value ranges for the different metrics, you can orient yourself on the values they found in the paper (you have to read them from the plots though).  Check the resulting classifications. Pick the threshold values that give the "best" results by inspections. This is not as systematic as the first option but might fit your needs already. For example if you just want to avoid to have segments that were falsely classified as "clean" you might just go for very conservative/safe threshold values. There is a big danger here though, that you will get lost in an endless loop of "maybe if I adjust this threshold a bit more" and will never stop exploring. To help with that, you might also reduce the number of metrics, groups or signals.


Is it possible to induce eye blinking? Long time screen users like software developers sometimes use computers so intensely that they do not blink enough with their eyes. This leads to dry eyes.

  Unfortunately, people typically don't blink their eyes normally when using a computer or other digital devices or simply watching television intently.
  Specifically, computer use affects both blink rate (how frequently we blink) and blink completeness (whether the eyelids close completely during a blink).

Is it possible to induce blinking by manipulating the screen, for example by regularly making it completely black for a split second?

References:
Blink patterns: reading from a computer screen versus hard copy. Optometry and Vision Science. March 2014.
Blink rate, blink amplitude, and tear film integrity during dynamic visual display terminal tasks. Current Eye Research. March 2011.
Computer vision syndrome: a review. Survey of Ophthalmology. May/June 2005.

There are multiple ways to trigger eyeblinks:

Typically in scientific research an air puff is used.
Anything that touches the cornea.
Loud noises.
Bright lights.
Looming stimuli (i.e. something that is or looks like it is approaching fast).
More broadly anything that is unexpected and triggers a sense of danger.

So in short it is possible to visually trigger blinks but as far as I know not anything that would be an agreeable experience to the observer.


Annoyance in animals When my dog (an English Cocker Spaniel, for what its worth) is behind some glass (e.g. a glass door or a car window) and someone taps on the glass, even just a little bit, she gets into a fit of rage. She has always been treated quite well, so I can't imagine what causes her to behave like this.

The first thing that came to my mind is that she perceives whoever is tapping the glass as teasing her, and she feels disrespected, or something like that. This sounds far fetched, but could there be any merit to this theory? If not, what else would cause her to do this?

I believe we know that monkeys interpret teasing correctly (I don't know this for a fact). That is, they know when they are being teased and they (correctly) interpret it as being disrespected. Could the same thing be true for less intelligent animals like dogs?

Teasing generally seems to have two components. First, as mentioned in the title of your question, it is a matter of becoming annoyed; specifically at behavior that is (often repetitively) enacted towards oneself. Furthermore, to know that someone is teasing you it is necessary to be able to conceptualize their intentions (otherwise known as having a "theory of mind"), which is necessary in order to potentially feel disrespected. It is uncontroversial that dogs can feel annoyed, just try relieving one of its food (or tapping on the glass it is behind ;). However, the extent to which dogs are able to conceive of the mental states of others is debated in animal psychology. It has been shown, for instance, that certain populations of dogs are unable to spontaneously adapt to human social cues. However, naturally, many pet domestic dogs are great at adapting to their owners behaviors. Dogs are not "man's best friend" for no reason - they do possess the ability to learn social cues. However, it seems that this has to be taught, whereas it seems that humans have a much greater innate predisposition to TOM/mentalizing. In conclusion, dogs' TOM seems to be a significantly more superficial ability than it is in humans. This leads me to suggest that tapping on the glass causes your Cocker Spaniel to either a) want to play oh-so-badly, or b) get (really) annoyed. They surely don't understand teasing with the full social capacity of a human.


Is synesthesia tied to experience? For example, do color blind people only able to perceive experienced colors through synesthesia? E.g. if a person both has synesthesia (like grapheme-color synesthesia or chromesthesia) and some kind of color blindness (say, protanopia, when individual can't experience "red" color) will all his/her synesthetic experiences be tied to the colors experienced? Or can synesthesia make a person feel "new" color (or any other experience)?

Can synesthesia make a person feel "new" color (or any other experience)?

The answer may be yes. You can find this quote “V. S. Ramachandran and E. M. Hubbard (in their 2001 PRSL paper) described a partially colorblind man with letter-color synesthesia who said that when synesthetically stimulated, he saw colors he had never seen with his eyes—he called these “Martian colors.” Ramachandran and Hubbard subsequently found that “the Martian color effect” might occur in noncolorblind synesthetes as well.” from several websites, such as this site and this site.

But I can’t find the original paper of V. S. Ramachandran and E. M. Hubbard. So, it’s impossible to verify the finding. Also, I can’t find any other reports of such a patient in the literature or any report of non-colorblind synesthetes who experienced “the Martian color effect” either. So, personally, I think this finding and the speculation that “the Martian color effect” might occur in non-colorblind synesthetes as well needs more confirmation.

Anyway, is there evidence that a person who is color-blind since birth can experience a color that he/she has never experienced before? Will his/her cortical color perception areas, which have never generated the missing color perception, able to generate it when given appropriate stimuli, such as from the eyes after gene therapy that restores the missing cone function in the retina? The answer from animal experiments is yes (for example see Ref1 and Ref2). So, potentially, a colorblind brain can still generate a color percept that it has never generated before, when given appropriate stimuli. Theoretically, then, synesthesia may be able to make a person feel “new” color he/she has never felt before if it can deliver appropriate stimuli to the color perception areas.


Lexical Decision (Web-)App I want to make a lexical decision experiment, is there any freely available software for this? A Javascript-based webapp would suit me best, as it would run in the browser without the need to install anything.

One option is to use Inquisit Web Edition.
 Here is an example script with a lexical decision task.

Unfortunately, it is not free and it requires installation of a plug-in.

Version 4 of Inquisit runs on OSX and Windows. Thus, it wont work in Linux or on phones, tablets, etc.


What subjects to study in order to prepare for a research career in theoretical neuroscience? Which topics in a dual degree in Cognitive science and Computer science at the graduate level  or systems neuroscience (experimental + theory) graduate degree will better prepare for a research career in theoretical neuroscience?

(trying to frame it in a more objective manner, as stackexchange forums prefer that)

There are several approaches to theoretical neuroscience.  I am currently taking the physics/mathematics approach: modelling the currents in neurons and coupling several neurons together through differential equations.

In Computer Science, the tendency is more towards machine learning: Bayesian statistics, artificial neural networks, signal processing, robotics, artificial intelligence.  It really depends on what level you want to engage the field.  For instance, if you want to study vision science, you'll want to learn more about vision and color perception and some basic physics/optics.  But I also think neurochemistry and neurophysics is important, just for breadth.

Computer scientists often use the leaky integrate and fire model or rate coding models.  There's something called the neural engineering framework that seeks to make networks of neurons do standard logical operations.  One of their projects is SPAUN, a whole brain simulation.


Does working memory have a role in creativity? What role does working memory play in creativity?

Creativity in this context being easily measurable creativity, so performance on things like the uses task etc. Divergent thinking is the ability to consciously generate new ideas that branch out to many possible solutions for a given problem. It can be tested using the S-A creativity test (Society For Creative Minds, 1969).

My assumption is that creativity is a form of divergent thinking and working memory is required for divergent thinking.  I was wondering if anyone could expand on or dispel this?

Takeuchi et al. (2011) had participants in an fMRI perform three tasks in order to measure creativity, working memory and intelligence.

S-A creativity test as a measure of creativity (Society For Creative Minds, 1969).
Verbal n-back as a measure of working memory (Calicott et al., 1999).
Raven's Advanced Progressive Matrix as a measure of intelligence (Raven, 1998).

They reported no association between creativity and WM performance after controlling for IQ.

  To our knowledge, this is the first study to investigate the association between individual creativity and functional activity during WM. Creativity and WM performances did not correlate in this study of young healthy and cognitively intact subjects. However, congruent with our hypothesis, our findings showed that reduced TID during the WM task in the precuneus (one of the key nodes of the DMN) is associated with creativity measured by the divergent thinking test.

There was no apparent evidence to suggest that performance on a WM task is associated with performance on a divergent thinking task, but the authors proposed a complex argument for the idea of creativity as "diffuse attention," which they argue may share a neural basis with WM (such that they are opponent processes). The evidence for this is indirect and seems difficult to reconcile with the concretely reported independence of WM and creativity performance, however.

References

Callicott, J. H., Mattay, V. S., Bertolino, A., Finn, K., Coppola, R., Frank, J. A., ... & Weinberger, D. R. (1999). Physiological characteristics of capacity constraints in working memory as revealed by functional MRI. Cerebral Cortex, 9(1), 20-26.
Raven, J. Court (1998). Manual for Raven’s progressive matrices and vocabulary scales. Oxford: Oxford Psychologists.
Society For Creative Minds (1969). Manual of S-A Creativity Test.
Tokyo Schinri Corporation. Tokyo.
Takeuchi, H., Taki, Y., Hashizume, H., Sassa, Y., Nagase, T., Nouchi, R., & Kawashima, R. (2011). Failing to deactivate: the association between brain activity during a working memory task and creativity. Neuroimage, 55(2), 681-687.


How have mean raw IQ scores changed over time (e.g., over the last 100 years)? I understand that by definition,  the mean IQ is 100.
And that over time IQ tests are updated to ensure that mean remains 100.
But if IQ scores were not updated, what would mean IQ be now and how has IQ changed over time?

Until recently, when people took older tests, they tended to score higher.
https://en.wikipedia.org/wiki/Flynn_effect

The Flynn effect is the substantial and long-sustained increase in
both fluid and crystallized intelligence test scores that were
measured in many parts of the world over the 20th century.[1] When
intelligence quotient (IQ) tests are initially standardized using a
sample of test-takers, by convention the average of the test results
is set to 100 and their standard deviation is set to 15 or 16 IQ
points. When IQ tests are revised, they are again standardized using a
new sample of test-takers, usually born more recently than the first.
Again, the average result is set to 100. However, when the new test
subjects take the older tests, in almost every case their average
scores are significantly above 100.

The recent years saw a reversal of the Flynn effect.


Is sexual desire an emotion? I see that in the Wikipedia page of emotion classification, sexual desire is only mentioned once (in Parrott's tree-structured list of emotion). It is absent from other kinds of classification.

What is sexual desire?

  Sexual desire is a motivational state and an interest in “sexual objects or activities, or as a wish, or drive to seek out sexual objects or to engage in sexual activities”. Synonyms for sexual desire are libido, sexual attraction and lust. Sexual desire is an aspect of a person's sexuality, which varies significantly from one person to another, and also varies depending on circumstances at a particular time. Not every person experiences sexual desire; those who do not experience it may be labelled asexual.

What is emotion?

  Emotions are biological states associated with the nervous system brought on by neurophysiological changes variously associated with thoughts, feelings, behavioural responses, and a degree of pleasure or displeasure. There is currently no scientific consensus on a definition. Emotion is often intertwined with mood, temperament, personality, disposition, creativity and motivation.

So it seems to me that you can consider sexual desire as an emotion. However, the lack of it in other kinds of classification make me question about that. I think sexual desire is common and basic enough to have a consideration in most classifications.

Sexual desire, libido, horniness, titillation, lust and eroticism are all listed as emotions in the Atlas of Personality, Emotion and Behaviour (Mobbs, 2020).  In the atlas taxonomy, emotion is defined the perception of a neurological impulse that initiates behaviour (typically abstract nouns).

The full catalogue is available at: https://doi.org/10.6084/m9.figshare.c.4792323

Mobbs AED (2020) An atlas of personality, emotion and behaviour. PLoS ONE 15(1): e0227877. https://doi.org/10.1371/journal.pone.0227877


Why I read by hearing the words? This question requires very little background:
1. English is my second language and I find myself thinking mostly in it
2. I tend to listen more than to read it

When I read a book from the computer screen (the same screen on which I watch documentaries) about science I tend to read the words but to also hear them in my mind, like if I was reading them out loud (or some documentary speaker was talking) and only after that I perceive the whole sentence. It seems to me that I can not control this process.

My expectations are that reading has nothing to do with hearing.

The opposite of my situation is to hear something and experience it reading it in your mind on a sheet of paper and after that you perceive the information.

Any idea why this is happening?

When I read a book I tend to read the words but to also hear them in my mind

Inner Speech is the general name given to this phenomenon,1  although it also goes by imagined speech, silent speech or covert speech, there are few studies and even less definite conclusions as to how it happens and its role in reading comprehension.

  and only after that I perceive the whole sentence.

In general, language comprehension goes through the perception of sounds, words and sentences followed by meaning ( independently or in succession) , in order to comprehend a sentence or paragraph you hold words or sentences in some form of short term memory, for visual language ( written words, sign language ), we have a visual sketchpad and for spoken words we have a phonological loop and other inter related memory structures,these buffers also connect or send information to other associational areas in the brain where meaning is presumably derived.2

  It seems to me that I can not control this process.

Another related concept to inner speech is private speech3, words spoken out loud to oneself. Private speech is both healthy and normal in children from the ages of 2 to 7 ( a student reading in class to himself in whispers for instance ), although we generally stop the public practice when we grow up due mostly to our social environment and other factors. It is then conceivable that our preferred way ( although not the only one) way of reading for comprehension is to use silent private speech which in turn goes through the language comprehension process outlined above.4

  My expectations are that reading has nothing to do with hearing.

Yes and no, while the entry point might be a different one ( visual vs auditory), most likely the language centers and higher associational areas get recruited by either one while reading or hearing, furthermore, by translating internally in between domains, you have access to memories specific to that domain, for instance: when perceiving visually a stop sign (and reacting rapidly), reading and imagining a color, or hearing how something smells5 .

  Any idea why this is happening?

Languages consisting of ideograms( Japanese kanji ) present some clues along with the previous overview. Even though the kanji ideograms have more in common with pictures than words; the principal speech comprehension centers get predominantly recruited ( there are still differences though).6 Language has also been predominantly spoken ( the written word is relatively new to our species ) so it makes sense from an adaptive perspective ( i.e it is more efficient) to have a language comprehension center devoted to the older spoken language ( or general sound deciphering) and co-opt it for reading, this new routing happens with the aid of inner silent speech ( which could be a modification of private speech) and other memory buffers.

Notes, reference & sources:

1. A great introduction and overview: Inner Speech: Development, Cognitive Functions, Phenomenology, and Neurobiology

2. Cognitive Neuroscience( Gazzinga) Has a great overview of language and memory and there are whole fields of Neurolinguistics and Psycholinguistics devoted to language.

3. The wiki on private speech and previous sources.

4. From Print to sound and meaning (Cognitive Neuroscience of Language -Kemmerer) presents a model of this arrangement.

5. A contrasting issue is early blind subjects that read in braile, the entry point here is tactile but ends up recruiting language and visual areas the same. see Visual Cortex Activity in Early and Late Blind People

6. Japanese and English sentence reading comprehension and writing systems: An fMRI study of first and second language effects on brain activation Presents a detailed account.


Is this expected to happen while asleep? I always knew that, while asleep, stuff like processing words and/or reading texts could not be done by the brain. I'm not even a student in the area, so by knew you could understand as vulgar knowledge.

What I noticed many times is that in my dreams I read and pay attention to words, and the most recent case was right today, when I composed a verse making fun of an existent melody (to put in context, is when you want to mock a song in some way). While the context of the verse and dream was given to my subconscious by my recent obsession about missing playing poker with my friends, what seemed unusual to me is that I did that in a vivid way to the point I remember it letter by letter (and laugh about).

The reason I ask about this is: Is this an expected thing that happens while asleep or could be a sign of a health problem? (don't know: stress, insomnia, or even something I should worry about)

An appropriate answer should be backed by a meaningful and reputed research result.

The appropriate answer is that dreams are generally not in any way diagnostic of a health issue. Being able to read while dreaming is absolutely not diagnostic. I can't imagine that any reputable research has been done on this topic.


Why are mind maps recommended for study and recap? In both my last year of high school and my freshmen year at the university, I got strong recommendations to study using mind maps - especially because this is apparently better to cope with large amounts of new information.

Is mind mapping effective in learning and reflecting on information?
If so, how does mind mapping help in learning and reflecting on information?

An excellent question! A 2011 paper in Science by Karpicke and Blunt in the Cognition and Learning Lab at Purdue University gets at this issue. They offer that:

  "Concept mapping is considered an active learning task, and it serves
  as an elaborative study activity when students construct concept maps
  in the presence of the materials they are learning. Under these
  conditions, concept mapping bears the defining characteristics of an
  elaborative study method: It requires students to enrich the material
  they are studying and encode meaningful relationships among concepts
  within an organized knowledge structure."

They go on in their paper, however, to demonstrate that concept mapping is far less efficient than an even simpler technique: repeated retrieval (e.g., self-testing). Practicing retrieval, they argue, "enhances learning by retrieval-specific mechanisms rather than by elaborative study processes."

Reference:

Karpicke, J.D., & Blunt, J.R. (2011). Retrieval practice produces more learning than elaborative studying with concept mapping. Science, 331, 772-775.


Would most people benefit from psychotherapy? At least in my country, undergoing psychotherapy is perceived negatively.
People in my country perceive people as either healthy (normal), or mad and in need of a psychologist. My perception is different. I think most people would benefit from psychological therapy.

Does the evidence support the idea that most people would benefit from psychotherapy?

The same methods that psychotherapy utilizes to help people overcome psychological problems are used in coaching to help healthy and successful persons to become even more successful and feel even more better.

So, yes, everyone can benefit from psychotherapy, you just don't have to call it that, which might make it easier for most people to accept it.

If I were a psychotherapist, I would call my service "mental fitness" and advertise it in the same manner as gyms advertise their services as a lifestyle ("Be sexy and successful!") instead of a health product ("Fight obesity!").


How do animals recognize other animals of their own species? My motivation for this question is dog-based, but I suppose it would apply equally well to humans. How do animals recognize their own kind, particularly where there is large variation in appearance?

The background is that I am reading "Discrimination of human and dog faces and inversion responses in domestic dogs (Canis familiaris)" by Racca et al. (2010; Animal Cognition 13: 525-533). These authors show that when dogs are presented upright objects, human faces, and dog faces, they spend more time gazing on novel objects and human faces than they do on familiar ones. However, they spend significantly more time gazing on familiar dog faces than they do on novel ones.

This got me thinking how a dog "knows" another face belongs to a dog. Acedotally (which I realize is worth approximately nil in science), my dog reacts very differently to seeing another dog in an adjacent car compared to a person. Given that there is so much phenotypic variation in dogs, how does it know that other animal is a dog, and not a cat or very large rodent? I could understand a lion recognizing another lion, because all lions look more or less the same.

The obvious: animals use a variety of senses

There's a wikipedia article on intra-species recognition. The article states:

  Different species may employ different methods, but all of them are
  based on one or more senses (after all, this is how the organism
  gather information about the environment). The recognition may happen
  by chemical signature (smell), by having a distinctive shape (sight),
  by emitting certain sounds (hearing), or even by behaviour patterns.
  Often a combination of these is used....
  Intra-species recognition systems are often subtle...
  Sometimes, too, intra-species recognition is fallible

Of course, this is all fairly obvious, true, and not that helpful.

A few articles of possible relevance

Mateo (2004) has a review of recognition systems in animals if you want a more general theoretical framework.
Pfennig (1998) discusses intra-species recognition and the relationship with mate selection.

Musings on your particular question

In your particular example of two cars driving along with windows closed, we are probably excluding senses of smell and sound and requiring the dogs to rely exclusively on sight.
I wonder whether prototype theory or some other human visual categorisation theory would apply to dogs also?

References

Mateo, J. (2004). Recognition systems and biological organization: the
perception component of social recognition. In Annales Zoologici
Fennici, volume 41, pages 729-745.
PDF
Pfenning (1988) PDF

I'm way outside my expertise here. I tossed up whether to post this at all. I figured I'd post in the absence of another answer a week after posting. The above represents what I found from a little research.


How to test effectiveness of a children's museum in improving cognitive function? For those who have never heard of a Children's Museum before, there is a national association in the US with some information.  The basic idea stems from Vygotsky-like paradigms of learning through play.

My first impulse was: write a GUI that presents a series of standard cognitive tests in a fun way, put the software on a computer in a kiosk during the museum events.  Finally, compare child performance on the test to the number of visits to children's museum.

Of course, there's some considerations: if somebody takes the test multiple times, they're probably going to get better at it, so this might give a false-positive (rising with the number of visits).  So, for instance, only the first test taken by each person would be considered for analysis.

But that is a rather inexperienced shot in the dark.  Any other ideas?

General literature on training and educational program evaluation

In general, you would want to read up about program evaluation in general, and educational program evaluation, and training evaluation in particular.
With regards to the educational context I found this article online.
With regards to training evaluation, you could check out Kraiger et al (1993) or Sackett and Mullen (1993) or any number of other textbook treatments of training evaluation.

Specific comments on evaluating a "children's museum"

What design will you use?: is it going to be a pre-post design where you compare knowledge before and after exposure to the program? Are you going to have a control group who does not experience the program or experiences an alternative program? How will you allocate participants to conditions? random allocation is better.
Decide on the constructs of interest?: What is the program meant to improve? You speak about quite general learning goals, but training programs are much more likely to have more specific effects. E.g., if you have a program that teaching addition, then students are likely to get better at addition, but their general intelligence is likely to be unchanged. You may also want to think about the time frame that benefits are meant to persist after exposure to the program. You can also look at Kirkpatrick's framework of training evaluation which talks about different kinds of outcome variables.
What will measure your constructs of interest?: Are you going to use existing measures or develop your own measures? If the content is highly specific to your program, then you will probably need to develop your own test items.
Determine your sample: How are you going to recruit your sample? How many participants will you need to ensure reasonable statistical power?
When and how will measures be administered? I think you would want to do this in a controlled setting. A kiosk would probably be problematic from a measurement perspective.

Rough starting point

Of course there are a whole range of issues related to program evaluation, and dealing with children introduces many additional issues.
The following might provide a rough starting point:

two groups: control and intervention; about 100 participants per group
three time points: before intervention, immediately after intervention, a few months after intervention
Use some general measures of ability related to the program as well as some highly specific measures that tie in closely to program content.
Also measure other factors like child and perhaps parent reactions to the program including both quantitative and qualitative evaluations.
Perhaps link in with some surrounding schools or day care facilities to recruit participants or use some form of waiting list system for admission to the program. Administer tests in a controlled environment (e.g., in a supervised room).

References

Kraiger, K., Ford, J.K. & Salas, E. (1993). Application of cognitive, skill-based, and affective theories of learning outcomes to new methods of training evaluation.. Journal of applied Psychology, 78, 311. PDF
Sackett, P.R. & Mullen, E.J. (1993). Beyond formal experimental design: Towards an expanded view of the training evaluation process. Personnel Psychology, 46, 613-627. PDF


Is depression an inflammatory disease? In the paper:

Michael Berk et al, So depression is an inflammatory disease, but where does the inflammation come from?, BMC Medicine 2013, 11:200, doi:10.1186/1741-7015-11-200

it is presented as an undisputed fact that depression is an inflammatory disease.

For example (the first sentence of the abstract):

  We now know that depression is associated with a chronic, low-grade inflammatory response and activation of cell-mediated immunity, as well as activation of the compensatory anti-inflammatory reflex system.

However, AFAIK, we are far from understanding the etiology of depression (perhaps there is no universal one). Sure, there are many correlates (for example – levels of neurotransmitters), but I haven't heard  that there a single, accepted cause (except for the cited paper). For the reference, Wikipedia mentions inflammation as one of multiple related conditions in the "Other hypotheses" section.

So, as of now, is it universally accepted that depression is an inflammatory disease?
And if not, is it at least one of many mainstream opinions?

Discussion on HN, through which I've learnt about this paper

There certainly isn't a single cause of depression. Wikipedia does not list inflammation, so that seems to be sufficient disproof of universal acceptance, and at least one candidate for representative of mainstream opinions. Berk and colleagues (2013) make a pretty convincing case though, so it may only be a matter of time, exposure to the evidence, and someone bothering to update Wikipedia.

For another, partially independent (probably cites some of the same studies), preexisting reference on the matter, check out Psychology Today's article, "The Brain on Fire: Inflammation and Depression: Inflammation and Its Effects on Mood" (Greenblatt, 2011, November 23). It too supports the potentially causal relationship, though I don't see any direct evidence of inflammation causing depression here. You may want to scrutinize it more closely than I have; if you find anything, please comment or edit!


Is back-prop biologically plausible? One of the common criticisms of Deep Learning is it's training algorithms, back-propagation of error (back-prop), has no biologically plausible implementation, despite evidence of something like it occurring in the brain. The default implementation is considered biologically implausible due to it's reliance on bi-directional synapses. However, there's been a lot of publications published showing implementations that should be plausible. Specifically, from section 2.2.2 of the review "Towards an integration of deep learning and neuroscience" and some discussion I've had:

Random synaptic feedback weights support error backpropagation for
deep learning
Direct Feedback Alignment (related to the
previous random weights idea) and it's inclusion in the Superspike algorithm
Deep learning with segregated
dendrites
Spike timing dependent plasticity (STDP) with
iterative inference and target propagation which is based off Difference Target Propagation
Kickback from "Kickback cuts Backprop's red-tape: Biologically plausible credit assignment in neural networks"
Generalized Recirculation from "Biologically Plausible Error-driven Learning using Local Activation Differences: The Generalized Recirculation Algorithm"
Contrastive Hebbian Learning from "Equivalence of backpropagation and contrastive Hebbian learning in a layered network"
Complex neurons from "Supervised and unsupervised learning with two sites of synaptic integration"
Using an attention mechanism from "A Biologically Plausible Learning Rule for Deep Learning in the Brain"
Layer-specific target from "GAIT-prop: A biologically plausible learning rulederived from backpropagation of error"

Are any of these implementable in spiking neurons, able to scale to more than two layers and have been shown to work on normal Deep Learning benchmarks such as MNIST or ImageNet?

Biological Plausibility of Back-Prop

No, the algorithm of back-prop (BP) isn't biologically plausible. However, there are other means which involve propagating the error through multiple layers of neurons in a feed-forward network which are biologically plausible. But before we evaluate these substitutions, let's review why back-prop isn't biologically plausible [1]:

1. Weight Transport Problem

BP uses the same weights for forward-pass and backward error propagation. But synapses are uni-directional.

2. Derivative Transport Problem

The derivative of each neuron is used to modulate the error signal in BP. Additionally, the derivative is propagated through each layer. How this derivative calculated by neurons and then propagated, is unclear.

3. Linear Feedback Problem

The BP feedback path is linear, but neurons aren't linear.

4. Spiking Problem

Neurons spike. BP is defined for rates.

5. Timing Problem

The BP error signal is expected to propagate instantaneously. Calculations and signal transmission in the brain do not happen instantaneously.

6. Target Problem

Most applications of BP rely on many examples with given labels, but where do those labels come from?

Replacements for Back-Prop

Most replacements for back-prop solve a subset of these problems, however none of them see to solve all of them. In "Spiking Deep Neural Networks: Engineered and Biological Approaches to Object Recognition", a method is constructed using the NEF that solves all problems except for the Target Problem. This means there are no replacements for BP that work for all cases where BP is applied, which is to be expected given this is what usually happens when biological plausibility is emphasized.

Beyond Back-Prop

However, it should be noted that there is more than back-propagation through fully-connected networks involved in Deep Learning. Specifically, the are a number of different architectures used, such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs).

CNNs aren't biologically plausible due to their reliance on weights being exactly equal across multiple locations.
RNNs rely on Back-Propagation Through Time (BPTT), of which there is currently no biologically plausible analogue [2].

This confusion between Deep Learning, neural network architectures and back-prop is reason that Yann LeCunn is trying to get people to adopt the term "Differentiable Computing" instead of "Deep Learning". At which point, the question must shift from "Is Deep Learning biologically plausible?" into "What aspects of Differentiable Computing are biologically plausible?" Which is much harder to answer, but at least we have a better question than when we started!

[1] Summarized from Eric Hunsberger's PhD Thesis "Spiking Deep Neural Networks: Engineered and Biological Approaches to Object Recognition"

[2] That being said, there are other means of learning (supposedly) biologically plausible recurrent neural network weights (FORCE training, Conceptors), however they don't resemble BPTT in any way. The discussion of these methods is outside the scope of this question.


What are effective strategies for increasing concentration and motivation when doing seemingly passive activities such as reading journal articles? Background

Unfortunately I am not a specialist in Cognitive Science I am just a regular CS student who has big interest in cognitive science.

I want to share with you some interesting observation I am sure all of us familiar with it, however I wonder whether there are some researches about this observation.

As a student I have to do some kind of activities all the time it can be reading papers, solving exercises, talking with classmates, thinking about problem in research. The problem is I find all these activities very  different in terms of engagement.

Let us consider solving exercises. This is an activity with a high level of engagement. When you do this you are very concentrated, I noticed that all my mental force are concentrated on this activity. I don't pay attention what happens around. I do hear and see people. However I don't pay attention to them, and I cannot control this state it happens unintentionally/ I wish I could go in this flow when I want, but I cannot. However I know what to do in order to get into this flow, just calm sit down get some exercises and try to solve it.

On the other hand reading papers has less engagement. I usually I set a goal to every day to read a paper (among all other tasks I plan to do every day) even when I don't need to read (of course there are days when I have to spend all day reading papers). The problem is when reading papers I need really quiet place, I get easily annoyed by talking people around me, the best place I found so far is library, but what really makes me crazy is not only people can shatter your peace but my mind doesn't want to concentrate on reading. I very often found myself daydreaming about something when reading  paper in this case I have to reread few last paragraphs, just because my mind didn't get them.

(Some thought about academical writings)I thought, what the reason of this problem, maybe we can start to write papers in different way, let say papers without obvious conclusion and result such that to cause you to think about it to derive the conclusion by yourself, maybe the best way to write two version of papers one is open ended and the second with results.

So far, I use the following technique to be concentrated when reading papers, before reading try do something with high engagement, solving exercise, programming a while and them start reading the paper.

Questions

What are effective strategies for increasing concentration and motivation when doing seemingly passive activities such as reading journal articles?

Increasing Concentration

A method that is geared espeacially towards reading scientific texts is SQ3R. SQ3R is short for survey, question, read, recite and review. So instead of "just reading" a text, one is supposed to

survey it first to grasp the basic outline by reading the abstract, introduction or table of contents
formulate questions as to what it is that one learns from the text

After these two steps you start "really reading" the text, which is the 3R- part of the method. After reading a passage, pause and summarize what you have learned. You can be critical and evaluate the things with respect to a certain criteria (e.g.: how much evidence does the author provide?).

Maybe you don't even have to take this method too literally. You might want to switch the order of the steps a little, or only do some of the things mentioned. Thinking about my way of reading papers, I often do some of the things, but not all of them. But that is of course just my personal experience.

Increasing Motivation

This is maybe the harder part of your question. Goal Setting Theory (Locke & Latham, 2002) might work. According to the theory, setting a specific and challenging goal leads to better performance than a vage and easy goal. In addition, setting a proximal learning goals is recommended, when "the knowledge or skill for attaining a goal is unknown" (Latham & Locke, 2007, p.293). This could be appropriate for a student reading papers, as he is probably not already familiar with the material. Setting a proximal goal also goes well with the notion of reading only a small protion of the text and then summarizing it (the 3R- part from above) as opposed to a more distal goal like: "I want to understand this paper". Using Goal Setting Theory amounts to a form of extrinisc motivation. It does not necessarily get you into a flow. So maybe this is not what you wanted when you asked the question. But after all, having to read a lot of papers as a student is an externally prescribed task.

References:

Latham, G. P., & Locke, E. A. (2007). New developments in and directions for goal-setting research. European Psychologist, 12(4), 290-300. PDF
Locke, E. A., & Latham, G. P. (2002). Building a practically useful theory of goal setting and task motivation: A 35-year odyssey. American psychologist, 57(9), 705. HTML


Two time points, control and experimental groups: What design is it? I managed to get myself confused on this one.
So I am planning to conduct an experiment within an organization. I want to explore effects of recognition on people's motivation. Recognition will be in a form of personalised recognition letter. Experimental group will receive the letter, control group won't.

I wanted to measure levels of intrinsic and extrinsic motivation in both groups prior to the intervention, and then post-intervention.

my IVs: intervention/no intervention; time period 1/time period 2
my DV: motivation

Questions:

is it independent groups design and I will need factorial ANOVA? Or time doesn't count as a variable?
or maybe I don't need to measure motivation levels before at all?

You could call it a 2 by 2 mixed design where condition is a between-subjects factor and has two levels (intervention, no intervention) and time is a within-subjects factor and has two levels (time 1 and time 2).

Regarding how to analyse this data, check out this question on Best practice when analysing pre-post treatment-control designs.


Toolbox for modelling visual search performance I'm looking for a toolbox to model visual search performance in a singleton search task based on line orientations (you need to find a line that is most different from all others in it's orientation).

The desirable features would be:

Feature-detectors that resemble real neurons.
Memory for distribution of distractors in feature space during previous trials.

Is there something like that? I also know that sometimes similar tasks are studied in texture discrimination. Maybe there is something close to what I need in that domain?

I'm assuming that you want some kind of "computer vision" model (in that you want to be able to provide the model with input stimuli in the form of an image), and that you want to predict some kind of behaviour? (e.g., RT from a search task). Fleshing out the different processes involved is not going to be trivial, so there probably isn't a "one-size-fits-all" "toolbox" for your problem.

Perhaps the "saliency map model" by Itti and Koch would be suitable. There are many more modern versions of this (including a MATLAB toolbox and a number of related models). While it is not necessarily the best, the advantages in this case are that Itti and Koch actually used an orientation pop-out task in their original paper (Vision Research, 2000). However, I'm not sure to what degree the feature detectors actually resemble neurons, and I don't think a memory component has been included.


Is there a relation between speed of executing a task and ones intelligence? I recently came across a code refactoring problem. Considering the risk of getting into a risky bug later I switched to my usual mode of think and solve it, rather than go and make the changes fast. However, another colleague of mine solved the same problem with a fast paced code changes approach. Both of them worked correctly. However, this incident made me wonder whether it was actually a problem with one's ability to solve the problem that led one to take a slower approach.

So my question is, whether intelligent people actually can finish their tasks faster, or whether it is the speed of working that gives an illusion of intelligence?

What is the significance of speed in finishing tasks in general?

Short answer: Processing speed is linked to executive functioning (EF) ability as well as specific, individual abilities (verbal, spatial, etc.), whereas generalized inspection time (IT) and reaction time (RT) to simple stimuli is more representative of general intelligence.

Detailed answer:
There are several factors that go into intelligence. Three specific, measurable paradigms are reaction time (RT), inspection time (IT), and speed of processing. Reaction time refers to the ability to respond to simple, familiar stimuli, and inspection time refers to the ability to identify a familiar stimulus. For example, if you are asked to press the space bar when you see a letter on the screen, your IT is being measured (time it takes to recognize the letter) as well as your RT (time it takes to press the space bar). Speed of processing is related to your ability to quickly perform familiarized or over-learned tasks, particularly when high mental efficiency is required. The difference: With RT and IT, you are asked to perform simple tasks that require little 'effort', yet they are (presumably) not tasks that are familiar to you. Speed of processing comes into play when you are asked to perform over-learned tasks that require more mental effort.

Though speed of processing has always been linked to intelligence in some form, it is now believed that RT and IT are related to general intelligence, whereas specific abilities (e.g. verbal abilities, spatial abilities) are moreso related to processing speed than to general intelligence. [1].

Speed of processing is often linked to working memory capacity. [2] This is demonstrated in those with certain learning disorders (such as ADHD), who often have working memory deficits and thus often process information slowly, regardless of IQ. Studies have also found that removing a time limit on testing removes the problems associated with dysfunctional working memory (such as lapses in attention). Thus it can be said that speed of processing is greater linked to executive functioning ability (which is a higher set of cognitive processes that working memory is a part of). [3]

So the answer to your question is that speed of processing is representative of specific abilities insofar as one's working memory capacity (and, by proxy, general executive functioning ability) is not dysfunctional, whereas the time it takes to identify and respond to a simple situation is linked to general intelligence.

In your particular instance, you were asked to answer an unfamiliar question with a non-trivial answer. Thus, it was speed of processing that was at play here, more closely linked to ability or knowledge of the topic at hand than general intelligence. The method in which the knowledge was acquired may have to do with intelligence, but there is too little context (and evidence) to support this.

Sources used:

[1] Placing inspection time, reaction time, and perceptual speed in the broader context of cognitive ability

[2] Conway AR, Kane MJ, Engle RW (December 2003). "Working memory capacity and its relation to general intelligence". Trends in Cognitive Sciences 7 (12): 547–52.

[3] "Working memory function in attention deficit hyperactivity disordered and reading disabled children". British Journal of Developmental Psychology 19 (3): 325–337.


What books should I study to have a decent understanding of psychology? Background:
I am a student currently doing my undergraduate degree (Electrical and Electronics, if it interests anyone). I am very much interested in studying psychology. I have read quite a bit on psychology, mostly on PsychCentral and PsychologyToday, but the knowledge I have is in bits and pieces. I want to have a well-organised knowledge of psychology like a student who is pursuing a career in psychology. The knowledge that I have right now feels like 'Googled knowledge' to me. I am of the belief that anyone should be able to learn anything he wants to, irrespective of whether he goes to college for it or not.

Question:
What subjects does a good university course on psychology have? (Yes! List all of them. Along with the years in which you studied them, starting from the freshman year!)
What are good textbooks for these subjects?

[It is not possible for me to get formal education in psychology. I would really appreciate it if you just accept this fact and not challenge it. :-)  The resources that I really have to study are the internet and books. (Yes, I'll buy them.) I want to make the best I can with what I've got.]

I’ve compiled a reading list based on the books I acquired during my undergraduate and graduate psychology programs. I’ve not listed the year I took the course because, with the exception of Introduction to Psychology being required first year and History and Systems being required in our last year (History and Systems was supposed to serve as a GRE study aid), the order of the courses were very flexible. Although there were some topics that were more likely to be taken in the second or third year, that was primarily due to how the instructor had structured the course; courses with more rigorous writing or exam requirements were reserved for later years. Because you will be conducting a self-study, you should generally be able to read/explore these topics in the order that you want.

Also, please note that all programs have a range of elective topics and areas of concentration that will vary. Finally, these books were all sufficient textbooks but are not the only option. In my experience, if you look at the top three psychology textbooks on Amazon for a given topic (e.g., social psychology) they will generally cover the same information and should meet your needs. I recommend using this list as a starting place to develop a list of psychology topics, rather than a strict list of books. You can read textbook reviews or consumer feedback and determine which book you prefer for a given topic. I have listed the most recent editions for the books that I used, but for most topics (except perhaps the neuropsychology books and abnormal [due to DSM-5]) you could safely use older editions dating back ten years.

Introduction to Psychology: This will provide you with an introductory overview of the field, including major theories and areas of psychology. The areas listed in this book (biological psychology, sensation and perception, consciousness, learning, memory, thinking/language/intelligence, motivation and emotion, lifespan development, human sexuality, personality, social psychology, and abnormal psychology) make up the core classes that were part of my undergraduate program.

Hockenbury, D. H., & Hockenbury, S. E. (2012). Psychology. Worth
Publishers. ISBN: 1429243678

Abnormal Psychology

Nolen-Hoeksema, S. (2001). Abnormal Psychology. McGraw Hill. ISBN:
0-07-235799-1
Barlow, D., & Durand, V. (2014). Abnormal psychology: An integrative
approach. Cengage Learning. ISBN: 1285755618
Halgin, R. P. (Ed.). (2000). Taking sides: Clashing views on
controversial issues in abnormal psychology. Dushkin/McGraw-Hill.
ISBN: 0-07-237193-5

Social Psychology

Brehm, S. S., Kassin, S. M., & Fein, S. (2001). Social Psychology.
Houghton Mifflin Company. ISBN: 0-618-12964-2

Biological Psychology/Neuropsychology

Kalat, J. (2012). Biological psychology. Cengage Learning. ISBN:
1111831009
Kolb, B., & Whishaw, I. Q. (2009). Fundamentals of human
neuropsychology. Macmillan. ISBN: 0716795868

Sensation and Perception: Neuropsychology specific to the five senses

Goldstein, E. (2013). Sensation and perception. Cengage Learning.
ISBN: 1133958494

Lifespan Development: The psychology of cognitive, emotional, and social development from birth to death.

Berger, K. S. (2003). The developing person through childhood and
adolescence. Macmillan. ISBN: 1-57259-429-2
Berk, L. (2013). Development through the lifespan. Pearson Education
India. ISBN: 0205957609

History and Systems of Psychology: While Intro to Psych will provide an overview of major areas and disciplines of psychology, this will provide a better sense of the development of psychology as a field and origin of different branches of psychology.

Thorne, B. M., & Henley, T. B. (1997). Connections in the history and
systems of psychology. Houghton, Mifflin and Company. ISBN:
0-618-41512-2

Behavior Therapy/Learning: This was an undergraduate introduction to classic learning theory and cognitive behavioral therapy.

Powell, R., Honey, P., & Symbaluk, D. (2012). Introduction to
learning and behavior. Cengage Learning. ISBN: 111183430X
Spiegler, M., & Guevremont, D. (2009). Contemporary behavior therapy.
Cengage Learning. ISBN: 049550906X
Seligman, M. (1975). Helplessness: On depression, development, and
death. A series of books in psychology. New York, NY: WH
Freeman/Times Books/Henry Holt & Co. ISBN: 0-7167-0752-7

Human Sexuality

Miracle, T. S., Miracle, A. W., & Baumeister, R. F. (2003). Human
sexuality: Meeting your basic needs. Prentice Hall. ISBN:
0-13-032658-5

Research Methods and Statistics: Included here because it is required in most programs, though it may not be of interest to you.

Smith, R., & Davis, S. (2012). The psychologist as detective: An
introduction to conducting research in psychology. ISBN: 0205859070
Gravetter, F., & Wallnau, L. (2006). Statistics for the behavioral
sciences. Cengage Learning. ISBN: 0-495-60220-5

My graduate work focused on clinical psychology and research, which this reading list reflects:

Sansone, C., Morf, C. C., & Panter, A. T. (Eds.). (2003). The Sage
handbook of methods in social psychology. Sage Publications. ISBN:
076192535X
Knapp, S. J., & VandeCreek, L. D. (2006). Practical ethics for
psychologists: A positive approach. American Psychological
Association. ISBN: 1-59147-326-8
Egan, G. (2013). The skilled helper: A problem-management and
opportunity-development approach to helping. Cengage Learning. ISBN:
0-495-60189-6
Dobson, K. S. (Ed.). (2009). Handbook of cognitive-behavioral
therapies. Guilford Press. ISBN: 978-1-60623-437-2
Beck, J. S. (2011). Cognitive behavior therapy: Basics and beyond.
Guilford Press. ISBN: 978-1-60918-504-6
Corrigan, P. W., Mueser, K. T., Bond, G. R., Drake, R. E., & Solomon,
P. (2012). Principles and practice of psychiatric rehabilitation: An
empirical approach. Guilford Press. ISBN: 978-1-60623-344-3
Sue, D. W., & Sue, D. (2012). Counseling the culturally diverse:
Theory and practice. John Wiley & Sons. ISBN: 978-0-470-08632-2


How similar are the brains of twins? I am currently reading undergraduate essays on biological dysfunction and schizophrenia. The students put a lot of weight in the fact that studies of monozygotic twins show only a 50% rate of concordance. How similar, in terms of anatomical structure and connectivity, are the brains of monozygotic twins?

Biondi et al. (1998) compared MR images of monozygotic twins and found that while the brains of monozygotic twins are not identical, they are similar. Relevant for understanding the concordance rate of schizophrenia in  monozygotic twins, Suddath et al. (1990) examined MR images of monozygotic twins who where discordant for schizophrenia. They found that the schizophrenic twin had enlarge cerebral ventricles and subtle anatomical abnormalities although the study seems to lack a control group of either both schizophrenic, both normal, or discordant on some other disease.


Pomodoro Technique vs Flow Pomodoro technique and entering into flow states are two commonly mentioned productivity techniques used by people studying or doing creative work. I have used these two techniques and I feel more comfortable with the flow state is it feels like a hyperfocused state.
Are there respectable scientific studies that support these techniques? Which technique is better?

Comparing the Pomodoro Technique and flow state is like comparing tomatoes and oranges. They are not two different techniques that you choose between. Pomodoro is a productivity / time management technique, and flow is a mental state. They are related in the sense that you could use Pomodoro to help get into a flow state, but you could also use some other technique for that purpose, which it sounds like you already do.
The canonical reference for flow is Flow: The Psychology of Optimal Experience by Mihály Csíkszentmihályi, who first used the term to refer to a mental state.
One thing to keep in mind about flow is that it's good for productivity, but not necessarily good for self-improvement. In a flow state, you tend to accomplish tasks without conscious thought, which accounts for the high productivity. But this also means that you aren't thinking about how you might get better. The process of deliberate practice could be seen as an anti-flow technique, where you consciously focus on each step of a task in order to improve. (1)
I didn't find any rigorous scientific research about the effectiveness of the Pomodoro Technique. This HBR article has some informal results, and anecdotally it's a popular technique among knowledge workers.


What sort of things are considered as "data" in cognitive science? I understand that the field is very broad, but I'm trying to arrive at a better idea of how different disciplines use the word "data".  For example, for computers it is:

  the quantities, characters, or symbols on which operations are
  performed by a computer, which may be stored and transmitted in the
  form of electrical signals and recorded on magnetic, optical, or
  mechanical recording media.

However, the same cannot be always so for data in the cognitive sciences. Can you give some examples of data in your research?

In The Personality Puzzle (2012), David Funder describes a taxonomy of four different kinds of data  that I've always found useful. The Personality Puzzle is a textbook in personality psychology, so its take on psychology is somewhat more as a social than biological science (though biology has its place too).

Briefly, here are the four kinds of data as described therein:

Self-reports: information provided by oneself about oneself, especially subjective info to which no one would otherwise have access; e.g., attitudes, beliefs, emotions, opinions, preferences, etc. This is often the domain of the Likert scale, though that's only one of very many assessment methods.
Informant reports: info provided about one person by others that is intended to describe the first person (not project info of interest about those reporting on that person). This info may also be subjective or socially constructed, but may be best operationalized as descriptions or judgments polled from people in a manner that welcomes this subjectivity. For example, a person's reputation or other characteristics may be assessed through the perspectives of others who may (or may not) know that person. Methods are otherwise similar to self-report in general.
Behavioral data: strictly objective and often observed in controlled environments or otherwise collected with a repeatable, classically empirical sampling method. This includes counts, measurements, or categorizations of behaviors like lever presses, choices or performance in a game or test, reaction time, stimulus discrimination accuracy, etc. These also include observations about autonomically regulated biological processes such as results from f/MRI, PET, CAT, EEGs, EKGs, heart rate or blood pressure readings, GSR, pupil dilation, etc., even enlargement of erectile genital organs (those studies are always interesting).
Life outcomes: also strictly objective, but generally less available to experimental manipulation, naturalistic, and often historical (i.e., already recorded or otherwise resolved to the state of interest). Examples include info about birth, graduation, employment, marriage, childbirth, divorce, death, etc., such as age at the time, location, partner, etc.


Why do we stress over the smallest things? I'm just curious to know: why do people stress over the smallest of issues? Not only is it common to almost everyone I know, but it is something that can drive people crazy.

For example, getting really stressed when you can't get something to work (even if it's a simple as a new program on your computer), or stressed when you misplace your keys at home and immediately blame your partner.

These rather simple things cause a great deal of stress (even for myself). While looking at my friends or family, stress over them cause me to realise how petty they are. Hasn't there got to be some cognitive reason for this?

I was having a discussion with my friend two days ago, when he told me these small stresses were a good thing, in that they make us forget about the big problems like recent job losses or events such as global warming.

Do we encapsulate ourselves in these petty matters as a means of protecting ourselves, or are we just selfish and ignorant?

This is highly individual, and related to the personality trait neurotocism.
From wiki:

  Individuals who score high on neuroticism are more likely than the
  average to experience such feelings as anxiety, anger, envy, guilt,
  and depressed mood.[2] They respond more poorly to stressors, are more
  likely to interpret ordinary situations as threatening, and minor
  frustrations as hopelessly difficult.
  http://en.wikipedia.org/wiki/Neuroticism


Where to find recent most important studies and researches? Is there any website or journal that publishes most significant recent studies and articles in psychology? I have access to EBSCO database, but there are thousands of articles and most of them of almost no importancy and I have no idea how to find those good and important ones.

By definition all journals publish "recent studies" because they are publishing all the time (either on a monthly/qaurterly basis). Sometimes, journals publish articles online months before in print. However i think your question is about finding the best articles, rather than journals, and there are a few tricks.

If you have access to any good search engine (google scholar, web of science, scopus), you can perform searches in there, and then rank articles by number of citations. This will give you the most important and talked about studies, although by nature they will be quite old studies, since in order to be the most cited they have to be out for a while.

Another good trick is to use webofscience / webofknowledge feature which lets you look at articles that have cited a specific paper. Say you find a classic study that you want to find more recent research on, webofknowledge will let you find recent studies that have cited that paper.

Alternatively a good place to start is looking through review articles or textbooks first. You can find these by adding "review" to your search terms, e.g. ("Social learning" AND "animals" AND "review").

Finally, looking at the web pages of important researchers in a given field would be a good place to find recent research, usually they will have fairly up to date lists of their recent research If you've done a bit of reading then you should be able to identify key researchers in a given field.


Why do people love nature? I wonder why we feel happy and comfortable when seeing the view of trees, green plants and flowers. Why do we admire sea, waves, fishes inside pure water and sun set? why do we love seeing the view of sky, moon and stars? Why people love nature even it is not real like a Picture on a computer?

To be more clear, People love seeing sea but the don't feel the same when they see a cup of water although they both are water.

Is it pure psychological reason? or There are some other biological reasons or chemistry of the brain?

Thank you very much,

People love nature because truth, nature/natural experience, and reality go hand in hand. Nature provides serenity, beauty, and calm. Our world of experience is what gives us, and provides for, life. Ultimately and fundamentally, the integrated extensiveness (and sensibility) of being and experience go hand in hand, as the self represents, forms, and experiences a comprehensive approximation of experience in general by combining conscious and unconscious experience. In fact, we always begin with typical/ordinary and common experience in establishing physical fundamentals/truths. Experience is the best teacher, and the creations of our thought that replace nature/natural experience, such as TV and mirrors, maximally reduce the integrated extensiveness of space/our experience. A true, extensive, integrated, and natural balance of being and experience is best. Balance and completeness go hand in hand. If we walk away from reality, reality walks away from us.


Does chewing gum mentally help basketball players make foul shots? I often see basketball players chew gum while making foul shots.

Does this help in their accuracy?
Any embodied cognitive explanation for this?

Chewing gum increases heart rate and blood pressure through muscular exercise (Farella, Bakke, Michelotti, Marotta & Martina, 1999) and enhances mental performance through improved delivery of glucose to the brain (Stephens & Tunney, 2004).

I could not find any references to embodiment playing a role in the effects of chewing.

Sources:

Farella, M., Bakke, M., Michelotti, A., Marotta, G., & Martina, R. (1999). Cardiovascular responses in humans to experimental chewing of gums of different consistencies. Archives of Oral Biology, 44, 835-842.
Stephens, R., & Tunney, R. J. (2004). Role of glucose in chewing gum-related facilitation of cognitive function. Appetite, 43, 211-213.


What is the brain power devoted to vision and haptics? I heard a talk by Vincent Hayward on the sense of touch as a multi-modal system, where he claimed that the brain power devoted to haptics is at least as big as the one devoted to vision. I have found some answers with respect to vision, which claim the percentage to be between 25%-33% of the neo-cortex. The cortical homunculus shows a sensory map of the body, where I guess the eye depicted is more related to the haptic part of the eye region, rather than the vision.

Can you confirm the percentage for vision?
What is the percentage for haptics?

Quotable sources would be fantastic of-course, but just a rough number would also do. I am mostly interested in the rough relative relation between the two modalities.

I'd argue that "brain power" is dangerously vague. Are you looking at weight, volume, area (including or excluding cortical folding), are you looking at just the cortex, or the whole brain?

At a lower level, are you counting just cell bodies, or do you count the processes that join them; do you just weigh the whole lot and try to figure out "power" that way? Do you count long axons projecting from the peripheral nervous system? Because touch would have a massive edge over vision if you counted the weight of those long, thick, myelinated axons in the spinal column.

None of those straight physical measures will give you an estimate of "power" because power implies other more cognitive factors; speed and capacity notably. Myelination gives speed of response to neurons, as does thickness. But a shorter neuron will be faster (more powerful?) than a longer one, and will also weigh less - clearly weight isn't a good estimator of speed, in fact the further information travels through axons the less "powerful" the whole system will be.

But that's just talking about speed - what about capacity? The overall number of indivudal points of input might relate to capacity, but the brain does plenty of post processing on visual input to allow it to process far more information than the eyes actually give it at any one time. Is capacity related to the number of synapses each neuron makes? This probably has something do to more with "depth" of processing than capacity, as it implies that each percept is sent to more places.

And beyond even speed, depth and capacity, what about learning? Which system has a greater ability to adaptively learn and pass learned information back into the decision making parts of the brain? How do you measure that? By the number of NMDA receptors in each system?

Also, what's this "touch" thing anyway? Are you talking about perception of heat, cold, pain (which sort, a$\delta$, perhaps C fibres)? Are you talking about sensations of pressure, like that felt when pushing a heavy object? Those sort of sensations are related more to proprioception than touch - they are all about sensing the environment's reaction to the body based on stretch receptors in the muscles, this is another type of input that makes up the heterogeneous sense labelled "touch".

Each of these types of pressure, superficial touch, pain, heat and cold have different afferent projections, and each has it's own substrate in the brain, with different architectures, different strengths and weaknesses - there is no straightforward "power" to compare any of those components of touch, much less to compare touch to something as remote as vision. This sort of question and attempts to answer it dangerously obscure the complex science behind both systems, giving a false sense of understanding where most of the above questions are unanswered, and possibly unanswerable.