Is it true that mirror neurons can make a man with an amputated arm feel sensation just by looking at someone else's arm, like Ramachandran said? In this Ted Talk Ramachandran sais that mirror neurons can make a person with an amputated arm feel sensation, is it true? And if so, why doesn't the brain feel a sensation by looking at someone else's arm when your arm is intact?

Mirror neurons exist and have been recorded from in primates and humans - these are cells that respond to the actions and inferred perceptions of others.
In papers by Ramachandran and others, they have shown that patients who have their arm anesthetized report experiencing a sensation of touch when they see someone else's arm touched:
Case, L. K., Abrams, R. A., & Ramachandran, V. S. (2010). Immediate interpersonal and intermanual referral of sensations following anesthetic block of one arm. Archives of neurology, 67(12), 1521-1523.
Case, L. K., Gosavi, R., & Ramachandran, V. S. (2013). Heightened motor and sensory (mirror-touch) referral induced by nerve block or topical anesthetic. Neuropsychologia, 51(10), 1823-1828.
These papers of course strongly suggest, but do not necessarily prove, that these phenomena occur due to mirror neurons.


Why does strobe lighting trigger seizures in photosensitive epilepsy? Photosensitive epilepsy (PSE) is a form of epilepsy in which seizures are triggered by visual stimuli that form patterns in time or space, such as flashing lights, bold, regular patterns, or regular moving patterns.

Why does strobe lighting trigger seizures in photosensitive epilepsy?

Seizures induced by stroboscopic lights are an example of reflex seizures. This type of epilepsy includes seizures evoked by touch and movements as well. The mechanism behind generalized reflex seizures (generalized epilepsy, as opposed to partial epilepsies, is accompanied by a loss of consciousness) was abstracted nicely by Ferlazzo et al., 2005:

  Patients with [] generalized reflex seizures appear to have regions of cortical hyperexcitability overlapping or coinciding with areas physiologically activated
  during specific sensory stimulations and cognitive or motor activities. When these areas receive appropriate afferent volleys and a critical mass of cortex is activated, an epileptic activity is produced that ultimately involves cortico-reticular or cortico-cortical pathways resulting in a generalized or bilateral epileptic event.

In other words, stimuli such as stroboscopic light evoke activity in sensory cortex. If the area of excitation is large enough and occurs in a region of the brain that has an epileptic focus (hyperexcitable cortex) than it may trigger a seizure characterized by an uncontrolled wave of activity spreading across the cortex.

Specifically for flashing-light induced seizures it is thought that seizures start in the visual cortex in the occipital lobe due to impaired cortical mechanisms of contrast gain control for certain visual patterns, producing an abnormal excitatory response to patterns of relatively low temporal frequency and high luminance contrast. Specifically, the seizures may be caused by a loss of control over high-frequency oscillatory processes that normally operate transiently to connect the involved neural assemblies. Generalized seizures can occur if normal excitation of visual cortex involves a ‘critical mass’ of synchronized activity in a cortical area with synchronization and subsequent spreading of excitation from the occipital lobe trigger zone (Parra et al., 2005).

References
- Ferlazzo et al., Brain (2005); 128: 700–10
- Parra et al., Curr Opin Neurol (2005); 18(2):155-9


Why is the sound of fingernails on a chalkboard so intolerable? I am curious as to what current research shows regarding why scraping noises such as fingernails on a chalkboard, a knife/fork scraping against a plate, metal grinding against metal or stone etc are so intolerable to humans. In doing some initial research for this I read the wikipedia article on Sound of fingernails scraping chalkboard (there's a wikipedia article on everything!) but I am looking for more references or updated research.

From the reading I have done, there seems to be two competing theories:

The sound is reminiscent of the warning calls of primates and triggers an evolutionary response left over from an earlier age designed to protect us from predators
The sound hits a resonante frequency of the inner ear which causes it to be particularly intolerable

To me personally the first theory makes very little sense. Hearing the warning calls of primates does not personally trigger anywhere near the same feelings of extreme frustration and irritability that I feel when I accidentally scrape my knife on my plate. Furthermore the feelings caused by the "nails on a chalkboard" sound do not at all trigger a fight-or-flight response or put me on edge as a loud noise or something that startles me does. If anything it is almost paralyzing, which seems counter to the evolutionary theory.

How accurate is the wikipedia article? Is there any newer / more widely accepted research available on what causes the sound of "fingernails on a chalkboard" to be so intensely awful to human beings?

My initial thoughts are that the sound produced a dissonant sound, that is (from the link):

  "An unstable tone combination is a dissonance; its tension demands an onward motion to a stable chord. Thus dissonant chords are 'active'; traditionally they have been considered harsh and have expressed pain, grief, and conflict."

—Roger Kamien (2008)

According to the article "Psychacoustics of a chilling sound", (Halpern et al. 1986), it is the low frequency components of the sound that cause the most discomfort. In their tests, removing the low frequency part in a digital simulation, made the sound a bit more bearable.

In the conclusion of the article, there is some support for the Wikipedia article that Josh Gitlin linked to in his question:

  the complex acoustic stimulus pictured in Figure I
  very closely resembles some of the spectrograms of warning
  cries emitted by macaque monkeys (Green, 1975). As
  another possibility, the signal may be similar to the vocalizations
  of some predator.


If orgasm triggers bonding and feelings of love, why don't people continue to stay in love? I am a bit confused by the effects of orgasm in bonding; everything I seem to read seems to be a bit careless with the truth and does not mention why people fall out of love or why people who are in relationships cheat, etc. Could anyone please elaborate?

Surely, orgasms do release drain out dopamine but you're forgetting another important factor in dopamine release, which is novelty.

Ever heard that couples get bored of sex after an year or two? It's because they find it routine and boring. Cheating (an e.g) gives you the thrill of novelty.

The same activities which we find thrilling / rewarding will not remain that way. It has something to do with the sensitivity of dopamine receptors. Take novelty seekers (e.g) they tend to find novel activities thrilling.

The worst scenario occurs, when a person no longer finds any activity interesting. That is nothing but Anhedonia.

EDIT: I'm sorry, but I just realized that staying in love is a bit different from enjoying orgasms after reading this. A relationship is far more complicated than just producing enough dopamine.

Release of enough endorphins, helps you stay happy, if you're happy you're likely to not hate other people around you, if you do not hate them, you're likely to like them by releasing enough oxytocin (physical touch etc.). Apart from that, a sense of responsibility and well being comes into picture when you're serotonin levels are moderate.

Definitely low dopamine levels is a cause, but not the only cause of cheating etc. Any imbalance of neurochemicals causes not only relationships fall, but also other unhealthy / anti social behavior.


Do female victims of rape have an increased risk of becoming a sex offender? It's said that men who are molested as children often become molestors when they get older. Is the same true of women who are raped? Is a female victim of rape more likely to become sexually warped in some way, e.g. initiating incest, pursuing children, dressing "slutty", protecting someone who molests children?

I figure if it's true that male victims of sexual assault often become predators, then it's likely true of female victims of sexual assault as well. The victims become the victimizers.

Our social constructs play a big role in influencing how we respond. As with most common cognitive mechanisms - confluence of environmental triggers meet a biological predisposition.

Regarding belief systems: in many traditions, femininity is guarded due to its relationship to motherhood. Women are thought not to be sexual. Masculinity is sexualized in a different manner, which perpetuates violence against women as well as the association of masculinity to aggression. Women who have been abused may not become aggressors- but instead are re-victimized. The idea that they will protect a perpetrator like a boyfriend or husband is a coping mechanism of sorts. On a cognitive level it is a fear-based response.The response is different for men and women due to evolutionary traits as well as learned behavior.

Many people experience sexual trauma and are not warped or broken or damaged, in part because their learned behavior is based on a positive role model who has taught proper coping mechanisms which increase protective factors.

I do believe, as a survivor of sexual violence myself, that there is a tendency to want to re-appropriate one's own sexuality and also to engage in a process of externalization through sexual experience and behavior in a way that might be labeled as deviant by others. Sometimes people respond by presenting as less feminine or less masculine as a way to distance oneself from the sexualization of their gender in order to feel safe. Sometimes people may respond by presenting self as hyper-sexual as a way to re-appropriate their own body. Of course - it's contextual. What one person chooses to present at one point and time can easily change as a reflection of the social construct.

Here is an interesting article examining the question of gender and sexual trauma.
Turchik, Hebenstreit, & Judson (2015)

You might need an academic login

This one focuses on the differences between the two genders: Cashmore & Shackel (2014)


Importance of Neural Synchrony to Cognition Is there a consensus on whether computation using Neural Synchrony is reasonable or not? In "How to Build a Brain", Chris Eliasmisth cites Yuko Munakata and R. C. O'Reilly as saying that "the available evidence does not establish that the observed synchrony of firing
is actually used for binding,instead of being an epiphenomenon" to dismiss current architectures such as LISA and DORA which use synchrony. Yet, there still seems to be papers published on using neural synchrony for computation. Additionally, Thagard still seems convinced of their importance saying that "spiking neurons have psychologically important qualitative properties such as becoming synchronized with each other, and neural synchrony has been proposed as a crucial ingredient in inference, analogy, and consciousness".

Are the authors of these new papers naive or is there convincing evidence for the meaningfulness of synchrony that Chris and I are missing here?

References:

O’Reilly, R. C. & Munakata, Y. (2000).Computational Explorations in Cognitive Neuroscience: Understanding the Mind by Simulating the Brain (1 ed.).
Cambridge, MA: The MIT Press.

As you have already hinted at, the issue is controversial. I could leave it at that and say "no, there is no consensus", and it would be a true answer, but it wouldn't be satisfying, wouldn't it? Instead, I'll briefly define the topic, give a few examples, and then a few recent criticisms. My answer will be weighted somewhat towards "cognition" instead of "computation", however different you consider them. It's more of a safari than a good answer I fear, I hope you're getting something out of this.

Neural synchrony is usually used to refer to oscillatory alignment; that means, some sort of oscillation occurs in a population of neurons, for example, an alpha rhythm as a ~10 Hz pulse; and neuronal synchrony is both, on the individual level, the degree to which individual neurons either take part in this oscillations, and/or align their spiking behaviour to certain parts of this oscillation, and on the population level, how other neuronal populations are aligned with this oscillation.

What is doubtlessly true is that the brain is full of oscillations. We know that at the very least since Hans Berger discovered the alpha wave back in the 1920s. When someone closes their eyes, we quickly see the 10 Hz rhythm. But once they open the eyes, or are disturbed in any way, it quickly disappears. Are these oscillations important per se, or just an epiphenomenon? Berger himself assume them to be the direct manifestation of unified brain state. But Berger was a bit of a crank. The well-respected British researcher and Nobel price laureate Lord Adrian who first replicated this finding assumed the 10 Hz rhythm was simply the "idling of the brain", the very absence of computation.

One contemporary researcher who assigns a functional and active role to the alpha rhythm is VanRullen, and I think much of his work is very interesting.

Let's look at some of the rather basic ways how oscillations and timing are relevant in the brain. First, timing in general. Our original understanding of neural communication (in part unveiled by aforementioned Lord Adrian!) focuses on the concept of rate coding and population coding; the net amount of spiking activity in a neuron, or in a population, is what matters. This is for example what happens in the peripheral nerve cells; when heat or pressure or pain are applied to the skin, the responding neurons directly communicate the degree of heat or pressure or pain by how much they ramp up their firing (at least at first, before Spike Frequency Adaption sets in).

Initially, this was seen as fully consistent with Hebbian learning - the more one neuron fires, the stronger the synapses with its targets become. But then Bi & Poo discovered Spike-Time Dependent Plasticity (STDP), and now everything is a bit more complicated. Remember Hebb's Law says

  When an axon of cell A is near enough to excite a cell B and repeatedly or persistently takes part in firing it, some growth process or metabolic change takes place in one or both cells such that A's efficiency, as one of the cells firing B, is increased.

Hebb's Law goes beyond saying A has to fire lots. It says, A's firing has to cause B's firing. And one component of causation is temporal precedence; so A's firing has to occur before B's firing for increasing synaptic strength. And this is just what Bi & Poo observed; only when A's spikes arrive in a short temporal window before B's own spike does Long-Term Potentation occur. If however B's spikes happen a bit before A's spikes, Long-Term Depression occurs.

So the temporal order of spikes matters. Neurons causing others to spike gain more influence over them, and neurons who're followers, not leaders are demoted.

Another bound for plasticity is of a neurochemical nature. Levels of catecholamines (neuromodulators) regulate if the hippocampus will encode an incoming stimulus, depending, for example, on its novelty. So only if neuromodulator levels are up does incoming information lead to lasting adaptations. During sleep, were we assume reconsolidating to happen, we observe that the brain stem sources of catecholamines (like the neurotransmitter norepinephrin and dopamine) are temporally correlated with the slow wave occurring during sleep. Specifically, Locus Coeruleus neurons spike right at the onset of the transition to the Up state. It seems the cortical oscillation is timed so that active states co-occur with high catecholamine levels.
This is a form of temporal coding called phase coding. The phase of the ongoing oscillation matters with respect to the incoming spike. It is also observed, for example, in the theta oscillation in the hippocampus. A range of theories exist for a possible function of theta phase locking; examples are that certain theta phases again indicate more receptive states (so that incoming information has a higher chance of being encoded during certain parts of the theta oscillations), or that the part of a theta phase a neuron spikes at indicates how important the information this neuron is encoding is.

Beyond phase coding, we find Singer's very popular binding by synchrony. How do to parts of the brain communicate to each other that they are "talking" about the same thing? Well, by alignment in the gamma band, that is, by phase locking of the two populations to the same ~40 Hz rhythm.

But how believable is all this?

There are many theoretical objections to specifically high-frequency binding by synchrony. For example, the power of oscillations fall of over distance as a function of its frequency; that means, slow oscillations travel far, but synchrony in fast oscillations cannot be sustained over long distances. (Slow oscillations are simply too slow for binding by synchrony.)

Another question is if there are even any gamma oscillations at all, if they are truly clock-like wave patterns or if they are simply a methodological artefact - traces of the sensitivity of the Fourier transformation to asynchronous activity, or filtered noise.

At least for humans, gamma band synchrony findings have become strongly suspect as it was shown that these patterns are better explained as the EEG traces of small eye movements or micro-saccades.

But this must not spell the death of all theories for a functional role of timing and oscillations, of all temporal codes and phase codes. In STDP, we have clear, anatomically sound evidence for the importance of temporal order in spiking, and simple evolutionary principles suggest neuronal populations will exploit such phenomena. However, the field is diverse and controversial. There is no universally accepted phenomenology, methodology, or theory. We have tidbits and fascinating findings, but nothing coherent. Cortical oscillations are sill mostly a riddle.

I think most recent contribution is the discovery of Cross-Frequency Phase Coupling by Canolty et al. They observe that the amplitude of the fast (gamma) oscillations depends on the phase of the slower theta or delta rhythms. The basic finding is quite similar to the observation of LC spike/cortical state phase coupling noted earlier, but now we observe this in the awake animal. And a clear proposal for a functional role of this mechanism has been made, too; I can simply quote the abstract of Lakatos et al.:

  Whereas gamma-band neuronal oscillations clearly appear integral to visual attention, the role of lower-frequency oscillations is still being debated. Mounting evidence indicates that a key functional property of these oscillations is the rhythmic shifting of excitability in local neuronal ensembles. Here, we show that when attended stimuli are in a rhythmic stream, delta-band oscillations in the primary visual cortex entrain to the rhythm of the stream, resulting in increased response gain for task-relevant events and decreased reaction times. Because of hierarchical cross-frequency coupling, delta phase also determines momentary power in higher-frequency activity. These instrumental functions of low-frequency oscillations support a conceptual framework that integrates numerous earlier findings.

Here is a video presentation on the topic.


How does the brain learn what something is for the first time? I'm trying to understand how the idea of what a thing is originates in humans.

For example, in computer science, it is possible to know what an object is and what it does, by examining its "parent/ancestor" objects with concepts of inheritance:

  In object-oriented programming (OOP), inheritance is a way to reuse
  code of existing objects, or to establish a subtype from an existing
  object

and polymorphism, where objects may share similar function:

  Subtype polymorphism, often referred to as simply polymorphism in the
  context of object-oriented programming, is the ability to create a
  variable, a function, or an object that has more than one form. In
  principle, polymorphism can arise in other computing contexts and
  shares important similarities with the concept of degeneracy in
  biology

What makes me interested in this is that human children do not learn all words at once - there's a slow, but steady exposure to new stimuli, which are quantified, remembered and become available as concepts and words. The exact order of exposure is unknown, but if I remember correctly, most people know about 20000 words, and use about 6000 in daily interactions.

For example, a child has never seen a potato. A child sees a potato for the first time.  A child has neither an idea nor a word for a potato. Now the child's brain has to create an idea of what a potato is.

The question: When a child is exposed to a new stimuli, as in the example above, does the child's brain:

create a brand new representation of an object
or does a person's brain modify and re-purpose the "closest matching"
idea and add extra attributes to it? (a potato looks like a brown rock)

In other words, has there been any research that found evidence for case 2: a "common ancestor" for ideas and objects within a person's mind? (if a person forgets "rock", then the person also forgets "potato").

I don't know where to begin a search for the answer. Are there some keywords that I can use? Maybe scholarly articles on cases of unusually high working memory capacity for related objects?

According to current models of human concept learning, the answer to your question is both.

Think of a simplified domain in which every object consists of only several features, and therefore can be visualized as a point in some multidimensional feature space. For example, the features that define objects might be its size, shape, color, and weight. Furthermore imagine that objects tend to be clustered throughout this space according to what category they belong to, because members of the same category are generated by the same natural process.

So based on current models, a novel stimulus is compared to existing concepts and is either placed into the concept (cluster) that it's closest to, or if it's insufficiently close to any existing concept, then a new concept will be created. This is the basic idea of current Bayesian theories such as the Rational Model, which treats human category learning as a problem of probability density estimation, and its contenders such as  SUSTAIN.

Here's a video lecture by Josh Tenenbaum, a leading researcher in both machine learning and cognitive science, in which he gives an excellent introduction to a number of these issues and many more.


Principles of grouping neurons This is an overview question. I wonder which principles of grouping neurons into higher units are there, and which principles I have overseen.

neurotransmitter systems: all neurons that release or react on a given (class or set of) neurotransmitters
functional systems: all neurons (and groups of neurons) that are involved in performing a given task or function
regions: all neurons in a given 3-dimensional volume of the brain, e.g. a voxel
nuclei etc: a group of nearby neurons which somehow belong to each other (morphologically or synaptically, possibly encapsulated by some "membrane")
clusters: a group of neurons (nearby or not) that are strongly interconnected by synapses
independent sets: of a multipartite subgraph of the brain network
groups defined by other graph-theoretical measures
pathways: a somehow distinguished (e.g. shortest) synaptical route from neuron (group) A to neuron (group) B
cortical layers
cortical columns

To make my question specific and not too broad, let me just ask the following:

  Which principles of grouping neurons is missing in the list above?

(There should be not so many.)

For each classified group of neurons some numbers will be interesting to know:

How many neurons do they typically comprise?
How many groups of the same kind are there?
How strongly do they overlap?

In anatomy/physiology, there are 2 major categorizations of the nervous system:

Central nervous system (brain + spinal cord) and peripheral nervous system (all other neural structures)
Somatic nervous system, which controls skeletal muscles and skin, and and autonomic n. system, which controls internal organs, blood vessels and glands and is further divided to sympathetic and parasympathetic system. Both the somatic and autonomic system have motor neurons that control muscles and sensory neurons that convey sensory signals.

Image source: Wikipedia, creative commons license

Neurons can be further categorized by neurotransmitters involved (dopamine system, acetylcholine system, etc.), and by various anatomical and functional subsystems.

Examples of anatomical and functional structures formed by neurons:

Cortical areas (functional areas of the brain cortex) (Lumen)
Main parts of the brain: cerebrum, cerebellum and brainstem, some of which can be further divided into hemispheres, lobes and folds
Deep structures of the brain: thalamus, hypotalamus, hypocampus, amygdala, corpus callosum, limbic system, pituitary gland, pineal gland, and structures collectivelly called basal ganglia, which include the caudate, putamen, and globus pallidus in the cerebrum, the substantia nigra in the midbrain, and the subthalamic nucleus in the diencephalon (Mayfield Clinic).
Areas containing either neuron cell bodies or axons: gray matter (cell bodies) and white matter (axons) of the brain and spinal cord (Indiana.edu)
Histological areas of the brain: layers and columns (Wikipedia)
Nuclei of the cranial nerves (Wikipedia)
Centers (cardiovascular center, reflex center for cough, vomiting, etc.) in medulla oblongata (Wikipedia)
Corticospinal tracts (Wikipedia)
Pathways - the term is usually used for cranial nerves: visual pathway, auditory pathway, etc.
Ganglia - anatomical structures containing neuron body cells in the peripheral nervous system (Wikipedia)
Nerve plexuses - branching networks of intersecting nerves (Wikipedia)
Reflex arcs (Wikipedia)


List of conflicts humans can have I am searching a list of conflicts humans can have.

Here I found some 7 types of conflicts

Person vs Person
Person vs self
Person vs. Fate/God(s)
Person vs. Nature
Person vs. Society
Person vs. the Unknown/Extraterrestrial
Person vs. Technology/Machinery

But the refer to literature, not to psychology.

This wikipedia page contains a list: Conflicts (Social science) But this is just a list of unrelated articles.

Is there a valuable book/article which provides an overview over the different conflicts humans can have?

In regards to a list, if there is anything like that it is simply internal and external conflicts (which encompasses your list, as well as deals with overlapping components of your list).

Furthermore, there are three major paradigms of sociology, one of which is conflict theory. This examines stratification (ie through classes) and inequality (ie of resources), largely being credited to Karl Marx. In general, the paradigms are different lenses with which to examine issues in society (gender, class, race, etc.).


Is there any empirical support evaluating the fast phobia cure? There have been several papers going against the effectiveness of NLP. One aggregate paper is referenced in the Wikipedia article on NLP, namely Witkowski (2010).
However, NLP seems to encompass a wide variety of techniques.
I'm particularly interested in the fast phobia cure.

Is there any empirical support for or against the fast phobia cure?

References

Witkowski, Tomasz (1 January 2010). "Thirty-Five Years of Research on Neuro-Linguistic Programming. NLP Research Data Base. State of the Art or Pseudoscientific Decoration?". Polish Psychological Bulletin 41 (2). doi:10.2478/v10059-010-0008-0.

Witkowski has written several articles reviewing NLP (2010, 2012) and in each case has found few studies that indicate clear support for the technique. He also argues that the articles which indicate no support for NLP are generally of stronger methodological quality than those which do not. The fast phobia cure is not directly mentioned in either paper.

Jemmer (2005) provides an overview of the fast phobia technique, and describes a handful of studies which have used and reported on it; you may find his paper to be a starting point for identifying information on the technique, although it seems most of the studies he cited are in the NLP database and it is unclear if they have been published in peer review journals. Jemmer's article acknowledges the lack of evidence, and is primarily written from a theoretical perspective.

A 2011 review identified three peer-reviewed studies and 1 dissertation that examined NLP techniques for phobia and reported the techniques to be effective (Biswal & Prusty). The review does not go into detail as to the exact NLP techniques used in these studies but this may be a source of literature for further reading. Biswal and Prusty (2011) also highlight some of the theoretical issues which have hampered NLP research and provide a helpful overview distinguishing some of NLP's techniques from other psychotherapeutic techniques.

A 2012 review examined 10 peer-reviewed NLP studies which were either randomized controlled trials or pre-post designs, 3 of which assessed fast phobia techniques (Sturt et al.). Some effects were found in terms of decreased fear or anxiety, but these generally occurred in all treatment groups (not just NLP) or in studies with no control group. Most outcomes were self-report measures. However, these studies may be the most relevant to your initial question.

Overall, the consensus of these reviews indicates that there is little evidence to support the use of NLP in general, including the fast phobia cure. However, the studies also note that the lack of high quality research may indicate more rigorous studies are needed before discarding the NLP concept entirely. Additionally, the reviews point out that several NLP phobia techniques are similar to other psychotherapy techniques for treating phobia, so there may be stronger evidence for those subcomponents elsewhere in the literature. These reviews should provide a good starting point and working vocabulary if you are interested in researching those subcomponents.

Biswal, R., & Prusty, B. (2011). Trends in neuro-linguistic programming (NLP): A critical review. Social Science International, 27(1), 41-56.

Jemmer, P. (2005). Phobia: Fear and loathing in mental spaces. European Journal of Clinical Hyponosis, 6(3), 24-32.

Sturt, J., Ali, S., Robertson, W., Metcalfe, D., Grove, A., Bourne, C., & Bridle, C. (2012). Neurolinguistic programming: A systematic review of the effects on health outcomes. British Journal of General Practice, November, e757-e764.

Witkowski, T. (2010). Thirty-five years of research on neuro-linguistic programming. NLP Research Database. State of the art or pseudoscientific decoration? Polish Psychological Bulletin, 41(2), 58-66.

Witkowski, T. (2012). A review of research findings on neuro-linguistic programming. The Scientific Review of Mental Health Practice, 9(1), 29-40.


Where does action based on thought originate within the human brain? A rather basic question, but I don't see answer in Google, so here it goes: Humans have thoughts, sometimes these thoughts carry with them motivations to act, urges, cravings, etc. All these can make a person start moving to accomplish something.

  For example: "I'm rather bored, I think I will go get a snack". What
  happens the moment I cross the threshold from thinking to actually
  getting up to get a snack?

What happens the moment the person starts to act based on a thought? Where in the human brain does a thought trigger action?

Update: In response to an answer suggesting that in many cases action comes first and rationalization for action comes second:

The kind of action that I'm talking about comes after a longer period deliberation, where the current state is being weighted against the benefit of the action to take.

For example in the situations below, a person can deliberate for minutes:

A person is in bed and is very close to sleep, being comfortable and relaxed. Loud noises from the outside disturb the person's attempt to fall asleep. In this case the person can experience conflict between staying in bed (comfortable but disturbed) or going to find earplugs / shut the windows (uncomfortable, but potentially lessening the disturbance)
A person is trying to meditate, thus relaxing the body and unfocusing the mind. An itch on the foot is disturbing the meditation. Such person can either continue the current state while ignoring the discomfort or scratch the itch and potentially lose the meditative state.

In the examples above, two conflicting courses of action are evaluated by the brain. Due to the ongoing discomfort, it is possible to stay in this state of "almost making a decision" for quite some time.  At a certain point the scale can tip into taking action to resolve the discomfort. What is it that causes the person to take action as opposed to inaction?

There are many areas of the brain that are associated with planning complex behavior. This is because planning and executing are mediated by the brain's capacity for executive functioning, and EF is further associated with many areas of the brain -- in this case, the the frontal lobes, the prefrontal cortex, the caudate nucleus, and the putamen all seem to play a role.

What typically happens is that a thought is formed ('I'm hungry, I want a cookie', etc.), and then potential actions are envisioned and evaluated for their predicted effect, in line with the common coding theory of the relationship between perception and action. From a functional standpoint, the caudate nucleus selects the appropriate action based on an evaluation of the outcome of the action. [1] [2]

The more complex the task, the more cognitive strategies you may need to use, and these are mediated by your executive functioning ability. Cognitive shifting or task switching, information updating and monitoring ("updating"), and inhibition (or the 'tuning out' of irrelevant stimuli) all play a role in planning and executing complex tasks, or sequences of behavior. [3] For example, the ability to act in momentarily unpleasant yet beneficial ways (i.e. going to the gym) requires cognitive inhibition of more immediately gratifying, yet irrelevant stimuli (i.e. sitting on the couch, eating pleasurable food). For tasks of this nature, the frontal lobe plays a greater role.

Certain neurotransmitters also play a role in your ability to stay focused and dedicated to a task. Dopamine in particular is responsible for motivation (including the motivation to act), and norepinephrine is responsible for vigilance of attention, thus increasing the likelihood that an action will be performed and completed successfully. With a reduction in these neurotransmitters, you may demonstrate attentional shifts. Long-term, uncontrollable shifts in attention are often representative of an underlying disorder, such as attention-deficit disorder.

Sources used:

[1] Grahn, Jessica; John A. Parkinson; Adrian M. Owen (12 April 2009). "The role of the basal ganglia in learning and memory: Neuropsychological studies". Behavioral Brain Research 199 (1): 53–60.

[2] Oury Monchi, Michael Petrides, Antonio P. Strafella, Keith J. Worsley, Julien Doyon (Feb. 2006). Functional role of the basal ganglia in the planning and execution of actions. Ann Neurol. 59(2): 257–264.

[3]  Miyake A1, Friedman NP, Emerson MJ, Witzki AH, Howerter A, Wager TD. (Aug. 2000) The unity and diversity of executive functions and their contributions to complex "Frontal Lobe" tasks: a latent variable analysis. Cogn Psychol. 41(1):49-100.


Resources for learning how best to learn fine motor skills I am interested in learning how best to learn a fine motor skill, in this case, playing a musical instrument. Presumably there are more or less effective ways to go about it.

Possible factors that I can think of include:

Practice schedule. e.g. how often? how long? time of day? how long does it take for the neural changes to occur? does it happen during rest?
Practice structure. e.g. include breaks? how long between breaks? how long should each break be? how many breaks?
Practice speed. e.g do something slowly first? how slowly? for how long? when to increase speed?
Practise focus. Are there things that are worth specifically directing attention to?
Non practise elements. Are there things that can be done outside of practising that help, e.g. visualisation? other exercises?

I appreciate that this is many questions rolled up into one, but my main point is how do I go about learning how best to learn fine motor skills, ideally outside of a teaching institution. Is there a good book on the subject? What even is the name of this subject?

I think the search term you're looking for is 'skill acquisition', but it's a super broad area. There's relevant stuff in memory, second language acquisition, sports science, and teaching surgeons surgery... it's all over the place.

There's a pretty sizeable literature looking just at music specifically, one review article that hits a few of the points you mentioned is this one:
 Hallam, S., Rinta, T., Varvarigou, M., Creech, A., Papageorgi, I., Gomes, T., & Lanipekun, J. (2012). The development of practising strategies in young people. Psychology of Music, 40(5), 652-680.

The references (and the people citing it) are probably as useful or maybe more useful than the specific results they present, although those are interesting too!

If you want something more pop-sci and readable with a bit of a human story The Art of Learning by Josh Waitzkin is a nice one. It's a personal story, not a scientific study, but not everything has to be an RCT, gotta generate hypotheses from some life experience first, right?

I think you might find that the main take-homes are pretty common sense... feedback is important, get lots of it and get it as close to real-time as possible, distributed practice schedules are better than cramming, and 'chunking' is super important, so focus on learning sensible `atoms', automatize them, and then combine them.

I know this answer only really scratches the surface of a huge area but anyway I hope it helps.


How can positive and negative mindsets influence interpersonal relationships with others? I want to know how positive and negative mindset can influence interpersonal relationships with others.  For example: if you have a negative mindset, would people not want to relate with you?

The lexical approach may assist. The lexical hypothesis states that, ‘All aspects of human personality, which are or have been of importance, interest or utility, have already become recorded in the substance of language’(Cattell, 1943) and, ‘When an idea is important, people are likely to have a word for it … the more important something is, … the more words there are likely to be’(Miller, 1996). The atlas of personality, emotion and behaviour uses a lexical approach to visualise words using the axes of affiliation and dominance (Mobbs, 2020).
Relevant synonyms are:

positive: assured, beneficial, clear, complete, confident, constructive, convincing, decisive, effective, persuasive, practical, pragmatic, proper, real, regular, sanguine, satisfied, sure, unreserved, useful, wholehearted, worthwhile.

negative: adversarial, adverse, damaging, derogatory, destructive, dismissive, disparaging, hostile, inhospitable, prejudicial, untoward.

At face value, people with the traits associated with positive are more likely to attract others.  The traits associated with negative are more likely to dissuade others from associating with the individual.
The visualisation of positive and negative according to the atlas approach is shown below.

References
Cattell RB. The description of personality: basic traits resolved into clusters. J Abnorm Soc Psychol. 1943; 38: 476–506. https://doi.org/10.1037/h0054116
Miller GA. The science of words. New York: Scientific American Library; 1996.
Mobbs AED (2020) An atlas of personality, emotion and behaviour. PLoS ONE 15(1): e0227877. https://doi.org/10.1371/journal.pone.0227877
Declared interest: I am the author of the atlas paper.


How do congenitally deaf and mute people think? If a person is born deaf and dumb, how can they think? In "what language" do these people think? Do they develop their own inner language?

Unfortunately I have not found an answer, and I actually doubt it has ever been elucidated.

Short answer
The inner voice of congenitally (pre-lingually) deaf people who have not received treatment like cochlear implantation, is not sound-based. Instead, it is mainly based on visual images, such as sign-language or printed material.

Background
According to an anecdotal report published in the Independent of a congenitally deaf person, who deliberately refused cochlear implantation or other treatments, the inner voice is a visual entity taking the form of sign-language, or visual images, or sometimes printed words.

An interesting report from UCL investigated congenitally deaf people suffering from positive psychotic symptoms. In normal-hearing people, positive psychotic symptoms typically involve hearing voices (auditory hallucinations). In congenitally deaf folks, who obviously never had the chance to hear any voices in their lives, these auditory hallucinations were described as

  [Not consisting of] sounds, but [...] the gender and identity of the voice [were recognized. They were] image[s] of [...] voice[s] signing [,] or lips moving in their mind.

Source
- The Independent, December 21, 2013, UK


Can brainwaves from EEG be used to measure enjoyment of media? It seems to be very hard to figure out automatically, what content I will enjoy and what content I will not enjoy.

Of course, there are methods that require me to sit in front of a computer and press yes or no when I see content to determine whether I like it or not. But not only is it tedious, it is also not precise. It is not precise, because there are always more emotions involved, it is about the state of emotions and not a single emotion.

Therefore my idea is this:

While I am watching pictures or media of other kind, my brain waves are measured. Having seen a lot of photo, there will be a certain correlation to a photo being seen and a brain reaction. I could use this information to predict which media will evoke certain emotions in me. The only drawback is that this is not a static database that can be used over time but due to my increase of knowledge it needs to be updated. But in general this should give useful information that enables prediction based on machine learning.

Will this approach give me or anyone else performing this experiment useful data?

I think the question whether this experiment will give you useful data can be split into two parts:

Does the EEG reflect the emotional state ?
Does the stimulus (media,pictures) induce such an emotional state ?

For the first question there is a lot of research going on and this review might be a good starting point to get into the topic. Without knowing much of the literature I would guess though, that you always need some ground-truth data of the emotional state to train your classifier. This would mean that you would need to somehow 'measure' your emotional state during the EEG recording. You could avoid this by separately 'measuring' your emotional state when watching the media but then you would have to assume that it's always the same emotional state which might not be true.

If you don't want to measure the emotional state, you could also try to do unsupervised learning on the EEG signal, maybe saying that you want to find 3 different emotional states and in the best case the algorithm will give you a nice partition of your stimuli into three categories but there is no way that it can know what emotions those categories stand for.

For the second question I guess it would make sense start with a set of stimuli for which you are sure that they induce strong emotions.

All of this is speaking of general emotional states. Reducing the problem to only distinguishing enjoyment vs. no enjoyment would make it a bit easier of course but the aspects to consider remain the same.


EPSP/IPSP amplitude values? I'm working with a Hodgkin-Huxley model that receives synaptic inputs from presynaptic neurons. If it receives a spike from an excitatory presynaptic neuron, the voltage of my HH neuron inceases by an amount $g$. If it receives a spike from an inhibitory neuron, the voltage jumps down by an amount $g \times K$ (so K is the factor controlling how much the voltage drops relative to how much it would increase from an excitatory neuron). I read in textbooks that the ratio of excitatory:inhibitory neurons is generally $4:1$. That implies that for the system to be "balanced", I should have $K=4$. If $K<4$, then there is a net drift upwards in voltage towards the threshold values, and for $K>4$, there is a net drift downwards away from the threshold.

I have two sub-questions:

1) Is there a typical value of $g$ (the EPSP amplitude) that is biologically plausible? I've seen anywhere from $0.1-0.5$ and above which is quite a big range. I know that there is often a big range based on stimulus and whatnot, but I'm looking for a biologically reasonable value.

2) What is a typical value of $K$? In other words, what is the size of a typical IPSP amplitude relative to the EPSP amplitude? I've seen anywhere from the amplitude being the same to the amplitude being 4x the EPSP amplitude (which of course is a mighty big range).

By definition, current-based synapses are biologically implausible.  After all, biological synapses are conductance-based [1].  It is possible that current based synapses are sufficient to answer the question you are asking.  It is also possible that they are not.  Generally, biological plausibility is not a matter of the parameter values you are using but rather a matter of whether the question you are asking has biological relevance. After all, unless you have a morphologically accurate simulation including every single receptor type, etc. your model is not biologically realistic.

The question you are asking doesn't have a good answer because you are asking a biologically non-sensical question:  what is the value of current based synapse magnitudes?
The only way one could possibly answer that question is if one knew why that question needs an answer.  Maybe you don't even need a reasonable value for the question you are trying to answer because the phenomenon is robust.  Maybe you need the answer to the fifth decimal place because your model is very sensitive to that value.

Point is, biological realism is incredibly context-specific.

[1] Although I have heard a strange argument that the high resistance at the spine neck means that synapses are practically current sources.  I don't know anyone that relies on that.


What scientific evidence is there for the definable real world quality of redness independent our perception? 'With light poise and counter-poise, Nature oscillates within prescribed limits. Yet thus all arise the varieties and conditions of the phenomena which are present to us in space and time.' - Goethe
The touchstone of Newton's theory was his famous experiment with the prism. A prism breaks a beam of white light into a rainbow of colors, spread across a whole visible spectrum. Then Newton realized that must be the elementary components that add up to create white.
While Newton used the standard prism, and passed white light through it, Goethe had also run a series of experiments, with a prism again, but by just looking through the prism.
And he found everything uniform, but when his prism passed through the fold of a cloud behind the sun, he was met with a blast of color, where he stated that 'color is the interchange of light and shadow.'
Goethe's ideas resemble a facile notion, popular among psychologists, but Feigenbaum argued that his (i.e., Goethe's) statement had true science in them which emphasized the repeatability of his experiments.
It was the perception of color, to both Goethe and Feigenbaum, that was universal and objective.
So in that sense, what scientific evidence is there for the definable real world quality of redness independent our perception?

Short answer
None.
Background
First off, I am not familiar with the principles as laid out in your question posed by Goethe and Feigenbaum (I'll look into these people, thanks for the pointer!).
However, I am familiar with Newton and with the interpretation of perception in general. Importantly, the late Neuroscientist Paul Bach-y-Rita  famously stated that (1972):

We see with the brain, not the eyes.

What he meant by that is that the brain has the ability to consciously perceive physical input. The eye serves to sense light and convey an electrical signal to the brain that translates the sensations to perceptions. The retina is sensitive to different wavelengths and red light activates different photosensitive cells (cones) than green or blue cones. The perceptual analogue arises only after extensive processing in higher brain centers.
In a series of experiments Bach-y-Rita showed that blind people are able to 'see with the skin' by converting camera images to tactile sensations on the body, a technique dubbed sensory substitution (Bach-y-Rita, 1969). Later, he founded a company (Wicab) that developed a sensory-substitution device on this principle, namely the BrainPort V100 (Stronks et al., 2016) (Fig. 1) that converts camera images to electrical stimuli on the tongue via a grid of 240 electrodes (the tongue display unit, or TDU) (Stronks et al., 2015). So a TDU allows people to 'taste the light'. These experiments showed that visual perceptions can be elicited by tactile stimulations, later corroborated by functional brain imaging, and thus that we see with the brain, not the eyes.
Having said all this it brings me back to your question...

[W]hat scientific evidence is there for the definable real world quality of redness independent our perception?

... and my answer on it would be: none.

Fig. 1. BrainPort V100 wearer. source: Independent
References
- Bach-y-Rita, Nature (1969); 221: 963-4
- Bach-y-Rita et al., Int J Human-Comp Interact (1972); 15(2): 285-95
- Stronks et al., Brain Res (2015); 1624: 140-52
- Stronks et al. Exp Rev Med Dev (2016); 13(10): 919-31


Is it true that old people loose the ability think creatively/ formulate new ideas My friend said something about that people get older than 50 loose the ability to think creatively and formulate new ideas.

There is also a saying like “stuck in his ways” and people say the “older you get the harder it is to change”

Is this a thing? If it is there a scientific name for it?

The question of whether it is true (or not) that

  old[er] people [in general] loose the ability think creatively or formulate new ideas

would lead to a very opinion based answer and therefore it is not a fit for this site.  Not everyone behaves or thinks in the same way.  However, where this is true of those who are in this situation, there are several possible names for it and they tend to be cognitive biases.  There is

Declinism

  The belief that a society or institution is tending towards decline. Particularly, it is the predisposition to view the past favourably (rosy retrospection) and future negatively.

Rosy Retrospection

  The remembering of the past as having been better than it really was.

System justification

  The tendency to defend and bolster the status quo. Existing social, economic, and political arrangements tend to be preferred, and alternatives disparaged, sometimes even at the expense of individual and collective self-interest.

Status Quo Bias

  An emotional bias; a preference for the current state of affairs. The current baseline (or status quo) is taken as a reference point, and any change from that baseline is perceived as a loss.

Choice-supportive bias

  In a self-justifying manner retroactively ascribing one's choices to be more informed than they were when they were made.


How image orientation influences perception Im a painter for many years. When I paint, I usually walk around and look at my painting for many hours. When painting session is long, it harder and harder to maintain a "fresh look".

By fresh look; I mean state of mind (perception) when I am as objective about my work as possible. The longer the session continues and painting is changed; its harder for me to be objective about it.

To be objective and fresh, artists would take many 5-min breaks in one painting session. I used to do that too, until I learned a "strange trick" from my friend.

Whole trick is to take your painting and just rotate it about 90 or 180 degrees for a moment and look at it. Surprisingly, this gives a fresh (somehow new) perspective at painting.

I would like to ask; why is that?

It seems to me, that somehow brain filters out many informations about images that it knows. When I rotate my image; it is recognized as different (not "known").

Any research on described phenomenon?

No life can emerge in chaos - for life to emerge the environment has to be orderly. Organisms have to adapt to their environment, meaning optimise (or satisfice) output in light of input. In a patternless environment, there is no chance doing so.

Our brain evolved in light of this - we constantly learn and update what the "norm" is - let it be there's light if it's day or the hair colour of your partner. Equally, the brain constantly compares stimuli to the norm - if it's all good, no action needed, but a deviation from the norm shall raise an alarm bell.

Thus, we are 'programmed' to ignore what's normal, and be alert to the abnormal. Perhaps the most famous example of it is the sound of mechanical clock, which is simply not perceived once we spend enough time in the room it is in.

In your specific case, seeing the same image for a prolong time results in it becoming a norm in our brain, resulting in reduced brain activity.


How does the brain know whether or not it comprehends a novel concept? There seem to be at least two kinds of confusion regarding novel concepts.

In one, the brain simply can't form an abstract model from whatever information is being presented. It's where you can't "wrap your head around" something.

In another, the brain perceives a cognitive dissonance, where something doesn't "add up", but further information provides a unifying model that can explain everything being presented.

They seem to be related.

The brain is somehow able to evaluate the fidelity of an abstract model that it's trying to construct. How does this happen?

Interesting question!  A related phenomenon called the illusion of explanatory depth (IOED) suggests that the human cognitive system has a systematic weakness in this kind of evaluation--I believe the classic example is asking people if they know how a helicopter works (most people say yes), and then asking them to explain how a helicopter works (very few people even get as far as mentioning airfoils or lift).

Although the mechanism behind the illusion of explanatory depth (and thus the mechanism behind evaluation of incomprehension in general) is understudied, a 2010 review examined six studies and drew a few conclusions:

IOEDs have been found in natural, mechanical, and social-psychological domains.
People who adopt a concrete construal style (as opposed to an abstract style), either naturally or from prompting, diminish the scope of their IOED.

Missing the trees for the forest: A construal level account of the illusion of explanatory depth. Alter, Adam L.; Oppenheimer, Daniel M.; Zemla, Jeffrey C. Journal of Personality and Social Psychology, Vol 99(3), Sep 2010, 436-451. http://dx.doi.org/10.1037/a0020218


Is there a term for trying to remember a word, but only remembering its first letter? This happens to me frequently. I'll say, "Oh you know that guy... uhh... I can't remember his name. But he starts with a 'Z'." You can remember part of the word but not the whole word.

Is there a term for this situation? What causes it?

This is called the Tip of the Tongue phenomenon.

  People in a tip-of-the-tongue state can often recall one or more features of the target word, such as the first letter, its syllabic stress, and words similar in sound and/or meaning. Individuals report a feeling of being seized by the state, feeling something like mild anguish while searching for the word, and a sense of relief when the word is found.

It's a very common phenomenon, and it presents itself in several similar forms, as the Wikipedia description notes. Remembering just the first letter is a common form but not the only cue.

There are a couple of suggested causes, but generally the problem is failure to completely retrieve information you "know" is in fact there. The Wikipedia article has some information on the general theories.


Are there researched approaches to learning a subject more quickly? TLDR at bottom.

So from my knowledge(correct me if I'm wrong) there is no evidence to suggest that we can improve general intelligence. But what about improving skills/intuition in specialized fields like programming or mathematics?

I went through this course on coursera called Learning how to learn by Barbara Oakley(engineering professor) who suggests the following to quickly learn new subjects:

Pomodoro technique 25 minutes study 5 min break
Eliminate Distractions
Do not neglect memory training. Recalling what you have studied is a great way to learn.
Practice and consistency.
Cramming is bad - it takes time to 'build neural chunks' as she says. I wasn't sure if this was based off of actual science or just conceptual.

I do not like method 1 at all from my experience. Often times when I am going through technical textbooks and I have a timer randomly go off on me at 25 minutes in the session, I find myself jumping from my seat and my productivity wanes. However, timers at around 45 minutes(where my brain seems to slow down) does not have this kind of effect.

But in Cal Newports Deep Work book, he suggests:

Absolutely no distractions. Even delete social media from your life. Isolation can be a very ideal way of achieving deep levels of focus
Be consistent.
Do not tap in to willpower
Use 'rituals' to turn the deep work mode on.

From my experience, point 1 has severely reduced my ADHD symptoms and as a result my productivity has greatly improved. But even then, I still wonder to myself how much validity there are to these two professors approaches? Neither are neuroscientists, cognitive scientists, or psychology professors. I want to know if there is some kind of research, evidence(strong or weak), that there are more effective approaches to learning a specific field at a much faster pace. I have also read summaries of 'Peak' by Anders Erikson who is an apparent authority in this topic but I still haven't found anything eye opening.

Basically, is it possible to learn a subject at a much faster pace through the use of different studying techniques such as mnemonics, spaced repetition, etc.

This question is pretty vague and broad, but the most researched techniques, according to a reasonably recent (and highly cited) review, Dunlosky et al. (2013):

It looks like distributive practice (spreading out activities over time, the opposite of cramming, I guess) and practice testing (i.e. trying to apply what you've learned) get the highest generalizability ranking. The techniques that get a moderate rating are somewhat related to these two (interleaved practice: alternating the types of activities involved), self-explanation (being aware of the steps during problem solving) and elaborative interrogation (somewhat related to the previous one: explaining [oneself] why some statements are true based on the previously learned concepts). Mnemonics, mental imagery, summarization, highlighting or re-reading were ranked low in overall utility.

But even for the high utility techniques some questions remain (that's why they're tagged with P-I for instance):

  For instance, self-explanation
  received a P-I rating for criterion tasks because the
  available evidence is positive on one dimension (generalizability
  across a range of criterion tasks) but is insufficient on
  another key dimension (whether the benefit of self-explanation
  generalizes across longer retention intervals). As another
  example, rereading received a Q-I rating for criterion tasks
  because evidence for the effectiveness of this technique over
  long retention intervals is qualified (i.e., under some learning
  conditions, it does not produce an effect for longer retention
  intervals), and insufficient evidence is available that is relevant
  to its effectiveness across different kinds of criterion
  tasks (e.g., rereading does boost performance on recall tasks,
  but little is known as to its benefits for comprehension).

You'll have to read the full for details as it's too much material to summarize here.

Also, I can't say if the findings still hold for special groups like ADHD.


Why are EEG markers usually sent over the parallel port? Usually, a study participant is viewing stimuli on a computer screen while their EEG is recorded through the hardware provided by a manufacturer. To later synchronize the EEG data to stimuli, an experimenter will send so-called 'markers' from the stimulation computer to the EEG hardware so that the markers are encoded in realtime together with the EEG data.

Why do most manufacturers use the old-fashioned parallel port for that?

I know, that the parallel port allows for a parallel transmission of up to 8 bits (i.e., 255 possible marker values and one '0' marker to indicate 'no marker') ... however, while that is a clear advantage, it comes at the cost of using a legacy port that is not available on modern computers.

Couldn't we just use a USB port to send data serially (in smaller bit packages) ... and then join these bits to a byte (8bits) to get the same number of possible markers? USB would in theory be fast enough to even compensate for the extra time needed to 'buffer' single bits and then encoding them as a byte.

Am I getting something wrong?

Why is the parallel port still so prevalent for this specific application (EEG)?

I think this is for scientists who like to design their own setups. I doubt medical EEGs have a parallel port. You do not always want to sync to a computer. You will often want to synhcronize it to a photodiode, an eyetracker, a tactile stimulator etc. With a parallel port you just plug that trigger to a given pin then you know that everytime your get an integer containing 2^(pin number) you have received a trigger on that pin: for ex. trigger on pin 0 if you are reading 1, on pin 4 if you are reading 16, and on pins 1, 3 and 6 if you are reading 74. Yes, you could read your triggers with a micropchip, then use a serial-USB converter, but that's needlessly complicated and less accurate. USB have surprisingly unreliable timings for a port that can work at such a high baudrate. So it's usually better to synchronize everything to an external input. I usually synchronize an eeg and an eyetracker to a photodiode, then I know they are synchronized perfectly (yet they often have a 1msec difference for some reason).

On top of that, I'm sure there must be some backward compatibility issues. If you are a small lab that has built a complicated setup over the years, you might not want to change your EEG if it means changing your entire apparatus.


Gain EQ for Introverted Person What method and/or technique is recommended to make an introverted person to gain high emotional intelligence, social skills and social competence in his/her personality?

What I have seen the method is to train specific Japanese martial arts (not all Japanese martial arts), read books, staying in a big city for instance capital city etc.

Basically an introverted or shy person is caught in a viscious circle:

you don't interact with people much because often you don't feel the need
because of this you don't have much practice in interacting with other people
so if you try to interact when you do feel the urge, you feel that you don't interact very successfully or even "fail"
this in turn reinforces your wish to not interact

What you need to do is break out of this self-reinforcing circle. But how?

If you want to become better at speaking a foreign language, reading books about language learning is not going to help you much. What you need to do is practice that language.

The only thing that will help you gain social competence is practice your social skills.

Cognitive-behavioural therapy for pathologically shy people consists of many components, such as psychoeducation (understanding the causes, stabilizing factors, and symptoms of your trait) and correction of dysfunctional beliefs (you are not worth less, on the contrary there are positive aspects of being introverted), which, in self-help, you can do with a book or through meditation, but the one central methodology, and the only thing that will instigate a change, is getting into the situation that you are afraid of: exposition (facing what you fear to lose your fear by realizing nothing bad is happening) and behavior training (building a new habit and competence).

If you want to help youself, you can of course read books on your problem to better understand what is going on and what you might do, but then you need to get out and do it. I would do:

define your ultimate goal (e.g. I want to be able to talk in front of an audience without stuttering)
break this mountain of a goal down into small, manageable goals (e.g. if you are afraid of approaching attractive girls, start with old ladies)
all goals, the ultimate and the subordinate goals, must be concrete and measurable (e.g. not "I want to be more extroverted", but "I want to smile back next time Paul smiles at me"); it must be absolutely clear and unmistakeable when you are in the situation you want to change and when you have achieved your goal; nothing vague and general that no-one can meet
practice regularly (e.g. consciously smile at every person you encounter on your way to work, every day)
this may be hard, so don't force yourself to be friendly to everybody all the time, note that even extroverted people don't interact with everybody always, and certainly are not always friendly; give yourself breaks and allow yourself to rest from your exercises (e.g. plan to not smile on your way home)
slowly increase difficulty (e.g. in week two start to say "hi" to those people that smile back; in week three, mention the wonderful weather; etc.)
accept that you are not extroverted, i.e. don't expect yourself to become what you are not comfortable with; be content with gaining confidence and competence to be outgoing whenever you feel like it, but allow yourself to remain by yourself when that is what you want; just try to observe yourself and take note of when you really want to be alone and when you are only afraid of socializing
accept that not everyone will love you; competent extroverts experience many refusals, they just have many prositive encounters to balance them; you aren't interested in everybody either, are you? so don't take it personal, move on to the next person and see if he is more welcoming -- one of the next persons will be
write a diary of what you did, what happened, any changes in your feeling and behaviour and in the reactions of the other people, and plan the next step
ask yourself: "What would I do if I weren't afraid?", then do that


What are the practical uses of ontologies? I have read many papers and books about ontologies, and I am trying to figure out that how they are used in a real project. For example, how can the ontology for a soccer player robot can be defined and used with a cognitive architecture in order to make it intelligent?

Are ontologies relations between terms in that domain of knowledge (for example relation between the ball and foot word, and physical rules definition and their relation with the foot and ball movement) or relations between tactics, strategies and different mixture of tactics?

Are there any clear examples of ontology usage in real projects and their combining usage with the cognitive architectures like ACT-R for augmenting the cognitive architecture?

Interesting question. "Ontology" is often used in confusing and polyvalent ways, so let's start by clearing up the terminology very quickly for those who aren't intimate with the various different meanings.

What does "ontology" mean?

Broadly, ontology the field is the philosophical study of being. An ontology is a method for establishing what beings or entities may exist (cf. epistemology's whether we should believe they exist), how they may be grouped, and the relations they may have.

In information and computer science, "ontology" is used in a related, but not identical sense to refer to formally defined sets of types, properties and the relationships between them. To answer your question, then, relations compose part of an ontology, but ontologies do not comprise sets of relations and nothing but sets of relations. From the Wikipedia page:

  An ontology is a description (like a formal specification of a program) of the concepts and relationships that can formally exist for an agent or a community of agents. This definition is consistent with the usage of ontology as set of concept definitions, but more general. And it is a different sense of the word than its use in philosophy. -- Tom Gruber, Toward Principles for the Design of Ontologies Used for Knowledge Sharing.

(Gruber updated the definition in 2007, but it is not so much different as an extension.)

Ontologies and ACT-R

ACT-R defines a basic ontology with the entities modules, buffers and pattern-matchers, ways to group entities within their type (e.g., perceptual-motor vs. memory modules), and the relations between them.

We use ontologies to abstract away from particular data structures. The ACT-R cognitive architecture both implies and specifies an ontology, and we can use that ontology to extend ACT-R, or make ACT-R talk to other architectures which may not have any data structure overlap with ACT-R. Oltramari et al. (2014) provides an apt concrete ("real"?) example. They coupled ACT-R to the SCOPE knowledge management system, where they use concrete information science ontologies in order to extend ACT-R to use abstract philosophical ontologies.

  In general, ACT-R models only employ as much knowledge as required to perform well-defined cognitive tasks. By and large, they can be seen as “monadic” agents, whose knowledge bases are limited, partially reusable and sporadically portable across experimental conditions. On the contrary, in order to replicate high-level contextual reasoning and pattern recognition in humans, large amount of common-sense knowledge should be available to ACTR: to overcome these limitations, we propose to equip ACT-R with a specific module for processing ontologies [philosophical sense], i.e. semantic specifications of a given domain or application (Guarino, 1998) [information science sense], which are generally used in combination with inference engines for deductive reasoning. Since the ACT-R declarative module supports a relatively coarse-grained semantics based on slot-value pairs, and the procedural system is not optimal to effectively manage complex logical constructs, a specific extension is needed to make ACT-R suitable to fulfill knowledge-intensive cognitive tasks like context-driven spatial reasoning. Accordingly, we engineered an extra module as a bridging component between the cognitive architecture and an external knowledge-base system KBS, SCONE (Fahlman, 2006).

References

Oltramari, A., Vinokurov, Y., Lebiere, C., Oh, J., & Stentz, A. (2014, March). Ontology-Based Cognitive System for Contextual Reasoning in Robot Architectures. In 2014 AAAI Spring Symposium Series.


Is there any research of spelling errors from a dual-process theory perspective? Checking the rather comprehensive but somewhat dated 2008 review of  Evans on dual-process theories, I didn't see anything about [mis]spelling.

But it seems to me an obvious thing to investigate from a dual-process perspective, because (in theory) the more elaborate rules you have to apply the more mistakes you're likely to make under time pressure.

So has anything like this been attempted?

Note that this is a little more sophisticated than simply asking if writing (never mind typing) faster results in more errors. You'd have to discern what's the likely cause of the errors, i.e. under time pressure, do you make more errors of the kind that require more complex "graphotactic" rules?

Well, it turns out there is some related research, but there are complications because spelling & writing is harder to investigate (compared to syllogisms, for instance)...

  Spelling relies on two sets of processes, depending on word
  frequency (for a review, see Tainturier and Rapp, 2001; Bonin,
  2003). For frequent words, the letter sequence is directly retrieved
  from the orthographic lexicon via the lexical route. For rare
  or unknown words, the letter sequence is arrived at indirectly,
  through a process of phoneme–grapheme conversion (assembled
  route). The resulting orthographic representation is stored in a
  graphemic buffer (Caramazza et al., 1987; Hillis and Caramazza,
  1989) until its graphomotor execution (i.e., initiation and implementation of motor programs and neuromuscular execution).
  Although the orthographic representation obviously needs to be
  retrieved or calculated prior to execution (i.e., during the writing
  latency; Bonin et al., 2002), Delattre et al. (2006) have shown that
  the orthographic processing of irregular and infrequent words is
  still generally incomplete at this stage, and therefore, continues
  during the graphomotor execution, thus, increasing handwriting duration. According to the authors, these results can be
  interpreted within the dual-route model. When a conflict arises
  between the outputs of the lexical and assembled spelling routes,
  it takes time to resolve, and the central processing of this conflict
  then cascades onto the graphomotor execution.

So yes, there is a posited "dual-route" model for spelling/writing, and yes, it's based on timing experiments... although these did not involve time pressure (or counting spelling errors by type), but rather is based on timing the writing of well-known vs obscure words. Whether this "dual route" neatly matches more conventional dual-process accounts of cognitions is a bit unclear to me.

The complications come from the fact that spelling and writing form a cascading process:

  Three factors seem to determine the temporal course of the
  central processing of spelling. The first one concerns the word’s
  lexical characteristics. The less frequent and/or regular the word,
  the longer the central processing takes and the more likely it is to
  be cascaded. The second factor concerns time pressure. Until now,
  the cascading phenomenon has only been observed for the production of successive words under time pressure (Delattre et al.,
  2006; Lambert et al., 2011; Maggio et al., 2012). Producing a single
  word without any time constraint should minimize cascading, by
  allowing the spelling process to be completed during the pause
  (i.e., latency) preceding execution. Third, according to capacity theory, the ability to cascade processing depends heavily on
  the writer’s development and expertise (Berninger and Swanson,
  1994; Alamargot et al., 2010). Because handwriting is not yet fully
  automatized in younger writers, especially those still in primary
  school (Bourdin and Fayol, 2000; Olive et al., 2009), they have to
  prevent overloading by segmenting and sequentializing the higher
  processes and are therefore, unable to engage in parallel, or cascaded, processing (see Olive and Kellogg, 2002; Alamargot et al.,
  2007).

Interestingly Kahaneman was also involved in formulating capacity theory. And it seems related to models of divided attention, which he also was involved with.

Anyway, if this is correct, an interesting conclusion is that if you have produce the spelling under time pressure and in a medium that you have little experience with (say you seldom handwrite, or you seldom type) then you are more likely to make spelling errors in that medium not simply because of mechanical issues, but also because it puts a sort of cognitive/time pressure even on processes that you have trained in (spelling).

The introduction of the Delattre paper also has some more interesting observations related to the complexity of the rules, particularly with respect to the how phonemic the orthography is and some empirical support from of specific forms of dysgraphia:

  The dual-route model of spelling production (e.g., Ellis, 1982)
  proposes that two processing systems operate in parallel: a lexical
  route that retrieves spellings of known words from a memory store
  of word-specific knowledge and a nonlexical (or assembled) route
  that generates spellings using a process of sublexical sound-to spelling
  conversion. The assembled spelling route would be efficient
  in languages whose orthographies have predictable or consistent
  orthographic-to-phonological correspondences (such as
  Turkish, Italian, and Japanese kana) but would be considerably
  less effective for English and French, whose orthographies are
  characterized by highly inconsistent relationships (e.g., the vowel
  /i:/ is spelled in many different ways in English words, as in eel,
  tea, theme, thief, Keith, people, me, key, quay, ski, etc.). There are
  many irregular and some almost arbitrarily spelled words in English
  (e.g., pint, yacht) and French (e.g., fraise, monsieur). The
  lexical route would work for all known words (irrespective of
  regularity) but could not provide spellings for new words or
  nonwords. The assembled route would work for nonwords but
  would often produce phonologically plausible errors (PPEs), particularly
  to irregular words, such as yacht (YOT) and monsieur
  (MESSIEU).

  Evidence consistent with the dual-route model comes primarily
  from studies of the spelling performance of neuropsychological
  patients with acquired central dysgraphia (for reviews see Barry,
  1994; Tainturier & Rapp, 2000). The separation of the dual routes
  is supported by the double dissociation between surface dysgraphia
  (e.g., Beauvois & De´rouesne´, 1981; Hatfield & Patterson,
  1983) and phonological dysgraphia (e.g., Shallice, 1981). Surfacedysgraphic
  people accurately spell more regular than irregular
  words (for which they make many PPEs) and are interpreted as
  having an impaired lexical route that forces overreliance on their
  preserved assembled route. Phonological-dysgraphic people have a
  marked impairment of nonword spelling but have relatively preserved
  word spelling and are interpreted as having an impaired
  assembled route but an intact lexical route.

  Although the lexical and assembled spelling routes are proposed
  to be separate, there are at least two lines of evidence to suggest
  that they interact at some level in normal spellers. First, observation
  of spelling errors in free writing (e.g., Ellis, 1979; Hotopf,
  1980) suggests that assembled spelling plays some role in writing;
  people sometimes make PPEs (e.g., Ver-knickers ayfasia) and may
  produce different alternative spellings on different occasions
  (which suggests that not all errors reflect inaccurate spelling
  knowledge). Second, there is experimental evidence showing lexical
  influence on assembled spelling; there are lexical priming
  effects on nonword spelling (e.g., Barry & Seymour, 1988; Campbell,
  1983; Perry, 2003). For example, the nonword /vi:m/ is more
  likely to be spelled as VEAM after hearing the word team, as
  VEEM after the word deem, and as VEME after the word theme.

  Dual-route models of spelling have been expressed in symbolic
  terms (e.g., Barry, 1994) but also as more interactive (Rapp,
  Epstein, & Tainturier, 2002) and connectionist (Houghton & Zorzi,
  2003) models. Although single-route models of spelling have been
  proposed (e.g., Brown & Loosemore, 1994; Bullinaria, 1997;
  Olson & Caramazza, 1994), Houghton and Zorzi (2003) have
  argued that these are currently unable to account for the full range
  of empirical data.

I quoted all this here because the Wikipedia article on spelling has basically zero psychology or neurology information.


What are some psychologically normal reasons for a parent to reject their child? In family psychology are there any normal (not abnormal) reasons to give up and cut off communication with your child (adult or otherwise)? I would think it would be rational to have a closed adoption of a baby and communication might need to stop if the child presents a constant danger.

A cuckolded father would be likely to reject a child who is discovered to not be his own. From evolutionary perspective, men who get cuckolded and take care of a genetically-distant man's child would fail to reproduce their own genes and increase the chance of survival of the genes of the other man who did the cuckolding. Thus rejecting such a child would be an evolutionary adaptation to the problem of paternity uncertainty.

Another reason could be that the mother misjudged the commitment of the father, and mated before such bond was established. This could be in combination with a father who's mating strategy favors fertilizing high quantity of women over investing in few offspring with one woman.


What is the difference between biological and artificial neural networks? I read that neural networks are of two types:
a) Biological neural networks
b) Artificial neural networks (or ANN)

I read, "Neural Networks are models of biological neural structures," and the biological neural structure referred to the brain in the context of that text. Is the brain called a biological neural network? If not, what is the difference between the two terms?

Artificial neural networks (ANNs) are mathematical constructs, originally designed to approximate biological neurons. Each "neuron" is a relatively simple element --- for example, summing its inputs and applying a threshold to the result, to determine the output of that "neuron".

Several decades of research went into discovering how to build network architectures using these mathematical constructs, and how to automatically set the weighting on each of the connections between the neurons to perform a wide range of tasks. For example, ANNs can do things like recognition of hand-written digits.

A "biological neural network" would refer to any group of connected biological nerve cells. Your brain is a biological neural network, so is a number of neurons grown together in a dish so that they form synaptic connections. The term "biological neural network" is not very precise; it doesn't define a particular biological structure.

In the same way, an ANN can mean any of a large number of mathematical "neuron"-like constructs, connected in any of a large number of ways, to perform any of a large number of tasks.


Do people with ADHD have reasoning abilities and mathematical abilities just like normal people? Do people with ADHD have reasoning abilities and mathematical abilities just like neurotypical people ?

Alright- neurodiversity vs neurotypical label aside, here is the definition of ADHD

http://www.cdc.gov/ncbddd/adhd/diagnosis.html

Here is the best example I could find which demonstrates effect of ADHD on mathematical reasoning:

http://ldq.sagepub.com/content/16/1/6.short

Here is a comparison between learners who are nonverbal, who have aspergers, and then those who have ADHD

http://www.tandfonline.com/doi/abs/10.1080/87565641.2010.494747#.VM1Cynvwo-g


Is neuroplasticity limited to the cerebral cortex in the brain? In this question, I am defining neuroplasticity as being the creation of new connections between neurons. I'm aware that there is a high degree of neuroplasticity in the cortex and that new connections are created frequently in that brain area. However, in what areas of the brain are the connections constant or change rarely? I'm assuming that any brain area that controls muscles (such as the superior colliculus in the midbrain) are statically connected.

Short answer
Subcortical structures can definitely show neuroplasticity in adults. Most likely, all brain structures can show plastic changes to some degree.

Background
The question is rather broad, as there are many subcortical structures and neuroplasticity is age-dependent. I will therefore restrict my answer to three examples I dug up from the literature.

For example, in primates it has been shown that thalamic and brainstem areas projecting to the somatosensory cortex are plastic and change their projections to the cortex to aid in the rearrangement of the somatotopical map (Jones, 2000).

Changes in the connectivity between hemispheres has been associated with plastic changes in the callosal pathway (corpus callosum) after somatosensory lesions in the cortex (Duffau, 2009).

As a last example, subcortical plasticity has been shown after lesioning the spinal cord in monkeys and rats. By interrupting the ascending projections of mechanoreceptor afferents of the forelimb and the rest of the lower body the corresponding part of the somatotopic representation of primary somatosensory cortex becomes completely deafferented and unresponsive to tactile stimuli. If some of the afferents from the hand remain intact after such dorsal column lesions, the remaining afferents will extensively reactivate portions of somatosensory cortex formerly representing the hand over the course of a month. This functional reorganization has been linked to the sprouting of preserved afferents within the cuneate nucleus of the dorsal column–trigeminal complex in the medulla, also subcortical brain structure (Kaas et al., 2009).

In terms of structures that are resilient to plasticity, Aguire from USC argues that every brain structure has the potential for neural plasticity to occur. Basically, because the term plasticity is pretty much all-encompassing, and I quote:

  [N]europlasticity is the ability of elements in the brain to show structural and functional changes in response to internal and external events. Neuroplasticity occurs at different levels: structural[ly], functional[ly] and [through] all the molecular and cellular mechanisms that accompany these changes. [...] At all times, these players are constantly changing [...].

Admittedly it is a popular-scientific and broad answer to this question, but I do agree with it.

References
- Duffau, Neurosci Res(2009); 65: 131–5
- Jones, Annu Rev Neurosci (2000); 23:1-37
- Kaas et al., Exp Neurol (2000); 209(2): 407–16


Is there a mechanical/vibrational communication method between pre- and post-synaptic terminals in addition to chemical and electrical synapses? I recall hearing something about there being a mechanical way that two neurons can communicate with each other in addition to the chemical and electrical synapse methods. Something about a certain frequency or physical pulse that can travel along the connexons across the gap junction that is received by the post-synaptic terminal.
Did I make this up?

Short answer
Action potentials travelling through the axon are accompanied by a mechanical displacement of the axonal membrane.
Background
Multiple studies have shown that a mechanical displacement of the axonal membrane accompanies an action potential. Hady & Machta (2015) used a computer model to show that these mechanical displacements are generated by the storage of energy  in the neuronal membrane when the action potential travels through the axon that alter the compressive electrostatic forces across the membrane. These forces lead to co-propagating mechanical displacements accompanying the action potentials, which the authors have dubbed 'action waves' (Hady & Machta, 2015).
It is important to realize that the action potential drives the action wave and communication between neurons. As far as I understand, the action wave has no known physiological function in neural communication, although it is a point of debate (Fox, 2018).
Reference
- Fox, Sci Am (2018), April issue
- Hady & Machta, Nat Comm (2015); 6: 6697


Are there samples of false but beneficial beliefs? Many people have false beliefs.

The fact that they have those shows that those beliefs may carry some evolutionary advantage.

If so, how?

How can false beliefs be profitable?

I guess it depends on what you mean by "false beliefs". If you mean beliefs such as magical thinking, illusory patterns, superstitious beliefs, etc, then the following may help.

From an evolutionary perspective, Foster and Koko (2009) argue that false beliefs such as superstitious thoughts/rituals may arise due to the consequence of making a false-negative error (i.e. dismissing a real pattern) being potentially dire, while making a false-positive error (identifying a non-existant pattern) may have little consequence at all.

A psychological explanation that is popular is the formation of false-beliefs as a means of gaining control over ones environment. Keinan (2002) proposes three ways in which engaging in false-beliefs may improve one's sense of control:

these beliefs may provide an explanatory power over perhaps
inexplicable events, making the environment seem predictable and
controllable;
false-beliefs may appear to provide a means of controlling a situation, such as engaging in a superstitious ritual;
engaging in false-beliefs may create a self-fulfilling prophecy (the person's faith in their beliefs may make them more optimistic of the situation, reduce their stress, and subsequently improve their performance).


Is there any actual evidence for the common model of the "real you" and a separate section that contains all your weaknesses? I have heard this model used or implied by multiple community sources, and some which have been endorsed; most will use different names for the two parts, for example the "subconscious" and "conscious"; or "you" and "your "; or, as in Ted Urban's widely circulated TED talk, the "rational human being" and the "instant gratification monkey". It also appears in some much more dubious contexts.
All advice that begins with this model inevitably ends with the assertion that the "real person" is perfect and can achieve whatever goal is being discussed if they only manage to defeat the "weaknesses" part.
Is there any actual psychological or neuroscientific evidence for this model actually being the case? I've never believed that there is, but replying that I believe that there are not two parts, there is only me and I am not perfect, has attracted actively hostile responses and claims that it contradicts established research, although the speakers could not cite such research.

For sure presentations aimed at lay audiences tend to oversimplify and exaggerate research findings, but for the underlying construct, there is a great deal of evidence, and it is considered widely accepted in the field.
The technical term for it is dual-process theory, and is often referred to as System 1 and System 2 based on the popular book Thinking, Fast and Slow, by Nobel laureate Daniel Kahneman, which is a very accessible source for anyone interested in the evidence-base behind this theory (or class of theories, as many have been proposed).  It is also a popular topic on this forum, so be sure to search for these keywords to learn more (examples: Is Decision-Making Emotionally Based, with Rationalization as the only Conscious Component?, Does fixing cognitive biases do more harm than use?, Research on aversion to cognitive effort?).
One quibble with the way some non-technical presentations refer to this construct is that they seem to imply that System 1 and 2 refer to distinct physical "parts" of a person.  For example, the left brain / right brain division can be a reasonable metaphor for lay persons, but it should not imply that a stroke in one half of your brain will turn you into Spock (an emotionless perfectly logical decision-maker).  It's important to emphasize the process part of dual-process theory, and to this end, authors in the field often use the terms Type 1 and Type 2 thinking instead.  For example, Type 1 (intuitive) thinking is likely to be composed of many sub-processes working in parallel, and Type 2 (rational) thinking surely depends on these processes for its own contributions.
Consequently, asserting a good/bad dichotomy to these processes is misleading, as they serve interdependent purposes.  There are many scenarios where Type 2 thinking is impractical due to time constraints and bounded rationality.  Evans and Stanovich, two of the leading researchers in the field, agree (excerpt from Evans, 2012):

In recent writing, I have attributed responsibility for a range of
cognitive biases roughly equally between type 1 and type 2 processing
... Stanovich ... similarly identifies a number of reasons for error
other than a failure to intervene with type 2 reasoning; for example,
people may reason in a quick and sloppy (but type 2) manner or lack
the necessary “mindware” for successful reasoning.


What does the statement mean "50% of happiness is determined by genetics"? I posted the question "Is 50% of a happiness determined by genetics?" on Skeptics but realize I don't fully understand the claim. What does it mean that 50% of happiness is determined by genetics?

Does it mean that each time a person is happy, 50% of the reason they are happy is because of genetics? How can that possibly make sense as happiness is a human construct so why wouldn't the genetic factor apply the same to other emotions like sadness?

Is an example of how genetics determines happiness, that someone is predisposed to liking chocolate, so if they're happy when eating chocolate cake, genetics is 50% of the reason they are happy? Is that the claim?

Does this mean that an unhappy person can't do that much to become happy?

EDIT: would it be correct to say a person can change their level of happiness by +/-50%? Is this what the claim is saying?

TL;DR does the statement mean a person has at most 50% control over how happy they are?

CBS New York reports on research presenting this claim.

The statement 50% of happiness is determined by genetics is presumably talking about heritability estimates.

It is probably talking about the percentage of variance explained by genetics.

These estimates are commonly estimated using twin studies. For example, you administer a survey to people that ask a bunch of questions about how happy they feel. There are a variety of measures (e.g., life satisfaction measures, quality of life measures, measures of tendencies to experience positive and negative emotions). If you administer these measures to twins, some of which are fraternal and some of which are identical, you can compare the degree to which the overlap in happiness scores increases in the identical over the fraternal twins.

A wide range of theories of well-being suggest that most people are happy most of the time. There is also theory to suggest that a person's emotional tendencies (e.g., see neuroticism, extraversion, well-being, and so on) are quite stable over long periods of time (i.e., over many years). So this does suggest, that at the very least, it is unusual for someone's emotional tendency to change dramatically over time.