# Question
Title: Can a positive change result in positive stress?
I have been researching the differences between stress and anxiety to understand them for my own curiosity. My basic understanding is that stress is a variation from routine or something that upsets your normal balance while anxiety is worry about something when there is no stressor.

My question, then, is this: if stress is caused by change to normal routine, would a good change with only positive effects still be considered stress? For example, going on vacation. The travel could certainly be stressful (or perhaps just anxious), but once a person arrives, lets assume they have a very good, relaxing stay. Could this be considered a stress since it is a change from the normal routine, despite having no negative effects?

I admit that most likely the answer lies in a misunderstanding I have about the definition of stress, but I am curious...

# Answer
> 2 votes
It sounds like you're looking for the word "eustress" or "good stress". Which isn't exactly a label of stress, which as commented is negative, but a positive perception of stress.

My favorite go to example is the positivity often associated with, "challenge accepted!" Here we have a change that is often motivational, difficult, and identifiable as worthwhile.

# Answer
> 2 votes
First, let's look at a definition of stress:

> Stress is a feeling of emotional or physical tension. It can come from any event or thought that makes you feel frustrated, angry, or nervous.
>
> Stress is your body's reaction to a challenge or demand. In short bursts, stress can be positive, such as when it helps you avoid danger or meet a deadline. But when stress lasts for a long time, it may harm your health.
>
> Source: http://umm.edu/health/medical/ency/articles/stress-and-anxiety

So, it is a reaction to a challenge or demand that results in tension.

*"My question, then, is this: if stress is caused by change to normal routine, would a good change with only positive effects still be considered stress? For example, going on vacation. The travel could certainly be stressful (or perhaps just anxious), but once a person arrives, lets assume they have a very good, relaxing stay. Could this be considered a stress since it is a change from the normal routine, despite having no negative effects?"*

According to the above definition, though the trip there may be stressful, for a normal person, the stay itself will likely not be considered "stress." However, this depends largely on the psychology of the person involved. For example, if someone has serious anxiety when breaking from routine, such a person would be more likely to find a vacation stressful, even the part of it that is supposed to be relaxing and enjoyable.

Stress is often presented by the healthcare system as a negative thing, however, the fight or flight response is something which allowed us to be more capable of survival in difficult situations, historically speaking. There are certain doctors/researchers who embrace this more positive outlook, attempting to see the possible positive aspects of stress, rather than viewing it as only a negative thing. This is useful because the mere act of viewing stress as only a negative thing can actually compound the amount of stress felt, as one is not only stressed, but becomes stressed *about* their stress. Here is some information and a TED talk by Kelly McGonigal who covers the idea of stress from that standpoint: http://www.ted.com/speakers/kelly\_mcgonigal She also wrote a book called "The Upside of Stress" if you're interested. I've listened to part of the audiobook of it and it's quite good.

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Tags: stress, anxiety
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# Question
Title: Is there any "predictive" component to positive/negative affect in Seasonal Affective Disorder and Bipolar Disorder?
I'm wondering if the human brain "predicts" how certain weeks of the year should feel?

For example, a child who is going to school may have a more positive affect in anticipation of summer holidays, and may feel more negatively towards the end of the summer, as he/she knows that freedom and fun are about to end.

Another example may be siblings' or parents' birthdays, where the anticipation of the birthday increases positive affect.

I'm wondering if year after year of such patterns (in childhood, the teenage years and maybe young adolescence) can create an association in the brain between positive/negative affect and the specific time of the year, or specific photoperiod duration (day length). What I'm trying to understand is, if a pattern of such ups and downs that may have been established in the childhood persists throughout adulthood?

**Have there been any studies that looked at the previous life history and incidence of mania/depression episodes in bipolar disorder, or the onset of depression in Seasonal Affective Disorder(SAD), and correlated them with holidays, birthdays, etc?** I've read that SAD may manifest a depression in any season, not just winter, which got me thinking of the possible causes.

# Answer
I found the term "holiday anniversary memory triggers" on a popular psychology website. It clusters a lot of symptoms together:

http://outofthefog.website/top-100-trait-blog/2015/11/4/holiday-anniversary-memory-triggers
> 1 votes

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Tags: emotion, abnormal-psychology, bipolar-disorder
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title: Acoustic and light wave coherency?

text:
# Question
Title: Acoustic and light wave coherency?
I know how some music notes combinations sound pleasing, yet others do not. Does the same occur with different frequencies of light (colors)? Since spectral color and acoustic pitch are both defined by their respective wavelengths (frequencies), it made me think that the psychological properties of the two may be related.

So do light waves, for example one with the same wave length as a mid-C and another with a mid-F wave, look nicely together? Or do certain colors when viewed simultaneously, or side by side, appear pleasing?

# Answer
First I have to say that the wavelengths of light are on a totally different order of magnitude than sound. So the parallel drawn in your question "do light waves, for example one with the same wave length as a mid-C and another with a mid-F wave, look nicely together?" may seem logical, but is on closer inspection not easily maintained. Instead, one way to address this question more appropriately would be to talk about wavelength differences; i.e., light with wavelengths differing X octaves compared to acoustic tones differing X octaves.

Having said that I think it is worthwhile to sidestep the theoretical approach and take a closer look at how auditory and visual sensory information is actually processed at a neurophysiological level.

Sound is processed in the inner ear (the cochlea), which basically works as a Fourier transformer, and specifically a frequency-to-place converter. The spatial distribution of the characteristic frequencies (the *tonotopy*) on the basilar membrane of the cochlea follows a pattern where one octave spans about 2.5 mm (Greenwood, 1990). For the approximately 10 octaves the human ear can hear (~20 Hz - 20 kHz) we have 16,000 inner hair cells. See the following picture for a rolled-out cochlea with the tonotopy illustrated:

source: what-when-how.com

The eye, on the other hand, analyzes light frequencies using just 3 colors (red, green, blue) by means of three cone classes (as opposed to 16,000 hair cells each sensitive to a slightly different acoustic frequency). Although the visual system does a great job in combining this sparse frequency information into a spectrum of colors, it is not a frequency analyzer as such. In fact, it is more of a frequency "combiner", as it combines the ratios of activation of the cone classes and runs it through a system of color opponency. By weighing the relative contributions of the three colors (RGB) using the opponent system (R-G, Y-B) the visual system estimates the color of the object you are looking at. Below on the left is illustrated the spectral frequency sensitivity of the three cone classes (note the unequal, non-octave distribution of the three across the dynamic spectrum range), and on the right the color-opponent (Hering) model.

source:huevaluechroma.com and giantitp.com

**The opponent nature of human vision (blue-yellow and red-green axis) results in a 2-dimensional color space which is very different from the 1-dimensional frequency space of the cochlea** (Mather, 2006). Note that the third visual dimension is brightness, comparable to the second dimension of loudness in the ear.

In all, based on a neurophysiological signal-processing point-of-view, **hearing and seeing frequencies are two completely different things**. Comparing octaves between the two is worse than comparing apples and oranges, as apples and oranges share at least the same dimensionality.

It probably doesn't answer the question, but it may answer the question why it cannot be answered in any logical, comprehensive and straightforward way without loosing oneself in subjective monologues about "*I like this and this combination of timbres but I don't like this color combination so much*" kind-of-thing. Admittedly, it can be experimentally addressed by inquiring about the subjective 'pleasantness' of a set of combinations of colors and pitches in a study population. But from a physical and pysiological perspective, comparing the two entities of light and sound through equal-octave comparisons doesn't make sense since: (1) the two entities are processed through completely different neurophysiological principles as described above, ('1D acoustic frequency Fourier analyzer' versus '2D spectral combiner'), and (2) they represent entirely different physical entities altogether (photons/EM waves versus air pressure differences). Their only commonality is that they have an oscillatory nature, but that's where the parallel starts, and ends.

**References**
Greenwood et al. *JASA* 1990; **87**:2592-605
Mather. Foundations of Perception 2006
> 9 votes

# Answer
Comparing the two gets into metaphysics. There have been theories of a 'light octave', since IR to UV is not terribly far from a single octave. Basically, in the standard sense, no, our vision does not perceive harmony in just the same way as our audition does with much lower-frequency sound waves.

Newton directly compared the two when he associated the Dorian scale (which is symmetric in pitch) to the Newton colors (ROYGBIV) as he was developing the theory of optics, where certain colors represented a 'whole step' and others a 'half step'. I think he later stated the idea didn't really have foundation. (My notions on such things are also odd, so I'm not really going to go into them here.) Musicians also tried (most famously Scriabin, who was synesthetic). In a way it mirrors the split from tonalism in music, to pitch sequences on one side, and to harmonic sequences on the other ('serialism' versus 'just intonation').

Not to say there are no associations to be made, but they are notably different systems as understood by the perceiver. (There are also vibrational theories associated with olfaction and haptics at other frequency ranges, but I think that would just make the issue more messy, not less.)
> 3 votes

# Answer
The answer is YES, light is exactly like sound when it comes to cognitive psychology. We relate to both in the same ways, and no feature of the physics of either acoustics or photonics refutes this. So yes, there are combinations of colors, tones, shades, shapes and forms which are found to be pleasing and a simple visit to any department store and a conversation with the sales staff as to what is flying off the shelves allows one to create products that will also sell, based on those perceived 'predilections'. These are voted on by millions of consumers across the globe and are quite predictable, understandable, and useful. We all know this, so I have no idea why anyone would bother to over technicalize this truth, and attempt to grind it into oblivion!?

Here are some references to such visual predilections:

www.tigercolor.com/color-lab/color-theory/color-theory-intro.htm#color\_harmonies

1stwebdesigner.com/please-clients-color-combinations/

inspirationfeed.com/inspiration/video-inspiration/30-aesthetically-pleasing-color-combinations/

“The various levels of formal, rhythmic, timbral, and harmonic stasis in Grouper’s music then act like the treatment of a canvas for musician and audience alike. That may seem like a forced analogy, but its fairly apt given Harris’s visual predilections—she was an art student at Berkeley before turning her focus to music, and still contributes visually to her music career with album artwork and concert videos. It’s fitting then that she describes her treatment of the beclouded lyrics as similar to her use of pastels in visual works, which really only invites further listener speculation.”

www.newmusicbox.org/articles/Traveling-Through-a-Sea-The-Music-of-Grouper/

“As for the screenplay by Adam Cooper, Bill Collage, Jeffrey Caine, and Steven Zaillian, it seems shaped by committee to play to the visual predilections of the director, which proves to be both strength and weakness, and it avoids the kind of right-and-wrong preachiness we sometimes expect in any faith-based movie.”

philadelphia.cbslocal.com/2014/12/11/movie-review-exodus-gods-and-kings/

“Lang unleashed the full force of his visual predilections in Metropolis.”

www.filmsufi.com/2008/11/metropolis-fritz-lang-1927.html

“The insights yielded will be of value to those with an interest in modern literature, differential aesthetics, visual culture, perception, and the experience of blindness.”

books.google.com/books/about/Toward\_an\_Aesthetics\_of\_Blindness.html?id=PINlAAAAMAAJ
> 1 votes

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Tags: cognitive-psychology, perception, color, hearing
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# Question
Title: How to interpret neuron spiking models one comes across in literature?
## Background

I'm in high school currently conducting research (obviously it is relatively rudimentary compared to what is being done in the labs, etc.) in computational neuroscience.

I'm dealing with multiple datasets each containing time series data for a majority of neurons in C. Elegans (the dataset is the one used in Saul Kato's Global Brain Dynamics Embed the Motor Command Sequence of Caenorhabditis elegans).

I'm looking to do a pairwise comparison of each neuron in every dataset; if $N\_{ij}$ is the $j^{th}$ neuron in the $i^{th}$ dataset, then I will do a pairwise comparison of all neurons in the $j^{th}$ column.

## Question

I'm going through this paper which proposes a method of comparing time series data across neurons. The paper uses this spiking model:

I'm wondering how neuroscientists approach such models they read about in literature; how they dissect it mathematically, what crosses their mind when they look at these models, etc. and where I can go to gain a rigorous foundation to truly and intuitively understand the models I read about in the future.

# Answer
* Read dayan and abbot "theoretical neuroscience"
* Learn differential equations
* Know the relationship between voltage, current, resistance and conductance
* Differential equations is absolutely essential though. you don't need to learn to solve them (the computer will do that for you), you just need to learn to know what they mean.
* How do researchers translate observations of nature into symbolic, mathematical approximations/models of these phenomena? By gaining intuition of how the model components relate to empirical observations. it is relatively rare that someone comes up with a new model from scratch. most of the time people retool or remix previous models.
> 7 votes

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Tags: cognitive-modeling, computational-modeling, dynamic-systems
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title: What causes emotions?

text:
# Question
Title: What causes emotions?
I have absolutely no knowledge of psychology. But I am wondering what causes emotions in human? Emotions such as happiness, sadness, love, hate etc. Is there some sort of hormones responsible for this? How does brain understands this?

# Answer
> 7 votes
Let's break this down into two terms: *affect* and *emotion*.

## Affect

Affect corresponds to two dimensions that underlie emotional experience: **valence** and **arousal**.

1. **Valence** \- feelings of pleasantness and unpleasantness
2. **Arousal** \- feelings of activation (e.g., alert, energized) and deactivation (e.g., de-energized, sleepy)

So what are the sources of these two basic sensory dimensions?

**One answer is**... immunologic, metabolic, and autonomic changes in the body, whose sensory input flows up and is processed by primary interoceptive cortex (posterior insula) (Barrett & Simmons, 2015). Think of the body as a source of sensory input, just like any other modality (visual, auditory, etc.).

Additionally, there are top-down predictions descending from agranular interoceptive cortex, which are actually responsible for most of our interoceptive sensations (i.e., conscious affect). That is, most of your affective feelings are produced by top-down predictions about input from the body rather than bodily input itself. Weird!

**Another part of the answer is...** endogenous opioid and cannabinoid signals in certain "hotspots" of the brain (e.g., nucleus accumbens, ventral pallidum), which are thought to mediate pleasure (Berridge & Kringelbach, 2013).

**But in general**... this is still being figured out.

## Emotion

The answer to this part depends on your theory, about which I'll be very brief.

**Basic emotion theorists** (e.g., Ekman & Cordaro, 2011) argue that emotions correspond to discrete, circumscribed parts of your brain (e.g., the amygdala and fear, the insula and disgust). We have "affect programs," that when activated, produce a discrete emotion (fear, anger, etc.).

**Constructionists** (e.g., Lindquist et al., 2013) argue that emotions are essentially interpretations of your affect (valence and arousal) in a given context. So "fear" is just a concept that you deploy in certain situations (e.g., when you feel negative, highly aroused, and are running from a bear). On this view, emotions emerge from interactions among distributed brain networks that are involved in more basic psychological processes (e.g., exteroception, interoception, conceptualization, language).

The meta-analytic evidence seems to favor the latter view, but there's still a buttload of work to be done on this end.

As far as controlling emotions--well, that's an entirely different question. But see James Gross for more info.

# Answer
> 3 votes
It mostly depends which theory you go by.

Psychologists have proposed **theories of emotion** to explain what emotions are, by what they are caused and what effect they have on living beings. There're different ways to categorize those theories like on the basis of the content of emotions for example and the major theories can be grouped into three main categories: physiological, neurological, and cognitive.

**James-Lange-Theory** This theory suggests that when you see an external stimulus that leads to a physiological reaction. Your emotional reaction is dependent upon how you interpret those physical reactions. For example, suppose you are walking in the woods and you see a grizzly bear.

**Cannon-Bard-Theory** Suggests that the physical and psychological experience of emotion happen at the same time, and that one does not cause the other.

**Schachter-Singer-Therory** This theory suggests that the physiological arousal occurs first, and then the individual must identify the reason for this arousal to experience and label it as an emotion. A stimulus leads to a physiological response that is then cognitively interpreted and labeled which results in an emotion. Schachter and Singer’s theory draws on both the James-Lange theory and the Cannon-Bard theory of emotion. Like the James-Lange theory, the Schachter-Singer theory proposes that people do infer emotions based on physiological responses. The critical factor is the situation and the cognitive interpretation that people use to label that emotion.

In case you want to delve a bit deeper into that topic visit source.

If you are looking for a general defintion of emotions go with this:

> Emotions are complex patterns of psychological and physiological reactions. They are object-related (= require an external stimulus) and mostly short-lived (in contrast to *moods*).

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Tags: emotion, brain-development
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title: Does electricity pass through synapse?

text:
# Question
Title: Does electricity pass through synapse?
As far as I understand, when a neuron fires the action potential generated in a cell body reaches only the presynaptic part of the synapse, then triggers the transmitter to pass through the gap, and that transmitter causes the membrane in the postsynaptic part to open ion channels, pumps, etc ..., which generate a completely new electric potential that finally reaches the receiver cell.

So the electricity generated in a firing neuron never actually reaches receivers (not directly)?

# Answer
> 6 votes
**Yes** – electricity does pass through synapses if the link between the neurons in question is constituted by an **electrical synapse**.

There are two different types of synapses, **chemical synapses** and **electrical synapses**.

At a chemical synapse, an arriving pre-synaptic action potential indeed causes the release of neurotransmitters which carry the signal across the synaptic cleft to the subsynaptic membrane. This can effect an action potential in the postsynaptic neuron (among other things).

At an electrical synapse, on the other hand, **ions do actually move from the presynaptic cell, through a gap junction channel, and to the postsynaptic cell**, capable to cause a depolarization there.

Electrical synapses are found in many animals (including human). Due to their different characteristics, like the lack of neurotransmitter-related mechanisms and a significantly smaller synaptic cleft, they e. g. allow for a faster propagation of a signal between two neurons (while the signal decreases in strength due to the lack of gain). They occur as a part of neural structures which require fast signal transmission.

(While more technical details can be found in the referenced sources, it is helpful to review some of the basic concepts to avoid misconceptions:

It is sometimes (naively) assumed that the propagation of an action potential consists in a flow of electric charge along the axon, but what actually happens is that ions move through the membrane, i. e. roughly along an axis that is orthogonal to the direction of the signal. *It is the action potential that moves along the axon.* Thus, the original question is **not** to be taken to mean *»Does the electric current that moves along the length of the axon also move through the synaptic cleft?«*

Still – even if the flow of electric charge does not constitute the action potential, *electricity can flow along the axon*, as well. This is what happens in the case of saltatory conduction between the nodes of Ranvier in myelinated axons. It is generally referred to as an *electrotonic potential*.)

# Answer
> 4 votes
> Does electricity pass through synapse?

No because ...

> ... when a neuron fires the action potential generated in a cell body reaches only the presynaptic part of the synapse, then triggers the transmitter to pass through the gap, and that transmitter causes the membrane in the postsynaptic part to open ion channels, pumps, etc ..., which generate a completely new electric potential that finally reaches the receiver cell.
>
> So the electricity generated in a firing neuron never actually reaches receivers (not directly) ...

You actually answered your own question.

*Keep in mind that neurotransmitter release and action potential are two different things. Sometimes the amount of neurotransmitter released are not enough to depolarize the postsynaptic membrane for an action potential to happen. Conversely action potentials can happen in the absence of neurotransmitter as it happens in many cells with peacemaking activity. Remember that action potentials are a result of the biophysical properties of the membranes where they are produced and of course this depends on the different ion channels present in that membrane.* (Source)

Also think about the mechanic of the saltatory conduction:

*Myelinated axons only allow action potentials to occur at the unmyelinated nodes of Ranvier that occur between the myelinated internodes. It is by this restriction that saltatory conduction propagates an action potential along the axon of a neuron at rates significantly higher than would be possible without the myelination of the axon (200 m/s compared to 2 m/s). As sodium rushes into the node it creates an electrical force which pushes on the ions already inside the axon. This rapid conduction of electrical signal reaches the next node and creates another action potential, thus **refreshing the signal**. In this manner, saltatory conduction allows electrical nerve signals to be propagated long distances at high rates without any degradation of the signal. Although the action potential appears to jump along the axon, this phenomenon is actually just the rapid, almost instantaneous, conduction of the signal inside the myelinated portion of the axon.* (Source)

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Tags: neuroscience
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# Question
Title: 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?

# Answer
> 5 votes
I am an Statistics student at University of Warwick (incoming Stanford University) and I have an interest in explaining machine learning concepts in a **non-mathematical/non-technical** way.

# Biological Neural Network

Our brain has a large network of interlinked neurons, which act as a highway for information to be transmitted from point A to point B. To send different kinds of information from A to B, the brain activates a different sets of neurons, and so essentially uses a different route to get from A to B. This is how a typical neuron might look like.

At each neuron, its dendrites receive incoming signals sent by other neurons. If the neuron receives a high enough level of signals within a certain period of time, the neuron sends an electrical pulse into the terminals. These outgoing signals are then received by other neurons.

# Artificial Neural Network

The ANN model is modelled after the biological neural network (and hence its namesake). Similarly, in the ANN model, we have an input node (in this example we give it a handwritten image of the number 6), and an output node, which is the digit that the program recognized.

*A simple Artificial Neural Network map, showing two scenarios with two different inputs but with the same output. Activated neurons along the path are shown in red.*

The main characteristics of an ANN is as such:

**Step 1.** When the input node is given an image, it activates a unique set of neurons in the first layer, starting a chain reaction that would pave a unique path to the output node. In Scenario 1, neurons A, B, and D are activated in layer 1.

**Step 2.** The activated neurons send signals to every connected neuron in the next layer. This directly affects which neurons are activated in the next layer. In Scenario 1, neuron A sends a signal to E and G, neuron B sends a signal to E, and neuron D sends a signal to F and G.

**Step 3.** In the next layer, each neuron is governed by a rule on what combinations of received signals would activate the neuron (rules are trained when we give the ANN program training data, i.e. images of handwritten digits and the correct answer). In Scenario 1, neuron E is activated by the signals from A and B. However, for neuron F and G, their neurons’ rules tell them that they have not received the right signals to be activated, and hence they remains grey.

**Step 4.** Steps 2-3 are repeated for all the remaining layers (it is possible for the model to have more than 2 layers), until we are left with the output node.

**Step 5.** The output node deduces the correct digit based on signals received from neurons in the layer directly preceding it (layer 2). Each combination of activated neurons in layer 2 leads to one solution, though each solution can be represented by different combinations of activated neurons. In Scenarios 1 & 2, two images given to the input. Because the images are different, the network activates a different set of neurons to get from the input to the output. However, the output is still able to recognise that both images are “6”.

Read the full post here, which includes some examples of handwritten digits that were used: https://annalyzin.wordpress.com/2016/03/13/how-do-computers-recognise-handwriting-using-artificial-neural-networks/

# Answer
> 15 votes
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.

# Answer
> 12 votes
I'm studying computer science at KIT (Karlsruhe Institute of Technology, Germany) specializing in Machine Learning and a minor in Mathematics. I am not a biologist.

An artificial neural network is basically a mathematical function. It is built from simple functions which have parameters (numbers) which get adjusted (learned). One example of such a function is:

$$\varphi(x\_1, \dots, x\_n) = \frac{1}{1+e^{\sum\_{i=1}^n w\_i x\_i}} \text{ with } w\_i \in \mathbb{R}, x\_i \in \mathbb{R}$$

As you can see, there are parameter $w\_i$ which can be set to any number. The $x\_i$ are the inputs. But those inputs themselves can be the output of another function $\varphi$.

A common way to visualize those simple functions is

There are thousands of those simple functions (also called "neurons") which build an artificial neural network. This results in a single function which has **millions of parameters** in the biggest networks. Neural networks use relatively simple topologies which can often be expressed in a tree structure:

Every single circle is one neuron (also called "perceptron" in some cases).

You have lots of training data, **train once a long time, then use it often**. A long time often means several days.

In an artificial neural network (ANN), the signal is send **synchronously**.

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As far as I know, the human brain isn't fully understood by now. From what I've heard, the basic building blocks are also called neurons. They look like that:

The idea is that axon terminals of one neuron, which are closer to the axon hillock of another neuron have more influence on the output of the signal. But the relationship is different. It is a process which is much better described by differential equations, not something simple as the equation for artificial neurons above. The neurons send their signals **asynchronously**. According to Wikipedia, humans have 86 000 000 000 neurons. They are certainly restricted in how they can be connected, but there are also certainly **many billions of parameters** which can be adjusted in "standard human brains".

By now, we don't know how humans really (exactly, in all details) learn. This is certainly a key difference. But we don't learn once for a long time and stop learning then. We are **continuously learning very short times**.

See also: On-line Recognition of Handwritten Mathematical Symbols, Chapter 4.3 for more details.

## TL;DR and some more facts

* **Signal transport and processing**: The human brain works asynchronously, ANNs work synchronously.
* **Parameter count**: Humans have many billions (businessinsider.de writes "1,000 trillion") of adjustable parameters / 86Bn neurons (source). Even the most complicated ANNs only have several million learnable parameters.
* **Training algorithm**: ANNs use Gradient Descent for learning. Human brains use something different (but we don't know what)
* **Processing speed**: Single biological neurons are slow, while standard neurons in ANNs are fast. (Yes, I did not confuse the two. The artificial ones are faster. And I ignore spiking networks as I didn't see a single example where they are actually useful)
* **Topology**: Biological neural networks have complicated topologies, while ANNs are often in a tree structure (I am aware of recurrent networks - they are still pretty simple from their structure)
* **Power consumption**: Biological neural networks use very little power compared to artificial networks
* Biological networks usually don't stop / start learning. ANNs have different fitting (train) and prediction (evaluate) phases.
* **Field of application**: ANNs are specialized. They can only perform one task. They might be perfect at playing chess, but they fail at playing go (or vice versa). Biological neural networks can learn completely new tasks.
* ANNs need a target function. You need to tell them what is good and what is bad. I'm not sure if you can compare this to e.g. pain in biological networks.

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Tags: terminology, neural-network
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# Question
Title: What cognitive bias prevents you from discarding stuff?
Let's say person is moving homes and has lots of kids toys, suits, shirts, ties and other stuff that he seldom uses.

He is am planning to sell it all in a car boot sale even if he knows that it's counter productive. He would have to use ~30£ on entry fees and fuel, without even accounting for Sunday lost.

Logical solution would be just drive to the nearest skip or charity shop, and yet he can't make himself to do it, **which of cognitive bias is at play here?**

I don't think this is 'sunk cost' because he is loosing that stuff anyway, it's just that loosing it and **knowing that someone else will be able to use it** somehow makes ones loss more acceptable, which is sub-optimal and suggests a bias.

# Answer
> 4 votes
One possible explanation for the scenario you are describing is Endowment effect.

> In psychology and behavioral economics, the endowment effect is the hypothesis that people ascribe more value to things merely because they own them.

One of the theories that explain the phenomenon is based on loss aversion :

> It was proposed by Kahneman and his colleagues that the endowment effect is, in part, due to the fact that once a person owns an item, forgoing it feels like a loss, and humans are loss-averse.

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Tags: bias
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# Question
Title: Do you need to pay an extra $300 to be able to retrieve data from the Emotiv Epoc via the python-emotiv library?
In the Emotiv website, they offer to pay an extra $300 to access "raw EEG data". If I don't pay that, will I still be able to retrieve the EEG data with the python-emotiv library?

# Answer
> 2 votes
For the non-eeg emotiv Epoc, the SDK only offers to retrieve the actions and their values detected from the device. But no raw data.

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Tags: eeg, software
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# Question
Title: how can the development of sexual preferences be influenced?
I am wondering about the development of sexual fetishes, not necessarily in its meaning of having a sexual affection for inanimate objects, but in its broader meaning of any type of sexual abnormality. As far as I know, such preferences develop through conditioning; i.e. in a state of arousal something not related to sex is perceived and assosiated with one's feelings. For example, one might experience a leather outfit while being aroused and develop a fetish for them.

This is quite a harmless example, but many fetishes may actually be harmful and an individual may want to prevent its development. For the sake of argument, a castration fetish could be considered extremely dangerous, leading to potential self harm at some point in the future.

Would a person who experiences arousal from such a fetish be able to prevent it from emerging? As an example, one could avoid masturbation while thinking of the unwanted fetish. This on the other hand would lead to repression of these unfulfilled desires and could possibly backfire.

Can the development of sexual preferences be actually stopped and/or influenced, and if so, what would be the best way to do so?

# Answer
> 9 votes
A bit of background on me: I’m a clinical psychologist and have worked with many sexual disorders, ranging from paedophile, to gender identity disorder. I am however no expert in any of these, so my answer is based on my own clinical experience and reading of the literature.

Most of my colleagues, and me, think that the general answer is: no – there is not much you can do to stop the development of a fetish. The most common fetish I encounter is SM / bondage. Most of my patients that have this fetish; feel that they had this inclination very early in life, and seldom are they traceable to specific events or experiences in their life.

Same goes with paedophilia. Here I think things are a bit more complicated, as there seems to be two kinds of people (that enter therapy that is, and as such come in contact with me). One group seem to be born with this fetish, if you can call it that. They don’t know why, and how they developed it, and many of them have poor insight into their condition.

On the other hand, there are the ones that spontaneously develop an interest in adulthood. They usually descript their fetish more as a curiosity toward the subject. And most of them never develop into a pure disorder (at least they don’t act on their impulses), and drops it after a while. These people usually develop the fetish during periods of stress.

To build the argument that fetishes are innate. I don’t know if this is a valid comparison to make, but I think most gay people would say that their sexual preference is not something that could be controlled with masturbation-regulation, or whatever. I think most of them would say, that being gay, is just who they are. An assertion supported by the fact that all animals ever closely studied have shown to have a few members of their group who are gay. As such, one could argue that sexual interest seem to very much linked to genetics and biology.

All of the above does not however preclude us from looking for ways to modify a fetish and/or reduce it. When I work with people who are distressed; there are a few things I focus on.

1.Make sure that the fetish is an actual problem. You would be surprised by how often people get panicked by fetish thoughts alone, without the sexual arousal or interest in acting on the fetish. If this is the case, we would work in a metacognitive framework to reduce patient response and thought about the fetish-thoughts. Other times the fetish is not a problem because there actually is nothing wrong with being into “weird” stuff.

2. If the fetish is a problem. The next step is basic Cognitive Psychology. A lot of people can have quite a lot of change in their problematic fetishes if they are just able to have a good narrative and a good ability to articulate the consequences of the fetish. Sometimes people are not even fully aware of the negative sides of their actions, and the fetish will itself diminish somewhat once they have a fuller understanding of the implications of acting on their desire.
3. Stimulus control. You don’t start working in a bakery to “satisfy” you need for food, when you are trying to lose weight. For the same reason one should avoid situations that trigger the problematic lusts. I once had a paedophile that wanted to work in a kindergarden – thinking that he would get fulfilled his need just by watching the kids, so that he would feel less need to act on impulses later. Same as with the old catharsis theory from Freud, the mind doesn’t seem to work that way.
4. Establish overriding associations. Sometimes it can help to try to associate the destructive fetish with something negative. For instance one could try to associate rape with going to jail, being beaten up, or something else negative. This is quite hard to do, and there are no good mainstream guides on this. It’s kind of the opposite to when people overcome their fears be associating something scary with something positive (like when you try to imagine that you are friends with the ghost, instead of its victim). We often find that a good way to remove something from the brain, is to overwrite it.
5. Reduce other stressors in life. Often fetishisms pop up in response to overwhelming stress from other parts in a persons’ life. An example could be a male that gets fired by a female boss, and starts to really dig in on fantasies about raping and murdering women. Another example would be children that gets messed up by a horrible upbringing, and start feeding their aggressive and dominant sexual fantasies (sex, dominance and aggression are linked in the mind for many people).
6. Learn coping strategies. Here one needs to be creative. This could range from not searching for related porn, all the way to masturbating instead of acting on an impulse. There are no “one answer fits all”, and needs to problem-solve with the person to find out what’s optimal, what’s necessary, and what’s possible.

One last note. Your question was mostly focused on the “development” of fetishes, and how to stop them. My answer was more a general answer to treatment of fetish disorders after they developed. But I do think that most of these points are relevant. When it comes to development of fetishes, I would say that my point 5 is most relevant – Try to reduce other stress, and try to create a happy life for the individual in general, and one significantly reduce the chance of antisocial behaviour of all kind, even destructive fetishes. Other than that, remember that you never change anybody, yourself or others, by force. They need to want it.

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Tags: developmental-psychology, clinical-psychology, sexuality, conditioning
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# Question
Title: Models relating neuron firing to oscillatory dynamics
Many papers published seem to focused on oscillations to characterize synchronisation and communication between different brain areas. For example, this paper from Voytek et. al where communication between brain areas increases with the abstractedness of the task.

Are there models that relate neuron firing to these types of oscillatory readings? In other words, given spiking data and location of a neuron ensemble, would it be possible to model the types of oscillations that might be read?

# Answer
> 1 votes
The oscillations measured by EEG, ECoG, and MEG are thought to originate in the apical dendrites' fluctuating potentials. Try looking into the forward problem of EEG. Like the inverse problem but in reverse. Given a known source potential (apparently it's very common to model cortical neurons' LFP as a distribution of current dipoles?) you solve the Poisson equation to get the potential at the recording electrode. I'm reading through this review right now and it's very interesting: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2234413/.

Other avenues which seem interesting are neural mass/neural field models, especially Walter Freeman's work on neurodynamics. See: http://www.scholarpedia.org/article/Freeman\_K-set.

Abstracted away from the biology a bit there's Jack Cowan's field models and stochastic neural networks. But they're both absolutely *prolific* and the math is dense and I'm not quite sure where to even really begin.

# Answer
> 1 votes
You really want to read the work by Gyorgy Buzsaki. The recent Schomburg et al., 2014 is quite illuminating although quite dense. Try my F1000 review for starters.
http://f1000.com/prime/contributor/evaluate/article/718892254

The original paper can be found here
http://www.sciencedirect.com/science/article/pii/S0896627314007818

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Tags: measurement, theoretical-neuroscience, computational-modeling
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# Question
Title: What are the different branches of Psychoanalysis?
I am trying to make a list of the main accepted branches of psychoanalysis to quiz a friend of mine. I don't know much about it and to learn more I need to know the main areas. So far I have

* Freudian Psychology
* Object Relations Theory
* Relations Theory
* Self-psychology

Does anyone know of a basic list of the main branches? My friend said these were the main ones, but I couldn't find a source to substantiate that and I want to verify these are indeed considered the main branches.

EDIT: By a "branch" or "school", I mean a general umbrella term people use to aggregate related trains of thought. In physics, this might be "general relativity" or "quantum mechanics".

# Answer
> 7 votes
In the context of the question I think it makes sense to limit the scope to earlier developments in psychoanalysis. Thompson (1957) gives an overview of what can be called ***psychoanalytic schools***. She includes:

* Freudian psychoanalysis
* Individual psychology (Alfred Adler)
* Analytical psychology (Carl Gustav Jung)
* Object relations theory (Sándor Ferenczi, Otto Rank)
* (Wilhelm Reich)
* Karen Horney (sometimes denoted »Culturalist Psychoanaysis«)
* Erich Fromm (sometimes denoted »Culturalist Psychoanaysis«)
* Harry Stack Sullivan (sometimes denoted »Culturalist Psychoanaysis«)

On the other hand, several ***psychoanalytic psychologies*** can be distinguished. Following a systematization by Gottfried Fischer, there are:

* Drive theory/drive psychology (psychodynamic theory)
* Ego psychology (Freudian psychoanalytic psychology/structural theory)
* Object relations theory
* Self psychology

Newer psychoanalytic schools comprise e. g. Lacanian psychoanalysis, interpersonal psychoanalysis and relational psychoanalysis – but for a more comprehensive list see Kernberg (2001) and Gabbard (2009).

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Literature:

* Frosh, Stephen (2012). A Brief Introduction to Psychoanalytic Theory. London: Palgrave.
* Gabbard, Glen O. (2009) Textbook of Psychotherapeutic Treatments. American Psychiatric Publishing. (Ch. 1: Theoretical Models of Psychodynamic Psychotherapy)
* Kernberg, Otto F. (2001). Recent Developments in the Technical Approaches of English-Language Psychoanalytic Schools. The Psychoanalytic Quarterly, Volume LXX, Issue 3, 519–547.
* Thompson, Clara Mabel (1957). The different schools of psychoanalysis. American Journal of Nursing, 57, 1304–1307.
* Thompson, Clara Mabel & Mullahy, Patrick (1951). Psychoanalysis: Evolution and Development (3rd ed.). New York: Hermitage House.

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Tags: psychoanalysis
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# Question
Title: Can electromagnetic fields be used to stimulate areas of the brain?
Recently I've come across an article from a questionable source called *10 Things An Electromagnetic Field Can Do To Your Brain*.

There are a lot of hints in this article that the writer doesn't have a strong understanding of what they are talking about, i.e. referring to electromagnetic waves as being 'high' and 'medium'. They could be high energy, high frequency, but not 'high'.

Regardless of the accuracy or technical mistakes of the writer, I would like to know if there is a lot of truth to this article. The article suggests that areas of the brain were targeted and stimulated with electromagnetic waves.

I know about TMS (Transcranial Magnetic Stimulation) devices which stimulate the brain via magnetic fields and tDCS which stimulate the brain via electric current, but I have never heard of any tEMS (transcranial Electro-Magnetic Stimulation) devices. Do they exist?

I've done some searches, but have only come up with results to the more common TMS device.

# Answer
> 2 votes
Maybe this is not what you expected, but since you mentioned electro-magnetic stimulation, I'd like to mention optogentics, where light (electro-magnetic waves) are used to

> control cells in living tissue, typically neurons, that have been genetically modified to express light-sensitive ion channels.

# Answer
> 1 votes
If I understand your question correctly, electro-magnetic stimulation is really quite the same thing as magnetic stimulation.

Typical transcranial magnetic stimulation devices use a large conductive loop, or sometimes 2 loops, and run large amounts of electric current through them. This causes a strong magnetic field to be produced. This magnetic field can alter the behavior of electric current in brain in different ways depending on how it's applied.

There is even a team working on a wearable 'shower cap' with small motors that quickly rotate small magnets. This is more portable, localizable, and versatile than the typical 'wand' based transcranial stimulation, and has shown real measurable effects to stroke victims and also for memory recall tests, so far. (It is very new, however)

One thing to keep in mind is that electricity and magnetism are two sides of the same coin, really, so saying 'electromagnetic field' stimulation is nearly indistinguishable from 'electric field' or 'magnetic field'.

That said, I can't speak for the article. The first line in the article does not bode well:

> We all know that electromagnetic fields are magic and can do anything at any time for any reason.

Maybe try to find some articles on the physics behind why it works, you might get a better answer. As an electrical engineer, I know first hand that this kind of physics can be daunting, but maybe you can find an ELI5 about it.

More to the point: the article is very click-baity, but yes, it is possible to use electromagnetic fields to stimulate specific areas of the brain.

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Tags: cognitive-neuroscience, stimulation
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# Question
Title: Can training on neural networks be selectively undone?
Say that you've trained a network with a set of training data comprising of data points A,B,C, and D.

Can the effect of, say, point B on the network be undone without also losing the training from points C and D? In other words, can we perform some operation on the ABCD-trained network and end up with a network identical to one that has been trained only on A,C, and D?

# Answer
> 2 votes
So lets be clear. (I think) we are talking about back propagation here.

Yes, you probably could get from the ABCD-trained network to an ACD-trained network.

The network adapts with each data point it is trained on. As such, the relationship between how an individual data point effects the net, changes with training. What really matters to the net is the average of all of these interactions, and this is were a lot of specific information related to individual data points is lost.

So in reality, achieving this would require you to know how the net (trained only on A) changed in response B. So we would need to be saving previous changes to weights and biases (for each data point if we wanted it to be more general/flexible).

I don't see this as particularly practical. But you could do it if you wanted.

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Tags: neural-network
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# Question
Title: Official term for the tendency to associate with like-minded people?
I want a term for the tendency of individuals to confirm their existing biases/opinions by seeking out and reinforcing their opinions with like-minded individuals (as far as I know, this is distinct from confirmation bias).

# Answer
> 4 votes
Self-selection bias is probably the best domain specific term. Generally, this is called assortativity, as in assortative mating.

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Tags: social-psychology, terminology
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# Question
Title: Is there a term for a measure in which an extremely high or low score is considered bad?
I'm writing up the results of a measure of emotional management, and I'm hypothesising that under- or over-management of emotions leads to negative consequences.

I'm looking for a term which expresses that both a very high, or a very low score, on this measure, is suboptimal (unlike, for example, IQ, in which a higher score is always considered superior to a lower one), but I can't think of, or find an appropriate term.

It was suggested to me, by a colleague, to use the term "curvilinear", but I don't think that expresses what I want.

# Answer
I recommend looking at non-scientific writing describing when too much AND too little of something is not good-- when average/in the middle is best for a certain outcome. This is true in many aspects of life, so you'll find a variety of words that may express what you want to convey about these high-end suboptimal and low-end suboptimal scores.

English StackExchage wordies may know an existing noun/adjective for exactly what you want. If there isn't a word to express what you mean, you're free to create one. Perhaps pairing the prefix "extra-" in the sense of "outside the optimal range", or the prefix "dys-" in the sense of "unfavorable scores" with word(s) relevant to the measure.
> 1 votes

# Answer
I think Inverted U is what you're looking for.

The specific example given by Wikipedia is the Yerkes–Dodson law, which essentially states that arousal levels that are too high and too low have negative effects on performance of certain tasks.

There are many other examples of this type of relationship. Here is another example, showing that the level of alpha (10 Hz neural oscillations) before a visual stimulus has an inverted U shaped relationship with the evoked response to the stimulus.
> 1 votes

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Tags: measurement, terminology
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# Question
Title: Problems with parameterizing neuronal simulation on a limited number of datasets
I'm hoping to contribute to the OpenWorm project by helping their efforts to parameterize the neurons in CElegans so the model elicits biologically realistic behavior.

The problem is I've got only five activity series datasets for all neurons in CE and I fear whatever model is trained on these datasets won't be an accurate model of the full space of neural activity in CElegans.

Can you give some ideas as to how the field works around this and where I can read about what methods are used to resolve this issue?

# Answer
> 2 votes
Because of variation between organisms, cells in the same organism, or even the same cell separated by a few days, can have different parameter set. However, I think this is where parameter fitting becomes useful. As suggested in the comments knowing how parameters change between cells or over time can be very insightful. Parameter Estimation is very important because it allows us gather more information about the parameter set from less experimental data and thus allowing more complex experiments.

Philosophy aside, here are some tips for getting into the field. I'd suggest reading this open access article by Van Giet *et al.* here and I'll give a brief review of their article.

**General Model** First one needs a general framework to work within,

* What is your type of neuron model going to be? a integrate and fire neuron(discontinuous reset) or is electrophysilogical model (continuous).
* What are the currents/channels/gates in it (Sodium, Potassium, Chlorine, Calcium)?
* what form do the differential equations take?
* What are the known/unknown parameters?

The more you can answer these questions the easier the parameter fitting process will be, but beware, a one size fits all approach rarely works in biology because of cell to cell variation.

**Error Function** Next one needs what is called an error function, or a way to tell if the model output voltage trace is similar to the actual voltage trace. The most classical (but in my honest opinion the worst one) is the $\mathcal{L}\_2$ norm on the voltages. The $\mathcal{L}\_2$ is simply

$$\sqrt{\sum^{N}\_i (V\_{model}(i)-V\_{data}(i))^2}$$

To see why this is so bad I attached a sample (simulated trace from the Hodgkin-Huxley model).

The Blue Trace is from a Neuron with slightly less injected current then the yellow Trace one. As you can see yellow has a faster frequency than blue, and as a result the $\mathcal{L}\_2$ norm is massive for each misaligned spike. However the spike trains are intuitively very close as seen not only in where the spikes line up but where the spikes so one would like a measure that defines misaligned phase and frequency.

Van Geit *et al's.* insight is that the $\mathcal{L}\_2$ is the wrong norm to compare voltage distance in. What they do is make a parametric plot of voltage verses voltage's derivative. The then compare distance between the curves like in the below plot.

.

We see that the voltage traces are indeed very similar, but to calculate distance between these curves, we must disregard time data. We can imagine subdividing phase space into a grid of equally sized boxes. Then count up the number of data points and model points in the boxes. In math notation this amounts to

$$ \sqrt{\sum^{N\_x,N\_y}\_{i,j} (V\_{model}(i,j)-V\_{data}(i,j))} $$

we have lost information about phase of the spike. It is also important to note that this is *highly dependent* on the size of the boxes, if they are too small the error will be high, too big the error will be to low. While there method may not be the only proposed solution it does better than the $\mathcal{L}\_2$

Here is both methods side by side for comparison. The black dot is the true solution. Blue is $\mathcal{L}\_2$ and Yellow is Van Geit's method. You'll note that both are \`\`noisy" but there is a better trend in Van Geit's method than the $\mathcal{L}\_2$ norm, thus optimization is easier. For the $\mathcal{L}\_2$ method notice how the function is flat far away from a very steep and narrow valley. This is hard for optimization algorithms to hit. Van Geit's method is better because it has more of a downward slope that can be followed to a better global minima.

Also Note that this noise is not from random variation (although that makes it worse) but rather from discretization of the data and model. (remember everything stored in a computer has a sample rate no matter how small).

**Optimization Algorithm** Now Once has an appropriate error function one needs to use a optimization algorithm too find the local minimum of said error function. In my example here, I am using injected current as my parameter, but in every neuron model has many parameters that one needs to optimize over so direct visualization like is usually impossible.

Another caveat is the \`\`noise". these local valleys can make optimization algorithms get stuck in the local minima. Stochastic (random) optimization algorithms like simulated annealing can help with getting stuck in these valleys, as they have a chance to jump past them.

**Good Initial guesses** As far as not responding the "full space'' of solutions, the more of the possible inputs one has the better chance of being able to predict a different input. Also defining the computational behavior of your neuron is a good start. Having a general model that acts qualitatively correctly but not quantitatively is often a good start to parameter fitting, This means one doesn't start with a neuron that doesn't respond to inputs, or something else physically unrealistic.

Anyway hope this gives a background to things to consider, this field is far from solved, and in need of creative solutions.

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Tags: theoretical-neuroscience, computational-modeling
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title: Why do people love nature?

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

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

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

Thank you very much,

# Answer
> 0 votes
People love nature because truth, nature/natural experience, and reality go hand in hand. Nature provides serenity, beauty, and calm. Our **world of experience** is what gives us, and provides for, life. Ultimately and fundamentally, the integrated extensiveness (and sensibility) of being and experience go hand in hand, as the self represents, forms, and experiences a comprehensive approximation of experience in general by combining conscious and unconscious experience. In fact, we always begin with typical/ordinary and common experience in establishing physical fundamentals/truths. Experience is the best teacher, and the creations of our thought that replace nature/natural experience, such as TV and mirrors, *maximally* **reduce** the integrated extensiveness of space/our experience. A true, extensive, integrated, and natural balance of being and experience is best. Balance and completeness go hand in hand. If we walk away from reality, reality walks away from us.

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Tags: cognitive-neuroscience, experimental-psychology, psychology
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# Question
Title: Which is a better statistical option to compare differences across groups?
I have two groups (13 experimental and 13 control participants) performing on two cognitive tasks. I have accuracy (omissions, commissions) and reaction time measurement from each test for each person. To avoid type-I error, I was suggested to decrease my number of DVs, I now have d-prime (d') and reaction time (RT) as the DVs (both continuous). I would like to compare performances on both the tasks, across both the groups. My questions pertaining to this design are:

1. Is d-prime a good measurement to substitute accuracy scores ? or could you please suggest a unitary index that would reflect behavioral performance (from omissions, commissions, RT data)
2. Should I do a one way MANOVA? (IV- groups; DV- test1 d', test2 d', test1 RT, test2 RT)?
3. or Should I do a mixed model MANOVA? (if yes, how to do this, what are my DVs)?

# Answer
> 3 votes
*If you have single-trial data*, the **drift-diffusion model/DDM** and related models, originating with Roger Ratcliff (1976/1978), can simultaneously fit the whole response distribution, both RTs and accuracies. It captures phenomena such that in some experiments, errors are systematically faster or slower than correct responses.

Fitting and interpreting the DDM can be non-trivial, but it has many advantages, such as

* accurately accounting for the distribution of RT data
* directly relating to cognitive processes (e.g. evidence accumulation speed, sensory encoding speed)

The DDM works by modeling the decision process as a random walk next to (usually two) decision thresholds (e.g. corresponding to the correct and the incorrect button in a 2-alternative false choice task), which after an initial period of encoding begins drifting towards the correct boundary at a speed corresponding to the effectivity of taking up evidence. Occasionally, the drift process reaches the wrong boundary. When a boundary is crossed, execution of the corresponding response is initiated.

The DDM is fitted to the whole RT distribution and the resulting parameters can be submitted to statistical tests between conditions. For an example of hierarchical Bayesian estimation of the model, consider HDDM.

# References

Ratcliff, R. & Murdock, B. B., Jr. (1976). Retrieval processes in recognition memory. Psychological Review, 83, 190-214.
Ratcliff, R. (1978). A theory of memory retrieval. Psychological Review, 85, 59-108.
Forstmann, B. U., Ratcliff, R., & Wagenmakers, E.-J. (2016). Sequential sampling models in cognitive neuroscience: Advantages, applications, and extensions. Annual Review of Psychology, 67, 641-666.
Ratcliff, R., Smith, P.L., Brown, S.D., & McKoon, G. (2016). Diffusion decision model: Current issues and history. Trends in Cognitive Science, 20, 260-281.
Wiecki TV, Sofer I and Frank MJ (2013). HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python. Front. Neuroinform. 7:14. doi: 10.3389/fninf.2013.00014

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Tags: cognitive-psychology, statistics, experiment-design
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# Question
Title: I need good introductory texts/publications on brain networks and functional integration/segregation
I am a soon to be graduating applied mathematician interviewing for a research position soon in a lab considered with neurological imaging and association of brain networks with things like aging, combined tasks, etc.

In my opinion, I believe I have a strong repertoire of applied mathematics and research experience in applied mathematics/computation relevant to the task at hand, and I can talk comfortably about the skills advertised (data analytics, programming, experimental design, etc.). My background is in graph theory, computational biology, and systems modeling. However, I want to be able to communicate about brain networks and integration/segregation of the brain while factors such as aging, task completion, injury, etc. change during the interview. Therefore, I would love to skim some introductory texts or read some landmark papers about this field so I can sell myself as competent for the job.

While the job itself does not require the research assistant to be equipped with such information, I think it would be best to up the ante in terms of how I present myself. Could anyone recommend such texts or literature?

If it helps, I have an undergraduate degrees in biology/biochemistry so I'm relatively familiar with the nomenclature surrounding neurophysiology, neurotransmitters, etc. and I have a working knowledge of an introductory neuroscience and psychology course so I am familiar with theories of memory, and the different parts of the human brain.

# Answer
> 3 votes
A good introductory book is "Networks of the Brain" by Olaf Sporns. It will give you a general overview of the ideas and theories in the field. For more details consult the bibliography or read some of the journal articles by Dr. Sporns.

https://mitpress.mit.edu/books/networks-brain

http://www.indiana.edu/~cortex/index.html

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Tags: cognitive-psychology, cognitive-neuroscience, cognitive-modeling
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# Question
Title: Is there any research showing we only like to see/read information on themes/topics/ideas we like?
I have been thinking about how using social networks (like Facebook, Twitter and etc) have been changing the way we think. For example, Facebook feed is tailored on the basis of what we like. On Twitter, I usually follow people whose ideas I adhere to. So we are being introduced to information we like more and more thereby making us biased towards ideas that we like.

My question is: can you kindly point me to research studies that show we like to see/read information on themes/topics/ideas that we like?

Can you kindly give me some pointers on that? Thanks in advance.

# Answer
What you describe is known as Selective Exposure to Information.

> Selective exposure is a theory within the practice of psychology, often used in media and communication research, that historically refers to individuals’ tendency to favor information which reinforces their pre-existing views while avoiding contradictory information.

Below find extracts from this article about selective exposure:

> The researchers found that people are about twice as likely to select information that supports their own point of view (67 percent) as to consider an opposing idea (33 percent). Certain individuals, those with close-minded personalities, are even more reluctant to expose themselves to differing perspectives
> ...
> Perhaps more surprisingly, people who have little confidence in their own beliefs are less likely to expose themselves to contrary views than people who are very confident in their own ideas ...
> The researchers also found, not surprisingly, that people are more resistant to new points of view when their own ideas are associated with political, religious or ethical values.

The above article is based on this research article.

A very related theory is the confirmation bias.

> Confirmation bias, also called confirmatory bias or myside bias, is the tendency to search for, interpret, favor, and recall information in a way that confirms one's beliefs or hypotheses, while giving disproportionately less consideration to alternative possibilities.

In my opinion the reasons why we employ selective exposure are:

* Preserve and form identity
* Belongingness
* The need for certainty. We need to have firm theories that do not change whenever we encounter dis-confirming evidence.
* Competence. The need to have good skills i.e. fishers forum
> 2 votes

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Tags: cognitive-psychology, social-psychology
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# Question
Title: Can the desire to change a romantic partner ever be satisfied?
Based on the typical relationship advise: "Don't try to change your partner" and such, I would say that many people want to see their romantic partners behaving just a little bit differently. It is a common thinking pattern.

For example, a person may be wanting for the strong and independent partner to be more caring and compassionate. Or wanting for a partner to spend more time listening, or being more punctual, etc.

These thoughts can be summarized as "Our relationship would be perfect if only he/she did XYZ". In other words, people expects to experience relationship bliss when their partner complies with their wishes.

It seems to me that the XYZ is always a moving target, and can never actually be fulfilled, a sort of mirage, just out of reach. This makes me think these thoughts could be caused by some neurochemical process.

**Is expectation of relationship bliss, conditional on XYZ is just a side effect of some neurochemical process?** Is it an expression of seeking novelty in a relationship ("same, but different")?

**Edit:** To clarify what I mean by Neurochemical: If a person ingests 8 shots of hard liquor, there's a new chemical -alcohol introduced into blood circulation. In a short time alcohol will affect cognition regardless of any protests from the person's higher order cognition. A person cannot will themselves to not feel the effects of the chemical and act normal.

The ingested chemical affects the brain (neurochemical?). Until the chemical is cleared from the circulation or neutralized, the person will continue experiencing cognitive effects of the chemical compound.

By **neurochemical process** I meant an indigenous process by which brain can release a brain affecting chemical/hormone that will act according to the model above. Adrenaline in fight/flight response is an example of such chemical. Maybe Oxytocin is another example. I know of words like psychoactive, psychedelic, neuromodulator and less scientific terms like "mind altering", but none of these seemed to fit.

# Answer
> 1 votes
People are different. Our thoughts and behaviour emerge from a neural network that is shaped by countless events and no two people experience the world exactly in the same way. Even identical twins present conflicting attitudes and beliefs.

Therefore, social interaction will always involve some level of conflict. Cultures form due to differences between agents.

This conflict is actually pivotal to our well-being, and is far better recognised by Eastern philosophy - conflict drives change, change results in conflict. If we all thought exactly the same, our life would likely be a a bore and we would have little motivation improve it.

Partners are no different from any other person, but our interaction with them is more intense, and often involves high personal stakes. In turn, conflicts are frequent and often emotional, but conflict resolution and behaviour change are not easy affairs.

You are right that our mental state is in constant flux - people's needs and aspirations change over time. So there will always be some other desired state - many cognitive models are goal-driven (goal being a desired state).

I'd attribute your concern mainly to social aspects that stem from some cognitive properties. I've covered individual differences, and due to limited relevance omitted pattern recognition and change detection, which also play an important role in relationships.

> This makes me think these thoughts could be caused by some neurochemical process.

I'm not sure what you mean by *neurochemical*, where did electricity go, and whether you simply mean a *cognitive process*. But the sentence is unclear since any though is caused by some cognitive process (involving both neurons and chemicals). I also don't quite see how such conclusion follows from the premise of goals being a moving target.

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Tags: cognitive-psychology, cognitive-neuroscience, sexuality, behavior
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# Question
Title: Which neurotransmitters can be measured in a living human brain?
I'm interested in learning more about the modern techniques that are used for scientific studies of neurotransmitters in the living human brain. As far as I know, there are 4 neuromodulator systems within the human brain.

They are:

Noradrenaline system

Dopamine system

Serotonin system

Cholinergic system

As far as I understand, some of biosynthesis pathways of these systems are interconnected, with the level of one neurotransmitter affecting levels of others further down the line.

**Can anyone comment on which ones of these neurotransmitter levels can the modern science (as of 2012) measure or at least estimate in the living human brain?**

How close is modern science to understanding the cascading effects that these neurotransmitter systems may have on each other?

**Update:** The other similar question deals with the imaging techniques of neurotransmitters, and this paper describes the process that might be used in the future, after tests and approvals. Structure-Guided Directed Evolution of Highly Selective P450-Based Magnetic Resonance Imaging Sensors for Dopamine and Serotonin

What is not very clear to me from the other answer if all 4 neurotransmitter systems listed above can be measured in a living brain, or if some of them are out of reach of modern science. **Can we measure Noradrenaline, Dopamine,Serotonin and Choline/Acetylcholine levels in a living brain using modern methods?**

Thank you for your input!

# Answer
> 10 votes
There are many, many more neuromodulators in the brain than that. Essentially anything that binds to G-protein coupled receptors could be considered a neuromodulator. Even "classic" fast neurotransmitters like GABA and glutamate have "neuromodulatory" receptors (GABA-B receptors for GABA, 3 different families of "metabotropic glutamate receptors"). Peptides (e.g., endogenous opioids, orexin, oxytocin...) also commonly bind to G-protein coupled receptors.

There are even "orphan receptors" that exist, but we haven't identified the chemical that naturally binds to them.

As you get deeper into pharmacology, you'll learn that each of the common neurotransmitters has MANY kinds of receptors that are located in different places and do different things. On the other hand, G-protein coupled receptors can be be classified according to which G proteins they bind to. "Second messengers" would be a good thing to search for to learn more about this (cAMP, phospholipase C.....).

To answer your question, though, we can measure the release of some neurotransmitters using PET. The idea is that you pick a drug that binds to a particular receptor for that neurotransmitter (e.g., dopamine). Then, you manufacture some of that drug such that one of the atoms in the drug is radioactive (i.e., the drug is made with a radio-isotope of carbon, fluorine, etc.). The PET scanner will pick up the radioactivity released by the drug, which will be localized to places that contain that type of receptor (e.g., D2 receptors). Drugs don't stick to receptors perfectly, though. The natural ligands for the receptors ALSO bind to the receptors.

You can take advantage of this by having two conditions in your experiment. In one, subjects do some control task while you measure the level of radioactivity in various parts of the brain. In the other, they do the task you're interested in. If that task is associated with an increase in dopamine release, you should see a DECREASE in the amount of radioactivity, since some of the receptors will now be occupied by normal, nonradioactive dopamine instead of the drug. The more dopamine release, the less radioactivity.

Neurotransmitter levels can also be measured directly using a technique called "microdialysis". The idea is that you've got an animal implanted with a probe that ends in a particular brain region you're interested in. The end of the probe is a "semi-permeable membrane", and you've got liquid flowing through the probe. At regular intervals, you take some of the liquid and use a chemistry technique called high performance liquid chromatography (HPLC) to measure the levels of various things that dissolved into the probe. In rare cases, you can do microdialysis experiments in humans (patients with severe epilepsy).

Another way of measuring the release of particular neurochemicals, with better time resolution than microdialysis, is fast scan cyclic voltammetry (sp?). I'm not really familiar with it, but it exists.

In terms of interactions among different neurotransmitter systems, there are many ways this can happen. Cells that release transmitter A might be excited or inhibited by transmitter B. Transmitters A and B might act on different G proteins in the same cell, with opposite effects on some downstream system ("Gi coupled receptors" and "Gs coupled receptors" have opposite effects on cAMP, for example). Receptors for two different transmitters may be physically right next to each other and affect each other's functioning (D2 receptors and adenosine A2A receptors, for example). Neurotransmitters may bind to each other's receptors or use each other's uptake proteins (cortical dopamine is taken up by norepinephrine transporters; there are norepinephrine receptors in the striatum despite the absence of norepinephrine terminals, presumably because they can be activated by dopamine). Single neurons may release more than one transmitter at a time (glutamate and dopamine can be released from the same cell). The downstream effects of one receptor may cause a second receptor to be phosphorylated, affecting its function in some way. Downstream effects could also change gene expression.

My suggestion would be to start searching PubMed for review papers related to things you're interested in. At least some of them should be available without a university library.

# Answer
> 0 votes
MRI Spectroscopy is another method for measuring neurotransmitters in the living human brain.

Here are some examples:

Dopamine Reduction in the Substantia Nigra of Parkinson's Disease Patients Confirmed by In Vivo Magnetic Resonance Spectroscopic Imaging

Direct detection of brain acetylcholine synthesis by magnetic resonance spectroscopy

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Tags: neuroscience, measurement, neurology
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# Question
Title: Why are most people not persuaded by rational arguments?
The sentence could look as a provocation for many people, but the thoughts are not always rational and linear. But why this happens? Is it possible to give a short answer?

*"Counter to what you might think consciously, few people are really persuaded by logical and rational arguments"*

source: https://www.youtube.com/watch?v=gLFhCrTt-ZA&t=1m20s

# Answer
You may be thinking of the Backfire Effect. When presented with logical and rational evidence disputing a strongly-held belief, most people's natural tendency is to hold on even tighter to those beliefs rather than to reassess their position.

As for *why* it happens... that's a matter of some debate (surprise, surprise), but the general thinking seems to be that it's a mental reaction to avoid cognitive dissonance. The page I linked contains references to several studies on the subject, though as you might expect, the results vary.
> 20 votes

# Answer
I'm not a cognitive science expert, but I happen to have some experience in change management / trying to convince people. There are in fact a lot of *logical* reasons for refusing logical and rational arguments.

Suppose someone tries to share an idea with you.

I will pass on the very obvious problems of "not befitting my interest" / "triggering culpability".

A VERY common problem is the fallacy that, "If I am wrong, then my opponent is right." If you hate your opponent (or whatever maybe impolite person is trying to tell you to change your ideas, e.g. your "bad way of living", or arrogantly seeing you as a miseducated inferior), then you'd rather die than accept that idea, which would $\rightarrow$ (fallacy) prove him right and thus $\rightarrow$ (fallacy) superior to you.

Another common problem (colleagues!) is, "I must show I'm the most intelligent." If someone tries to challenge one of your ideas, then it $\rightarrow$ (fallacy) makes him more intelligent than you, since $\rightarrow$ (fallacy) you were wrong. You will then try to find whatever counter-argument you can to prove him wrong, (fallacy) $\rightarrow$ thus reasserting yourself as more intelligent.

Another common but more subtle problem is that we all unconsiously build a representation of the world so that we can think on how to adapt to it (evolution). And of course we stabilize this representation when it fits correctly $=$ when we are in no immediate danger *and also* when we are in a comfortable position ;) Example: "The society rules are that people who adhere to the dominant opinion are more likely to succeed" (adaptation to environment) $+$ "People who don't share this dominant opinion are fascists/integrists/extremists, etc., who are a minority anyway" (rationalization of why I adhere to it, advantageous position). Now suppose that an idea challenges your representation of the world. Then it implies $\rightarrow$ that you are no longer in a superior position, and $\rightarrow$ that the rules of the world may not be what you thought, and that $\rightarrow$ you may be bad at understanding the world, thus in a weak position for planning corrective actions ($=$ adapting). Such a calling into question is incredibly painful! To evolve from this situation, one needs to experience full grief (as in "Five Stages of Grief").

I speak from experience. I once had the mindset, "Rules of the world are following religion X" $+$ "Those who don't follow religion X are pagans/heretics/whatever bad people" (but it's the same even outside religion). The challenge was when I realized after an event that $1)$ I was not that good, and $2)$ "pagans/heretics" were actually better than me on this subject. This triggered a very painful 5-stage grief process over more than 6 months where I suffered a lot before re-establishing a new, more correct vision of the world fitting those new pieces. I still needed a few years to fully unwrap things. From my experience, it seems I was lucky to be able to do that since it's not a given (cf. all possible failures of the 5-stages). And seeing backward, it was not the fault of religion X at all. I had built this simple and a bad representation myself to avoid facing some unpleasant truths.

Another common problem is the incorrect mixing of opinions and culture, which fallaciously leads to: idea challenged $\rightarrow$ (fallacy) culture challenged $\rightarrow$ (fallacy) our identity is challenged $\rightarrow$ (fallacy) our ancestor's work and worth challenged. Who would want that?

What you should understand is that the mind needs some security and self-confidence. All the mechanisms I exposed are mostly subconscious and argument rejection results mostly from an auto-defense of the mind, though we still *have* partial control over it. (I'm sure you have examples of people who honestly face the truth and others who never want to face it.)

If you encounter people that have realized all those points, discussion is easy even if you are not polite or your ideas are not well refined. They will look at the good points, accept the ideas and even help you refine your ideas. This is how everyone should be!

For other people, I've found that challenging ideas is better done when:

1. you are polite and non-threatening
2. you first outline the strength and qualities of the people you speak to their culture $+$ their ancestors
3. you clearly separate the challenged ideas from culture and show similar idea change by good/respected people in their own culture
4. as much as possible you make the new idea look like it comes from themselves.

Oh, and one last thing: humility. Everyone trying to spread an idea obviously thinks of it as "logical and rational", so if it's not accepted $\rightarrow$ (wrong!) it means that people are not rational $\rightarrow$ (wrong!) people need to be reeducated $\rightarrow$ (wrong!) there are some horrible opponents who fight my ideas, I must suppress them. Such thoughts led and are still leading to atrocities. Maybe it's just you who are wrong, illogical and irrational ;)
> 7 votes

# Answer
Some generalizations:

* Because Enlightenment-era rationality, with its values of liberalism and rationality and progress, has a very bad (read: hypocritical) historical track record of irrational, inegalitarian, maximally exploitative colonialism. Phrenology and Orientalism are among its crown jewels. The first chapter of Immanuel Wallerstein's *World-Systems Analysis: An Introduction*, dedicated entirely to post-Enlightenment knowledge-structures, is a very good read on this.
* Because all too often in relationships, "rationality" is a fantastic card to play for manipulative, abusive boyfriends/girlfriends everywhere. *Captain Awkward* is a fantastic blog for this, search its entries for "rational" sometime.
* Because rationality is often a function of education, and education is often a function of wealth.
* Because the true rationalist and the true narcissist both claim to be completely rational. Rationality is a *very* widely held virtue, for better *and* for worse.
* Because the Newtonian/Euclidean/Cartesian foundations of our understanding of the world are in serious question right now, in this era of quantum mechanics and chaos theory. What if the universe *itself* was irrational? Nonrational? Extrarational?

People aren't stupid. An intuitive distrust of the institutions associated with "rationality" isn't necessarily irrational.
> 3 votes

# Answer
I am not an expert, but I have given this question a fair bit of thought. I would suggest that the tendency to oppose rational arguments in favor of maintaining beliefs depends upon what beliefs we are speaking of. There are many beliefs that do change, but these tend to revolve around mere fact.

When you look at deeper belief, much of it is based upon self image. People often decide what type of person they are (or want to be) and then adopt the beliefs they think that type of person is supposed to have, complete with the standard rationales.

So, when you challenge their belief, you are not just challenging some rational thought, but rather challenging how their world works and who they are. When that happens, there is considerable cognitive dissonance, and people start doing mental gymnastics to find a way out of the situation.
> 2 votes

# Answer
I am not an expert.

1. Words are vague. People can call something investment even if no money is invested.
2. It's much more effective to read people's motives than to read their words.
3. Humans are self seeking rational assholes. Reasoning are often done for moral reasoning. The thing is none of us are too moral. We do the moral acts for indirect benefit of avoiding punishments. Saying something is wrong means absolutely nothing to motivate a person unless he see a disadvantage of that.

Let me share you an experience about how a lawyer manage to sell me an insurance.

I am already afraid of buying insurance. So many people says that insurance agent are liars.

However, I got a lawyer and I only want to buy a little bit.

I asked the lawyer, I want a small insurance. The rest of the money should be invested. They agreed.

I asked them, "How much of the money is for investment and how much for insurance." The lawyer said all investment.

One year latter I learned that I lost half of the money for "fees". The lawyer simply said it's all investment. Unit link is long term investment.

So basically I ended up buying a small insurance at 100 times of normal price. The money I thought are invested are gone for that irrational fee. I filed a lawsuit for that.

He is in a very stretch sense, technically correct. The insurance is small. The benefit is small. Even the insurance company claimed the same thing. Unit link is long term investment. It's an investment where 100% of the money is spent on fees. But technically it's still an investment.

Here, a "reasoning" that "it's all investment" is absolutely useless. It doesn't mean what I think it means. It makes me throw money away.

And that leads to what typical problems we have on "reasoning"

I would give another sample.

Bob sees money on table. I said don't steal it's wrong to steal.

What really happens is that humans are rational assholes. Bob would steal if and only if he won't get caught. However, humans like to pretend that they are "moral" people. Humans like to pretend that they wouldn't steal not because they might get caught but because they are a moral person.

Here, any rational reasoning of whether stealing is wrong or not will be totally irrelevant. You can say stealing is wrong. Bob will say that it's government's responsibility to avoid corruption. Most of us would break the law and find some justification to do it. So what's the point of reason?
> 1 votes

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Tags: cognitive-psychology, communication
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# Question
Title: Why are some people jealous of other people's success?
I have seen many time in my life where I encountered few peoples who hate those person who are going great with their life and achieving something. I mean why some people hate those person who are doing great in some particular field but the other guy is not able to do it.

For example, if 2 persons are working together and among them one of them is getting famous and achieving so many things then the other guy starts hating him and sees him as an enemy or rival.

Is there any explanation behind this type of behaviour or it is common to most of the people as it is natural?

# Answer
Social Order and Hierarchy. As Humans our brains are designed to see where we fit in the social order. If someones success is perceived as a threat, it can lead to anxiety and fear from the person whom is resentful and jealous.

While in the modern world there is no need for this fear, our ancestors had to compete within their tribe(s) for resources,status,choice etc. If one member of the tribe gained more status than another they would have more access to resources, supplies, privilege, reproductive power etc. This could lead to competition from other members of the tribe fearful that they would not have enough resources, or access to enough supplies, ultimately seeing one of their tribe members as a potential threat to their own well-being.This applies to survival and reproduction value as well.

In conclusion: While this type of behavior can still be common, it is a highly outdated form of thinking that comes from our hardwired tribe mentality, defense mechanisms,and the need for humans to look for for a social order and hierarchy in modern society.
> 4 votes

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Tags: cognitive-psychology, social-psychology
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# Question
Title: How come that someone understands an utterance only after a few moments?
I have seen and experienced the following phenomena. It often happen in a work environment but can happen anytime and anywhere:

1) Person A is doing something that requires full concentration (like reading or thinking deeply).

2) Person B suddenly ask/say something to Person A

3) Person A replied with "What do you say?" or "Pardon please" (or something similar, as if he/she doesn't hear what person B said) after some brief pause/delay.

4) Person B didn't answer back (optional)

5) Person A answers/responses (before Person B repeats what he/she said) to Person B (as if he/she heard it fully)

Is there a psychological term that describes/explain it? How it is happening? What is its effect with the brain of Person A if there is?

P.S. I don't know what is the right tag for it.

# Answer
I think what you describe can be explained by echoic memory and working memory.

> **Echoic memory** is one of the sensory memory registers; a component of sensory memory (SM) that is specific to retaining auditory information. The sensory memory for sounds that people have just perceived is the form of echoic memory. ... This particular sensory store is capable of storing large amounts of auditory information that is only retained for a short period of time (3–4 seconds). This echoic sound resonates in the mind and is replayed for this brief amount of time shortly after the presentation of auditory stimuli.

.

> **Working memory,** a core executive function, is a cognitive memory buffer with a limited capacity that is responsible for the transient holding, processing, and manipulation of information. Working memory is an important process for reasoning and the guidance of decision making and behavior.

.

Person A is fully concentrated and his working memory capacity is full, so he does not pay attention to what the other person is saying. But when person A asks "What do you say?", working memory resources are released and attention is diverted to the echoic memory which replays what person B said.
> 1 votes

# Answer
Probably, everyone has experienced such situation, although only a few people pay attention to this.

It is a usual human behaviour. People do ask about your question to get some time for thinking what to answer. Furthermore, this behaviour is very common among journalists, because this may be a way to avoid answering the question.

In addition, there is another reason. A person who is asking feels more confidence. Thus, people may ask again to bring the situation under their own control.
> 0 votes

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Tags: cognitive-psychology
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title: Why do people hide wealth?

text:
# Question
Title: Why do people hide wealth?
I was reading about Panama leaks and I was wondering why do people keep their wealth secret? What's the psychology behind it?

# Answer
Quiet simply: loss aversion

People are adverse to loss, the majority of people who are wealthy pay into a system they get little direct benefit from, in comparison to poorer people who tend to get back what they put in or more depending on circumstance. However the rich, and everyone else, benefit from being in wealthy westernised societies with higher levels of tax, because people have more money in these countries. It is the tax system which allows these countries to develop their citizens, poor countries have lower levels of education and poor infrastructure as a result of low taxation and poor distribution of expenditure. However people do not calculate costs and indirect benefits together..."individuals bracket indirect benefits and costs separately. This is the case when the primitive utility function"..."satisfies the decomposability property (Tversky and Kahnemann, 1991)" Alesinay and Passarelliz (2015). Basically as indirect benefits are not calculated directly from costs individuals will look to avoid loss, its quiet natural to avoid loss. If you think about inheritance tax, money and property that have already been taxed are taxed again, surely an individual should be able to decide what to do with their property? Of course the state would agree for redistributing wealth for the benefit of society. Although this would seem unfair to the individual who saved in comparison to those that spent all they had. The point is that its just as easy to justify tax avoidance as it is to promote taxation, we could easily get into the principles of collectivism and individualism here but that is for the politics and philosophy areas of stackexchange.
> 2 votes

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Tags: cognitive-psychology, social-psychology, economics
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# Question
Title: What do anatomical substrates of conditioned taste aversion tell us about  treatment?
Conditioned taste aversions (CTAs) or Garcia effect are a byproduct of feeling ill after we've consumed a certain food. These aversions is present even if the illness is not related to ingestion and are difficult to extinguish in humans. This makes sense in light of the fact that in model systems like the rat they are entrenched in brainstem circuitry (Mickley et al., 2011).

**With such a deep association taking place, does the likelihood of extinguishing these aversions via cognitive therapy (e.g., CBT) decrease dramatically?** What would be a possible inroad into treating human subjects with such an aversion?

> Mickley GA, Wilson GN, Remus JL, Ramos L, Ketchesin KD, Biesan OR, Luchsinger JR, & Prodan S. (2011). Periaqueductal gray c-Fos expression varies relative to the method of conditioned taste aversion extinction employed. *Brain Res.*;1423:17-29. http://dx.doi.org/10.1016/j.brainres.2011.09.033

# Answer
> 4 votes
Your question presupposes that 'deep' (in the brainstem) is the same thing as difficult to extinguish. But the anatomical location doesn't tell us how difficult it is to unlearn a CTA. One reason CTAs are difficult to extinguish is because extinction relies upon exposure to the cue (taste, in this case). And not many animals (including humans) will voluntarily re-expose themselves to unpleasant tastes. The resistance to extinction usually claimed for CTAs is more likely due to avoidance behaviour, rather than anatomical location of the neuroplasticity involved. When CTAs are extinguished by forcing the animal to taste the cue (e.g,. by gavaging), extinction occurs at the same rate as other flavour preferences. Source: http://ses.library.usyd.edu.au/handle/2123/372

An implication for treating CTAs in humans (e.g., after chemotherapy) is that re-exposure to the taste will eventually be successful. Obtaining voluntary re-exposure in the patient might be achieved by counter-conditioning such as combining the taste with a sweet additive.

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Tags: psychiatry, conditioning
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