# Question
Title: Do we recognize ourselves better when we see our mirror image?
A friend of mine recently noticed that we both have a birthmark on the face. He looked at me and said that we have exactly the same mark. But he has it left and I right. But, when looking in a mirror, we see it on the other side.

So, I wonder: **Do we recognize ourselves better when we see our mirror image compared with *e.g.* a video of ourselves?** Where is this studied?

# Answer
> 6 votes
Bredart (2003) discusses your exact hypothesis and reports the results of a couple of studies. I'd recommend having a read of the article.

The authors acknowledge that in contrast to familiar others the experience of our own face typically comes through self-inspection in mirrors.

They summarise some relevant literature:

> Troje and Kersten (1999) showed that participants were faster when naming frontal views compared with profile views of their own face, and that this advantage for frontal views disappeared when naming familiar colleagues’ faces. In addition, Laeng and Rouw (2001) showed that the full-frontal view is superior to other views for facial self-recognition but not for the recognition of other people’s faces. A pose corresponding to 22.5 degrees from the frontal view seems to be optimal for other people’s faces. However, for highly familiar faces (e.g. faces of close friends or partners), the frontal view could be recognised as quickly as the 22.5 degrees view. In short, because of ecological constraints on visual experience, self-recognition is easier from frontal views than from other views. This superiority of frontal views was not observed for other highly familiar faces.

They also discuss one methodology that involves "searching for a target face among a set of other faces". Thus, the speed of finding the face is one way operationalising familiarity.

With regards to their findings, the following quotes the abstract:

> Experiment 1 examined our ability to recognise the usual horizontal orientation of our own face (mirror orientation) as compared with another very familiar face (normal orientation). Participants did not use the same kind of information in determining the orientation of self-face as in determining the orientation of the other familiar face. The proportion of participants who reported having based their judgement on the location of an asymmetric feature (e.g. a mole) was higher when determining their own face’s orientation than when determining the other familiar face’s orientation. In experiment 2, participants were presented with pairs of manipulated images of their own face and of another familiar face showing conflicting asymmetric features and configural information. Each pair consisted of one picture showing a given face’s asymmetric features in a mirror-reversed position, while the facial configuration was left unchanged, and one picture in which the location of the asymmetric features was left unchanged, while the facial configuration was mirror-reversed. As expected from the hypothesis that asymmetric local features are more frequently used for self-face judgements, participants chose the picture showing mirror-reversed asymmetric features when determining the usual orientation of their own face significantly more often than they chose the picture showing normally oriented asymmetric features when determining the orientation of the other face. These results were explained in terms of competing forward and mirror-reversed representations of our own face.

### Reference

* Bredart, S. (2003). Recognising the usual orientation of one's own face: the role of asymmetrically located details. Perception, 32, . DOC
* Laeng B, Rouw R, 2001 “Canonical views of faces and the cerebral hemispheres” Laterality 6 193-224.
* Troje N F, Kersten D, 1999 “Viewpoint-dependent recognition of familiar faces” Perception 28 483-487.

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Tags: reference-request, perception, vision
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# Question
Title: Physiological differences between brains of Conservatives and Liberals
I work for a non-profit research organization and I have been assigned to do research on this topic. I have been doing my best to find studies on this topic but every website and article seems to only reference the study by Amodio et al (2007).

* What other research has examined physiological differences between brains of Conservatives and Liberals?
* What is the current understanding of what, if any, brain differences exist?

### References

* Amodio, D. M., Lost, J. T., Master, S. L., & Yee, C. M. (2007). Neurocognitive correlates of liberalism and conservatism, Nature Neuroscience. PDF

# Answer
> 10 votes
The easiest way to work forward from a well-cited article is to do a forward Google Search. My answer is almost completely based on such a search and concentrates on three brain regions: amygdala, insula cortex, and the anterior cingulate cortex; note that all three regions are linked to emotion.

Keep in mind: when you take any two groups of people that differ significantly in behavior, socio-economic background, age, education-level, etc. It is not difficult to find differences between them on many fronts, and certain brain-structures is one of them. The difficulty of these studies, is two-fold: (1) the researchers have to do very good controls to make it believable that the difference loads on political ideology and not one of the many other things differences in political ideology usually correlates with, and (2) provide (or at least make believable to exist) some sort of causal relationship between the brain-structures they observe and the relevant behavior (i.e. political leaning). When you read these papers, these are the two points you should carefully check.

---

Oxley et al. (2008) showed that you don't need a brain scaner to observe correlations between physiological differences and political ideology:

> \[I\]ndividuals with measurably lower physical sensitivities to sudden noises and threatening visual images were more likely to support foreign aid, liberal immigration policies, pacifism, and gun control, whereas individuals displaying measurably higher physiological reactions to those same stimuli were more likely to favor defense spending, capital punishment, patriotism, and the Iraq War.

The nice thing about these measurements, is that a mechanism for the correlation is easier to establish: if you are more likely to react strongly in your experiencing and processing environmental threats, then you are more likely to have that reflected in your political ideology.

Schreiber et al. (2009) followed a similar line of thought by studying how Republicans and Democrats perform in a risk-taking tasks. While the 54 participants were evaluating risks, the researchers used an fMRI to look at the activation in their amygdala. This is a natural brain region to look at, since it is believed to be important for emotional processing. They concluded:

> a two parameter model of partisanship based on amygdala and insula activations achieves better accuracy in predicting whether someone is a Democrat or a Republican than a well established model in political science based on parental socialization of party identification.

The importance of the amygdala has also been tested across culturues. Rule et al. (2010) conducted a study in snap judgements in voting decisons of American and Japanese natives and showed analogous activation of the amygdala in both groups even though the traits that lead to judgments differ across the two cultures.

The importance of the insula is also not surprising, since this brain region is associated with processing of social emotions such as disgust (Wicker et al., 2003), reacting to norm-violation in ultimatum game (Sanfey et al., 2003), and empathy (Singer, 2006). Chiao et al. (2009) showed that activation in the left anterior insula (and anterior cingulate) cortex is linked with preference for hierarchical rather than egalitarian social relations; something of importance for differentiating the Conservative/Liberal mindset.

The anterior cingulate cortex (ACC) is involved in the experience of anxiety, and empathy (Decety & Jackson, 2004). Recently, Inzlicht et al. (2009) linked activity in the ACC to religiousness; in a behavioral task they showed:

> Results showed that stronger religious zeal and greater belief in God were associated with less ﬁring of the ACC in response to error and with commission of fewer errors. These correlations remained strong even after we controlled for personality and cognitive ability. These results suggest that religious conviction provides a framework for understanding and acting within one’s environment, thereby acting as a buffer against anxiety and minimizing the experience of error.

Since religion is often an important distinguishing factor between conservatives and liberals, it is not surprising for activity in the ACC to also be distinguishing for political ideology.

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Tags: social-psychology, neuroscience, reference-request, moral-psychology, political-psychology
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# Question
Title: Appropriate metric(s) for quantifying the accuracy gain obtained from averaging dyads of estimates instead of adopting individual estimates?
*Background*

The question relates to research I am doing into the Wisdom of Crowds effect (Galton, 1907; Page, 2007; Surowiecki, 2004), in which an average of the estimates made by individuals proves to be highly accurate relative to the estimates made by the individuals themselves. For example, if we ask a bunch of participants to provide an estimate of the number of jellybeans in a jar, and then take the average of those estimates, the average tends to be more accurate than almost all of the individuals in the group. Specifically I am thinking here about a special case in which crowd wisdom is computed using pairs of different individuals (or, pairs of estimates taken from the same individual at different times).

*The Question*

**I am seeking to investigate the appropriateness of various metrics for quantifying the accuracy gain obtained from averaging dyads of estimates instead of adopting individual estimates.**

I'll attempt to illustrate the question using a simplified example, in which three participants provide a single estimate. Let's say the estimates provided are 1, 4, and 6, and that the true value is 5.

We calculate the error that arises when we compare averaged pairs of estimates with the truth. The process is done exhaustively so with three participants we have six pairs \[average of participant 1's estimate & participant 2's estimate, 1 & 3, 2 & 1, 2 & 3, 3 & 1, 3 & 2\]. Previous studies (e.g. Herzog & Hertwig, 2009) have calculated the gains from averaging by subtracting the error of the averaged estimates from the error of the initial estimates. Specifically, they've defined percentage gain as Gain From Averaging divided by Absolute Error of Estimate 1 multiplied by 100. This is illustrated in Figure 1.

You get zero absolute gain from averaging if all answers are above the true value, or if all answers are below the true value. As soon as there is some mix of answers below and above the true value you get absolute gains from averaging. In Figure 1 we have both an absolute gain from averaging and a percentage gain from averaging, and this seems reasonable.

Things start getting a little strange if I change Person 3's estimate from 6 to 50 (see Figure 2). Now some of the percentages become massively negative. Without attempting to present anything formal, here's an prose description of why this happens. When the very high wrong answer (50) comes appears in the Value #1 column and the low mildly wrong answer (1) appears in the Value #2 column we get a high absolute error on Estimate 1 (45) and a medium-sized absolute error from averaging (20.5). Our gain from averaging is 24.5 but we only get a modest percentage gain (54.44%). When they reverse positions and 1 is in the Value #1 column and 50 is in the Value #2 column, we get a low absolute error on Estimate 1 (4) and the same absolute error from averaging we had just before (20.5). We have lost 16.5 from averaging, which is less than the 24.5 we gained above. However, when we turn this into a percentage loss it's massively bigger than our old percentage gain (-412.50%). Intuitively this seems rather unfair.

*Initial thoughts about answering the question*

The reason I initially adopted the percentages approach is that I was following the precedent of Herzog and Hertwig (2009). However, I'm starting to wonder if a better approach might be to divide the sum of Gains From Averaging by the sum of Absolute Errors of Estimate 1. This would mean that the overall 'gain' from averaging could never be negative. In Figure 1 it would be 4/12. In Figure 2 it would be 10/100. I would greatly appreciate input from readers into the question of what the most appropriate metric is.

Finally, readers may wonder why we average dyad by dyad rather than just taking the average of all three participants. The reason is that we are looking for a way to compare with another condition in which we take two estimates from each participant and average those. Figure 3 illustrates this process. We want to be able to say something like "Averaging two estimates from each participant creates an accuracy gain of \[some number\]. However, it is not as effective as averaging guesses between participants, which produces an accuracy gain of \[some other number\]."

*Links*

Link to an imgur album containing all the figures.
Link to the Excel file used to generate the figures.

*References*

Galton, F. (1907). Vox populi. *Nature*, *75*, 450-451.
Herzog, S. M., & Hertwig, R. (2009). The wisdom of many in one mind. *Psychological Science*, *20*, 231-237.
Page, S. E. (2007). *The Difference: How the power of diversity creates better groups, firms, schools and societies*. Princeton: Princeton University Press.
Surowiecki, J. (2004). *The wisdom of crowds: Why the many are smarter than the few*. London: Abacus.

# Answer
*The following are just my thoughts on what seems to make sense from first principles. I don't have a detailed understanding of what is standard practice in the wisdom of crowds literature. I've also only given what you've written a basic read. I.e., enough to understand the broad question, but not enough to follow exactly what you've done.*

Let $y\_i$ be the prediction of the $i$th individual, $i=1, \ldots, n$, and let $T$ equal the true value of the thing predicted.

Let the prediction created by averaging individual $i$ and $j$ be $$d\_{ij} = \frac{y\_i + y\_j}{2}$$ where $i \neq j$.

Let $y'\_i$ and $d'\_{ij}$ be absolute errors from the true value. i.e.,

$$\begin{align} y'\_i & = |T - y\_i| \\ d'\_{ij} & = |T - d\_{ij}| \end{align}$$

Let $d'\_{i.}$ be the average absolute error for participant $i$ after averaging over all possible dyads the person could be a part of. I.e.,

$$d'\_{i.} = \frac{1}{n-1}\sum\_{i=1}^n d'\_{ij} $$ where $i \neq j$. This represents the expected error in prediction if participant $i$ generates a prediction with a random other person.

If we denote average error across individuals as $\bar{d}'$ and $\bar{y}'$ for dyadic and individual predictions respectively we could then compute both the average raw improvement in prediction as

$$\bar{y}' - \bar{d}' $$

or the average raw improvement as a percentage

$$\frac{\bar{y}' - \bar{d}'}{\bar{y}'} \times 100$$

Both the raw and percentage improvement above seem like reasonable and complementary representations of the average improvement obtained when a person generates a prediction with a random other person.
> 6 votes

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Tags: methodology, decision-making, mathematical-psychology, collaboration, wisdom-of-crowds
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# Question
Title: Neurotransmitter based imaging techniques
All the brain imaging techniques I know fall into two categories:

1. Tracking blood

1. Either by looking at the magnetic (fMRI), or near-infared absorption (diffuse optical imaging, NIRS) properties of hemoglobin, or
    2. Injecting tracers into the blood stream (PET, SPECT)
2. Tracking electric and magnetic fields in neurons (EEG, MEG).

The problem with the first approach is that it is fundamentally secondary in nature: it tracks the response of the vascular system to brain activity. Although the BOLD signal correlates well with neural activity, it is still an indirect indicator of firing rate, has time lags, and limited spatial (limited by distribution of capillaries) and temporal (limited by flow rate) resolution.

The second approach is better, but still not perfect from a pharmacology perspective. Although it gives us good information about the post-synaptic potential (EEG) or intraneuron potential (MEG), it still provides no information on specific neurotransmitters released. The approach also suffers from limitations on spatial resolution and the fact that EM-fields follow the superposition principle and thus it is mathematically impossible to reconstruct signals that interfere destructively outside the neuron but before the sensors.

The perfect approach for a pharmacologist would be to track individual types on neurotransmitters. **Are there imagining techniques that use the resonance, absorption, or other properties of neurotransmitters (instead of hemoglobin)? Or is there a fundamental reason why this won't work?**

I know that the same exact techniques as for hemoglobin won't work (since as far as I know most neurotransmitters don't contain nice things like iron to play with), but is there a reason other resonance or scattering techniques wouldn't work?

---

The closest work I know in this direction is the event-related optical signal (Gratton & Fabiani, 2001) because it tracks the light-scattering properties of something other than hemoglobin: neural tissue. Unfortunately, this is still tracking activity of the neuron and not neurotransmitters.

# Answer
Resonance methods can be used to measure neurotransmitter levels. Magnetic Resonance Spectroscopy can measure the levels of a large number of neurotransmitters. However, this has always been viewed as a fairly static measure of neurotransmitter levels, and so has not been widely used as a measure of neural activity. However, Paul Mullins at Bangor University has been doing some work using spectroscopy to measure neurotransmitter levels in different parts of the brain. From the work I have seen him present so far, it is sensitive enough to track stimulus driven changes in neurotransmitter levels with a standard blocked design (ie 18sec blocks of stimulation followed by 18sec of rest). I'm not too sure whether it has the same functional contrast-to-noise as the BOLD response and it definitely has a lower spatial resolution than BOLD techniques. This work is currently being prepared for publication so I shouldn't say too much.

**References**

Novotny, E. J., Fulbright, R. K., Pearl, P. L., Gibson, K. M., & Rthman D. L. (2003). Magnetic resonance spectroscopy of neurotransmitters in human brain, Annals of Neurology, 54, S25-S31. PubMed.
> 6 votes

# Answer
I found an example of a system that researchers are aiming to use in the future for determining the level of neurotransmitter activity in the brain using MRI. You were on the right track with the utility of hemoglobin. The molecule used is somewhat similar. To understand how the probes were generated requires a bit of a biological detour.

There are enzymes in the body known as P450 cytochromes, so named because they were observed as absorbing light in the 450 nm range. They are membrane bound (e.g., in the mitochondria) and one of their primary purposes is to carry out monooxygenase reactions, and liver-based P450s are responsible much of the drug metabolism that goes on in the body. So, different classes of these enzymes have a high affinity for certain molecules. The most important characteristic that the P450s possess is a heme group, which is paramagnetic, and will produce a signal in an MRI.

These P450 enzymes are also found in bacteria, which can be readily used as a test bed due to their rapid cell division. What these scientists have done is repeatedly mutated bacteria and tested the affinity of the P450s of the resulting mutants for various molecules (in this case serotonin and dopamine).

So, in retaining a culture of the bacteria, scientists can mass produce the mutated heme groups from the bacterial P450s. Presumably once the sequence of the subunit is determined, it could be created using standard techniques.

Some challenges remain. Primarily, the probes will have to be checked for safety, and measures will have to be taken to make them into robust MRI contrast agents, and ensure that they can localize and persist in the brain for the duration of testing. Presumably, the proper correlations between strength of signal and local transmitter concentration can be established with *in vitro* studies. It sounds like we're fairly close to non-invasive methods of measuring neurotransmitter levels.

Reproduced from here

> Brustad, E.M., Lelyveld, V.S., et al (2012). Structure-guided directed evolution of highly selective P450-based magnetic resonance imaging sensors for dopamine and serotonin. Journal of Molecular Biology, *in press*, doi.
> 6 votes

# Answer
It's a bit of an art, currently. Following is **one technique** I witnessed in a lab that takes electrophysiological recordings of tadpole and rat neurvous sytems.

The lab that I worked with entrains the neuron, recording it's electrical activity (in a series of drug tests) and injects a marker that goes into the neuron (a GFP-like protein that binds to precursors for serotonin or dopamine or GABA and glows in pictures). Then they mark the brain tissue and the recording so they'll be associated, then after they have a bunch of recordings, they look at all the brain tissues and see which ones expressed the dopamine, GABA, or serotonin.

Now they can associate electrophysiological behavior with a particular neurotransmitter.

In addition to this, there's a **general neurochemical anatomy** that's known. Serotonergic neurons are only found in the brainstem, for instance and dopamine is only in the substantia nigra pars compacta, ventral tegmental area, and hypothalamus and has four different types of projections to other cell bodies.

Of course, for proof, staining (as described above) is still preferred by reviewers.
> 5 votes

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Tags: neuroscience, methodology, neuroimaging, psychopharmacology
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title: What is the reliability of GPA?

text:
# Question
Title: What is the reliability of GPA?
I'm in the process of performing a meta-analysis that includes Grade Point Average (GPA) as one of the variables. For some purposes, it might be useful to have an estimate of the reliability of measurement for GPA.

* **What has empirical research estimated the reliability of GPA to be?**
* **What factors influence the reliability of GPA measurement?**

### Additional points

* I'm looking for specific coefficient values that I could use in a meta-analytic context. I am not interested in personal opinions about the value of GPA.
* I can also see that reliability would vary based on how you define reliability.
* I imagine that GPA would be more reliable and valid when it is obtained from a group of students at a single university. I can also see that GPAs based on more units of study would be more reliable.
* I can also see that in some contexts GPA is an end itself, and therefore it would not be appropriate to adjust for reliability.

# Answer
> 2 votes
Bacon and Bean (2006) discuss the issue of the reliability and validity of GPA. They report the results of two studies that looked at the reliability of GPA in samples of business students at the same university.

* Average intercourse grade correlations were typically between $\bar{r} =.18$ and $\bar{r} =.38$.
* Estimates of reliability for GPA ranged from .67 to .94.
* There is a simplex structure to GPA whereby correlations between GPA for a given year correlate more highly with GPAs of other years that are closer in time (e.g., correlations between consecutive year GPAS from years 1 to 2, 2 to 3, and 3 to 4 where .74, .79, and .74 respectively. In contrast the correlation between GPA year 1 with year 4 was .60.
* Average intercourse correlations within disciplines tend to be higher than across course correlations.
* In general, reliability increased as more courses/subjects were included.

The above estimates are based on correlations that use "+/-" system of grading. Universities that use straight letter grades should have lower reliability and those that use a 100 point numeric grading system should be more reliable.

### References

* Bacon, D.R. & Bean, B. (2006). GPA in research studies: An invaluable but neglected opportunity. Journal of Marketing Education, 28, 35-42.

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Tags: performance, educational-psychology, reliability, meta-analysis
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# Question
Title: Inferring relationships between psychological variables in clinical samples and issues in generalisation
### Context

I sometimes speak to researchers studying the relationship between variables in clinical psychology samples. A typical example is as follows:

* 100 patients with diagnosed depression
* many clinically relevant variables are measured such as demographics, anxiety, intelligence, drug and alcohol use, and so on.

Researchers often want to then develop models of what predicts depression.

However, the problem is that the sample was selected because they already have been deemed to possess a certain threshold level of depression. Substantial variation still remains in depression with some participants being more severe than others.

Thus, there are problems in trying to generalise observed relationships to describe what predicts depression, because it is not a random sample of the population.

I use depression as a specific case, but the problem applies to many studies of clinical populations (e.g., kids with behavioural problems, kids with intellectual disabilities, OCD, etc.).

### Question

* What advice would you give to such researchers about how to analyse and generalise from such data?
* Are there any references that provide an example of best practice of how to analyse and generalise from such data?

# Answer
> 4 votes
I don't know if you can completely remove the selection bias from such a sample.

You seem to be referring (in some sense, at least) to regression towards the mean. This is one of the biggest (if not the biggest) problem with much research on clinical samples.

What I would do (assuming resources) would be to take the same size (or larger) sample from the general population, and administer all of the same measures and tests to them. This would allow you to separate the predictors of the clinical outcome versus the variation due to other factors. I would probably employ matching from the clinical sample to the general sample (Gelman and Hill have a great chapter in their book about the matching, and that entire book is filled with helpful advice to analogous problems.

In my research, (on predictors of placebo response) I took large samples from the University where I was conducting my research on all of my self report measures, and compared my experimental population to them to determine if my sample were representative of the larger populatiom, which is a somewhat similiar approach to a common problem.

Unfortunately, other than the Gelman and Hill book, I'm not aware of any literature on the topic (but that may be my own fault).

I hope this helps.

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Tags: methodology, abnormal-psychology, experimental-psychology, statistics
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# Question
Title: When counting a given letter in sentences, why do people tend to omit occurrences in certain common words?
I have noticed that when I, and presumably others, count the number of times the letter `F` appears in the following passage:

```
FINISHED FILES ARE THE RESULT
OF YEARS OF SCIENTIFIC
STUDY COMBINED WITH THE
EXPERIENCE OF YEARS

```

They typically get a count of three, yet the real answer is six. The letter `F` in the the word "OF" tends to be omitted from the count.

I imagine that this effect has something to do with top-down processing.

### Questions

* Have there been any scientific studies of this or a similar task?
* What proportion of people complete the task successfully?
* What explains the tendency of people to not count the letter F's in the word "OF"?

# Answer
**What explains the tendency of people to not count the letter F's in the word "OF"?**

One possibility to explain this effect is related to the phenomenon of **word skipping**. When we read, we do not fixate every word, but skip a certain proportion of words while making educated guesses instead. Whether or not a certain word is skipped seems to depend on its length and its predictability, that is, how likely a word is given its predecessor (e.g, Rayner et al., 2011). For your example, the preposition "of" might be very likely to be skipped because it is very short and some grammatical clauses always ask for this preposition.

Please see PubMed for a more comprehensive literature search on word skipping: http://www.ncbi.nlm.nih.gov/pubmed?term=%22word%20skipping%22

**References**
Rayner K, Slattery TJ, Drieghe D, Liversedge SP. (2011). Eye movements and word skipping during reading: effects of word length and predictability. J Exp Psychol Hum Percept Perform. 37(2):514-28
> 10 votes

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Tags: perception, linguistics
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# Question
Title: Why does a stuffed up nose clear up momentarily when the person having it is startled or has an orgasm?
I have experienced this phenomena many, many times and I'm sure it's not only me. I guess the sudden rise in arousal opens up the nostrils in a kind of fight or flight response, but I'm interested in the more intricate details of why this happens.

# Answer
Norepinephrine is responsible for, among many other things, causing a constriction the nasal vasculature and slowing capillary leakage that would lead to a runny nose.

Both the startle response (sympathetic) and the orgasm response (sharp transition between high peak of sympathetic response and descent into parasympathetic) result in large releases of epinephrine and norepinephrine into the bloodstream from the adrenal medulla.
> 14 votes

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Tags: physiology
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# Question
Title: Method for evaluating how emotionally evocative a question is?
I would like to measure the change in emotional state in response to a question. For example, asking the question, "What is your favorite color?" would be fairly benign; I would not expect any change in emotional state. However, I would expect a strong emotional response if I asked "What type of person do you hate?" or "Have you ever smoked marijuana?"

Ideally, we would measure this immediately after asking the question. **Does anybody have any suggestions on how this can be done, or how it has been done reliably in the past?** I have access to surveys and special cameras (thermal, pupil analysis, etc) if it helps.

**Edit:** To clarify, I'm more interested in measuring the level of emotional arousal more than measuring what specific emotion somebody is feeling. For example, I don't care if somebody is frightened or angry, just the extent to which the emotion caused arousal.

# Answer
> 5 votes
You could go with the most direct approach: After every question, ask your subjects how emotionally aroused the last question made them, for example by using a visual analogue scale. Now, this might not be suitable for your research (maybe you don't want your subjects to start to think about their own emotional state), but I think there's a danger in using advanced measurement technologies just for the heck of it. I would imagine a direct question would give your research quite high face validity for example.

However, if want to go with a more indirect approach I would recommend you check skin conductance measurements out. Here, you could for example (there are numerous examples) check out the research on precognition, which started with an experiment by Dean Radin. In these studies, you can see how skin conductance measurements vary with the content of presented pictures quite nicely (never mind if you agree with the precognition hypothesis or not).

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Tags: measurement, reference-request, emotion
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# Question
Title: What test can be used to measure memory?
We want to have a test to determine the status of a person's memory.

For example, a good test might consist of multtiple choice questions and take 5 - 10 minutes. The end result would be a summary of an individuals' memory based on their score.

### Questions

* What tests are currently used to measure a person's memory?

# Answer
There are a wide variety of memory tests available for different purposes (sometimes clinical, sometimes for research). Also as Ben Brocka mentions, they can be more targeted as well.

One test I can think of at the top of my head that is available for free online is the Montreal Cognitive Assessment (MOCA) that you might be interested in. It serves as a quick screening for cognitive impairment but there is one section for memory. Usually these are used prior to further testing. I can update my answer later if I find more.

One that is well known and is widely used in clinical settings is the Wechsler-Memory-Scale (WMS). The latest version is WMS-IV but it is more comprehensive and not free.

Considering you asked for something around 5-10 min. you are probably more interested in ones used in research/educational settings. Here are two I found:

1) Faceblind is run by the Prosopagnosia Research Centers (Dartmouth College, Harvard University, University College London). There you can find a test on visual memory for celebrity faces (which would be considered Long Term Memory).

2) Their site links to tests from another group:

> "Test My Brain is a collaborative effort between the Vision Lab and the Social Neuroscience and Psychopathology Lab at Harvard University."

They offer more visual memory tests, some on faces, words, numbers etc.
> 7 votes

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Tags: memory, methodology, test
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# Question
Title: For depression diagnoses, does one make a clear distinction between endogenous and exogenous causes of depression?
Roughly speaking, we might imagine that people have depression predominantly for one of two reasons:

* **Endogenously induced:** The person has some inherent inballance between different neurotransmittors; some part of the persons's brain that regulates emotions is damaged et cetera.
* **Exogenously induced:** The person has no friends; the person has been left by several of his/her partners; the person is unemployed and can't get a job et cetera.

Obviously, in many cases it will not be this black and white.

# Answer
> 3 votes
---

Whew, OK. I am going to take a crack at this. The question asks about depression *diagnoses*, so I will interpret and focus on that accordingly. I think we can all agree that making any clear distinction between endogenous and exogenous causes of depression is difficult, since 1) liken to the Nature vs. Nurture question, people generally agree that Major Depression is a result of multiple factors, and 2) clinicians disagree on which (exogenous vs. endogenous) tends to be the "primary" cause of depression \[\].

When it comes to making a clinical diagnosis, psychiatrists and other mental health professionals will use the multi-axial system in documentation. **Axis IV** is a part of the system, and is where exogenous factors can be reported as psychosocial and environmental problems that may affect the diagnosis, treatment, and prognosis \[\]. In addition, the clinician should know to keep in mind that psychosocial problems may develop *as a consequence of the patient's psychopathology*!

Examples of commonly listed psychosocial and environmental problems include family problems (illness, death), social environment (**isolation**), educational/occupational problems, economic problems, etc., etc.

> The evaluation of stressors is based on a clinician's assessment of the stress that an average person with similar sociocultural values and circumstances would experience from psychosocial stressors \[\]. *The judgement is based on the degree of change that the stressor causes in the person's life, the degree to which the event is desired and under the person's control, and the number of stressors.*

---

**Tidbits**

* To make a quick note about endogenous factors, it is interesting to note that the most consistent abnormality in those with depressive disorders is increased frequency of abnormal hyperintensities in subcortical regions of the brain...
* A long-standing clinical observation is that stressful life events more often precede first, rather than subsequent, episodes of mood disorders.
* ^ One theory proposed is that the stress accompanying a first episode results in long-lasting changes in the brain's biology... so a person has a high(er) risk of experiencing subsequent episodes of (a) mood disorder(s), **even without an external stressor** \[\].
* While some clinicians believe that life events play the primary or principal role in depression, others suggest that life events have only a limited role in the onset and timing of depression.
* What may seem to be a relatively mild stressor to outsiders may be devastating to the patient due to particular/personal idiosyncratic meanings the patient attach to the event.
* Edward Bibring thought perhaps depression is \[the result of\] the phenomenon that sets in when a person becomes cognizant of a discrepancy between his high ideals and the inability to meet the goals appropriate to reach said ideals.

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I suppose I did not provide an adequate answer to your question. Given what I have looked into, it appears that individuality plays a ginormous factor in determining one's personal cause(es), and not only do clinicians disagree on the source of depression, but it appears that when clinicians make their diagnosis/diagnoses, a clear distinction between endogenous and exogenous influences is **not** made. At least, generally speaking...

### References

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Tags: abnormal-psychology, psychiatry, depression
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# Question
Title: Is it reasonable to have a factor with only two levels in a carry-over design for an fMRI study?
I'm planning a carry-over design for an fMRI study.

To save time, since it seems that I'll need a huge number of trials for my purpose, I'm wondering if it's reasonable to have a matrix 2x3x3, meaning that one dimension has only 2 levels instead of 3 as the others do.

# Answer
*I'm not an expert in neuroimaging, so I had to search a little bit to learn about how carry-over designs apply to fMRI (I found Aguirre, 2007). Thus, feel free to correct me if there is something specific about this problem domain that influences the correct answer to this question.*

However, based on general principles of experimental design of repeated measures experiments, you always have to choose

* how many factors you want,
* how many levels you want for each factor,
* what levels you have for each factor, and
* what factors you hold constant.

The particular levels you choose are directly tied to your research question. There are often trade-offs between the cost of resources required to have more experimentally manipulated levels and the benefit of additional questions that can be answered. Thus, I don't think a black and white answer can be given. You need to weigh up the pros and cons.

And presumably you have already made many experimental design decisions to get to this point. There's nothing magical about 3 levels to a factor. If anything, in experimental psychology two levels seems more common. And you could have four or five or more.

### References

* Aguirre, G.K. (2007). Continuous carry-over designs for fMRI. Neuroimage, 35, 1480-1494. HTML
> 3 votes

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Tags: methodology, statistics, neuroimaging, fmri
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# Question
Title: Is there a reduction of "Brain Fog" with fewer hours of sleep?
I've heard patients who complain of "brain fog" (and fatigue) claim a reduction in "brain fog" (and more mental clarity) when they get fewer hours of sleep (usually less than 5.5 hours).

Here I'd define brain fog as a lack of mental clarity, slow and muddled thinking, trouble stringing thoughts, drowsiness, a reduced ability to focus, a feeling of drifting off, and a reduced ability to shift attention. Delirium (without hallucination) could be a close medical term.

My questions are:

1. Any theories on why this may happen?
2. Is anyone familiar with any research regarding less brain fog with less sleep?

I've read in a paper by MacLean and Datta (2007) that sleep deprivation has been successfully used to treat depression, but not so with anxiety.

> Indeed, in clinical studies, sleep deprivation has been an effective form of treatment for major depressive disorders in humans (Clark et al., 2001; Giedke et al., 2003; Gillin et al., 2001); but deprivation has shown little or negative results in patients diagnosed with anxiety disorders (Dinges et al., 1997; Labbate et al., 1998). Results from recent REM and total sleep deprivation studies in rodents demonstrate the anxiogenic effect of disrupted sleep (Silva et al., 2004; Suchecki et al., 2002a; Suchecki et al., 2002b).

Depression and delirium are two distinct things, and I'd be interested in hearing more about how sleep deprivation effects delirium -- since it seems that brain fog is not a widely used term.

<sub> Robert Ross MacLean and Subimal Datta (2007). The relationship between anxiety and sleep-wake behavior after stressor exposure in the rat. Brain Res. 2007 August 20; 1164: 72–80. Published online 2007 June 27. doi: 10.1016/j.brainres.2007.06.034 </sub>

---

I'm going to update this as I learn more (until I get a reasonable answer), in attempt to both log and share what I'm learning on the subject.

> Using imaging, he found that a small area of the cerebral cortex in the front of the brain — the anterior cingulate cortex — which was consistently overactive in depressed patients, quieted to normal levels of activity after the patients were deprived of sleep. And when the patients were allowed to sleep, the activity in this area returned to the elevated levels.

<sub> SEJNOWSKI, T. (2010, April 7). In Sleepless Nights, a Hope for Treating Depression \- NYTimes.com. Opinion - Opinionator - NYTimes.com. </sub>

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> A study in rats suggests that individual neurons take a nap when the brain is forced to stay awake, and that the basic unit of sleep is the electrical activity of single cortical neurons.

<sub> Colwell, C. S. (2011). Neuroscience: Sleepy neurons? Nature. Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. Retrieved from http://www.nature.com/nature/journal/v472/n7344/full/472427a.html </sub>

# Answer
> 11 votes
The scientific concept which most closely matches your description of "brain fog" is sleep inertia.

> Any theories on why this may happen?

First, a brief detour. Sleep is divided up into 5 stages (stages 1, 2, 3, 4, and REM). Since 2007, NREM sleep has been reclassified into stages N1, N2, N3, with N3 being a combination of the former stages 3 and 4; however, most scientific papers are still using the old system, so I'll refer to them by the old stage names. Below, you can see a typical hypnogram, where sleep stage is plotted versus time for one night's sleep. Cycles through the night tend to progress from 1→2→3→2→REM, but can change unexpectedly if the subject is awakened.

(image from Wikipedia)

While sleep inertia has been well researched since the late 70s, its definition relies on changes in responses to behavioral measures rather than any specific anatomical structures that might be involved. In other words, it is difficult to "diagnose" someone with sleep inertia without seeing their performance on a demanding cognitive task.

It is known that waking up results from a signal that travels between the reticular system of the thalamus to the thalamus itself, and from the thalamus onto the cortex. Many studies have used fMRI as a means to catch the brain as it falls asleep, but there don't seem to be too many which capture that moment of awakening.

Sleep staging (how levels of sleep are scored, as seen above) relies on EEG measures, so it is natural that after a subject wakes up from a study, their EEG signals can continue to be measured. This gives researchers an opportunity to see into the dynamics of the cortex, but anatomical resolution and involvement of subcortical structures (like the thalamus) is not measurable. It would be nice to have a functional picture of subcortical activity to gauge the progression of waking.

A recent EEG study by Marzano (2011) found that the waking brain had a higher degree of delta activity in occipito-parietal (more posterior) areas, and a lower degree of delta activity in the frontal areas. They found increases in beta activity in the frontal areas, which tended to be stronger after awakening from stage 2 sleep than from REM sleep. This study did not attempt to localize any anatomical structures, but in general indicates that more posterior portions of the brain (perhaps associated with vision and posture) tended to mimic the activity found in slow-wave sleep for a time after awakening.

Sleep inertia has been found to depend on

* prior sleep duration
* sleep stage prior to being awake
* time of day of awakening

and last between 30 minutes and 3-4 hours depending on prior sleep deprivation and other factors.

However, the effects of it seem to vary greatly based on the task that the brain is asked to attend to during that time.

> Is anyone familiar with any research regarding less brain fog with less sleep?

On the extreme timescale of a short nap, this has been shown to be true, but the results can be extrapolated to longer time scales. Tassi (2000) reported on a study in which the subjects took 20, 50, and 80 minute naps. The 50 minute nap-takers were found to have more intense sleep inertia, most likely due to the chance to lapse into a higher percentage of slow wave sleep during that time (stages 3 + 4 under the old system, and stage N3 in the new one) and potentially not return to stage 1 or 2 before awakening. The 80 minute nappers, which one might think would have worse sleep inertia upon waking, were able to get into REM sleep, and so experienced less sleep inertia (this is a slight contradiction to Marzano's result above, but I think Tassi's assertion is more widespread in the literature). However, Tassi also reported a study where decrements in performance were reported in REM sleep with a higher density of eye movements.

Sleep deprivation tends to increase the amount of deeper sleep once the person has the opportunity to rest. In that case, regardless of stage upon awakening, the sleep inertia tends to be worse.

Matchock (2010) has reevaluated some of the experimental evidence in light of circadian influences. He added ultradian phase (the marker of one's progress through the circadian day) and whether awakenings were forced or self-imposed to Tassi's list of factors above. Levels of cognition and performance, both hindered in sleep inertia situations, are found not to be uniform throughout the 24 hour day. Matchock reported on studies where late afternoon naps were more restorative and hindered cognitive function less (less sleep inertia). Other findings in his review found a relationship between both drops in core body temperature and body temperature of the extremities (both factors known to vary over the day) tended to increase sleep inertia.

> \[1\] Marzano, C., Ferrara, M., et al (2011). Electroencephalographic sleep inertia of the awakening brain. Neuroscience 176:308-317.
>
> \[2\] Matchock, R.L. (2010). Circadian and sleep episode duration influences on cognitive performance following the process of awakening. International Review of Neurobiology, 93:129-151. doi
>
> \[3\] Tassi, P., Muzet, A. (2000) Sleep Inertia. Sleep Medicine Reviews 4:341–353.

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Tags: sleep
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# Question
Title: How many bits of data would it take to represent an entire life as a film?
Imagine your life as a film. Add all the stuff you know.

**Is it possible to express this amount of data in bits?** (A rough order of magnitude would be ok.)

See also: Partitions and Savants:

# Answer
> 3 votes
This is a tough question, and there's a few routes to go. When we are watching this life played back, do we want to be able to go to any arbitrary moment and observe what was happening, or do we only want to watch life as we watch it? This would be the difference between recording all information that bombards our brain, or just the information that we are attending to.

We'll go with the first one, as this will be easier.

I'm going to ignore 'thoughts', and just look at information as it enters the body.

We need to know a couple things before we start.

What is the data rate of our eyes? What is the data rate of our ears?

As these are our most dominant senses, if we want a few orders of magnitude for information, we will get it from these two.

Researchers at the University of Pennsylvania School of Medicine say that the data rate for the eye is about 10 million bits per second, or about 1.25 Mb/s.

Our eyes have about 120 million cells, and they sample at roughly 30 Hz. Determining the number of 'bits' is hard, as eyes have a nonlinear response, so the amount of information they are transmitting is dependent on what the cells are observing. I will trust their number.

As vision is our most powerful sense, and accounts for over 40% of the processing in our brain, we know that the majority of the information will be from the eyes. (EDIT: This is incorrect, see the data below.)

Now onto the ears - our ears can hear up to about 20 KHz, and to actually pick up these sounds we need to sample at twice that frequency, or 40 KHz. That doesn't tell us how much information we actually get though. This question on Yahoo! Answers goes a little bit deeper, specifying that ears cannot distinguish information that is represented in more than 16 bits.

This is kind of an interesting way to determine the sensitivity of our ears, as we don't have to wonder 'well, how well can I distinguish what I hear?', rather the question is 'We have these samples of audio, and people can't hear the difference between them, therefore our ears cannot transmit this much information'.

So we have eyes and ears, and we now need to do some math.

I'm going to assume all these rates are fixed, the actual information that is transmitted is nonlinear as the spike trains from our cells change depending on what they are sensing.

I wrote a little python program, available here.

> With the information from above in hand, we have the following:
>
> Eyes data rate is 2.4 MB per second.
>
> Ears data rate is 687.5 MB per second.
>
> over 60 years, our eyes will transmit 4.2 PB
>
> over 60 years, our ears will transmit 1.2 EB
>
> The total information we will receive will be upwards of...
>
> 1.2 Exabytes

Now this sounds a little silly, do our ears really transmit more information than our eyes? Actually yes, because they are sampled so much more frequently. The eyes sample at roughly 30 Hz, whereas the ears sample at 44 KHz.

This analysis ignores the number of cells, and is likely incorrect for a number of reasons. We ignore the other senses, as well as information being sent between brain regions (processing of information).

This question brings up an interesting point though, the raw information that we receive is meaningless, only through successive iterations of information abstraction (what neural networks do, they operate on regions of information, gaining a higher and higher level picture) can we begin to distinguish the world as it is. When we see something, we can immediately break the world apart into segments, we know what can move, we know where things are, we know when we put them there. This isn't information that we were given at our current place in time, it's rules that we have learned about what we see in the world through a lifetime.

Additional source of information: How many colors and shades can the human eye distinguish in a single scene? This Photography.SE question goes into logic about how much information we can discern, more closely matching the analysis on the Ears, rather than the research data that we used.

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Tags: long-term-memory
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# Question
Title: What are good examples of applying dynamical systems in cognitive science?
I'm a mathematics and physics student very much interested in cognitive science. Recently I've been hearing about "a new approach" in cognitive science via dynamical system theory.

* What are some good examples of using differential equations to model cognitive phenomena?
* What papers would you recommend?

# Answer
> 12 votes
Given your background and interest in modeling, I would highly recommend The Cambridge Handbook of Computational Psychology. The book provides an overview for several of the prominent modeling paradigms in cogsci, including dynamical systems, as well as many concrete examples--albeit most using other computational paradigms.

Dynamical systems, to my knowledge, are most used in the field of motor control. Though to be honest, dyn systems is not 'my' paradigm, and most of my knowledge comes from the aforementioned book.

In particular, the chapter "Dynamical Systems Approaches to Cognition" by G. Schoner gives this example that has always stuck in my mind:

> A highly illustrative example comes from the orientation behaviors of the common house ﬂy (Reichardt & Poggio, 1976; Poggio & Reichardt, 1976). Flies orient toward moving objects, which they chase as part of their mating behavior. Detailed analysis revealed that the circuitry underlying this behavior forms a simple controller: a motion detection system fed by luminance changes on the ﬂy’s facet eye drives the ﬂight motor, generating an amount of torque that is a function of where on the sensory surface motion was detected. If the speck of motion is detected on the right, a torque to the right is generated. If the speck is detected on the left, a torque to the left is generated. The level of torque passes through zero when the speck is right ahead. The torque changes the ﬂight direction of the ﬂy, which in turn changes the location on the facet eye at which the moving stimulus is detected. Given the aerodynamics of ﬂies, the torque and its on-line updating generate an orientation behavior, in which the insect orients its ﬂight into the direction in which a moving stimulus is detected.

# Answer
> 9 votes
I have a similar background to you, and have found a lot of interesting things in evolutionary game theory (you can follow links from my profile for more). But on the specific content of your question: I have come across to uses of dynamic systems on the opposite ends of cognition. Beer's work on modeling minimal cognition, and Busemeyer & Townsend's work on human decision making.

### Minimal cognition

Beer's work models simple cognitive agents as dynamic recurrent neural networks. He then either hand-builds the agents, or evolves them, and analyzes them from a situated cognition perspective by treating them as dynamic systems.

* Beer, R. D. (1995). On the Dynamics of Small Continuous-Time Recurrent Neural Networks. Adaptive Behavior, 3(4), 469-509. doi:10.1177/105971239500300405
* Beer, R. D. (2003). The Dynamics of Active Categorical Perception in an Evolved Model Agent. Adaptive Behavior, 11(4), 209-243. doi:10.1177/1059712303114001

Minimal cognition research tends to use dynamic systems much more heavily than other fields I am familiar with. This blog provides a very thorough survey of papers in the field. A short 'manifesto':

### Human decision making

Busemeyer & Towsend on the other hand try to describe how humans deliberate and make decisions. One of the key aspects they want to capture is not just the outcome of human decision making (with all of its flaws and irrationality) but also the deliberation time. To do this, they introduced decision field theory which models human decision making as a stochastic dynamic process.

* Busemeyer, J. R., & Townsend, J. T. (1993) Decision Field Theory: A dynamic cognition approach to decision making. Psychological Review, 100, 432-459. \[pdf\]
* Busemeyer, J. R. & Diederich, A. (2002) Survey of decision field theory. Mathematical Social Sciences, 43, 345-370. \[pdf\]

### Development

Esther Thelen and Linda Smith wrote a nice book examining human development from a dynamic systems approach:

https://mitpress.mit.edu/books/dynamic-systems-approach-development-cognition-and-action

# Answer
> 6 votes
Great to hear you're interested in applying your quantitative background to cognitive science; the field can definitely use more individuals like you!

I'm not sure to what degree these models might be meet your definition of "dynamical systems", but here are some off the top of my head:

* stochastic models of human response time and accuracy in 2-alternative speeded choice experiments. Here's a recent paper that does well to summarize two dominant models in this field.
* Holographic models of semantic memory (includes dynamic encoding and retrieval processes)
* Jeff Hawkins' (yes, that Jeff Hawkins) very cool Hierarchical Temporal Memory Model (lots of info here)

# Answer
> 5 votes
From my social psychology perspective, there has been some computational modelling work on things like attitudinal influence dynamics. See: Nowak, A., Szamrej, J., & Latané, B. (1990). From private attitude to public opinion: a dynamic theory of social impact. *Psychological Review, 97*, 362-476.

Robin Vallacher and Andrzej Nowak crop up a lot in this field, and they're a joy to read. Perhaps this is less up your alley, since social psychologists are less interested in formulating differential equations and more interested in just applying the *ideas* of complexity science to their research methods, but it's certainly a step forward from what's been going on in the field so far. If anyone's interested in those broad concepts, try reading: Nowak, A. (2004). Dynamical Minimalism: Why Less is More in Psychology. *Personality and Social Psychology Review, 8*, 183-192.

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Tags: reference-request, cognitive-modeling, mathematical-psychology
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# Question
Title: What is the correlation between Grade Point Average (GPA) and intelligence?
* **What is an authoritative empirical estimate of the correlation between pscyhometric measures of intelligence and Grade Point Average (GPA)?**
* **What are the main factors that influence the size of the correlation? E.g., country, level of schooling (e.g., primary, secondary, university), method of GPA measurement, etc.**

Specifically, I'm interested in estimates derived ideally from meta-analyses. But estimates based on large sample studies would also be welcome.

# Answer
*Assessing Adolescent And Adult Intelligence* (Kaufman & Lichtenberger, 2005) goes through quite a bit of the research on this. Or you can use the correlation of 0.7 that they report, which is based on an aggregation of more recent studies of adult intelligent test scores and academic achievement. I don't see where they break down country, but they do look at level of schooling a bit. Perhaps some of their sources will help.
> 3 votes

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Tags: measurement, intelligence, iq, educational-psychology, correlation
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# Question
Title: What is the scientific term or concept for inner thought control?
Usually when a thought arises, it seems that we quickly scurry after it, unconsciously getting caught up with whatever everyday thoughts come up. These can be invoked internally or externally. (No reference to that phenomenon but for example, you may have just read that and add more thoughts or complicated it. )

**What is the scientific term or concept that explains being able to NOT follow and run after every thought that arises out of the brain or not be swayed by them in anyway?**

# Answer
Your question touches on a number of different active research areas in cognitive science and cognitive neuroscience.

The motoric component to not "following and running after every thought" is commonly understood to reflect a capacity for response inhibition - that is, the ability to override or cancel ongoing or prepotent motor commands. This process is thought by some to be similar to that involved in reducing perceptual or cognitive interference, for example in attending to a particular type of information despite salient or prepotent sources of distraction (e.g., as studied in the Stroop and Flanker tasks), or in reducing interference from recently abandoned information/goals (e.g., variously studied in terms of negative priming and lag-2 repetition cost respectively).

However, there are other perspectives. One is that the ability to maintain an overall task set - perhaps a more stable one, that has a hierarchical influence over other more transient thoughts/perceptions - might be responsible for keeping these kinds of more extraneous exogenous and endogenous distractions at bay, through a process known as competitive lateral inhibition. Keywords for this kind of work include biased competition, goal maintenance, context maintenance, and active maintenance.

Finally, there is a third line of work relevant to your question, in which cognitive processes are selectively granted control over behavior. This has so far been studied primarily in the domain of visual search, although computational models suggest that it may have rather domain-general applications. In the visual search literature relevant keywords are "accessory items in working memory". In the modeling literature, this is known as an "output gate."
> 9 votes

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Tags: terminology, philosophy-of-mind
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# Question
Title: What constructs help explain limited cognitive processing and the cognitive effects of rules that limit decision making choices?
Supposed that I'm a married man, and my wife asks me to pick out a paint color for our new house. It's not terribly mentally taxing. However, my wife starts to add rules. The color can't be too bright, no green, neutral, etc. The additional rules that my wife give me add an additional burden to the process of selecting a color. So in my mind, there is the base cognitive effort required to select a color, and a secondary cognitive burden that requires me to process the rules that my wife gave me.

**What mental effort constructs would apply in this scenario?**

From instruction design, cognitive load theory defines intrinsic load, extraneous load, and germane load. In my example, I think intrinsic load would map somewhat to the base effort required to choose a color, and extraneous load would map to the additional rules imposed by my wife. However, I'm not sure that the process of *learning* as explained by cognitive load theory translates well into this scenario where a *choice/decision* is trying to be made. **Are there other constructs that would be more applicable?**

# Answer
> 6 votes
There is an unclear relationship between classical conceptions of a unitary view of mental workload to the modern constructs of cognitive psychology and neuroscience that are relevant to your question. This is partly because mental workload is tough to define, and also because it is far too coarse a construct given the extremely large variety of dynamic cognitive factors that play a role in determining human performance. Hopefully this will become clear in the following description.

There is clearly difficulty incurred when one must pick just one option among many, without further guidance, as in your example. Recent work (Snyder et al., PNAS 2010) indicates this kind of difficulty arises from at least two isolable sources: the relative prepotency of the various colors (e.g., the problem is easier if you have a single favorite color, and harder if you like all colors equally) and the total option space (e.g., easier if you only have 3 colors of paint to choose from, harder if you have 500). These seem to have distinct and roughly additive effects on reaction time, at least in speeded lexical tasks, suggesting they both contribute to what you might call "mental workload."

This "underdetermined selection" problem can be made somewhat easier when additional criteria are specified, but not all criteria are equal. "Not green" and "Not bright" are simple cues but are obviously less effective than "blue" or "0 0 255," both because they fail to reduce the problem space as effectively, and because they directly specify distracting information (the colors you're NOT supposed to pick), which will slow visual search processes (e.g., Kiyonaga, Egner & Soto, 2012). Other cues - e.g., "something that goes well with the carpet" - may be more effective at reducing the problem space but probably incur additional mental workload, due to requiring what's known as relational reasoning. There is also clearly a further "working memory load" incurred by the need to simultaneously consider many criteria in selecting the correct paint color.

To the extent that the number of rules given to you exceeds your working memory capacity, you may chose to store those rules in what's sometimes known as secondary memory (e.g., Unsworth & Engle, Psych Review 2007). According to some conceptions of working memory (e.g., Oberauer et al Psychonomic Bulletin & Review, 2012), these items will then fall outside of the so-called "region of direct access," meaning that there are reaction time costs to retrieving these rules. Moreover, maintaining the intention to retrieve those rules at a later point - say, after processing those that do currently occupy your working memory - may itself add a cost to reaction time (e.g., Einstein, et al JEP:G 2005). There are also further "focus switching" costs (Oberauer, 2003) incurred when moving the single focus of attention to each of the rules that fall within the region of direct access.

If these rules are being provided during the "paint search task," they would also probably exert additional costs on reaction time. This again is probably due to multiple sources of interference. One of these likely reflects what's known as dual task costs - you're simultaneously listening to your wife while also trying to find the relevant paint color, and either resource sharing or rapid switching among tasks must occur. On the other hand, even if these rules are provided soon after some other external event in this paint search task, you may also be substantially more delayed in acting upon them (this is known as the "psychological refractory period" effect).

As if that weren't enough, as recently demonstrated by Scalf, Dux & Marois (JoCN, 2011), encoding of information into working memory yields delays in top-down attention in visual cortex.

And finally, under conditions of high working memory load, perceptual selection processes operate less efficiently (e.g., Lavie et al JEP:G 2004), further exacerbating any of the above deleterious effects on your ability to rapidly choose an appropriate paint color from those in front of you.

### References

* Einstein, G.O., McDaniel, M.A., Thomas, R., Mayfield, S., Shank, H., Morrisette, N. & Breneiser, J. (2005). Multiple processes in prospective memory retrieval: factors determining monitoring versus spontaneous retrieval.. Journal of Experimental Psychology: General, 134, 327. PDF
* Lavie, N., Hirst, A., de Fockert, J.W. & Viding, E. (2004). Load theory of selective attention and cognitive control.. Journal of Experimental Psychology: General; Journal of Experimental Psychology: General, 133, 339.
* Kiyonaga, A., Egner, T. & Soto, D. (2012). Cognitive control over working memory biases of selection. Psychonomic Bulletin & Review, , 1-8.
* Oberauer, K. (2003) Selective attention to elements in working memory. Experimental Psychology, 257-269.
* Oberauer, K., Lewandowsky, S., Farrell, S., Jarrold, C. & Greaves, M. (2012). Modeling working memory: An interference model of complex span. Psychonomic Bulletin & Review, , 1-41.
* Scalf, P.E., Dux, P.E. & Marois, R. (2011). Working Memory Encoding Delays Top--Down Attention to Visual Cortex. Journal of Cognitive Neuroscience, 23, 2593-2604.
* Snyder, H. R., Hutchinson, N., Nyhus, E., Curran, T., Banich, M. T., O'Reilly, R. C. & Munakata, Y. (2010). Neural inhibition enables selection during language processing. Proceedings of the National Academy of Sciences, 107, 155-167.
* Unsworth, N. & Engle, R.W. (2007). The nature of individual differences in working memory capacity: active maintenance in primary memory and controlled search from secondary memory.. Psychological review, 114, 104. PDF

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Tags: decision-making, problem-solving
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# Question
Title: Is there a canonical reference for behavioral, attentional, and memory tests?
In researching another question, I read a few review articles that were testing behavioral and attentional variables in response to different sleep parameters. I was curious about some of these tests, including, but not limited to, the following:

* Attentional network test
* Visual analog scale
* Digit symbol substitution task
* Psychomotor vigilance test
* Four-choice reaction time test
* Two-choice visual reaction time
* Letter cancellation

Rather than asking for a laundry list of their characteristics, which would rail against my question asking sensibilities, I'd like to know if there is a canonical reference in which I could look up the bases for these tests.

Ideally, it would describe the tests, their objectives, the proper procedures (and any variants), statistical power as a function of participants, and any particular information about different brain areas or deficits that the tests can definitively provide. It may well be that I'll have to go back to their origins in the literature, but it would seem that there would be some sort of handbook available.

# Answer
> 7 votes
I'm not aware of a comprehensive resource that details all of this information for all of these tests. A simple solution would be to find a specific reference for each of the tests you're interested in.

A good place to start looking for these references might be The Cognitive Atlas, which has a Tasks section. For example, the page about Digit/Symbol coding test gives some information about the task, what it measures, and relevant bibliography.

For the **Attentional Network Test** the canonical reference is probably the paper that introduced it:

* Fan, J., McCandliss, B. D., Sommer, T., Raz, M., & Posner, M. I. (2002). Testing the efficiency and independence of attentional networks. Journal of Cognitive Neuroscience, 14, 340–347. PDF

**Visual analog scale**, as far as I know, is not a specific test, but rather a methodology of presenting a visual scale to which the participants compare something (usually something 'subjective' like pain).

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# Question
Title: How do the brains of savants such as Orlando Serrell and Temple Grandin compare to a standard brain?
There are the examples of Orlando Serrell and Temple Grandin, who remember quite a lot, due to autism.

**How do their brains compare to a standard brain?**

See also: Partitions and Volume:

# Answer
I believe the answer lies in minicolumnar morphology in the neocortex. It's been shown that the minicolumns of autsitics and gifted individuals have narrower minicolumns, with greater spacing between each minicolumn. It's speculated that this creates an increased ability to distinguish percepts. Here is a paper on the topic:

Casanova MF, Switala AE, Trippe J, & Fitzgerald M. (2007) Comparative minicolumnar morphometry of three distinguished scientists. *Autism* 11(6):557-69.

I recommend reading through more of Casanova's work on the topic if you're interested.
> 9 votes

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Tags: autism, savant-syndrome, neurology, long-term-memory
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# Question
Title: Are different types of long term memories stored in different parts of the brain?
I recently had some questions concerning the capacity of the brain's memory:

* Are different types of long term-memories like know-how, your-life, etc. remembered in different parts of the brain?
* If so, how large are these different kinds of partitions of the brain?

See also: Savants and Volume.

# Answer
As far as your first question is concerned:
It seems that you're interested in the distinction between *declarative* and *nondeclarative* forms of memory. These different forms of memory have also been termed *knowing that* and *knowing how* (Cohen & Squire, 1980)

* Nondeclarative memory, according to Squire (2004), is an umbrella term refering to Procedural Memory, Priming, Classical Conditioning and nonassociative forms of learning. It seems that this type of knowledge is located over different areas in the brain, including Neocortex, Amygdala, Cerebellum and Neostriatum.
* Declarative memory is divided into semantic and episodic memory, which might be what you mean by *your-life*. In the brain, this form of memory is associated with the Hippocampus, whose major areas are the Dentate Gyrus and the CA3 and CA1 regions.

References:
Cohen, N. J. and Squire, L. R. (1980). Preserved learning and retention of pattern-analyzing skill in amnesia: Dissociation of knowing how and knowing that. *Science*, 210, 207–210.

Squire, L. R. (2004). Memory systems of the brain: a brief history and current perspective. *Neurobiology of learning and memory*, 82, 171–177.
> 6 votes

# Answer
Just to add to Jens answer, opinion is still divided regarding whether memory is subserved by distinct systems, or is a distributed, emergent property of perceptual, navigational and semantic systems. Whereas patient data has always strongly implicated distinct memory systems (e.g., declarative vs non-declarative), multivariate fMRI studies have provided good support for reinstatement theories, where successful retrieval of memories involves reinstatement of perceptual states. Moreover, there is growing evidence that regions that are thought to be amodal memory structures (e.g., hippocampus, perirhinal cortex), are involved in perceptual discrimination judgements and show preferences for different categories of visual input. For example, damage to the hippocampus can impair scene discrimination judgements whereas damage to the perirhinal cortex can impair face and object discrimination judgements. So it could be the case that there really aren't any dedicated memory structures per se, but memory is the co-ordinated reactivation of mechanisms involved in perception and action (probably via top down signals from frontal lobes).

The references provided by Jens provide good coverage of the distinct systems view of memory so I'll just provide some references for the distributed and reinstatement views.

**References**

Murray, E. A., Bussey, T. J., & Saksida, L. M. (2007). Visual perception and memory: A new view of medial temporal lobe function in primates and rodents. *Annual Review of Neuroscience*, 30, 99-122.

Graham, K.S., Barense, M.D. & Lee, A.C.H. (2010). Going beyond LTM in the MTL: a synthesis of neuropsychological and neuroimaging findings on the role of the medial temporal lobe in memory and perception. *Neuropsychologia*, 48, 831-853.

Polyn S.M., Natu V.S., Cohen J.D., & Norman K.A. (2005) Category-specific cortical activity precedes recall during memory search. *Science*, 310, 1963-1966.

Johnson, J. D., McDuff, S. G. R., Rugg, M. D., & Norman, K. A. (2009). Recollection, familiarity, and cortical reinstatement: A multivoxel pattern analysis. *Neuron*, 63, 697-708

Xue G, Dong Q, Chen C, Lu ZL, Mumford JA, Poldrack R (2010). Greater Neural Pattern Similarity Across Repetitions is Associated with Better Memory. Science, 330, 97-101.
> 8 votes

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Tags: neuroscience, long-term-memory
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# Question
Title: Is there a region of cortex which over a period of development becomes the seat of self?
# Background

Mountcastle's hypothesis, which is based on the observation of uniform cortical anatomy, suggests that the there might be a uniform cortical "algorithm". The only reason that some cortical regions seem to be specialized for particular functions, like vision, hearing, etc. is that they happen to be connected to corresponding sensory input. The ferret sensory input rewiring experiments confirms this hypothesis (rewiring auditory cortex in ferrets to receive visual input, lets them see just as good).

Regions of the cortex which are not connected directly to any sensory input listen in on the broadcasts that are sent by neighboring regions, either directly or through the thalamus (which is currently thought to be some sort of relaying mechanism) and do further transformations and refinements at a more abstract level. For example in the case of vision, it is known that the primary visual cortex, V1, consists of a sheet of cells/columns that are sensitive to edges oriented and/or moving in particular directions. The "higher" regions of visual cortex, take the output of V1 and further process it. Neurons in V4, for example, are known to be sensitive to objects like a chair or a dog *or your grandmother*. Much of this is discussed in detail by Jeff Hawkins in *On Intelligence* where he speculates that cortical regions are connected up in a hierarchy something like:

Hawkins, however, does not talk much about that top level region, and only makes a passing speculation that it might be the hippocampus. **But, it seems to be screaming at you, that whatever it is, it must be the seat of the self.**

Googling on these ideas led me to Cartesian Theater, a term that philosopher, Daniel Dennett derisively uses to refer to the idea that there is a central place in the brain, where everything comes together. For example, in the Multiple drafts model Dennett says:

> "The multiple drafts model of consciousness was developed as an alternative to the perennially attractive, but incoherent, model of conscious experience called Cartesian materialism, the idea that after early unconscious processing occurs in various relatively peripheral brain structures "everything comes together" in some privileged central place in the brain, which one might call the **Cartesian Theater** -- for "presentation" to the inner self or homunculus. *There is no such place in the brain*, but many theories seem to presuppose that there must be something like it."

However, I didn't find his arguments very compelling.

# Question

**Given that there are regions of cortex that are dedicated to vision, sound, touch processing, etc., is there a region of cortex, that listens to only the final assembled portions from several "lower" regions of cortex, which then over a period of development (by age 1.5?) becomes the seat of self?**

If this is the case, Dennett's criticism of the Cartesian Theater and a 'homunculus' observing it is outdated.

# Update

I believe the source of all the homunculus confusion to be the little green homunculus in *Men In Black I*, and Daniel Dennett's use of this imagery to caricature any argument for a region in the brain where everything comes together and therefore being the seat of the self.

In essence what I'm saying is that only a small subset of the brain is the seat of consciousness, the reason being that large portions of the cortex seem to essentially be doing pre-processing steps. For example, V1 the largest area of the cortex seems to be assembling the visual field from the split up portions coming from the eye via the LGN in the thalamus.

This by itself does not lead to an infinite regress, as the problem (of making sense of the world) is simplified a lot after all the pre-processing steps.

Another way of putting my point is via the following simple analogies:

```
| body        | brain                         | Self      |
|-------------+-------------------------------+-----------|
| corporation | executive staff               | CEO       |
| army        | officer corps                 | General   |
| nation      | congress/senate/supreme court | President |

```

**Some more clarification on the homunculus fallacy confusion:** Almost everyone agrees that no fallacy whatsoever is being made by saying that the brain is the seat of consciousness (SoC). Similarly, no fallacy is made merely by claiming that a subset of the brain is the SoC. A homunculus fallacy is made if it is further claimed that by identifying the SoC, an explanation of consciousness has been given. ***As Dennett rightly says, an explanation of consciousness should not contain components that are themselves fully conscious***. Doing so only postpones the problem and leads to infinite regress. In my question's background, I'm not trying to imply that I have explained consciousness, all I'm saying is that there is evidence that only a subset of the brain is the SoC, and this SoC could be regarded as being at the center of a Cartesian theater. And of course, instead of light and sound being projected/played in this theater, there are only streams of neural spikes, representing light, sound, etc. in transduced form.

# Answer
Modern homunculus arguments don't assert that there is physically a little man in your head. This would be a completely vacuous argument, and nobody would make it in the present day. When people make the homunculus fallacy today, they usually do it in the same fashion as you do: all the sensory information is assembled 'somewhere' and then 'some brain region' perceives it. It is an infinite regress in the sense that you didn't explain how perceiving is done, you just delegated it to a region of the brain you don't understand well. This is the same as Descartes believing that the 'seat of the soul' is the pineal gland. Except you replaced that gland (which we understand relatively well) by another region of the brain that we understand less well. Notice how this has no explanatory power. Not only that, it can be experimentally falsified (to a certain extent)!

It is hard to study consciousness scientifically because no one has given it a good operational definition. However, most discussions of consciousness talk about things like qualia or basic subjective experiences. One of the most common ones discussed is the experience of colour.

Physics does not have colour, it just has a continuous spectrum of wavelengths. Even when you look at the sensitivity of the 3 types of cones in the retina it is not discrete, but continuous. The categories of colours (i.e. "that's red", "that's blue") are produced by perception and these discrete-ish categories form the basis of colour qualia. Scientists can study these categories by asking participants if various stimuli feel like the same colour. What is known, is that the arbitrary boundaries of the categories people draw between colours is language dependent!

This tells you that the 'linguistic processing' and 'colour processing' regions of the mind interact to produce the qualia of colour. In other words this is a piece of evidence in support of the Whorf hypothesis: language effects your subjective conscious experience. This might seem like support for integration and higher level perception by a single region, but there is a kicker.

Gilbert et al. (2006) showed that the Whorf hypothesis is supported in the right visual field but not the left. In other words, when I present colours in one part of your visual field, you experience them one way and when I present them to the other then you experience them in a fundamentally different way. The right visual field integrates with your linguistic processing and the other doesn't. Hence, you can't localize the qualia of colour to either the right or left hemisphere. They both experience them and this is usually not perceivable to us without a controlled experiment.

Simply put, there is no reason to believe that all sensory experience is somehow synthesized and presented to a 'seat of consciousness'. Unless you are willing to make the tautological statement that the 'seat of consciousness' is the whole brain (or almost all of it). This is consistent with most modern formal approaches to consciousness that model it as highly distributed over the whole brain, with no single 'seat'. For more info, look at the answers on the following question:

What are current neuronal explanations and models of 'consciousness'?

<sub> Gilbert, A. L., Regier, T., Kay, P., & Ivry, R. B. (2006). Whorf hypothesis is supported in the right visual field but not the left. Proceedings of the National Academy of Sciences of the United States of America, 103(2), 489-494. </sub>
> 16 votes

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Tags: neuroscience, consciousness, philosophy-of-mind
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title: Hearing first but understanding later?

text:
# Question
Title: Hearing first but understanding later?
I have experienced this phenomenon several times and checked with other people as well.

It goes like this: you hear something, but it's just a sound with no meaning. Some seconds later, you consciously remember the sound and make sense out of it (like a word or a phrase that somebody tells).

Although both processes (remembrance and understanding) are fairly common, I find it weird that understanding is not automatically triggered when processing a sound and it can be demanded on purpose

Is there any name for this phenomenon? (Would appreciate some detail on it too.)

# Answer
> 4 votes
The phenomena broadly makes sense in terms of information processing models of memory and cognition.

### The phonological loop

For example, you could think about the phenomena in terms of a phonological loop. To Quote the Wikipedia article on Baddeley's model of working memory

> The phonological loop (or "articulatory loop") as a whole deals with sound or phonological information. It consists of two parts: a short-term phonological store with auditory memory traces that are subject to rapid decay and an articulatory rehearsal component (sometimes called the articulatory loop) that can revive the memory traces.
>
> Any auditory verbal information is assumed to enter automatically into the phonological store. Visually presented language can be transformed into phonological code by silent articulation and thereby be encoded into the phonological store. This transformation is facilitated by the articulatory control process. The phonological store acts as an 'inner ear', remembering speech sounds in their temporal order, whilst the articulatory process acts as an 'inner voice' and repeats the series of words (or other speech elements) on a loop to prevent them from decaying. The phonological loop may play a key role in the acquisition of vocabulary, particularly in the early childhood years.\[3\] It may also be vital for learning a second language.

### Applying this to the phenomena

* In the very short term (perhaps a few seconds), you presumably have a internal representation of the raw sound, which might if you were to attend to it afterwards be then processed into words and meaning.
* Alternatively, you may hear the words but not process the meaning. Presumably these words can remain represented for a little longer in your short term memory than can the raw sounds (as a very rough guess, perhaps up to 10 or 20 seconds). And then you can return to the words and process them.
* Another possibility is that you have basically processed the meaning of the original words, but were perhaps immediately distracted, and then a little later you remembered what was said and that you need to respond.

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Tags: terminology, memory, perception
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# Question
Title: Spurious attractors in Hopfield networks
A classic "Hopfield network" is a type of artificial neural network in which the units are bi-stable and fully interconnected by symmetrically weighted connections. In 1982, Hopfield showed that such networks are characterized by an "energy function", under which stored memories correspond to local energy minima \[1\].

In a 1983 paper \[2\], Hopfield et al further showed that "spurious memories" (local energy minima that are created during training, in addition to the intended target patterns) can be suppressed by an "unlearning procedure", during which the network is repeatedly allowed to relax from random states, and the resulting states then "unlearned" by anti-Hebbian weight adjustments. The procedure affects spurious memories more than the desirable "learned memories", thus improving recall performance. However, the paper offers no explanation for why this should be so.

A 2004 paper by Robins and McCallum \[3\] demonstrates that spurious memories can be distinguished from learned ones because their "energy profiles" are different. Specifically, the ratio of lowest to highest energy contributions from individual units is significantly smaller in states corresponding to spurious memories than in states corresponding to learned memories. Again, the effect is not accounted for (except for a tentative partial explanation).

My questions are:

1. Is there a relationship between these two findings, i.e. does the lower "energy ratio" of spurious states explain their greater susceptibility to unlearning?
2. Have any explanations for either or both of these phenomena been put forward since the publication of the papers?
3. Are there other ways to suppress or detect spurious memories in the Hopfield family of neural networks?

\[1\] Hopfield, J. J. (1982). Neural networks and physical systems with emergent collective computational abilities. Proceedings of the National Academy of Sciences, 79(8), 2554 –2558.

\[2\] Hopfield, J. J., Feinstein, D. I., & Palmer, R. G. (1983). “Unlearning” has a stabilizing effect in collective memories. Nature, 304(5922), 158–159.

\[3\] Robins, A. V., & McCallum, S. J. R. (2004). A robust method for distinguishing between learned and spurious attractors. Neural Networks, 17(3), 313–326. doi:10.1016/j.neunet.2003.11.007

# Answer
> 8 votes
I think that your intuition about the lower "energy ratio" of spurious states explaining their greater susceptibility to unlearning might be correct.

In a Hopfield Network spurious states are activity patterns that have not been explicitly embedded in the synaptic matrix, but are nonetheless stable. They are in other words "unwanted" attractor states that, by virtue of a finite overlap with the "wanted" attractor states, come about as a local minimum in the energy function. The unlearning rule in Hopfield et al. (1983) consists in modifying the synaptic matrix so as to decrease the energy of the stable states in which the network dynamics settles down, be them spurious or embedded states. Because the spurious states have higher energy than the embedded states, they are more strongly affected by the unlearning step.

Now, why do spurious states have higher energy than the embedded attractor states? Well, this is actually not true in general, but it is the case in a regime where the Hopfield network doesn't exceed its loading capacity, that is when the number of learned patterns over number of units $p/N$ is lower than the critical capacity $\alpha\_c\approx0.138$. In this regime, it is possible to estimate the overlap of the spurious states with the learned patterns, and show that is generally lower than $1$ (the overlap of the learned patterns with themselves). Because of how the Hebbian construction of the synaptic matrix in the Hopfield model, this overlaps are terms that appears in the energy function. The energy of a pattern is namely proportional to minus the square root of its overlap with the learned patterns. This means that the spurious patterns have higher energy than the learned ones.

In general this kind of naive considerations has to be supported by more rigorous arguments based on probability theory. These for instance point out that even for the regime below $\alpha\_c$ the retrieved patterns are actually spurious states as soon as the number of embedded patterns $p$ exceeds above $\frac{N}{2\ln N}$. Such spurious states have however such a high overlap with the learned patterns ($0.97$) that they basically coincide with them.

This result and generalizations thereof for non-zero temperature (i.e. noise in the dynamics) and beyond critical capacity have been worked out in the following very technical paper:

and in the book:

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Tags: computational-modeling, neural-network, connectionism
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# Question
Title: What structures in the brain are called upon to strengthen coupling between bilateral movements?
It is very difficult for the normally-coordinated person to be able to pat his/her head and rub his/her stomach at the same time (or pick a similar activity). It seems to be possible to maintain the separate hand motions over the short term, but keeping the movements separate is almost impossible to keep up. One ends up either rubbing the head while rubbing the stomach or patting the head while patting the stomach before long. Effectively, there seems to be a "locking" between the motor cortices across the hemispheres during bilateral movements of the arms.

Given all of this complex coordination that is possible between the two arms/hands, what are the structures within the brain that are called upon to strengthen the coupling between the two arms during bilateral movements? Why do the hemispheres try to lock their activity rather than letting both arms act independently?

# Answer
It's not so much a "locking" between the two hemispheres as it is a combination of an asymmetrical representation of the ipsilateral (same side) limb in cortex, and phase transitions, which bring the limbs into a more energetically favorable state.

Kelso (1984) compares the phase transition to that of a racehorse, which is able to adjust its gait for the optimal use of oxygen in its blood. In his study, regardless of whether a subject's limb was loaded or unloaded during a trial, there was a phase resetting after the subject reached a certain frequency (constant within subjects). You can see in the diagram below that the dotted line of one arm's trajectory is 180° out of phase with the other, the solid line, and at a certain point, they fall into lockstep.

Ziemann (2001) study points to another possible reason for the synchronization. In right handed subjects, there tends to be a dominance of the left motor cortex in the activation of the ipsilateral hand. Trying to do different motions with both hands may "pull" the activity towards what the left hand is doing. Presumably, there might be a similar behavior in left-handed subjects, but as in hearing and language, there is not a perfect symmetry of cortical features for left-handers.

In terms of structures that *do* govern bilateral coordination, Sadato et al (1997) used PET scanning to establish that, at least in right handed subjects, the right dorsal premotor area along with the right posterior supplementary motor area, were significantly more active while making parallel movements. I found no further evidence of it, but this could be a channel through which some of the phase shifting is taking place.

## References

1. Kelso, J.A.S. (1984). Phase transitions and critical behavior in human bimanual coordination. American Journal of Physiology, 246 (Regulatory Integrative Comp. Physiol 15):R1000-1004.
2. Sadato, N., Yonekura, Y., et al (1997). Role of the supplementary motor area and the right premotor cortex in the coordination of bimanual finger movements. Journal of Neuroscience, 17(24): 9667-9674. PDF
3. Sakurada, T., Gomi, H., Ito, K. (2009). Multiple interactions between hemispheres of the brain modulating coupling of bilateral movements. The 31st Annual International Conference of the IEEE EMBS Minneapolis, Minnesota, USA, September 2-6, 2009: 5922-5925.
4. Ziemann, U., Hallett, M. (2001). Hemispheric asymmetry of ipsilateral motor cortex activation during unimanual motor tasks: further evidence for motor dominance. Clinical Neurophysiology, 112: 107-113.
> 6 votes

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Tags: neuroscience, motor, synchronization, coordination
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