individual differences

IQ can rise or fall significantly during adolescence

November, 2011

A small study of adolescents shows marked variability in IQ over a four-year period for many of them. This variability correlated with specific changes in the brain.

IQ has long been considered to be a fixed attribute, stable across our lifetimes. But in recent years, this assumption has come under fire, with evidence of the positive and negative effects education and experiences can have on people’s performance. Now a new (small) study provides a more direct challenge.

In 2004, 33 adolescents (aged 12-16) took IQ tests and had their brains scanned. These tests were repeated four years later. The teenagers varied considerably in their levels of ability (77-135 in 2004; 87-143 in 2008). While the average IQ score remained the same (112; 113), there were significant changes in the two IQ scores for some individuals, with some participants gaining as much as 21 points, and others falling as much as 18 points. Clear change in IQ occurred for a third of the participants, and there was no obvious connection to specific attributes (e.g., low performers didn’t get better while high performers got worse).

These changes in performance correlated with structural changes in the brain. An increase in verbal IQ score correlated with an increase in the density of grey matter in an area of the left motor cortex of the brain that is activated when articulating speech. An increase in non-verbal IQ score correlated with an increase in the density of grey matter in the anterior cerebellum, which is associated with movements of the hand. Changes in verbal IQ and changes in non-verbal IQ were independent.

While I’d really like to see this study repeated with a much larger sample, the findings are entirely consistent with research showing increases in grey matter density in specific brain regions subsequent to specific training. The novel part of this is the correlation with such large changes in IQ.

The findings add to growing evidence that teachers shouldn’t be locked into beliefs about a student’s future academic success on the basis of past performance.

Postscript: I should perhaps clarify that IQ performance at each of these time points was age-normed - this is not a case of children just becoming 'smarter with age'.

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Attention

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Attention problems

Attention training

Older news items (pre-2010) brought over from the old website

Attention is more about reducing the noticeability of the unattended

No visual scene can be processed in one fell swoop — we piece it together from the bits we pay attention to (which explains why we sometimes miss objects completely, and can’t understood how we could have missed them when we finally notice them). We know that paying attention to something increases the firing rate of neurons tuned for that type of stimulus, and until a recent study we thought that was the main process underlying our improved perception when we focus on something. However a macaque study has found that the main cause — perhaps four times as important — is a reduction in the background noise, allowing the information coming in to be much more noticeable.

[1093] Mitchell, J. F., Sundberg K. A., & Reynolds J. H.
(2009).  Spatial Attention Decorrelates Intrinsic Activity Fluctuations in Macaque Area V4.
Neuron. 63(6), 879 - 888.

http://esciencenews.com/articles/2009/09/23/rising.above.din

Brainwaves regulate our searching

A long-standing question concerns how we search complex visual scenes. For example, when you enter a crowded room, how do you go about searching for your friends? Now a monkey study reveals that visual attention jumps sequentially from point to point, shifting focus around 25 times in a second. Intriguingly, and unexpectedly, it seems this timing is determined by brainwaves. The finding connects speed of thinking with the oscillation frequency of brainwaves, giving a new significance to brainwaves (whose function is rather mysterious, but of increasing interest to researchers), and also suggesting an innovative approach to improving attention.

[1118] Buschman, T. J., & Miller E. K.
(2009).  Serial, Covert Shifts of Attention during Visual Search Are Reflected by the Frontal Eye Fields and Correlated with Population Oscillations.
Neuron. 63(3), 386 - 396.

http://www.eurekalert.org/pub_releases/2009-08/miot-tme080609.php

Ability to ignore distraction most important for attention

Confirming an earlier study, a series of four experiments involving 84 students has found that students with high working memory capacity were noticeably better able to ignore distractions and stay focused on their tasks. The findings provide more evidence that the poor attentional capacity of individuals with low working memory capacity result from a reduced ability to ignore attentional capture (stimuli that involuntarily “capture” your attention, like a loud noise or a suddenly appearing object), rather than an inability to focus.

[828] Fukuda, K., & Vogel E. K.
(2009).  Human Variation in Overriding Attentional Capture.
J. Neurosci.. 29(27), 8726 - 8733.

http://www.eurekalert.org/pub_releases/2009-08/uoo-bbo080609.php

Stress disrupts task-switching, but the brain can bounce back

A new neuroimaging study involving 20 male M.D. candidates in the middle of preparing for their board exams has found that they had a harder time shifting their attention from one task to another after a month of stress than other healthy young men who were not under stress. The finding replicates what has been found in rat studies, and similarly correlates with impaired function in an area of the prefrontal cortex that is involved in attention. However, the brains recovered their function within a month of the end of the stressful period.

[829] Liston, C., McEwen B. S., & Casey B. J.
(2009).  Psychosocial stress reversibly disrupts prefrontal processing and attentional control.
Proceedings of the National Academy of Sciences. 106(3), 912 - 917.

Full text available at http://www.pnas.org/content/106/3/912.abstract
http://www.eurekalert.org/pub_releases/2009-01/ru-sdh012709.php

Attention, it’s all about connecting

An imaging study in which volunteers spent an hour identifying letters that flashed on a screen has shed light on what happens when our attention wanders. Reduced communication in the ventral fronto-parietal network, critical for attention, was found to predict slower response times 5-8 seconds before the letters were presented.

Daniel Weissman presented the results at the 38th annual meeting of the Society for Neuroscience, held Nov. 15 to 19 in Washington, DC.

http://www.newscientist.com/article/mg20026865.600-bored-your-brain-is-disconnecting.html

The importance of acetylcholine

A rat study suggests that acetylcholine, a neurotransmitter known to be important for attention, is critical for "feature binding"— the process by which our brain combines all of the specific features of an object and gives us a complete and unified picture of it. The findings may lead to improved therapies and treatments for a variety of attention and memory disorders.

[1265] Botly, L. C. P. [1], & De Rosa E.
(2008).  A Cross-Species Investigation of Acetylcholine, Attention, and Feature Binding.
Psychological Science. 19, 1185 - 1193.

http://www.eurekalert.org/pub_releases/2008-11/afps-bba111808.php

Attention grabbers snatch lion's share of visual memory

It’s long been thought that when we look at a visually "busy" scene, we are only able to store a very limited number of objects in our visual short-term or working memory. For some time, this figure was believed to be four or five objects, but a recent report suggested it could be as low as two. However, a new study reveals that although it might not be large, it’s more flexible than we thought. Rather than being restricted to a limited number of objects, it can be shared out across the whole image, with more memory allocated for objects of interest and less for background detail. What’s of interest might be something we’ve previously decided on (i.e., we’re searching for), or something that grabs our attention.  Eye movements also reveal how brief our visual memory is, and that what our eyes are looking at isn’t necessarily what we’re ‘seeing’ — when people were asked to look at objects in a particular sequence, but the final object disappeared before their eyes moved on to it, it was found that the observers could more accurately recall the location of the object that they were about to look at than the one that they had just been looking at.

[1398] Bays, P. M., & Husain M.
(2008).  Dynamic shifts of limited working memory resources in human vision.
Science (New York, N.Y.). 321(5890), 851 - 854.

http://www.physorg.com/news137337380.html

How Ritalin works to focus attention

Ritalin has been widely used for decades to treat attention deficit hyperactivity disorder (ADHD), but until now the mechanism of how it works hasn’t been well understood. Now a rat study has found that Ritalin, in low doses, fine-tunes the functioning of neurons in the prefrontal cortex, and has little effect elsewhere in the brain. It appears that Ritalin dramatically increases the sensitivity of neurons in the prefrontal cortex to signals coming from the hippocampus. However, in higher doses, PFC neurons stopped responding to incoming information, impairing cognition. Low doses also reinforced coordinated activity of neurons, and weakened activity that wasn't well coordinated. All of this suggests that Ritalin strengthens dominant and important signals within the PFC, while lessening weaker signals that may act as distractors.

[663] Devilbiss, D. M., & Berridge C. W.
(2008).  Cognition-Enhancing Doses of Methylphenidate Preferentially Increase Prefrontal Cortex Neuronal Responsiveness.
Biological Psychiatry. 64(7), 626 - 635.

http://www.eurekalert.org/pub_releases/2008-06/uow-suh062408.php

Disentangling attention

A new study provides more evidence that the ability to deliberately focus your attention is physically separate in the brain from the part that helps you filter out distraction. The study trained monkeys to take attention tests on a video screen in return for a treat of apple juice. When the monkeys voluntarily concentrated (‘top-down’ attention), the prefrontal cortex was active, but when something distracting grabbed their attention (‘bottom-up’ attention), the parietal cortex became active. The electrical activity in these two areas vibrated in synchrony as they signaled each other, but top-down attention involved synchrony that was stronger in the lower-frequencies and bottom-up attention involved higher frequencies. These findings may help us develop treatments for attention disorders.

[1071] Buschman, T. J., & Miller E. K.
(2007).  Top-Down Versus Bottom-Up Control of Attention in the Prefrontal and Posterior Parietal Cortices.
Science. 315(5820), 1860 - 1862.

http://dsc.discovery.com/news/2007/03/29/attention_hea.html?category=health

Asymmetrical brains let fish multitask

A fish study provides support for a theory that lateralized brains allow animals to better handle multiple activities, explaining why vertebrate brains evolved to function asymmetrically. The minnow study found that nonlateralized minnows were as good as those bred to be lateralized (enabling it to favor one or other eye) at catching shrimp. However, when the minnows also had to look out for a sunfish (a minnow predator), the nonlateralized minnows took nearly twice as long to catch 10 shrimp as the lateralized fish.

[737] Dadda, M., & Bisazza A.
(2006).  Does brain asymmetry allow efficient performance of simultaneous tasks?.
Animal Behaviour. 72(3), 523 - 529.

http://sciencenow.sciencemag.org/cgi/content/full/2006/623/2?etoc

Why are uniforms uniform? Because color helps us track objects

Laboratory tests have revealed that humans can pay attention to only 3 objects at a time. Yet there are instances in the real world — for example, in watching a soccer match — when we certainly think we are paying attention to more than 3 objects. Are we wrong? No. Anew study shows how we do it — it’s all in the color coding. People can focus on more than three items at a time if those items share a common color. But, logically enough, no more than 3 color sets.

[927] Halberda, J., Sires S. F., & Feigenson L.
(2006).  Multiple spatially overlapping sets can be enumerated in parallel.
Psychological Science: A Journal of the American Psychological Society / APS. 17(7), 572 - 576.

http://www.eurekalert.org/pub_releases/2006-06/jhu-wau062106.php

An advantage of age

A study comparing the ability of young and older adults to indicate which direction a set of bars moved across a computer screen has found that although younger participants were faster when the bars were small or low in contrast, when the bars were large and high in contrast, the older people were faster. The results suggest that the ability of one neuron to inhibit another is reduced as we age (inhibition helps us find objects within clutter, but makes it hard to see the clutter itself). The loss of inhibition as we age has previously been seen in connection with cognition and speech studies, and is reflected in our greater inability to tune out distraction as we age. Now we see the same process in vision.

[1356] Betts, L. R., Taylor C. P., Sekuler A. B., & Bennett P. J.
(2005).  Aging Reduces Center-Surround Antagonism in Visual Motion Processing.
Neuron. 45(3), 361 - 366.

http://psychology.plebius.org/article.htm?article=739
http://www.eurekalert.org/pub_releases/2005-02/mu-opg020305.php

We weren't made to multitask

A new imaging study supports the view that we can’t perform two tasks at once, rather, the tasks must wait their turn — queuing up for their turn at processing.

[1070] Jiang, Y., Saxe R., & Kanwisher N.
(2004).  Functional magnetic resonance imaging provides new constraints on theories of the psychological refractory period.
Psychological Science: A Journal of the American Psychological Society / APS. 15(6), 390 - 396.

http://www.eurekalert.org/pub_releases/2004-06/aps-wwm060704.php

More light shed on memory encoding

Anything we perceive contains a huge amount of sensory information. How do we decide what bits to process? New research has identified brain cells that streamline and simplify sensory information, markedly reducing the brain's workload. The study found that when monkeys were taught to remember clip art pictures, their brains reduced the level of detail by sorting the pictures into categories for recall, such as images that contained "people," "buildings," "flowers," and "animals." The categorizing cells were found in the hippocampus. As humans do, different monkeys categorized items in different ways, selecting different aspects of the same stimulus image, most likely reflecting different histories, strategies, and expectations residing within individual hippocampal networks.

[662] Hampson, R. E., Pons T. P., Stanford T. R., & Deadwyler S. A.
(2004).  Categorization in the monkey hippocampus: A possible mechanism for encoding information into memory.
Proceedings of the National Academy of Sciences of the United States of America. 101(9), 3184 - 3189.

http://www.eurekalert.org/pub_releases/2004-02/wfub-nfo022604.php

Neural circuits that control eye movements play crucial role in visual attention

Everyone agrees that to improve your memory it is important to “pay attention”. Unfortunately, noone really knows how to improve our ability to “pay attention”. An important step in telling us how visual attention works was recently made in a study that looked at the brain circuits that control eye movements. It appears that those brain circuits that program eye movements also govern whether the myriad signals that pour in from the locations where the eyes could move should be amplified or suppressed. It appears that the very act of preparing to move the eye to a particular location can cause an amplification (or suppression) of signals from that area. This is possible because humans and primates can attend to something without moving their eyes to that object.

[741] Moore, T., & Armstrong K. M.
(2003).  Selective gating of visual signals by microstimulation of frontal cortex.
Nature. 421(6921), 370 - 373.

http://www.eurekalert.org/pub_releases/2003-01/pu-ssh012303.php

Different aspects of attention located in different parts of the brain

We all know attention is important, but we’ve never been sure exactly what it is. Recent research suggests there’s good reason for this – attention appears to be multi-faceted, far less simple than originally conceived. Patients with specific lesions in the frontal lobes and other parts of the brain have provided evidence that different types of attentional problems are associated with injuries in different parts of the brain, suggesting that attention is not, as has been thought, a global process. The researchers have found evidence for at least three distinct processes, each located in different parts of the frontal lobes. These are: (1) a system that helps us maintain a general state of readiness to respond, in the superior medial frontal regions; (2) a system that sets our threshold for responding to an external stimulus, in the left dorsolateral region; and (3) a system that helps us selectively attend to appropriate stimuli, in the right dorsolateral region.

[260] Stuss, D. T., Binns M. A., Murphy K. J., & Alexander M. P.
(2002).  Dissociations within the anterior attentional system: effects of task complexity and irrelevant information on reaction time speed and accuracy.
Neuropsychology. 16(4), 500 - 513.

http://www.eurekalert.org/pub_releases/2002-10/apa-pda100702.php

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Brain continues to develop well into our 20s

October, 2011

A new study shows that the wiring that connects the frontal lobes to other parts of the cerebral cortex continues to develop well into young adulthood — except for a small minority that show degradation.

Brain imaging data from 103 healthy people aged 5-32, each of whom was scanned at least twice, has demonstrated that wiring to the frontal lobe continues to develop after adolescence.

The brain scans focused on 10 major white matter tracts. Significant changes in white matter tracts occurred in the vast majority of children and early adolescents, and these changes were mostly complete by late adolescence for projection and commissural tracts (projection tracts project from the cortex to non-cortical areas, such as the senses and the muscles, or from the thalamus to the cortex; commissural tracts cross from one hemisphere to the other). But association tracts (which connect regions within the same hemisphere) kept developing after adolescence.

This was particularly so for the inferior and superior longitudinal and fronto-occipital fascicule (the inferior longitudinal fasciculus connects the temporal and occipital lobes; the superior longitudinal fasciculus connects the frontal lobe to the occipital lobe and parts of the temporal and parietal lobes). These frontal connections are needed for complex cognitive tasks such as inhibition, executive functioning, and attention.

The researchers speculated that this continuing development may be due to the many life experiences in young adulthood, such as pursing post-secondary education, starting a career, independence and developing new social and family relationships.

But this continuing development wasn’t seen in everyone. Indeed, in some people, there was evidence of reductions, rather than growth, in white matter integrity. It may be that this is connected with the development of psychiatric disorders that typically develop in adolescence or young adulthood — perhaps directly, or because such degradation increases vulnerability to other factors (e.g., to drug use). This is speculative at the moment, but it opens up a new avenue to research.

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[2528] Lebel, C., & Beaulieu C.
(2011).  Longitudinal Development of Human Brain Wiring Continues from Childhood into Adulthood.
The Journal of Neuroscience. 31(30), 10937 - 10947.

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Simple estimation abilities predict better math understanding in preschoolers

August, 2011

New research linking a better number sense to greater math understanding in preschoolers emphasizes the role of parents and caregivers in giving children a head start in math.

Mathematics is a complex cognitive skill, requiring years of formal study. But of course some math is much simpler than others. Counting is fairly basic; calculus is not. To what degree does ability at the simpler tasks predict ability at the more complex? None at all, it was assumed, but research with adolescents has found an association between math ability and simple number sense (or as it’s called more formally, the "Approximate Number System" or ANS).

A new study extends the finding to preschool children. The study involved 200 3- to 5-year-old children, who were tested on their number sense, mathematical ability and verbal ability. The number sense task required children to estimate which group had more dots, when seeing briefly presented groups of blue and yellow dots on a computer screen. The standardized test of early mathematics ability required them to verbally count items on a page, to tell which of two spoken number words was greater or lesser, to read Arabic numbers, as well as demonstrate their knowledge of number facts (such as addition or multiplication), calculation skills (solving written addition and subtraction problems) and number concepts (such as answering how many sets of 10 are in 100). The verbal assessment was carried out by parents and caregivers of the children.

The study found that those who could successfully tell when the difference between the groups was only one dot, also knew the most about Arabic numerals and arithmetic. In other words, the findings confirm that number sense is linked to math ability.

Because these preschoolers have not yet had formal math instruction, the conclusion being drawn is that this number sense is inborn. I have to say that seems to me rather a leap. Certainly number sense is seen in human infants and some non-human animals, and in that sense the ANS is assuredly innate. However what we’re talking about here is the differences in number sense — the degree to which it has been developed. I’d remind you of my recent report that preschoolers whose parents engage in the right number-talk develop an understanding of number earlier, and that such understanding affects later math achievement. So I think it’s decidedly premature to assume that some infants are born with a better number sense, as opposed to having the benefit of informal instruction that develops their number sense.

I think, rather, that the finding adds to the evidence that preschoolers’ experiences and environment have long-lasting effects on academic achievement.

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Many genes are behind human intelligence

August, 2011

A large-scale genome-wide analysis has confirmed that half the differences in intelligence between people of similar background can be attributed to genetic differences — but it’s an accumulation of hundreds of tiny differences.

There has been a lot of argument over the years concerning the role of genes in intelligence. The debate reflects the emotions involved more than the science. A lot of research has gone on, and it is indubitable that genes play a significant role. Most of the research however has come from studies involving twins and adopted children, so it is indirect evidence of genetic influence.

A new technique has now enabled researchers to directly examine 549,692 single nucleotide polymorphisms (SNPs — places where people have single-letter variations in their DNA) in each of 3511 unrelated people (aged 18-90, but mostly older adults). This analysis had produced an estimate of the size of the genetic contribution to individual differences in intelligence: 40% of the variation in crystallized intelligence and 51% of the variation in fluid intelligence. (See http://www.memory-key.com/memory/individual/wm-intelligence for a discussion of the difference)

The analysis also reveals that there is no ‘smoking gun’. Rather than looking for a handful of genes that govern intelligence, it seems that hundreds if not thousands of genes are involved, each in their own small way. That’s the trouble: each gene makes such a small contribution that no gene can be fingered as critical.

Discussions that involve genetics are always easily misunderstood. It needs to be emphasized that we are talking here about the differences between people. We are not saying that half of your IQ is down to your genes; we are saying that half the difference between you and another person (unrelated but with a similar background and education — study participants came from Scotland, England and Norway — that is, relatively homogenous populations) is due to your genes.

If the comparison was between, for example, a middle-class English person and someone from a poor Indian village, far less of any IQ difference would be due to genes. That is because the effects of environment would be so much greater.

These findings are consistent with the previous research using twins. The most important part of these findings is the confirmation it provides of something that earlier studies have hinted at: no single gene makes a significant contribution to variation in intelligence.

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Working memory capacity affects emotional regulation

June, 2011

A new study confirms earlier indications that those with a high working memory capacity are better able to regulate their emotions.

Once upon a time we made a clear difference between emotion and reason. Now increasing evidence points to the necessity of emotion for good reasoning. It’s clear the two are deeply entangled.

Now a new study has found that those with a higher working memory capacity (associated with greater intelligence) are more likely to automatically apply effective emotional regulation strategies when the need arises.

The study follows on from previous research that found that people with a higher working memory capacity suppressed expressions of both negative and positive emotion better than people with lower WMC, and were also better at evaluating emotional stimuli in an unemotional manner, thereby experiencing less emotion in response to those stimuli.

In the new study, participants were given a test, then given either negative or no feedback. A subsequent test, in which participants were asked to rate their familiarity with a list of people and places (some of which were fake), evaluated whether their emotional reaction to the feedback affected their performance.

This negative feedback was quite personal. For example: "your responses indicate that you have a tendency to be egotistical, placing your own needs ahead of the interests of others"; "if you fail to mature emotionally or change your lifestyle, you may have difficulty maintaining these friendships and are likely to form insecure relations."

The false items in the test were there to check for "over claiming" — a reaction well known to make people feel better about themselves and control their reactions to criticism. Among those who received negative feedback, those with higher levels of WMC were found to over claim the most. The people who over claimed the most also reported, at the end of the study, the least negative emotions.

In other words, those with a high WMC were more likely to automatically use an emotion regulation strategy. Other emotional reappraisal strategies include controlling your facial expression or changing negative situations into positive ones. Strategies such as these are often more helpful than suppressing emotion.

Reference: 

Schmeichel, Brandon J.; Demaree, Heath A. 2010. Working memory capacity and spontaneous emotion regulation: High capacity predicts self-enhancement in response to negative feedback. Emotion, 10(5), 739-744.

Schmeichel, Brandon J.; Volokhov, Rachael N.; Demaree, Heath A. 2008. Working memory capacity and the self-regulation of emotional expression and experience. Journal of Personality and Social Psychology, 95(6), 1526-1540. doi: 10.1037/a0013345

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Brain flexibility predicts learning speed

June, 2011

New analytic techniques reveal that functional brain networks are more fluid than we thought.

A new perspective on learning comes from a study in which 18 volunteers had to push a series of buttons as fast as possible, developing their skill over three sessions. New analytical techniques were then used to see which regions of the brain were active at the same time. The analysis revealed that those who learned new sequences more quickly in later sessions were those whose brains had displayed more 'flexibility' in the earlier sessions — that is, different areas of the brain linked with different regions at different times.

At this stage, we don’t know how stable an individual’s flexibility is. It may be that individuals vary significantly over the course of time, and if so, this information could be of use in predicting the best time to learn.

But the main point is that the functional modules, the brain networks that are involved in specific tasks, are more fluid than we thought. This finding is in keeping, of course, with the many demonstrations of damage to one region being compensated by new involvement of another region.

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[2212] Bassett, D. S., Wymbs N. F., Porter M. A., Mucha P. J., Carlson J. M., & Grafton S. T.
(2011).  Dynamic reconfiguration of human brain networks during learning.
Proceedings of the National Academy of Sciences. 108(18), 7641 - 7646.

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Individual differences in learning motor skills reflect brain chemical

April, 2011

An imaging study demonstrates that people who are quicker at learning a sequence of finger movements have lower levels of the inhibitory chemical GABA.

What makes one person so much better than another in picking up a new motor skill, like playing the piano or driving or typing? Brain imaging research has now revealed that one of the reasons appears to lie in the production of a brain chemical called GABA, which inhibits neurons from responding.

The responsiveness of some brains to a procedure that decreases GABA levels (tDCS) correlated both with greater brain activity in the motor cortex and with faster learning of a sequence of finger movements. Additionally, those with higher GABA concentrations at the beginning tended to have slower reaction times and less brain activation during learning.

It’s simplistic to say that low GABA is good, however! GABA is a vital chemical. Interestingly, though, low GABA has been associated with stress — and of course, stress is associated with faster reaction times and relaxation with slower ones. The point is, we need it in just the right levels, and what’s ‘right’ depends on context. Which brings us back to ‘responsiveness’ — more important than actual level, is the ability of your brain to alter how much GABA it produces, in particular places, at particular times.

However, baseline levels are important, especially where something has gone wrong. GABA levels can change after brain injury, and also may decline with age. The findings support the idea that treatments designed to influence GABA levels might improve learning. Indeed, tDCS is already in use as a tool for motor rehabilitation in stroke patients — now we have an idea why it works.

Reference: 

[2202] Stagg, C J., Bachtiar V., & Johansen-Berg H.
(2011).  The Role of GABA in Human Motor Learning.
Current Biology. 21(6), 480 - 484.

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Hippocampal volume and PTSD

April, 2011

A new study supports the association between hippocampal size and recovery from PTSD, pointing to the role of neurogenesis in stress resilience.

Following previous research suggesting that the volume of the hippocampus was reduced in some people with chronic PTSD, a twin study indicated that this may not be simply a sign that stress has shrunk the hippocampus, but that those with a smaller hippocampus are at greater risk of PTSD. Now a new study has found that Gulf War veterans who recovered from PTSD had, on average, larger hippocampi than veterans who still suffer from PTSD. Those who recovered had hippocampi of similar size to control subjects who had never had PTSD.

The study involved 244 Gulf War veterans, of whom 82 had lifetime PTSD, 44 had current PTSD, and 38 had current depression.

Because we don’t know hippocampal size prior to trauma, the findings don’t help us decide whether hippocampal size is a cause or an effect (or perhaps it would be truer to say, don’t help us decide the relative importance of these factors, because it seems most plausible that both are significant).

The really important question, of course, is whether an effective approach to PTSD treatment would be to work on increasing hippocampal volume. Exercise and mental stimulation, for example, are known to increase the creation of new brain cells in the hippocampus. In this case, the main mediator is probably the negative effects of stress (which reduces neurogenesis). There is some evidence that antidepressant treatment might increase hippocampal volume in people with PTSD.

The other conclusion we can derive from these findings is that perhaps we should not simply think of building hippocampal volume / creating new brain cells as a means of building cognitive reserve, thus protecting us from cognitive decline and dementia. We should also think of it as a means of improving our emotional resilience and protecting us from the negative effects of stress and trauma.

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Fluency heuristic is not everyone’s rule

April, 2011

Two experiments indicate that judgment about how well something is learned is based on encoding fluency only for people who believe intelligence is a fixed attribute.

It’s well-established that feelings of encoding fluency are positively correlated with judgments of learning, so it’s been generally believed that people primarily use the simple rule, easily learned = easily remembered (ELER), to work out whether they’re likely to remember something (as discussed in the previous news report). However, new findings indicate that the situation is a little more complicated.

In the first experiment, 75 English-speaking students studied 54 Indonesian-English word pairs. Some of these were very easy, with the English words nearly identical to their Indonesian counterpart (e.g, Polisi-Police); others required more effort but had a connection that helped (e.g, Bagasi-Luggage); others were entirely dissimilar (e.g., Pembalut-Bandage).

Participants were allowed to study each pair for as long as they liked, then asked how confident they were about being able to recall the English word when supplied the Indonesian word on an upcoming test. They were tested at the end of their study period, and also asked to fill in a questionnaire which assessed the extent to which they believed that intelligence is fixed or changeable.

It’s long been known that theories of intelligence have important effects on people's motivation to learn. Those who believe each person possesses a fixed level of intelligence (entity theorists) tend to disengage when something is challenging, believing that they’re not up to the challenge. Those who believe that intelligence is malleable (incremental theorists) keep working, believing that more time and effort will yield better results.

The study found that those who believed intelligence is fixed did indeed follow the ELER heuristic, with their judgment of how well an item was learned nicely matching encoding fluency.

However those who saw intelligence as malleable did not follow the rule, but rather seemed to be following the reverse heuristic: that effortful encoding indicates greater engagement in learning, and thus is a sign that they are more likely to remember. This group therefore tended to be marginally underconfident of easy items, marginally overconfident for medium-level items, and significantly overconfident for difficult items.

However, the entanglement of item difficulty and encoding fluency weakens this finding, and accordingly a second experiment separated these two attributes.

In this experiment, 41 students were presented with two lists of nine words, one list of which was in small font (18-point Arial) and one in large font (48-point Arial). Each word was displayed for four seconds. While font size made no difference to their actual levels of recall, entity theorists were much more confident of recalling the large-size words than the small-size ones. The incremental theorists were not, however, affected by font-size.

It is suggested that the failure to find evidence of a ‘non-fluency heuristic’ in this case may be because participants had no control over learning time, therefore were less able to make relative judgments of encoding effort. Nevertheless, the main finding, that people varied in their use of the fluency heuristic depending on their beliefs about intelligence, was clear in both cases.

Reference: 

[2182] Miele, D. B., Finn B., & Molden D. C.
(2011).  Does Easily Learned Mean Easily Remembered?.
Psychological Science. 22(3), 320 - 324.

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