Skill Memory

We say so blithely that children learn by copying, but a recent study comparing autistic children and normally-developing ones shows there’s more to this than is obvious.

The study, involving 31 children with ASD, 30 typically developing children matched for language skills, and 30 typically developing age-matched children, had the children watch an adult model how to perform a simple action. The demonstration included two vital actions and one superfluous action. The child was then asked to undertake the same task (without mentioning any need to copy all of the actions of the adult exactly as they had seen them).

Almost all children (97%) successfully managed the task, but while typical children copied 43-57% of the unnecessary actions, autistic children copied only 22%. This despite the fact that, when shown the demonstration again and asked to judge whether each action was “sensible” or “silly,” the children (and especially typical children) had no trouble recognizing the unnecessary actions as silly.

In other words, it’s not about reasoning ability, it’s about social motivation. Typical children want to please adults and ‘fit in’, so they copy even the silly actions. Autistic children care less about this.

The findings point to the social nature of copying behavior — it’s not simply about learning.

http://www.futurity.org/society-culture/kids-with-autism-mimic-%e2%80%98more-efficiently%e2%80%99/

[3360] Marsh L, Pearson A, Ropar D, Hamilton A. Children with autism do not overimitate. Current Biology [Internet]. 2013 ;23(7):R266 - R268. Available from: http://www.cell.com/current-biology/abstract/S0960-9822(13)00207-8

I reported recently on how easily and quickly we can get derailed from a chain of thought (or action). In similar vein, here’s another study that shows how easy it is to omit important steps in an emergency, even when you’re an expert — which is why I’m a great fan of checklists.

Checklists have been shown to dramatically decrease the chances of an error, in areas such as flying and medicine. However, while surgeons may use checklists as a matter of routine (a study a few years ago found that the use of routine checklists before surgery substantially reduced the chances of a serious complication — we can hope that everyone’s now on board with that!), there’s a widespread belief in medicine that operating room crises are too complex for a checklist to be useful. A new study contradicts that belief.

The study involved 17 operating room teams (anesthesia staff, operating room nurses, surgical technologists, a surgeon), who participated in 106 simulated surgical crisis scenarios in a simulated operating room. Each team was randomized to manage half of the scenarios with a set of crisis checklists and the remaining scenarios from memory alone.

When checklists were used, the teams were 74% less likely to miss critical steps. That is, without a checklist, nearly a quarter (23%) of the steps were omitted (an alarming figure!), while with a checklist, only 6% of the steps were omitted on average. Every team performed better when the checklists were available.

After experiencing these situations, almost all (97%) participants said they would want these checklists used if they experienced such a crisis if they were a patient.

It’s comforting to know that airline pilots do have checklists to use in emergency situations. Now we must hope that hospitals come on board with this as well (up-to-date checklists and implementation materials can be found at www.projectcheck.org/crisis).

For the rest of us, the study serves as a reminder that, however practiced we may think we are, forgetting steps in an action plan is only too common, and checklists are an excellent means of dealing with this — in emergency and out.

We know that stress has a complicated relationship with learning, but in general its effect is negative, and part of that is due to stress producing anxious thoughts that clog up working memory. A new study adds another perspective to that.

The brain scanning study involved 60 young adults, of whom half were put under stress by having a hand immersed in ice-cold water for three minutes under the supervision of a somewhat unfriendly examiner, while the other group immersed their hand in warm water without such supervision (cortisol and blood pressure tests confirmed the stress difference).

About 25 minutes after this (cortisol reaches peak levels around 25 minutes after stress), participants’ brains were scanned while participants alternated between a classification task and a visual-motor control task. The classification task required them to look at cards with different symbols and learn to predict which combinations of cards announced rain and which sunshine. Afterward, they were given a short questionnaire to determine their knowledge of the task. The control task was similar but there were no learning demands (they looked at cards on the screen and made a simple perceptual decision).

In order to determine the strategy individuals used to do the classification task, ‘ideal’ performance was modeled for four possible strategies, of which two were ‘simple’ (based on single cues) and two ‘complex’ (based on multiple cues).

Here’s the interesting thing: while both groups were successful in learning the task, the two groups learned to do it in different ways. Far more of the non-stressed group activated the hippocampus to pursue a simple and deliberate strategy, focusing on individual symbols rather than combinations of symbols. The stressed group, on the other hand, were far more likely to use the striatum only, in a more complex and subconscious processing of symbol combinations.

The stressed group also remembered significantly fewer details of the classification task.

There was no difference between the groups on the (simple, perceptual) control task.

In other words, it seems that stress interferes with conscious, purposeful learning, causing the brain to fall back on more ‘primitive’ mechanisms that involve procedural learning. Striatum-based procedural learning is less flexible than hippocampus-based declarative learning.

Why should this happen? Well, the non-conscious procedural learning going on in the striatum is much less demanding of cognitive resources, freeing up your working memory to do something important — like worrying about the source of the stress.

Unfortunately, such learning will not become part of your more flexible declarative knowledge base.

The finding may have implications for stress disorders such as depression, addiction, and PTSD. It may also have relevance for a memory phenomenon known as “forgotten baby syndrome”, in which parents forget their babies in the car. This may be related to the use of non-declarative memory, because of the stress they are experiencing.

[3071] Schwabe L, Wolf OT. Stress Modulates the Engagement of Multiple Memory Systems in Classification Learning. The Journal of Neuroscience [Internet]. 2012 ;32(32):11042 - 11049. Available from: http://www.jneurosci.org/content/32/32/11042

I’ve reported before on how London taxi drivers increase the size of their posterior hippocampus by acquiring and practicing ‘the Knowledge’ (but perhaps at the expense of other functions). A new study in similar vein has looked at the effects of piano tuning expertise on the brain.

The study looked at the brains of 19 professional piano tuners (aged 25-78, average age 51.5 years; 3 female; 6 left-handed) and 19 age-matched controls. Piano tuning requires comparison of two notes that are close in pitch, meaning that the tuner has to accurately perceive the particular frequency difference. Exactly how that is achieved, in terms of brain function, has not been investigated until now.

The brain scans showed that piano tuners had increased grey matter in a number of brain regions. In some areas, the difference between tuners and controls was categorical — that is, tuners as a group showed increased gray matter in right hemisphere regions of the frontal operculum, the planum polare, superior frontal gyrus, and posterior cingulate gyrus, and reduced gray matter in the left hippocampus, parahippocampal gyrus, and superior temporal lobe. Differences in these areas didn’t vary systematically between individual tuners.

However, tuners also showed a marked increase in gray matter volume in several areas that was dose-dependent (that is, varied with years of tuning experience) — the anterior hippocampus, parahippocampal gyrus, right middle temporal and superior temporal gyrus, insula, precuneus, and inferior parietal lobe — as well as an increase in white matter in the posterior hippocampus.

These differences were not affected by actual chronological age, or, interestingly, level of musicality. However, they were affected by starting age, as well as years of tuning experience.

What these findings suggest is that achieving expertise in this area requires an initial development of active listening skills that is underpinned by categorical brain changes in the auditory cortex. These superior active listening skills then set the scene for the development of further skills that involve what the researchers call “expert navigation through a complex soundscape”. This process may, it seems, involve the encoding and consolidating of precise sound “templates” — hence the development of the hippocampal network, and hence the dependence on experience.

The hippocampus, apart from its general role in encoding and consolidating, has a special role in spatial navigation (as shown, for example, in the London cab driver studies, and the ‘parahippocampal place area’). The present findings extend that navigation in physical space to the more metaphoric one of relational organization in conceptual space.

The more general message from this study, of course, is confirmation for the role of expertise in developing specific brain regions, and a reminder that this comes at the expense of other regions. So choose your area of expertise wisely!

Back when I was young, sleep learning was a popular idea. The idea was that a tape would play while you were asleep, and learning would seep into your brain effortlessly. It was particularly advocated for language learning. Subsequent research, unfortunately, rejected the idea, and gradually it has faded (although not completely). Now a new study may presage a come-back.

In the study, 16 young adults (mean age 21) learned how to ‘play’ two artificially-generated tunes by pressing four keys in time with repeating 12-item sequences of moving circles — the idea being to mimic the sort of sensorimotor integration that occurs when musicians learn to play music. They then took a 90-minute nap. During slow-wave sleep, one of the tunes was repeatedly played to them (20 times over four minutes). After the nap, participants were tested on their ability to play the tunes.

A separate group of 16 students experienced the same events, but without the playing of the tune during sleep. A third group stayed awake, during which 90-minute period they played a demanding working memory task. White noise was played in the background, and the melody was covertly embedded into it.

Consistent with the idea that sleep is particularly helpful for sensorimotor integration, and that reinstating information during sleep produces reactivation of those memories, the sequence ‘practiced’ during slow-wave sleep was remembered better than the unpracticed one. Moreover, the amount of improvement was positively correlated with the proportion of time spent in slow-wave sleep.

Among those who didn’t hear any sounds during sleep, improvement likewise correlated with the proportion of time spent in slow-wave sleep. The level of improvement for this group was intermediate to that of the practiced and unpracticed tunes in the sleep-learning group.

The findings add to growing evidence of the role of slow-wave sleep in memory consolidation. Whether the benefits for this very specific skill extend to other domains (such as language learning) remains to be seen.

However, another recent study carried out a similar procedure with object-location associations. Fifty everyday objects were associated with particular locations on a computer screen, and presented at the same time with characteristic sounds (e.g., a cat with a meow and a kettle with a whistle). The associations were learned to criterion, before participants slept for 2 hours in a MR scanner. During slow-wave sleep, auditory cues related to half the learned associations were played, as well as ‘control’ sounds that had not been played previously. Participants were tested after a short break and a shower.

A difference in brain activity was found for associated sounds and control sounds — associated sounds produced increased activation in the right parahippocampal cortex — demonstrating that even in deep sleep some sort of differential processing was going on. This region overlapped with the area involved in retrieval of the associations during the earlier, end-of-training test. Moreover, when the associated sounds were played during sleep, parahippocampal connectivity with the visual-processing regions increased.

All of this suggests that, indeed, memories are being reactivated during slow-wave sleep.

Additionally, brain activity in certain regions at the time of reactivation (mediotemporal lobe, thalamus, and cerebellum) was associated with better performance on the delayed test. That is, those who had greater activity in these regions when the associated sounds were played during slow-wave sleep remembered the associations best.

The researchers suggest that successful reactivation of memories depends on responses in the thalamus, which if activated feeds forward into the mediotemporal lobe, reinstating the memories and starting the consolidation process. The role of the cerebellum may have to do with the procedural skill component.

The findings are consistent with other research.

All of this is very exciting, but of course this is not a strategy for learning without effort! You still have to do your conscious, attentive learning. But these findings suggest that we can increase our chances of consolidating the material by replaying it during sleep. Of course, there are two practical problems with this: the material needs an auditory component, and you somehow have to replay it at the right time in your sleep cycle.

A review of 10 observational and four intervention studies as said to provide strong evidence for a positive relationship between physical activity and academic performance in young people (6-18). While only three of the four intervention studies and three of the 10 observational studies found a positive correlation, that included the two studies (one intervention and one observational) that researchers described as “high-quality”.

An important feature of the high-quality studies was that they used objective measures of physical activity, rather than students' or teachers' reports. More high-quality studies are clearly needed. Note that the quality score of the 14 studies ranged from 22%! to 75%.

Interestingly, a recent media report (NOT, I hasten to add, a peer-reviewed study appearing in an academic journal) spoke of data from public schools in Lincoln, Nebraska, which apparently has a district-wide physical-fitness test, which found that those were passed the fitness test were significantly more likely to also pass state reading and math tests.

Specifically, data from the last two years apparently shows that 80% of the students who passed the fitness test either met or exceeded state standards in math, compared to 66% of those who didn't pass the fitness test, and 84% of those who passed the fitness test met or exceeded state standards in reading, compared to 71% of those who failed the fitness test.

Another recent study looks at a different aspect of this association between physical exercise and academic performance.

The Italian study involved138 normally-developing children aged 8-11, whose attention was tested before and after three different types of class: a normal academic class; a PE class focused on cardiovascular endurance and involving continuous aerobic circuit training followed by a shuttle run exercise; a PE class combining both physical and mental activity by involving novel use of basketballs in varying mini-games that were designed to develop coordination and movement-based problem-solving. These two types of physical activity offered the same exercise intensity, but very different skill demands.

The attention test was a short (5-minute) paper-and-pencil task in which the children had to mark each occurrence of “d” with double quotation marks either above or below in 14 lines of randomly mixed p and d letters with one to four single and/or double quotation marks either over and/or under each letter.

Processing speed increased 9% after mental exercise (normal academic class) and 10% after physical exercise. These were both significantly better than the increase of 4% found after the combined physical and mental exertion.

Similarly, scores on the test improved 13% after the academic class, 10% after the standard physical exercise, and only 2% after the class combining physical and mental exertion.

Now it’s important to note is that this is of course an investigation of the immediate arousal benefits of exercise, rather than an investigation of the long-term benefits of being fit, which is a completely different question.

But the findings do bear on the use of PE classes in the school setting, and the different effects that different types of exercise might have.

First of all, there’s the somewhat surprising finding that attention was at least as great, if not better, after an academic class than the PE class. It would not have been surprising if attention had flagged. It seems likely that what we are seeing here is a reflection of being in the right head-space — that is, the advantage of continuing with the same sort of activity.

But the main finding is the, also somewhat unexpected, relative drop in attention after the PE class that combined mental and physical exertion.

It seems plausible that the reason for this lies in the cognitive demands of the novel activity, which is, I think, the main message we should take away from this study, rather than any comparison between physical and mental activity. However, it would not be surprising if novel activities that combine physical and mental skills tend to be more demanding than skills that are “purely” (few things are truly pure I know) one or the other.

Of course, it shouldn’t be overlooked that attention wasn’t hampered by any of these activities!

Previous research has found that carriers of the so-called KIBRA T allele have been shown to have better episodic memory than those who don’t carry that gene variant (this is a group difference; it doesn’t mean that any carrier will remember events better than any non-carrier). A large new study confirms and extends this finding.

The study involved 2,230 Swedish adults aged 35-95. Of these, 1040 did not have a T allele, 932 had one, and 258 had two.  Those who had at least one T allele performed significantly better on tests of immediate free recall of words (after hearing a list of 12 words, participants had to recall as many of them as they could, in any order; in some tests, there was a concurrent sorting task during presentation or testing).

There was no difference between those with one T allele and those with two. The effect increased with increasing age. There was no effect of gender. There was no significant effect on performance of delayed category cued recall tests or a visuospatial task, although a trend in the appropriate direction was evident.

It should also be noted that the effect on immediate recall, although statistically significant, was not large.

Brain activity was studied in a subset of this group, involving 83 adults aged 55-60, plus another 64 matched on sex, age, and performance on the scanner task. A further group of 113 65-75 year-olds were included for comparison purposes. While in the scanner, participants carried out a face-name association task. Having been presented with face-name pairs, participants were tested on their memory by being shown the faces with three letters, of which one was the initial letter of the name.

Performance on the scanner task was significantly higher for T carriers — but only for the 55-60 age group, not for the 65-75 age group. Activity in the hippocampus was significantly higher for younger T carriers during retrieval, but not encoding. No such difference was seen in the older group.

This finding is in contrast with an earlier, and much smaller, study involving 15 carriers and 15 non-carriers, which found higher activation of the hippocampus in non-T carriers. This was taken at the time to indicate some sort of compensatory activity. The present finding challenges that idea.

Although higher hippocampal activation during retrieval is generally associated with faster retrieval, the higher activity seen in T carriers was not fully accounted for by performance. It may be that such activity also reflects deeper processing.

KIBRA-T carriers were neither more nor less likely to carry other ‘memory genes’ — APOEe4; COMTval158met; BDNFval66met.

The findings, then, fail to support the idea that non-carriers engage compensatory mechanisms, but do indicate that the KIBRA-T gene helps episodic memory by improving the hippocampus function.

BDNF gene variation predicts rate of age-related decline in skilled performance

In another study, this time into the effects of the BDNF gene, performance on an airplane simulation task on three annual occasions was compared. The study involved 144 pilots, of whom all were healthy Caucasian males aged 40-69, and 55 (38%) of whom turned out to have at least one copy of a BDNF gene that contained the ‘met’ variant. This variant is less common, occurring in about one in three Asians, one in four Europeans and Americans, and about one in 200 sub-Saharan Africans.  

While performance dropped with age for both groups, the rate of decline was much steeper for those with the ‘met’ variant. Moreover, there was a significant inverse relationship between age and hippocampal size in the met carriers — and no significant correlation between age and hippocampal size in the non-met carriers.

Comparison over a longer time-period is now being undertaken.

The finding is more evidence for the value of physical exercise as you age — physical activity is known to increase BDNF levels in your brain. BDNF levels tend to decrease with age.

The met variant has been linked to higher likelihood of depression, stroke, anorexia nervosa, anxiety-related disorders, suicidal behavior and schizophrenia. It differs from the more common ‘val’ variant in having methionine rather than valine at position 66 on this gene. The BDNF gene has been remarkably conserved across evolutionary history (fish and mammalian BDNF have around 90% agreement), suggesting that mutations in this gene are not well tolerated.

Trying to learn two different things one after another is challenging. Almost always some of the information from the first topic or task gets lost. Why does this happen? A new study suggests the problem occurs when the two information-sets interact, and demonstrates that disrupting that interaction prevents interference. (The study is a little complicated, but bear with me, or skip to the bottom for my conclusions.)

In the study, young adults learned two memory tasks back-to-back: a list of words, and a finger-tapping motor skills task. Immediately afterwards, they received either sham stimulation or real transcranial magnetic stimulation to the dorsolateral prefrontal cortex or the primary motor cortex. Twelve hours later the same day, they were re-tested.

As expected from previous research, word recall (being the first-learned task) declined in the control condition (sham stimulation), and this decline correlated with initial skill in the motor task. That is, the better they were at the second task, the more they forgot from the first task. This same pattern occurred among those whose motor cortex had been stimulated. However, there was no significant decrease in word recall for those who had received TMS to the dorsolateral prefrontal cortex.

Learning of the motor skill didn't differ between the three groups, indicating that this effect wasn't due to a disruption of the second task. Rather, it seems that the two tasks were interacting, and TMS to the DLPFC disrupted that interaction. This hypothesis was supported when the motor learning task was replaced by a motor performance task, which shouldn’t interfere with the word-learning task (the motor performance task was almost identical to the motor learning task except that it didn’t have a repeating sequence that could be learned). In this situation, TMS to the DLPFC produced a decrease in word recall (as it did in the other conditions, and as it would after a word-learning task without any other task following).

In the second set of experiments, the order of the motor and word tasks was reversed. Similar results occurred, with this time stimulation to the motor cortex being the effective intervention. In this case, there was a significant increase in motor skill on re-testing — which is what normally happens when a motor skill is learned on its own, without interference from another task (see my blog post on Mempowered for more on this). The word-learning task was then replaced with a vowel-counting task, which produced a non-significant trend toward a decrease in motor skill learning when TMS was applied to the motor cortex.

The effect of TMS depends on the activity in the region at the time of application. In this case, TMS was applied to the primary motor cortex and the DLPFC in the right hemisphere, because the right hemisphere is thought to be involved in integrating different types of information. The timing of the stimulation was critical: not during learning, and long before testing. The timing was designed to maximize any effects on interference between the two tasks.

The effect in this case mimics that of sleep — sleeping between tasks reduces interference between them. It’s suggested that both TMS and sleep reduce interference by reducing the communication between the prefrontal cortex and the mediotemporal lobe (of which the hippocampus is a part).

Here’s the problem: we're consolidating one set of memories while encoding another. So, we can do both at the same time, but as with any multitasking, one task is going to be done better than the other. Unsurprisingly, encoding appears to have priority over consolidation.

So something needs to regulate the activity of these two concurrent processes. Maybe something looks for commonalities between two actions occurring at the same time — this is, after all, what we’re programmed to do: we link things that occur together in space and time. So why shouldn’t that occur at this level too? Something’s just happened, and now something else is happening, and chances are they’re connected. So something in our brain works on that.

If the two events/sets of information are connected, that’s a good thing. If they’re not, we get interference, and loss of data.

So when we apply TMS to the prefrontal cortex, that integrating processor is perhaps disrupted.

The situation may be a little different where the motor task is followed by the word-list, because motor skill consolidation (during wakefulness at least) may not depend on the hippocampus (although declarative encoding does). However, the primary motor cortex may act as a bridge between motor skills and declarative memories (think of how we gesture when we explain something), and so it may this region that provides a place where the two types of information can interact (and thus interfere with each other).

In other words, the important thing appears to be whether consolidation of the first task occurs in a region where the two sets of information can interact. If it does, and assuming you don’t want the two information-sets to interact, then you want to disrupt that interaction.

Applying TMS is not, of course, a practical strategy for most of us! But the findings do suggest an approach to reducing interference. Sleep is one way, and even brief 20-minute naps have been shown to help learning. An intriguing speculation (I just throw this out) is that meditation might act similarly (rather like a sorbet between courses, clearing the palate).

Failing a way to disrupt the interaction, you might take this as a warning that it’s best to give your brain time to consolidate one lot of information before embarking on an unrelated set — even if it's in what appears to be a completely unrelated domain. This is particularly so as we get older, because consolidation appears to take longer as we age. For children, on the other hand, this is not such a worry. (See my blog post on Mempowered for more on this.)

[2338] Cohen DA, Robertson EM. Preventing interference between different memory tasks. Nat Neurosci [Internet]. 2011 ;14(8):953 - 955. Available from: http://dx.doi.org/10.1038/nn.2840

Working memory capacity and level of math anxiety were assessed in 73 undergraduate students, and their level of salivary cortisol was measured both before and after they took a stressful math test.

For those students with low working memory capacity, neither cortisol levels nor math anxiety made much difference to their performance on the test. However, for those with higher WMC, the interaction of cortisol level and math anxiety was critical. For those unafraid of math, the more their cortisol increased during the test, the better they performed; but for those anxious about math, rising cortisol meant poorer performance.

It’s assumed that low-WMC individuals were less affected because their performance is lower to start with (this shouldn’t be taken as an inevitability! Low-WMC students are disadvantaged in a domain like math, but they can learn strategies that compensate for that problem). But the effect on high-WMC students demonstrates how our attitude and beliefs interact with the effects of stress. We may all have the same physiological responses, but we interpret them in different ways, and this interpretation is crucial when it comes to ‘higher-order’ cognitive functions.

Another study investigated two theories as why people choke under pressure: (a) they’re distracted by worries about the situation, which clog up their working memory; (b) the stress makes them pay too much attention to their performance and become self-conscious. Both theories have research backing from different domains — clearly the former theory applies more to the academic testing environment, and the latter to situations involving procedural skill, where explicit attention to the process can disrupt motor sequences that are largely automatic.

But it’s not as simple as one effect applying to the cognitive domain, and one to the domain of motor skills, and it’s a little mysterious why pressure could have too such opposite effects (drawing attention away, or toward). This new study carried out four experiments in order to define more precisely the characteristics of the environment that lead to these different effects, and suggest solutions to the problem.

In the first experiment, participants were given a category learning task, in which some categories had only one relevant dimension and could be distinguished according to one easily articulated rule, and others involved three relevant dimensions and one irrelevant one. Categorization in this case was based on a complex rule that would be difficult to verbalize, and so participants were expected to integrate the information unconsciously.

Rule-based category learning was significantly worse when participants were also engaged in a secondary task requiring them to monitor briefly appearing letters. However it was not affected when their secondary task involved them explicitly monitoring the categorization task and making a confidence judgment. On the other hand, the implicit category learning task was not disrupted by the letter-monitoring task, but was impaired by the confidence-judgment task. Further analysis revealed that participants who had to do the confidence-judgment task were less likely to use the best strategy, but instead persisted in trying to verbalize a one- or two-dimension rule.

In the second experiment, the same tasks were learned in a low-pressure baseline condition followed by either a low-pressure control condition or one of two high-pressure conditions. One of these revolved around outcome — participants would receive money for achieving a certain level of improvement in their performance. The other put pressure on the participants through monitoring — they were watched and videotaped, and told their performance would be viewed by other students and researchers.

Rule-based category learning was slower when the pressure came from outcomes, but not when the pressure came from monitoring. Implicit category learning was unaffected by outcome pressure, but worsened by monitoring pressure.

Both high-pressure groups reported the same levels of pressure.

Experiment 3 focused on the detrimental combinations — rule-based learning under outcome pressure; implicit learning under monitoring pressure — and added the secondary tasks from the first experiment.

As predicted, rule-based categories were learned more slowly during conditions of both outcome pressure and the distracting letter-monitoring task, but when the secondary task was confidence-judgment, the negative effect of outcome pressure was counteracted and no impairment occurred. Similarly, implicit category learning was slowed when both monitoring pressure and the confidence-judgment distraction were applied, but was unaffected when monitoring pressure was counterbalanced by the letter task.

The final experiment extended the finding of the second experiment to another domain — procedural learning. As expected, the motor task was significantly affected by monitoring pressure, but not by outcome pressure.

These findings suggest two different strategies for dealing with choking, depending on the situation and the task. In the case of test-taking, good test preparation and a writing exercise can boost performance by reducing anxiety and freeing up working memory. If you're worried about doing well in a game or giving a memorized speech in front of others, you instead want to distract yourself so you don't become focused on the details of what you're doing.

Laparoscopic surgery makes intense demands on cognitive, perceptual and visuospatial abilities, rendering it particularly vulnerable to the effects of alcohol (and also making it a sensitive indicator). In a real-world type experiment, students and experts participated in a study looking at the effects of previous-night’s carousing on next-day’s performance on the Minimally Invasive Surgical Trainer Virtual Reality (for which all participants received training, providing baseline scores).

The first experiment involved 16 male final-year science students, of whom 8 were asked to consume alcohol freely at a group dinner, while the other 8 went to a dinner at which no alcohol was served. The second experiment involved eight laparoscopic experts, all of whom were asked to consume alcohol freely at their group dinner. Participants were tested on the simulator the next day at 9:00 a.m., 1:00 p.m. and 4:00 p.m.

Among the students, those who had consumed excessive alcohol performed considerably worse in terms of time, errors and economy of diathermy (ability to perform technique designed to produce local application of heat), and showed considerable performance variability. Their performance in terms of errors and diathermy was significantly impaired compared to that of the control group. Differences in the time it took participants to perform the tasks were only significant at 9:00 a.m.

Experts were (thankfully!) less impaired by their night out. Nevertheless, they made more errors than they had at baseline, and the difference at 1:00 p.m. was statistically significant. They were also significantly slower during the 1:00 p.m. tests. Performance had returned to baseline levels by 4:00 p.m.

The mental differences between a novice and an expert are only beginning to be understood, but two factors thought to be of importance are automaticity (the process by which a procedure becomes so practiced that it no longer requires conscious thought) and chunking (the unitizing of related bits of information into one tightly integrated unit — see my recent blog post on working memory). A new study adds to our understanding of this process by taking images of the brains of professional and amateur players of the Japanese chess-like game of shogi.

Eleven professional, 9 high- and 8 low-rank amateur players of shogi were presented with patterns of different types (opening shogi patterns, endgame shogi patterns, random shogi patterns, chess, Chinese chess, as well as completely different stimuli — scenes, faces, other objects, scrambled patterns).

It was found that the board game patterns, but not the other patterns, stimulated activity in the posterior precuneus of all shogi players. This activity, for the professional players, was particularly strong for shogi opening and endgame patterns, and activity in the precuneus was the only regional activity that showed a difference between these patterns and the other board game patterns. For the amateurs however, there was no differential activity for the endgame patterns, and only the high-rank amateurs showed differential activity for the opening shogi patterns. Opening patterns tend to be more stereotyped than endgame patterns (i.e., endgame patterns are better reflections of expertise).

The players were then asked for the best next-move in a series of shogi problems (a) when they only had one second to study the pattern, and (b) when they had eight seconds. When professional players had only a second to study the problem, the caudate nucleus was active. When they had 8 seconds, activity was confined to the cerebral cortex, as it was for the amateurs in both conditions. This activity in the caudate, which is part of the basal ganglia, deep within the brain, is thought to reflect the development of an intuitive response.

The researchers therefore suggest that this type of intuition, an instinct achieved through training and experience, is what marks an expert. Making part of the process unconscious not only makes it faster, but frees up valuable space in working memory for aspects that need conscious thought.

The posterior precuneus directly connects with the dorsolateral prefrontal cortex, which in turn connects to the caudate. There is also a direct connection between the precuneus and the caudate. This precuneus-caudate circuit is therefore suggested as a key part of what makes a board-game expert an expert.

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.

Two experiments involving a total of 191 volunteers have investigated the parameters of sleep’s effect on learning. In the first experiment, people learned 40 pairs of words, while in the second experiment, subjects played a card game matching pictures of animals and objects, and also practiced sequences of finger taps. In both groups, half the volunteers were told immediately following the tasks that they would be tested in 10 hours. Some of the participants slept during this time.

As expected, those that slept performed better on the tests (all of them: word recall, visuospatial, and procedural motor memory), but the really interesting bit is that it turned out it was only the people who slept who also knew a test was coming that had improved memory recall. These people showed greater brain activity during deep or "slow wave" sleep, and for these people only, the greater the activity during slow-wave sleep, the better their recall.

Those who didn’t sleep, however, were unaffected by whether they knew there would be a test or not.

Of course, this doesn’t mean you never remember things you don’t intend or want to remember! There is more than one process going on in the encoding and storing of our memories. However, it does confirm the importance of intention, and cast light perhaps on some of your learning failures.

In a recent study, volunteers were asked to solve a problem known as the Tower of Hanoi, a game in which you have to move stacked disks from one peg to another. Later, they were asked to explain how they did it (very difficult to do without using your hands.) The volunteers then played the game again. But for some of them, the weight of the disks had secretly reversed, so that the smallest disk was now the heaviest and needed two hands.

People who had used one hand in their gestures when talking about moving the small disk were in trouble when that disk got heavier. They took longer to complete the task than did people who used two hands in their gestures—and the more one-handed gestures they used, the longer they took.

For those who had not been asked to explain their solution (and replayed the game in the interval) were unaffected by the disk weights changing. So even though they had repeated the action with the original weights, they weren’t thrown by the unexpected changes in weights, as those who gestured with one hand were.

The findings add to the evidence that gestures make thought concrete. Related research has indicated that children can come to understand abstract concepts in mathematics and science more readily if they gesture (and perhaps if their teachers gesture).

[2043] Beilock SL, Goldin-Meadow S. Gesture Changes Thought by Grounding It in Action. Psychological Science [Internet]. 2010 ;21(11):1605 - 1610. Available from: http://pss.sagepub.com/content/21/11/1605.abstract

There are a number of ways experts think differently from novices (in their area of expertise). A new study involving 72 college-age typists with about 12 years of typing experience and typing speeds comparable to professional typists indicates that our idea that highly skilled activities operate at an unconscious level is a little more complex than we thought.

In three experiments, these skilled typists typed single words shown to them one at a time on a computer screen, while occasionally the researchers inserted errors in the words they typed, or corrected errors they made. When asked to report errors, typists took credit for corrected errors and accepted blame for inserted errors, claiming authorship for the appearance of the screen. Not surprising in the first experiment, when the typists weren’t told what the researchers were doing. But even in the later experiments, when they knew some of the errors and some of the corrections weren’t theirs, they still tended to take responsibility for what they saw.

Nevertheless, regardless of what they saw and what they thought, their typing rate wasn’t affected by inserted errors. Only when the typists themselves made errors, regardless of whether or not the researchers corrected them, did their fingers slow down.

In other words, it wasn’t the feedback of the look of the word on the screen that triggered the finger slow-down, but the ‘knowledge’ the fingers had as to what they had done.

But it was the appearance of the words on the screen that governed the typists’ reporting of errors, leading the researchers to propose two error detection processes: an outer loop that supports conscious reports and an inner loop process that slows keystrokes after errors.

Logan, G.D. & Crump, M.J.C. 2010. Cognitive Illusions of Authorship Reveal Hierarchical Error Detection in Skilled Typists. Science, 330 (6004), 683-686. http://www.sciencemag.org/content/330/6004/683.abstract?sid=140a96b9-ef5...

I’m not at all sure why the researcher says they were “stunned” by these findings, since it doesn’t surprise me in the least, but a series of experiments into the role of imagination in creating false memories has revealed that people who had watched a video of someone else doing a simple action often remembered doing the action themselves two weeks later. In fact in my book on remembering intentions, which includes a chapter on remembering whether you’ve done something, I mention the risk of imagining yourself doing something (that you then go on to believe you have actually done it), and given all the research on mirror neurons, it’s no big step to go from watching someone doing something to remembering that you did it. Nevertheless, it’s nice to get the confirmation.

The experiments involved participants performing several simple actions, such as shaking a bottle or shuffling a deck of cards. Then they watched videos of someone else doing simple actions—some of which they had performed themselves and some of which they hadn’t. Two weeks later, they were asked which actions they had done. They were much more likely to falsely remember doing an action if they had watched someone else do it — even when they had been warned about the effect.

It seems likely that this is an unfortunate side-effect of a very useful ability — namely our ability to learn motor skills by observing others (using the aforesaid mirror neurons) — and there’s probably not a great deal we can do to prevent it happening. It’s just a reminder of how easy it is to form false memories.

[1839] Lindner I, Echterhoff G, Davidson PSR, Brand M. Observation Inflation. Psychological Science [Internet]. 2010 ;21(9):1291 - 1299. Available from: http://pss.sagepub.com/content/21/9/1291.abstract

A new study explains why variable practice improves your memory of most skills better than practice focused on a single task. The study compared skill learning between those asked to practice one particular challenging arm movement, and those who practiced the movement with other related tasks in a variable practice structure. Using magnetic stimulation applied to different parts of the brain after training (which interferes with memory consolidation), it was found that interference to the dorsolateral prefrontal cortex, but not to the primary motor cortex, affected skill learning for those engaged in variable practice, whereas interference to the motor cortex, but not to the prefrontal cortex, affected learning in those engaged in constant practice.

These findings indicate that variable practice involves working memory (which happens in the prefrontal cortex) rather than motor memory, and that the need to re-engage with the task each time underlies the better learning produced by variable practice (which involves repeatedly switching between tasks). The experiment also helps set a time frame for this consolidation — interference four hours after training had no effect.

A new study challenges the popular theory that expertise is simply a product of tens of thousands of hours of deliberate practice. Not that anyone is claiming that this practice isn’t necessary — but it may not be sufficient. A study looking at pianists’ ability to sight-read music reveals working memory capacity helps sight-reading regardless of how much someone has practiced.

The study involved 57 volunteers who had played piano for an average of 18.6 years (range from one to 57 years). Their estimated hours of overall practice ranged from 260 to 31,096 (average: 5806), and hours of sight-reading practice ranged from zero to 9,048 (average: 1487 hours). Statistical analysis revealed that although hours of practice was the most important factor, nevertheless, working memory capacity did, independently, account for a small but significant amount of the variance between individuals.

It is interesting that not only did WMC have an effect independent of hours of practice, but hours of practice apparently had no effect on WMC — although the study was too small to tell whether a lot of practice at an early age might have affected WMC (previous research has indicated that music training can increase IQ in children).

The study is also too small to properly judge the effects of the 10,000 hours deliberate practice claimed necessary for expertise: the researchers did not advise the number of participants that were at that level, but the numbers suggest it was low.

It should also be noted that an earlier study involving 52 accomplished pianists found no effect of WMC on sight-reading ability (but did find a related effect: the ability to tap two fingers rapidly in alternation and to press a computer key quickly in response to visual and acoustic cues was unrelated to practice but correlated positively with good sight-readers).

Nevertheless, the findings are interesting, and do agree with what I imagine is the ‘commonsense’ view: yes, becoming an expert is all about the hours of effective practice you put in, but there are intellectual qualities that also matter. The question is: do they matter once you’ve put in the requisite hours of good practice?

A number of studies have shown the benefits of sleep for consolidating motor learning. A new study extends this research to a more complex motor task: "Guitar Hero III", a popular video game. There was significantly greater improvement after a night’s sleep (average 68% in performance accuracy vs 63% for students who learnt the task in the morning and were tested in the evening), and a significant correlation between sleep duration and the amount of improvement.

Higginson, C.D. et al. 2010. So you wanna be a rock star? Sleep on it. Presented at SLEEP 2010, the 24th annual meeting of the Associated Professional Sleep Societies LLC, in San Antonio, Texas.

A rat study has revealed that as the rats slowly learned a new rule, groups of neurons in the medial frontal cortex switched quite abruptly to a new pattern corresponding directly to the shift in behavior, rather than showing signs of gradual transition. Such sudden neural and behavioral transitions may correspond to so- called "a-ha" moments, and support the idea that rule learning is an evidence-based decision process, perhaps accompanied by moments of sudden insight.

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

How long does it take to form a habit?

A study involving 96 people who were interested in forming a new habit such as eating a piece of fruit with lunch or doing a 15 minute run each day has found that in the early days, daily repetition sharply increased automaticity (the ease with which you do it) and then reached a plateau. On average, habits took 66 days to become as automatic as they’d ever be. However, there was a very wide variation (18 to 254 days) depending on the nature of the habit (more difficult habits, such as doing 50 sit-ups a day, showed a slower rate of steadier increase). There was also variability among individuals, with some showing ‘habit-resistance’. The good news is that missing a single day did not reduce the chance of forming a habit. The findings also point to the value of getting off to a good start.

Lally, P., Jaarsveld, C. H. M. V., Potts, H. W. W., & Wardle, J. (2009). How are habits formed: Modelling habit formation in the real world. European Journal of Social Psychology, Published online ahead of print. doi: 10.1002/ejsp.674.

http://ow.ly/CGUt

Imagining is as good as doing

A series of experiments in which some participants practiced identifying which line a central line was closest to, while others simply imagined the bisecting line's proximity based on an audio tone, found that both methods produced similar levels of perceptual learning. It has (understandably) been assumed that perceptual learning requires stimulus processing -- synapses firing in response to an actual physical cue. But this demonstrates that mental imagery is sufficient. The finding adds to a growing number of studies suggesting that thinking about something over and over again can be almost as good as doing it.

Tartaglia, E.M., Bamert, L., Mast, F.W. & Herzog, M.H. 2009. Human Perceptual Learning by Mental Imagery. Current Biology, Published online ahead of print 3 December 2009. 

http://www.physorg.com/news179067145.html

Magnetic brain stimulation improves skill learning

A study in which volunteers were trained for four days to track an apparently random target on a computer screen, in which random movement was interspersed with a repeated pattern not consciously perceived by the participants, found that those who received excitatory transcranial magnetic stimulation to the left dorsal premotor cortex were significantly better at tracking the repeating pattern than those who received inhibitory stimulation or sham stimulation. The findings support the view that the dorsal premotor cortex is important for learning motor skills, specifically through consolidation of the learned behavior.

Boyd, L.A. & Linsdell, M.A. 2009. Excitatory repetitive transcranial magnetic stimulation to left dorsal premotor cortex enhances motor consolidation of new skills. BMC Neuroscience, 10, 72doi:10.1186/1471-2202-10-72.

http://www.eurekalert.org/pub_releases/2009-07/bc-mbs070309.php

Motor skill learning may be enhanced by mild brain stimulation

In a study in which subjects practiced a challenging motor task over five consecutive days, those who received 20 minutes of a mild electrical current to the primary motor cortex improved significantly more that that of the control group, apparently through an effect on consolidation. Although both groups subsequently forgot the skill at about the same rate, those who had received the electrical stimulation still performed better after 3 months because they had learned the skill better. The findings hold promise for enhancing rehabilitation for people with traumatic brain injury, stroke and other conditions.

Reis, J. et al. 2009. Noninvasive cortical stimulation enhances motor skill acquisition over multiple days through an effect on consolidation. PNAS, 106, 1590-1595.

http://www.eurekalert.org/pub_releases/2009-01/nion-msl011609.php

Why it’s so hard to disrupt your routine

New research has added to our understanding of why we find it so hard to break a routine or overcome bad habits. The problem lies in the competition between the striatum and the hippocampus. The striatum is involved with habits and routines, for example, it records cues or landmarks that lead to a familiar destination. It’s the striatum that enables you to drive familiar routes without much conscious awareness. If you’re travelling an unfamiliar route however, you need the hippocampus, which is much ‘smarter’.  The mouse study found that when the striatum was disrupted, the mice had trouble navigating using landmarks, but they were actually better at spatial learning. When the hippocampus was disrupted, the converse was true. This may help us understand, and treat, certain mental illnesses in which patients have destructive, habit-like patterns of behavior or thought. Obsessive-compulsive disorder, Tourette syndrome, and drug addiction all involve abnormal function of the striatum. Cognitive-behavioral therapy may be thought of as trying to learn to use one of these systems to overcome and, ultimately, to re-train the other.

Lee, A.S. et al. 2008. A double dissociation revealing bidirectional competition between striatum and hippocampus during learning. Proceedings of the National Academy of Sciences, 105 (44), 17163-17168.

http://www.eurekalert.org/pub_releases/2008-10/yu-ce102008.php

Over-thinking and motor skills

Skilled athletes often maintain that thinking too much about executing a skill disrupts their performance. Now a study of 80 golfers has found that intermediate-skilled golfers asked to verbally describe a new putt after learning it took twice as many goes to sink their putts as similarly experienced golfers who weren’t asked to put their learning into words. On the other hand, golfers of lower skill benefited from such verbalization. The effect is thought to be similar to verbal overshadowing, an effect previously demonstrated for taste and appearance, where, for example, trying to describe a face interferes with subsequent recognition of that face.

Flegal, K.E. & Anderson, M.C. 2008. Overthinking skilled motor performance: Or why those who teach can't do. Psychonomic Bulletin & Review, 15, 927-932. 

http://www.physorg.com/news145638602.html

Passive learning imprints on the brain just like active learning

New research adds to other recent studies showing that observation can act like actual practice in acquiring new motor skills. In a study where participants played a video game in which they had to move in a particular sequence to match the position of arrows on the screen (similar to the popular Dance Revolution game), it was found that brain activity in the Action Observance Network (mostly in the inferior parietal and premotor cortices) was similar for dance sequences that were actively rehearsed daily for five days, and a different set of sequences that were passively observed for an equivalent amount of time, but declined for unfamiliar sequences.

Cross, E.S. et al. 2008. Sensitivity of the Action Observation Network to Physical and Observational Learning. Cerebral Cortex, Advance Access published on May 30, 2008. doi:10.1093/cercor/bhn083

http://www.eurekalert.org/pub_releases/2008-07/dc-drr071408.php

Songbirds offer clues to highly practiced motor skills in humans

A study of singing in the Bengalese finch has revealed information about motor skills that may benefit human performers and people needing motor rehabilitation. The tune of songbirds is a complex skill, achieved over a long period of practice as juveniles, and culminating in a highly stereotyped, stable song. But it turns out to be not as fixed as was thought. Adult songbirds, it seems, rely on auditory feedback to maintain their song. This study found that providing disruptive auditory feedback to a subset of the vocalizations almost immediately produced an appropriately targeted change in the bird's song. The study also found that really big changes could also be produced, but it had to be done incrementally, in small steps.

Tumer, E.C. & Brainard, M.S. 2007. Performance variability enables adaptive plasticity of 'crystallized' adult birdsong. Nature, 450, 1240-1244.

http://www.eurekalert.org/pub_releases/2007-12/uoc--soc122107.php

Language center executive organizer of action plans

Broca's area is the region in the brain traditionally known as the ‘language center’, however recent research has broadened that understanding. The most recent study reveals that this region, and its counterpart in the right hemisphere, becomes active when people are asked to organize plans of action — an activity that we must now distinguish from a simple action sequence, which didn’t require these regions. These regions appear to implement a specialized executive system controlling the selection and nesting of action segments in a hierarchical structure of behavioral plans. This general executive function may explain Broca’s key role in language production.

Koechlin, E. & Jubault, T. 2006. Broca's Area and the Hierarchical Organization of Human Behavior. Neuron, 50, 963–974.

http://www.eurekalert.org/pub_releases/2006-06/cp-wtb060806.php

Planning is goal-, not action-, oriented

Studies in which monkeys were asked to perform a complex task involving several discrete steps have revealed that the brain's "executive" center, in the lateral prefrontal cortex, plans behaviors not by specifying movements required for given actions, but rather the events that will result from those actions.

Mushiake, H. et al. 2006. Activity in the Lateral Prefrontal Cortex Reflects Multiple Steps of Future Events in Action Plans. Neuron, 50, 631–641.

http://www.eurekalert.org/pub_releases/2006-05/cp-tbe051106.php

People can learn motor skills by watching

Sure we learn by doing, but we also learn by watching. Recent imaging studies have shown that when we observe the actions of others, we activate the same neural circuitry responsible for planning and executing our own actions. Now a new study has demonstrated that such observation can actually facilitate motor learning. This occurred even when observers were distracted by another task (doing arithmetic) while watching, indicating that the process does not require conscious awareness. However, although there was no sign of muscle activity during the observation, the beneficial effects of observing were significantly reduced when the subjects were asked to perform unrelated arm movements during observation.

Mattar, A.A.G. & Gribble, P.L. 2005. Motor Learning by Observing. Neuron, 46 (1), 153–160.

http://www.eurekalert.org/pub_releases/2005-04/cp-pcl040105.php

Brain prefers 'automatic pilot' during learning

When people are asked to perform a classification or decision on an object, they become more efficient with repetition of the task. When subject's brains are imaged during such tasks, they show reduced activity -- called "neural priming" -- as the task is learned and performance improves. New research suggests that rather than this being due to the cortex refining its knowledge about the object being learned about (eliminating attributes of the object not needed in the task), the cortex is instead just refining learning of a particular response. Thus we become more rapid with repetition of a decision task simply because we are recovering our prior responses.
In the study, participants were asked to judge whether objects such as an acorn, a stroller, a bicycle pump or a shuttlecock were "bigger than a shoebox." After practicing this task, they were then asked if the objects were "smaller than a shoebox." If the brain's representation of the size of the object is what is being rapidly recovered with repetition, just changing the direction of the question from a 'bigger than' to a 'smaller than' question should not make a difference in performance. If, however, the brain is recovering earlier responses, then changing the direction of the question will make a considerable difference to performance – which it did.

Dobbins, I.G., Schnyer, D.M., Verfaellie, M. & Schacter, D.L. 2004. Cortical activity reductions during repetition priming can result from rapid response learning. Nature, 428, 316-319 (18 Mar 2004) Letters to Nature

http://www.eurekalert.org/pub_releases/2004-03/du-est030804.php

Reading verbs activates motor cortex areas

A new imaging study has surprised researchers by revealing that parts of the motor cortex respond when people do nothing more active than silently reading. However, the words read have to be action words. When such words are read, appropriate regions are activated – for example, reading “lick” will trigger blood flow in sites of the motor cortex associated with tongue and mouth movements. Moreover, activity also occurs in premotor brain regions that influence learning of new actions, as well as the language structures, Broca's area and Wernicke's area. The researchers suggest that these findings challenge the assumption that word meanings are processed solely in language structures – instead, our understanding of words depends on the integration of information from several interconnected brain structures that provide information about associated actions and sensations.

Hauk, O., Johnsrude, I. & Pulvermüller, F. 2004. Somatotopic Representation of Action Words in Human Motor and Premotor Cortex. Neuron, 41, 301-7.

http://www.sciencenews.org/20040207/fob2.asp

Learning a sequence with explicit knowledge of that sequence involves same

Imaging studies have found that sequence learning accompanied with awareness of the sequence activates entirely different brain regions than learning without awareness of the sequence. It has not been clear to what extent these two forms of learning (declarative vs procedural) are independent. A new imaging study devised a situation where subjects were simultaneously learning different sequences under implicit or explicit instructions, in order to establish whether, as many have thought, declarative learning prevents learning in procedural memory systems. It was found that procedural learning activated the left prefrontal cortex, left inferior parietal cortex, and right putamen. These same regions were also active during declarative learning. It appears that, in a well-controlled situation where procedural and declarative learning are occurring simultaneously, the same neural network for procedural learning is active whether that learning is or is not accompanied by declarative knowledge. Declarative learning, however, activates many additional brain regions.

Willingham, D.B., Salidis, J. & Gabrieli, J.D.E. 2003. Direct Comparison of Neural Systems Mediating Conscious and Unconscious Skill Learning. Journal of Neurophysiology, 88, 1451-1460.

Brain anticipates events to learn routines

A new study may help explain why “cognitive” practice of physical actions can be useful (e.g., sportsmen or musicians mentally “practicing” their skills). The study using macaque monkeys found that neurons in the visual cortex were more active when the monkeys anticipated the occurrence of predictable events. "These results show that as we practice and anticipate which events are going to happen, the brain is also preparing itself."

Ghose, G.M. &Maunsell, J.H.R. 2002. Attentional modulation in visual cortex depends on task timing. Nature, 419: 6907, 616-9.

http://www.eurekalert.org/pub_releases/2002-10/bcom-bae100802.php

Improving motor skills through sleep

People taught a simple motor sequence (to type a sequence of keys on a computer keyboard as quickly and accurately as possible) practised it for 12 minutes and were then re-tested 12 hours later. Those who practised in the morning and tested later that same day improved their performance by about 2%. Those trained in the evening and re-tested after a good night's sleep, however, improved by about 20%. The amount of improvement was directly correlated with the amount of Stage 2 (a stage of non-rapid eye movement or NREM) sleep experienced, particularly late in the night. "This is the part of a good night's sleep that many people will cut short by getting up early in the morning."

Laureys, S., Peigneux, P., Perrin, F. & Maquet, P. 2002. Sleep and Motor Skill Learning. Neuron, 35, 5-7.

http://www.eurekalert.org/pub_releases/2002-07/hms-pmp070102.php

New research into motor skills distinguishes between learning and performance

The cerebellum has long been associated with motor skills and coordination. A new study has shown that, although it is active when we are engaging in movement, it is not active when we are learning new motor skills. The findings suggest the cerebellum is involved in the improvement in performance gained through practice, rather than the initial learning of the motor sequence. This research may lead to a better understanding that ultimately sees the development of better rehabilitation strategies for patients with cerebellar disease. It also points to an intriguing difference between learning a motor skill and improving it.

Seidler, R.D., Purushotham, A., Kim, S.-G., Ugurbil, K., Willingham, D. & Ashe, J. 2002. Cerebellum Activation Associated with Performance Change but Not Motor Learning. Science, 296 (5575), 2043-6.

http://www.eurekalert.org/pub_releases/2002-06/vrcs-sop061302.php

The neural basis for motor learning

Learning happens when a brain cell gets stimulated in a way that reduces its ability to respond to a particular brain messenger called glutamate. In the cerebellum there are very large, strangely shaped brain cells called Purkinje cells that receive more connections than other types of neurons and fire 50 times per second even when you're sleeping. These cells are involved in simple motor learning processes. A recent study provides support for an earlier study that found there are fewer receptors for glutamate on the surface of neurons during long-term synaptic depression, by demonstrating that the other three possible causes for this reduced response to glutamate do not occur.

Linden, D.J. 2001.The expression of cerebellar LTD in culture is not associated with changes in AMPA-receptor kinetics, agonist affinity, or unitary conductance. Proc. Natl. Acad. Sci. USA, 98 (24), 14066-14071.

New motor skills consolidated during sleep

An imaging study that sheds light on the gain in performance observed during the day after learning a new task. Following training in a motor skill, certain brain areas appear to be reactivated during REM sleep, resulting in an optimization of the network that subtends the subject's visuo–motor response.

Laureys, S., Peigneux, P., Phillips, C., Fuchs,S., Degueldre, C., Aerts, J., Del Fiore,G., Petiau, C., Luxen, A., Van der Linden, M., Cleeremans, A., Smith, C. & Maquet, P. (2001). Experience-dependent changes in cerebral functional connectivity during human rapid eye movement sleep [Letter to Neuroscience]. Neuroscience, 105 (3), 521-525.

http://tinyurl.com/ix9b