procedural memory

Even short periods of exercise help you learn and remember

  • A small study of young adults found that 10 minutes of light exercise improved memory for details and increased relevant brain activity.
  • Another study found that 15 minutes of more intense exercise after learning a new motor skill resulted in better skill performance a day later.

Ten minutes of light exercise boosts memory

Following rat studies, a study involving 36 healthy young adults has found that 10 minutes of light exercise (such as tai chi, yoga, or walking) significantly improved highly detailed memory processing and resulted in increased activity in the hippocampus.

It also boosted connectivity between the hippocampus and cortical regions that support detailed memory processing (parahippocampal, angular, and fusiform gyri), and the degree of improvement in this connectivity predicted the extent of this memory improvement for an individual.

The memory task involved remembering details of pictures of objects from everyday life, some of which were very similar to other pictures, requiring participants to distinguish between the different memories.

Mood change was also assessed, and the researchers ruled out this as a cause of the improved memory.

Exercise after learning helps you master new motor skills

Another recent study found that 15 minutes of cardiovascular exercise after learning a new motor skill resulted in better skill learning when tested a day later.

Exercise was also found to decrease desynchronization in beta brainwaves and increase their connectivity between hemispheres. The degree of improvement in skill learning reflected changes in beta-wave desynchronization. It appears that exercise helped the brain become more efficient in performing the skill.

The motor skill consisted of gripping an object akin to a gamers' joystick and using varying degrees of force to move a cursor up and down to connect red rectangles on a computer screen as quickly as possible.

Note that there was no difference between the two groups (those who exercised and those who didn’t) 8 hours after learning — the difference didn’t appear until after participants had slept. Sleep helps consolidate skill learning.


Suwabe, K. 2018. Rapid stimulation of human dentate gyrus function with acute mild exercise. Proceedings of the National Academy of Sciences Oct 2018, 115 (41) 10487-10492; DOI: 10.1073/pnas.1805668115

[4398] Dal Maso, F., Desormeau B., Boudrias M-H., & Roig M.
(2018).  Acute cardiovascular exercise promotes functional changes in cortico-motor networks during the early stages of motor memory consolidation.
NeuroImage. 174, 380 - 392.


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Kids with autism mimic ‘more efficiently’

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.



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Checklists dramatically reduce errors in operating room crises

February, 2013

A simulated study of life-threatening surgical crises has found that using a checklist reduced the omission of critical steps from 23% to 6%.

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

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.


[3262] Arriaga, A. F., Bader A. M., Wong J. M., Lipsitz S. R., Berry W. R., Ziewacz J. E., et al.
(2013).  Simulation-Based Trial of Surgical-Crisis Checklists.
New England Journal of Medicine. 368(3), 246 - 253.


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How stress affects your learning

October, 2012

A small study shows that stress makes it more likely for learning to use more complicated and subconscious processes that involve brain regions involved in habit and procedural learning.

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 O. T.
(2012).  Stress Modulates the Engagement of Multiple Memory Systems in Classification Learning.
The Journal of Neuroscience. 32(32), 11042 - 11049.


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How piano tuning changes the brain

September, 2012

In another example of how expertise in a specific area changes the brain, brain scans of piano tuners show which areas grow, and which shrink, with experience — and starting age.

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!



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Sleep learning making a comeback?

August, 2012

Two new studies provide support for the judicious use of sleep learning — as a means of reactivating learning that occurred during the day.

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.



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Support for link between physical activity & academic success

March, 2012

A review supports the benefits of physical activity for children’s and adolescent’s scholastic performance, but points to the need for better studies. A recent study looks at the effects on attention of different types of physical activity.

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!



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Memory genes vary in protecting against age-related cognitive decline

November, 2011

New findings show the T variant of the KIBRA gene improves episodic memory through its effect on hippocampal activity. Another study finds the met variant of the BDNF gene is linked to greater age-related cognitive decline.

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.



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Preventing interference between topics or skills

September, 2011

Learning two tasks or subjects one after another typically leads to poorer remembering of the first. A new study indicates the cause and suggests a remedy.

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, D. A., & Robertson E. M.
(2011).  Preventing interference between different memory tasks.
Nat Neurosci. 14(8), 953 - 955.


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The effect of stress on performance depends on individual and situational factors

September, 2011

A new study shows how stress only impacts math performance in those with both higher working memory capacity and math anxiety, while another shows that whether or not pressure impacts your performance depends on the nature of the pressure and the type of task.

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.



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