Strategies

Music training protects against aging-related hearing loss

February, 2012

More evidence that music training protects older adults from age-related impairment in understanding speech, adding to the potential benefits of music training in preventing dementia.

I’ve spoken before about the association between hearing loss in old age and dementia risk. Although we don’t currently understand that association, it may be that preventing hearing loss also helps prevent cognitive decline and dementia. I have previously reported on how music training in childhood can help older adults’ ability to hear speech in a noisy environment. A new study adds to this evidence.

The study looked at a specific aspect of understanding speech: auditory brainstem timing. Aging disrupts this timing, degrading the ability to precisely encode sound.

In this study, automatic brain responses to speech sounds were measured in 87 younger and older normal-hearing adults as they watched a captioned video. It was found that older adults who had begun musical training before age 9 and engaged consistently in musical activities through their lives (“musicians”) not only significantly outperformed older adults who had no more than three years of musical training (“non-musicians”), but encoded the sounds as quickly and accurately as the younger non-musicians.

The researchers qualify this finding by saying that it shows only that musical experience selectively affects the timing of sound elements that are important in distinguishing one consonant from another, not necessarily all sound elements. However, it seems probable that it extends more widely, and in any case the ability to understand speech is crucial to social interaction, which may well underlie at least part of the association between hearing loss and dementia.

The burning question for many will be whether the benefits of music training can be accrued later in life. We will have to wait for more research to answer that, but, as music training and enjoyment fit the definition of ‘mentally stimulating activities’, this certainly adds another reason to pursue such a course.

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The problem in correcting false knowledge

February, 2012

Whether corrections to students’ misconceptions ‘stick’ depends on the strength of the memory of the correction.

Students come into classrooms filled with inaccurate knowledge they are confident is correct, and overcoming these misconceptions is notoriously difficult. In recent years, research has shown that such false knowledge can be corrected with feedback. The hypercorrection effect, as it has been termed, expresses the finding that when students are more confident of a wrong answer, they are more likely to remember the right answer if corrected.

This is somewhat against intuition and experience, which would suggest that it is harder to correct more confidently held misconceptions.

A new study tells us how to reconcile experimental evidence and belief: false knowledge is more likely to be corrected in the short-term, but also more likely to return once the correction is forgotten.

In the study, 50 undergraduate students were tested on basic science facts. After rating their confidence in each answer, they were told the correct answer. Half the students were then retested almost immediately (after a 6 minute filler task), while the other half were retested a week later.

There were 120 questions in the test. Examples include: What is stored in a camel's hump? How many chromosomes do humans have? What is the driest area on Earth? The average percentage of correct responses on the initial test was 38%, and as expected, for the second test, performance was significantly better on the immediate compared to the delayed (90% vs 71%).

Students who were retested immediately gave the correct answer on 86% of their previous errors, and they were more likely to correct their high-confidence errors than those made with little confidence (the hypercorrection effect). Those retested a week later also showed the hypercorrection effect, albeit at a much lower level: they only corrected 56% of their previous errors. (More precisely, on the immediate test, corrected answers rose from 79% for the lowest confidence level to 92% for the highest confidence. On the delayed test, corrected answers rose from 43% to 70% on the second highest confidence level, 64% for the highest.)

In those instances where students had forgotten the correct answer, they were much more likely to reproduce the original error if their confidence had been high. Indeed, on the immediate test, the same error was rarely repeated, regardless of confidence level (the proportion of repeated errors hovered at 3-4% pretty much across the board). On the delayed test, on the other hand, there was a linear increase, with repeated errors steadily increasing from 14% to 23% as confidence level rose (with the same odd exception — at the second highest confidence level, proportion of repeated errors suddenly fell).

Overall, students were more likely to correct their errors if they remembered their error than if they didn’t (72% vs 65%). Unsurprisingly, those in the immediate group were much more likely to remember their initial errors than those in the delayed group (85% vs 61%).

In other words, it’s all about relative strength of the memories. While high-confidence errors are more likely to be corrected if the correct answer is readily accessible, they are also more likely to be repeated once the correct answer becomes less accessible. The trick to replacing false knowledge, then, is to improve the strength of the correct information.

Thus, as recency fades, you need to engage frequency to make the new memory stronger. So the finding points to the special need for multiple repetition, if you are hoping to correct entrenched false knowledge. The success of immediate testing indicates that properly spaced retrieval practice is probably the best way of replacing incorrect knowledge.

Of course, these findings apply well beyond the classroom!

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[2725] Butler, A. C., Fazio L. K., & Marsh E. J.
(2011).  The hypercorrection effect persists over a week, but high-confidence errors return.
Psychonomic Bulletin & Review. 18(6), 1238 - 1244.

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'Exergames' may provide greater cognitive benefit for older adults

February, 2012

An intriguing pilot study finds that regular exercise on a stationary bike enhanced with a computer game-type environment improves executive function in older adults more than ordinary exercise on a stationary bike.

We know that physical exercise greatly helps you prevent cognitive decline with aging. We know that mental stimulation also helps you prevent age-related cognitive decline. So it was only a matter of time before someone came up with a way of combining the two. A new study found that older adults improved executive function more by participating in virtual reality-enhanced exercise ("exergames") that combine physical exercise with computer-simulated environments and interactive videogame features, compared to the same exercise without the enhancements.

The Cybercycle Study involved 79 older adults (aged 58-99) from independent living facilities with indoor access to a stationary exercise bike. Of the 79, 63 participants completed the three-month study, meaning that they achieved at least 25 rides during the three months.

Unfortunately, randomization was not as good as it should have been — although the researchers planned to randomize on an individual basis, various technical problems led them to randomize on a site basis (there were eight sites), with the result that the cybercycle group and the control bike group were significantly different in age and education. Although the researchers took this into account in the analysis, that is not the same as having groups that match in these all-important variables. However, at least the variables went in opposite directions: while the cybercycle group was significantly younger (average 75.7 vs 81.6 years), it was significantly less educated (average 12.6 vs 14.8 years).

Perhaps also partly off-setting the age advantage, the cybercycle group was in poorer shape than the control group (higher BMI, glucose levels, lower physical activity level, etc), although these differences weren’t statistically significant. IQ was also lower for the cybercycle group, if not significantly so (but note the high averages for both groups: 117.6 vs 120.6). One of the three tests of executive function, Color Trails, also showed a marked group difference, but the large variability in scores meant that this difference was not statistically significant.

Although participants were screened for disorders such as Alzheimer’s and Parkinson’s, and functional disability, many of both groups were assessed as having MCI — 16 of the 38 in the cybercycle group and 14 of the 41 in the control bike group.

Participants were given cognitive tests at enrolment, one month later (before the intervention began), and after the intervention ended. The stationary bikes were identical for both groups, except the experimental bike was equipped with a virtual reality display. Cybercycle participants experienced 3D tours and raced against a "ghost rider," an avatar based on their last best ride.

The hypothesis was that cybercycling would particularly benefit executive function, and this was borne out. Executive function (measured by the Color Trails, Stroop test, and Digits Backward) improved significantly more in the cybercycle condition, and indeed was the only cognitive task to do so (other cognitive tests included verbal fluency, verbal memory, visuospatial skill, motor function). Indeed, the control group, despite getting the same amount of exercise, got worse at the Digits Backward test, and failed to show any improvement on the Stroop test.

Moreover, significantly fewer cybercyclists progressed to MCI compared to the control group (three vs nine).

There were no differences in exercise quantity or quality between the two groups — which does argue against the idea that cyber-enhanced physical activity would be more motivating. However, the cybercycling group did tend to comment on their enjoyment of the exercise. While the enjoyment may not have translated into increased activity in this situation, it may well do so in a longer, less directed intervention — i.e. real life.

It should also be remembered that the intervention was relatively short, and that other cognitive tasks might take longer to show improvement than the more sensitive executive function. This is supported by the fact that levels of the brain growth factor BDNF, assessed in 30 participants, showed a significantly greater increase of BDNF in cybercyclists.

I should also emphasize that the level of physical exercise really wasn't that great, but nevertheless the size of the cybercycle's effect on executive function was greater than usually produced by aerobic exercise (a medium effect rather than a small one).

The idea that activities that combine physical and mental exercise are of greater cognitive benefit than the sum of benefits from each type of exercise on its own is not inconsistent with previous research, and in keeping with evidence from animal studies that physical exercise and mental stimulation help the brain via different mechanisms. Moreover, I have an idea that enjoyment (in itself, not as a proxy for motivation) may be a factor in the cognitive benefits derived from activities, whether physical or mental. Mere speculation, derived from two quite separate areas of research: the idea of “flow” / “being in the zone”, and the idea that humor has physiological benefits.

Of course, as discussed, this study has a number of methodological issues that limit its findings, but hopefully it will be the beginning of an interesting line of research.  

Reference: 

[2724] Anderson-Hanley, C., Arciero P. J., Brickman A. M., Nimon J. P., Okuma N., Westen S. C., et al.
(2012).  Exergaming and Older Adult Cognition.
American Journal of Preventive Medicine. 42(2), 109 - 119.

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Latest London taxi driver study shows brain changes driven by learning

January, 2012
  • A comparison of the brains of London taxi drivers before and after their lengthy training shows clearly that the increase in hippocampal gray matter develops with training, but this may come at the expense of other brain functions.

The evidence that adult brains could grow new neurons was a game-changer, and has spawned all manner of products to try and stimulate such neurogenesis, to help fight back against age-related cognitive decline and even dementia. An important study in the evidence for the role of experience and training in growing new neurons was Maguire’s celebrated study of London taxi drivers, back in 2000.

The small study, involving 16 male, right-handed taxi drivers with an average experience of 14.3 years (range 1.5 to 42 years), found that the taxi drivers had significantly more grey matter (neurons) in the posterior hippocampus than matched controls, while the controls showed relatively more grey matter in the anterior hippocampus. Overall, these balanced out, so that the volume of the hippocampus as a whole wasn’t different for the two groups. The volume in the right posterior hippocampus correlated with the amount of experience the driver had (the correlation remained after age was accounted for).

The posterior hippocampus is preferentially involved in spatial navigation. The fact that only the right posterior hippocampus showed an experience-linked increase suggests that the right and left posterior hippocampi are involved in spatial navigation in different ways. The decrease in anterior volume suggests that the need to store increasingly detailed spatial maps brings about a reorganization of the hippocampus.

But (although the experience-related correlation is certainly indicative) it could be that those who manage to become licensed taxi drivers in London are those who have some innate advantage, evidenced in a more developed posterior hippocampus. Only around half of those who go through the strenuous training program succeed in qualifying — London taxi drivers are unique in the world for being required to pass through a lengthy training period and pass stringent exams, demonstrating their knowledge of London’s 25,000 streets and their idiosyncratic layout, plus 20,000 landmarks.

In this new study, Maguire and her colleague made a more direct test of this question. 79 trainee taxi drivers and 31 controls took cognitive tests and had their brains scanned at two time points: at the beginning of training, and 3-4 years later. Of the 79 would-be taxi drivers, only 39 qualified, giving the researchers three groups to compare.

There were no differences in cognitive performance or brain scans between the three groups at time 1 (before training). At time 2 however, when the trainees had either passed the test or failed to acquire the Knowledge, those trainees that qualified had significantly more gray matter in the posterior hippocampus than they had had previously. There was no change in those who failed to qualify or in the controls.

Unsurprisingly, both qualified and non-qualified trainees were significantly better at judging the spatial relations between London landmarks than the control group. However, qualified trainees – but not the trainees who failed to qualify – were worse than the other groups at recalling a complex visual figure after 30 minutes (see here for an example of such a figure). Such a finding replicates previous findings of London taxi drivers. In other words, their improvement in spatial memory as it pertains to London seems to have come at a cost.

Interestingly, there was no detectable difference in the structure of the anterior hippocampus, suggesting that these changes develop later, in response to changes in the posterior hippocampus. However, the poorer performance on the complex figure test may be an early sign of changes in the anterior hippocampus that are not yet measurable in a MRI.

The ‘Knowledge’, as it is known, provides a lovely real-world example of expertise. Unlike most other examples of expertise development (e.g. music, chess), it is largely unaffected by childhood experience (there may be some London taxi drivers who began deliberately working on their knowledge of London streets in childhood, but it is surely not common!); it is developed through a training program over a limited time period common to all participants; and its participants are of average IQ and education (average school-leaving age was around 16.7 years for all groups; average verbal IQ was around or just below 100).

So what underlies this development of the posterior hippocampus? If the qualified and non-qualified trainees were comparable in education and IQ, what determined whether a trainee would ‘build up’ his hippocampus and pass the exams? The obvious answer is hard work / dedication, and this is borne out by the fact that, although the two groups were similar in the length of their training period, those who qualified spent significantly more time training every week (an average of 34.5 hours a week vs 16.7 hours). Those who qualified also attended far more tests (an average of 15.6 vs 2.6).

While neurogenesis is probably involved in this growth within the posterior hippocampus, it is also possible that growth reflects increases in the number of connections, or in the number of glia. Most probably (I think), all are involved.

There are two important points to take away from this study. One is its clear demonstration that training can produce measurable changes in a brain region. The other is the indication that this development may come at the expense of other regions (and functions).

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Dealing with math anxiety

November, 2011

A new study shows that some math-anxious students can overcome performance deficits through their ability to control their negative responses. The finding indicates that interventions should focus on anticipatory cognitive control.

Math-anxiety can greatly lower performance on math problems, but just because you suffer from math-anxiety doesn’t mean you’re necessarily going to perform badly. A study involving 28 college students has found that some of the students anxious about math performed better than other math-anxious students, and such performance differences were associated with differences in brain activity.

Math-anxious students who performed well showed increased activity in fronto-parietal regions of the brain prior to doing math problems — that is, in preparation for it. Those students who activated these regions got an average 83% of the problems correct, compared to 88% for students with low math anxiety, and 68% for math-anxious students who didn’t activate these regions. (Students with low anxiety didn’t activate them either.)

The fronto-parietal regions activated included the inferior frontal junction, inferior parietal lobule, and left anterior inferior frontal gyrus — regions involved in cognitive control and reappraisal of negative emotional responses (e.g. task-shifting and inhibiting inappropriate responses). Such anticipatory activity in the fronto-parietal region correlated with activity in the dorsomedial caudate, nucleus accumbens, and left hippocampus during math activity. These sub-cortical regions (regions deep within the brain, beneath the cortex) are important for coordinating task demands and motivational factors during the execution of a task. In particular, the dorsomedial caudate and hippocampus are highly interconnected and thought to form a circuit important for flexible, on-line processing. In contrast, performance was not affected by activity in ‘emotional’ regions, such as the amygdala, insula, and hypothalamus.

In other words, what’s important is not your level of anxiety, but your ability to prepare yourself for it, and control your responses. What this suggests is that the best way of dealing with math anxiety is to learn how to control negative emotional responses to math, rather than trying to get rid of them.

Given that cognitive control and emotional regulation are slow to mature, it also suggests that these effects are greater among younger students.

The findings are consistent with a theory that anxiety hinders cognitive performance by limiting the ability to shift attention and inhibit irrelevant/distracting information.

Note that students in the two groups (high and low anxiety) did not differ in working memory capacity or in general levels of anxiety.

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Deep male voice helps women remember

November, 2011

It seems that what is said by deeper male voices is remembered better by heterosexual women, while memory is impaired for higher male voices. Pitch didn’t affect the memorability of female voices.

I had to report on this quirky little study, because a few years ago I discovered Leonard Cohen’s gravelly voice and then just a few weeks ago had it trumped by Tom Waits — I adore these deep gravelly voices, but couldn’t say why. Now a study shows that woman are not only sensitive to male voice pitch, but this affects their memory.

In the first experiment, 45 heterosexual women were shown images of objects while listening to the name of the object spoken either by a man or woman. The pitch of the voice was manipulated to be high or low. After spending five minutes on a Sudoku puzzle, participants were asked to choose which of two similar but not identical versions of the object was the one they had seen earlier. After the memory test, participants were tested on their voice preferences.

Women strongly preferred the low pitch male voice and remembered objects more accurately when they have been introduced by the deeper male voice than the higher male voice (mean score for object recognition was 84.7% vs 77.8%). There was no significant difference in memory relating to pitch for the female voices (83.9% vs 81.7% — note that these are not significantly different from the score for the deeper male voice).

So is it that memory is enhanced for deeper male voices, or that it is impaired for higher male voices (performance on the female voices suggests the latter)? Or are both factors at play? To sort this out, the second experiment, involving a new set of 46 women, included unmanipulated male and female voices.

Once again, women were unaffected by the different variations of female voices. However, male voices produced a clear linear effect, with the unmanipulated male voices squarely in the middle of the deeper and higher versions. It appears, then, that both factors are at play: deepening a male voice enhances its memorability, while raising it impairs its memorability.

It’s thought that deeper voices are associated with more desirable traits for long-term male partners. Having a better memory for specific encounters with desirable men would allow women to compare and evaluate men according to how they might behave in different relationship contexts.

The voices used were supplied by four young adult men and four young adult women. Pitch was altered through software manipulation. Participants were told that the purpose of the experiment was to study sociosexual orientation and object preference. Contraceptive pill usage did not affect the women’s responses.

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Music training and language skills

November, 2011

A month-long music-based program produced dramatic improvement in preschoolers’ language skills. Another study helps explain why music training helps language skills.

Music-based training 'cartoons' improved preschoolers’ verbal IQ

A study in which 48 preschoolers (aged 4-6) participated in computer-based, cognitive training programs that were projected on a classroom wall and featured colorful, animated cartoon characters delivering the lessons, has found that 90% of those who received music-based training significantly improved their scores on a test of verbal intelligence, while those who received visual art-based training did not.

The music-based training involved a combination of motor, perceptual and cognitive tasks, and included training on rhythm, pitch, melody, voice and basic musical concepts. Visual art training emphasized the development of visuo-spatial skills relating to concepts such as shape, color, line, dimension and perspective. Each group received two one-hour training sessions each day in classroom, over four weeks.

Children’s abilities and brain function were tested before the training and five to 20 days after the end of the programs. While there were no significant changes, in the brain or in performance, in the children who participated in the visual art training, nearly all of those who took the music-based training showed large improvements on a measure of vocabulary knowledge, as well as increased accuracy and reaction time. These correlated with changes in brain function.

The findings add to the growing evidence for the benefits of music training for intellectual development, especially in language.

Musical aptitude relates to reading ability through sensitivity to sound patterns

Another new study points to one reason for the correlation between music training and language acquisition. In the study, 42 children (aged 8-13) were tested on their ability to read and recognize words, as well as their auditory working memory (remembering a sequence of numbers and then being able to quote them in reverse), and musical aptitude (both melody and rhythm). Brain activity was also measured.

It turned out that both music aptitude and literacy were related to the brain’s response to acoustic regularities in speech, as well as auditory working memory and attention. Compared to good readers, poor readers had reduced activity in the auditory brainstem to rhythmic rather than random sounds. Responsiveness to acoustic regularities correlated with both reading ability and musical aptitude. Musical ability (largely driven by performance in rhythm) was also related to reading ability, and auditory working memory to both of these.

It was calculated that music skill, through the functions it shares with reading (brainstem responsiveness to auditory regularities and auditory working memory) accounts for 38% of the difference in reading ability between children.

These findings are consistent with previous findings that auditory working memory is an important component of child literacy, and that positive correlations exist between auditory working memory and musical skill.

Basically what this is saying, is that the auditory brainstem (a subcortical region — that is, below the cerebral cortex, where our ‘higher-order’ functions are carried out) is boosting the experience of predictable speech in better readers. This fine-tuning may reflect stronger top-down control in those with better musical ability and reading skills. While there may be some genetic contribution, previous research makes it clear that musicians’ increased sensitivity to sound patterns is at least partly due to training.

In other words, giving young children music training is a good first step to literacy.

The children were rated as good readers if they scored 110 or above on the Test of Word Reading Efficiency, and poor readers if they scored 90 or below. There were 8 good readers and 21 poor readers. Those 13 who scored in the middle were excluded from group analyses. Good and poor readers didn’t differ in age, gender, maternal education, years of musical training, extent of extracurricular activity, or nonverbal IQ. Only 6 of the 42 children had had at least a year of musical training (of which one was a poor reader, three were average, and two were good).

Auditory brainstem responses were gathered to the speech sound /da/, which was either presented with 100% probability, or randomly interspersed with seven other speech sounds. The children heard these sounds through an earpiece in the right ear, while they listened to the soundtrack of a chosen video with the other ear.

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[2603] Moreno, S., Bialystok E., Barac R., Schellenberg E. Glenn, Cepeda N. J., & Chau T.
(2011).  Short-Term Music Training Enhances Verbal Intelligence and Executive Function.
Psychological Science. 22(11), 1425 - 1433.

Strait, Dana L, Jane Hornickel, and Nina Kraus. “Subcortical processing of speech regularities underlies reading and music aptitude in children.” Behavioral and brain functions : BBF 7, no. 1 (October 17, 2011): 44. http://www.ncbi.nlm.nih.gov/pubmed/22005291.

Full text is available at http://www.behavioralandbrainfunctions.com/content/pdf/1744-9081-7-44.pd...

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How your hands affect your thinking

October, 2011

Two recent studies in embodied cognition show that hand movements and hand position are associated with less abstract thinking.

I always like studies about embodied cognition — that is, about how what we do physically affects how we think. Here are a couple of new ones.

The first study involved two experiments. In the first, 86 American college students were asked questions about gears in relation to each other. For example, “If five gears are arranged in a line, and you move the first gear clockwise, what will the final gear do?” The participants were videotaped as they talked their way through the problem. But here’s the interesting thing: half the students wore Velcro gloves attached to a board, preventing them from moving their hands. The control half were similarly prevented from moving their feet — giving them the same experience of restriction without the limitation on hand movement.

Those who gestured commonly used perceptual-motor strategies (simulation of gear movements) in solving the puzzles. Those who were prevented from gesturing, as well as those who chose not to gesture, used abstract, mathematical strategies much more often.

The second experiment confirmed the results with 111 British adults.

The findings are consistent with the hypothesis that gestures highlight and structure perceptual-motor information, and thereby make such information more likely to be used in problem solving.

That can be helpful, but not always. Even when we are solving problems that have to do with motion and space, more abstract strategies may sometimes be more efficient, and thus an inability to use the body may force us to come up with better strategies.

The other study is quite different. In this study, college students searched for a single letter embedded within images of fractals and other complex geometrical patterns. Some did this while holding their hands close to the images; others kept their hands in their laps, far from the images. This may sound a little wacky, but previous research has shown that perception and attention are affected by how close our hands are to an object. Items near our hands tend to take priority.

In the first experiment, eight randomly chosen images were periodically repeated 16 times, while the other 128 images were only shown once. The target letter was a gray “T” or “L”; the images were colorful.

As expected, finding the target letter was faster the more times the image had been presented. Hand position didn’t affect learning.

In the second experiment, a new set of students were shown the same shown-once images, while 16 versions of the eight repeated images were created. These versions varied in their color components. In this circumstance, learning was slower when hands were held near the images. That is, people found it harder to recognize the commonalities among identical but differently colored patterns, suggesting they were too focused on the details to see the similarities.

These findings suggest that processing near the hands is biased toward item-specific detail. This is in keeping with earlier suggestions that the improvements in perception and attention near the hands are item-specific. It may indeed be that this increased perceptual focus is at the cost of higher-order function such as memory and learning. This would be consistent with the idea that there are two largely independent visual streams, one of which is mainly concerned with visuospatial operations, and the other of which is primarily for more cognitive operations (such as object identification).

All this may seem somewhat abstruse, but it is worryingly relevant in these days of hand-held technological devices.

The point of both these studies is not that one strategy (whether of hand movements or hand position) is wrong. What you need to take away is the realization that hand movements and hand position can affect the way you approach problems, and the things you perceive. Sometimes you want to take a more physical approach to a problem, or pick out the fine details of a scene or object — in these cases, moving your hands, or holding something in or near your hands, is a good idea. Other times you might want to take a more abstract/generalized approach — in these cases, you might want to step back and keep your body out of it.

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Gesture & embodied cognition

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

Connection between language and movement

A study of all three groups of birds with vocal learning abilities – songbirds, parrots and hummingbirds – has revealed that the brain structures for singing and learning to sing are embedded in areas controlling movement, and areas in charge of movement share many functional similarities with the brain areas for singing. This suggests that the brain pathways used for vocal learning evolved out of the brain pathways used for motor control. Human brain structures for speech also lie adjacent to, and even within, areas that control movement. The findings may explain why humans talk with our hands and voice, and could open up new approaches to understanding speech disorders in humans. They are also consistent with the hypothesis that spoken language was preceded by gestural language, or communication based on movements. Support comes from another very recent study finding that mice engineered to have a mutation to the gene FOXP2 (known to cause problems with controlling the formation of words in humans) had trouble running on a treadmill.
Relatedly, a study of young children found that 5-year-olds do better on motor tasks when they talk to themselves out loud (either spontaneously or when told to do so by an adult) than when they are silent. The study also showed that children with behavioral problems (such as ADHD) tend to talk to themselves more often than children without signs of behavior problems. The findings suggest that teachers should be more tolerant of this kind of private speech.

[436] Feenders, G., Liedvogel M., Rivas M., Zapka M., Horita H., Hara E., et al.
(2008).  Molecular Mapping of Movement-Associated Areas in the Avian Brain: A Motor Theory for Vocal Learning Origin.
PLoS ONE. 3(3), e1768 - e1768.

[1235] Winsler, A., Manfra L., & Diaz R. M.
(2007).  "Should I let them talk?": Private speech and task performance among preschool children with and without behavior problems.
Early Childhood Research Quarterly. 22(2), 215 - 231.

http://www.physorg.com/news124526627.html
http://www.sciam.com/article.cfm?id=song-learning-birds-shed
http://www.eurekalert.org/pub_releases/2008-03/gmu-pkd032808.php

Kids learn more when mother is listening

Research has already shown that children learn well when they explain things to their mother or a peer, but that could be because they’re getting feedback and help. Now a new study has asked 4- and 5-year-olds to explain their solution to a problem to their moms (with the mothers listening silently), to themselves or to simply repeat the answer out loud. Explaining to themselves or to their moms improved the children's ability to solve similar problems, and explaining the answer to their moms helped them solve more difficult problems — presumably because explaining to mom made a difference in the quality of the child's explanations.

[416] Rittle-Johnson, B., Saylor M., & Swygert K. E.
(2008).  Learning from explaining: Does it matter if mom is listening?.
Journal of Experimental Child Psychology. 100(3), 215 - 224.

http://www.physorg.com/news120320713.html

Gesturing helps grade-schoolers solve math problems

Two studies of children in late third and early fourth grade, who made mistakes in solving math problems, have found that children told to move their hands when explaining how they’d solve a problem were four times as likely as kids given no instructions to manually express correct new ways to solve problems. Even though they didn’t give the right answer, their gestures revealed an implicit knowledge of mathematical ideas, and the second study showed that gesturing set them up to benefit from subsequent instruction. The findings extend previous research that body movement not only helps people to express things they may not be able to verbally articulate, but actually to think better.

[1170] Broaders, S. C., Cook S W., Mitchell Z., & Goldin-Meadow S.
(2007).  Making Children Gesture Brings Out Implicit Knowledge and Leads to Learning.
Journal of Experimental Psychology: General. 136(4), 539 - 550.

http://www.eurekalert.org/pub_releases/2007-11/apa-ghg102907.php

Doodling can help memory recall

A study in which 40 academics were asked to listen to a two and a half minute tape giving several names of people and places, and were told to write down only the names of people going to a party, has found that those who were asked to shade in shapes on a piece of paper at the same time, recalled on average 7.5 names of people and places compared to only 5.8 by those who were not asked to doodle. This supports the idea that a simple secondary task like doodling can be useful to stop your mind wandering when it’s doing something boring.

Andrade, J. 2009. What does doodling do? Applied Cognitive Psychology, Published online 27 February

http://www.eurekalert.org/pub_releases/2009-02/w-dd022509.php

Actors’ memory tricks help students and older adults

The ability of actors to remember large amounts of dialog verbatim is a marvel to most of us, and most of us assume they do by painful rote memorization. But two researchers have been studying the way actors learn for many years and have concluded that the secret of actors' memories is in the acting; an actor learning lines by focusing on the character’s motives and feelings — they get inside the character. To do this, they break a script down into a series of logically connected "beats" or intentions. The researchers call this process active experiencing, which uses "all physical, mental, and emotional channels to communicate the meaning of material to another person." This principle can be applied in other contexts. For example, students who imagined themselves explaining something to somebody else remembered more than those who tried to memorize the material by rote. Physical movement also helps — lines learned while doing something, such as walking across the stage, were remembered better than lines not accompanied with action. The principles have been found useful in improving memory in older adults: older adults who received a four-week course in acting showed significantly improved word-recall and problem-solving abilities compared to both a group that received a visual-arts course and a control group, and this improvement persisted four months afterward.

[2464] Noice, H., & Noice T.
(2006).  What Studies of Actors and Acting Can Tell Us About Memory and Cognitive Functioning.
Current Directions in Psychological Science. 15(1), 14 - 18.

http://www.eurekalert.org/pub_releases/2006-01/aps-bo012506.php

People remember speech better when it is accompanied by gestures

A recent study had participants watch someone narrating three cartoons. Sometimes the narrator used hand gestures and at other times they did not. The participants were then asked to recall the story. The study found that when the narrator used gestures as well as speech the participants were more likely to accurately remember what actually happened in the story rather than change it in some way.

The research was presented to the British Psychological Society Annual Conference in Bournemouth on Thursday 13 March.

Gesturing reduces cognitive load

Why is it that people cannot keep their hands still when they talk? One reason may be that gesturing actually lightens cognitive load while a person is thinking of what to say. Adults and children were asked to remember a list of letters or words while explaining how they solved a math problem. Both groups remembered significantly more items when they gestured during their math explanations than when they did not gesture.

[1300] Goldin-Meadow, S., Nusbaum H., Kelly S. D., & Wagner S.
(2001).  Explaining math: gesturing lightens the load.
Psychological Science: A Journal of the American Psychological Society / APS. 12(6), 516 - 522.

tags memworks: 

tags strategies: 

Multitasking

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

Improving your multitasking skills

Teaching older brains to regain youthful skills

Researchers have succeeded in training seniors to multitask at the same level as younger adults. Over the course of two weeks, both younger and older subjects learned to identify a letter flashed quickly in the middle of a computer screen and simultaneously localize the position of a spot flashed quickly in the periphery as well as they could perform either task on its own. The older adults did take longer than the younger adults to reach the same level of performance, but they did reach it.

[571] Richards, E., Bennett P. J., & Sekuler A. B.
(2006).  Age related differences in learning with the useful field of view.
Vision Research. 46(25), 4217 - 4231.

http://www.eurekalert.org/pub_releases/2006-10/mu-yct100206.php

Age and individual differences

Teen's ability to multi-task develops late in adolescence

A study involving adolescents between 9 and 20 years old has found that the ability to multi-task continues to develop through adolescence. The ability to use recall-guided action to remember single pieces of spatial information (such as looking at the location of a dot on a computer screen, then, after a delay, indicating where the dot had been) developed until ages 11 to 12, while the ability to remember multiple units of information in the correct sequence developed until ages 13 to 15. Tasks in which participants had to search for hidden items in a manner requiring a high level of multi-tasking and strategic thinking continued to develop until ages 16 to 17. "These findings have important implications for parents and teachers who might expect too much in the way of strategic or self-organized thinking, especially from older teenagers."

[547] Luciana, M., Conklin H. M., Hooper C. J., & Yarger R. S.
(2005).  The Development of Nonverbal Working Memory and Executive Control Processes in Adolescents.
Child Development. 76(3), 697 - 712.

http://www.eurekalert.org/pub_releases/2005-05/sfri-tat051205.php

About multitasking

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

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

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

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

Asymmetrical brains let fish multitask

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

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

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

How much can your mind keep track of?

A recent study has tried a new take on measuring how much a person can keep track of. It's difficult to measure the limits of processing capacity because most people automatically break down large complex problems into small, manageable chunks. To keep people from doing this, therefore, researchers created problems the test subjects wouldn’t be familiar with. 30 academics were presented with incomplete verbal descriptions of statistical interactions between fictitious variables, with an accompanying set of graphs that represented the interactions. It was found that, as the problems got more complex, participants performed less well and were less confident. They were significantly less able to accurately solve the problems involving four-way interactions than the ones involving three-way interactions, and were completely incapable of solving problems with five-way interactions. The researchers concluded that we cannot process more than four variables at a time (and at that, four is a strain).

[415] Halford, G. S., Baker R., McCredden J. E., & Bain J. D.
(2005).  How many variables can humans process?.
Psychological Science: A Journal of the American Psychological Society / APS. 16(1), 70 - 76.

http://www.eurekalert.org/pub_releases/2005-03/aps-hmc030805.php

We weren't made to multitask

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

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

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

Why multitasking is a problem

Talking, walking and driving with cell phone users

Another cellphone-multitasking study! Compared with people walking alone, in pairs, or listening to their ipod, cell phone users were the group most prone to oblivious behavior: only 25% of them noticed a unicycling clown passing them on the street, compared to 51% of single individuals, 61% of music player users, and 71% of people in pairs. In fact, cell phone users even had problems walking — walking more slowly, changing direction more often, being prone to weaving, and acknowledging other people more rarely.

Hyman, I.E.Jr, Boss, S. M., Wise, B. M., McKenzie, K. E., & Caggiano, J. M. (2009). Did you see the unicycling clown? Inattentional blindness while walking and talking on a cell phone. Applied Cognitive Psychology, 9999(9999), n/a. doi: 10.1002/acp.1638.

http://www.eurekalert.org/pub_releases/2009-10/w-tuc101909.php

Chronic media multitasking correlated with poor attention

Media multitasking — keeping tabs on email, texts, IM chat, the web — is routine among young people in particular. We know that humans can’t really multitask very successfully — that what we do is switch tracks, and every time we do that there’s a cost, in terms of your efficiency at the task. But what about long-term costs of chronic multitasking? A study that selected 19 students who multitasked the most and 22 who multitasked least, from a pool of 262 students, found those who multitasked least performed better on three cognitive tests that are thought to reflect ability to ignore distracting information, ability to organize things in working memory, and ability to switch between tasks. The findings can’t answer whether chronic media multitasking reduces these abilities, or whether people who are poor at these skills are more likely to succumb to chronic media multitasking, but they do demonstrate that chronic media multitasking is associated with this particular information processing style.

[890] Ophir, E., Nass C., & Wagner A. D.
(2009).  From the Cover: Cognitive control in media multitaskers.
Proceedings of the National Academy of Sciences. 106(37), 15583 - 15587.

http://www.wired.com/wiredscience/2009/08/multitasking/

Cell phone ringtones can pose major distraction, impair recall

Cell phones ringing during a concert is not simply irritating. It appears that in a classroom, a cell phone left to ring for 30 seconds significantly affected the students’ recall for the information presented just prior to and during the ringing. The effect was even greater when the phone’s owner rummaged frantically through her bag. Ringtones that are popular songs were even greater distractions. However, with repeated trials, people could be trained to reduce the negative effects; being warned about the distracting effects also helped people be less affected.

[1299] Shelton, J. T., Elliott E. M., Eaves S. D., & Exner A. L.
(2009).  The distracting effects of a ringing cell phone: An investigation of the laboratory and the classroom setting.
Journal of Environmental Psychology. 29(4), 513 - 521.

http://www.eurekalert.org/pub_releases/2009-06/wuis-cpr060209.php

Police with higher multitasking abilities less likely to shoot unarmed persons

In a study in which police officers watched a video of an officer-involved shooting that resulted in the death of the officer before participating in a computer-based simulation where they were required to make split-second decisions whether to shoot or not to shoot someone, based on slides showing a person holding either a gun or a harmless object like a cell phone, it was found that among those more stressed by the video, those with a lower working memory capacity were more likely to shoot unarmed people. Working memory capacity was not a significant factor for those who did not show heightened negative emotionality in response to the video.

[739] Kleider, H. M., Parrott D. J., & King T. Z.
(2009).  Shooting behaviour: How working memory and negative emotionality influence police officer shoot decisions.
Applied Cognitive Psychology. 9999(9999), n/a - n/a.

http://www.eurekalert.org/pub_releases/2009-03/gsu-pwh033009.php

Switchboard in the brain helps us learn and remember at the same time

It’s very common that we are required to both process new information while simultaneously recalling old information, as in conversation we are paying attention to what the other person is saying while preparing our own reply. A new study confirms what has been theorized: that there is a bottleneck in our memory system preventing us from doing both simultaneously. Moreover, the study provides evidence that a specific region in the left prefrontal cortex can resolve the bottleneck, possibly by allowing rapid switching between learning and remembering. This is supported by earlier findings that patients with damage to this area have problems in rapidly adapting to new situations and tend to persevere in old rules. The same region is also affected in older adults.

[1355] Huijbers, W., Pennartz C. M., Cabeza R., & Daselaar S. M.
(2009).  When Learning and Remembering Compete: A Functional MRI Study.
PLoS Biol. 7(1), e1000011 - e1000011.

Full text is available at http://biology.plosjournals.org/perlserv/?request=get-document&doi=10.1371/journal.pbio.1000011
http://www.eurekalert.org/pub_releases/2009-01/plos-sit010909.php

Neural bottleneck found that thwarts multi-tasking

An imaging study has revealed just why we can’t do two things at once. The bottleneck appears to occur at the lateral frontal and prefrontal cortex and the superior frontal cortex. Both areas are known to play a critical role in cognitive control. These brain regions responded to tasks irrespective of the senses involved, and could be seen to 'queue' neural activity — that is, a response to the second task was postponed until the response to the first was completed. Such queuing occurred when two tasks were presented within 300 milliseconds of each other, but not when the time gap was longer.

[896] Dux, P. E., Ivanoff J., Asplund C. L., & Marois R.
(2006).  Isolation of a Central Bottleneck of Information Processing with Time-Resolved fMRI.
Neuron. 52(6), 1109 - 1120.

http://www.eurekalert.org/pub_releases/2007-01/vu-nbf011807.php

How multitasking impedes learning

A number of studies have come out in recent years demonstrating that the human brain can’t really do two things at once, and that when we do attempt to do so, performance is impaired. A new imaging study provides evidence that we tend to use a less efficient means of learning when distracted by another task. In the study, 14 younger adults (in their twenties) learned a simple classification task by trial-and-error. For one set of the cards, they also had to keep a running mental count of high tones that they heard while learning the classification task. Imaging revealed that different brain regions were used for learning depending on whether the participants were distracted by the other task or not — the hippocampus was involved in the single-task learning, but not in the dual-task, when the striatum (a region implicated in procedural and habit learning) was active. Although the ability of the participants to learn didn’t appear to be affected at the time, the distraction did reduce the participants' subsequent knowledge about the task during a follow-up session. In particular, on the task learned with the distraction, participants could not extrapolate from what they had learned.

[1273] Foerde, K., Knowlton B. J., & Poldrack R. A.
(2006).  Modulation of competing memory systems by distraction.
Proceedings of the National Academy of Sciences. 103(31), 11778 - 11783.

http://www.sciencedaily.com/releases/2006/07/060726083302.htm

Doing two things at once

Confirmation of what many of us know, and many more try to deny - you can't do two complex tasks simultaneously as well as you could do either one alone. Previous research has showed that when a single area of the brain, like the visual cortex, has to do two things at once, like tracking two objects, there is less brain activation than occurs when it watches one thing at a time. This new study sought to find out whether something similar happened when two highly independent tasks, carried out in very different parts of the brain, were done concurrently. The two tasks used were language comprehension (carried out in the temporal lobe), and mental rotation (carried out in the parietal lobe). The language task alone activated 37 voxels of brain tissue. The mental rotation task alone also activated 37 voxels. But when both tasks were done at the same time, only 42 voxels were activated, rather than the sum of the two (74). While overall accuracy did not suffer, each task took longer to perform.

[2546] Just, M A., Carpenter P. A., Keller T. A., Emery L., Zajac H., & Thulborn K. R.
(2001).  Interdependence of Nonoverlapping Cortical Systems in Dual Cognitive Tasks.
NeuroImage. 14(2), 417 - 426.

http://www.nytimes.com/2001/07/31/health/anatomy/31BRAI.html

The costs of multitasking

Technology increasingly tempts people to do more than one thing (and increasingly, more than one complicated thing) at a time. New scientific studies reveal the hidden costs of multitasking. In a study that looked at the amounts of time lost when people switched repeatedly between two tasks of varying complexity and familiarity, it was found that for all types of tasks, subjects lost time when they had to switch from one task to another, and time costs increased with the complexity of the tasks, so it took significantly longer to switch between more complex tasks. Time costs also were greater when subjects switched to tasks that were relatively unfamiliar. They got "up to speed" faster when they switched to tasks they knew better. These results suggest that executive control involves two distinct, complementary stages: goal shifting ("I want to do this now instead of that") and rule activation ("I'm turning off the rules for that and turning on the rules for this").

[1124] Rubinstein, J. S., Meyer D. E., & Evans J. E.
(2001).  Executive Control of Cognitive Processes in Task Switching,.
Journal of Experimental Psychology: Human Perception and Performance. 27(4), 763 - 797.

http://www.apa.org/journals/xhp/press_releases/august_2001/xhp274763.html

Brain's halves compete for attention

Claus Hilgetag, of Boston University, and his colleagues fired focused magnetic pulses through healthy subjects' skulls for 10 minutes to induce 'hemispatial neglect'. This condition, involving damage to one side of the brain, leaves patients unaware of objects in the opposite half of their visual field (which sends messages to the damaged half of the brain). The subjects showed the traditional symptoms of hemispatial neglect. They were worse at detecting objects opposite to the numb side of their brain, and worse still if there was also an object in the functioning half of the visual field. Yet numbed subjects were better at spotting objects with the unaffected half of their brains. This behavior confirms the idea that activity in one half of the brain usually eclipses that in the opposite half. The finding supports the idea that mental activity is a tussle between the brain's many different areas.

[720] Hilgetag, C. C., Theoret H., & Pascual-Leone A.
(2001).  Enhanced visual spatial attention ipsilateral to rTMS-induced 'virtual lesions' of human parietal cortex.
Nat Neurosci. 4(9), 953 - 957.

http://www.nature.com/nsu/010830/010830-5.html

Multitasking and driving

Why cell phones and driving don't mix

A host of studies have come out in recent years demonstrating that multitasking impairs performance and talking on a cell phone while driving a car is a bad idea. A new study helps explain why. In two different experiments, subjects were found to be four times more distracted while preparing to speak or speaking than when they were listening. The researcher expects the effect to be even stronger in real-life conversation. It was also found that subjects could complete the visual task in front of them more easily when the projected voice also was in front. This suggests that it may be easier to have all things that require attention in the same space.

[1132] Almor, A.
(2008).  Why Does Language Interfere with Vision-Based Tasks?.
Experimental Psychology (formerly "Zeitschrift für Experimentelle Psychologie"). 55(4), 260 - 268.

http://www.sciencedaily.com/releases/2008/05/080531084958.htm

Talking on a cellphone while driving as bad as drinking

Yet another study has come out rubbing it in that multitasking comes with a cost, and most particularly, that you shouldn’t do anything else while driving. This study demonstrates — shockingly — that drivers are actually worse off when using a cell phone than when legally drunk. The study had 40 volunteers use a driving simulator under 4 different conditions: once while legally intoxicated, once while talking on a hands-free cell phone, once while talking on a hand-held cell phone, and once with no distractions. There were differences in behavior —drunk drivers were more aggressive, tailgated more, and hit the brake pedal harder; cell phone drivers (whether hands-free and hand-held ) took longer to hit the brakes, and got in more accidents. But in both cases drivers were significantly impaired.

[1250] Strayer, D. L., Drews F. A., & Crouch D. J.
(2006).  A Comparison of the Cell Phone Driver and the Drunk Driver.
Human Factors: The Journal of the Human Factors and Ergonomics Society. 48(2), 381 - 391.

http://www.sciencentral.com/articles/view.htm3?article_id=218392815
http://www.eurekalert.org/pub_releases/2006-06/uou-doc062306.php
http://www.guardian.co.uk/mobile/article/0,,1809549,00.html

Performing even easy tasks impairs driving

In yet another demonstration that driving is impaired when doing anything else, a simulator study has found that students following a lead car and instructed to brake as soon as they saw the illumination of the lead car's brake lights, responded slower when required to respond to a concurrent easy task, where a stimulus - either a light flash in the lead car's rear window or an auditory tone - was randomly presented once or twice and participants had to indicate the stimulus' frequency. The finding suggests that even using a hands-free device doesn’t make it okay to talk on a cell phone while driving.

[837] Levy, J., Pashler H., & Boer E.
(2006).  Central interference in driving: is there any stopping the psychological refractory period?.
Psychological Science: A Journal of the American Psychological Society / APS. 17(3), 228 - 235.

http://www.psychologicalscience.org/media/releases/2006/pr060303.cfm

Talking and listening impairs your ability to drive safely

A study involving almost 100 students driving virtual cars has provided evidence that people have greater difficultly maintaining a fixed speed when performing tasks that simulated conversing on a mobile phone. Both speaking and listening were equally distracting.

[203] Kubose, T. T., Bock K., Dell G. S., Garnsey S. M., Kramer A. F., & Mayhugh J.
(2006).  The effects of speech production and speech comprehension on simulated driving performance.
Applied Cognitive Psychology. 20(1), 43 - 63.

http://www.eurekalert.org/pub_releases/2005-08/jws-cpu082205.php

Cell phone users drive like seniors

Another study on the evils of multitasking, in particular, of talking on a cellphone while driving. This one has a nice spin — the study found that when young motorists talk on cell phones, they drive like elderly people, moving and reacting more slowly and increasing their risk of accidents. Specifically, when 18- to 25-year-olds were placed in a driving simulator and talked on a cellular phone, they reacted to brake lights from a car in front of them as slowly as 65- to 74-year-olds who were not using a cell phone. Although elderly drivers became even slower to react to brake lights when they spoke on a cell phone, they were not as badly affected as had been expected. An earlier study by the same researchers found that motorists who talk on cell phones are more impaired than drunken drivers with blood alcohol levels exceeding 0.08.

[339] Strayer, D. L., & Drew F. A.
(2004).  Profiles in Driver Distraction: Effects of Cell Phone Conversations on Younger and Older Drivers.
Human Factors: The Journal of the Human Factors and Ergonomics Society. 46(4), 640 - 649.

http://www.eurekalert.org/pub_releases/2005-02/uou-cpu020105.php

Complex mental tasks interfere with drivers' ability to detect visual targets

The researchers studied 12 adults who drove for about four hours on the highway north from Madrid. During the journey, drivers listened to recorded audio messages with either abstract or concrete information (acquisition task), and later were required to freely generate a reproduction of what they had just listened to (production task). Although the more receptive tasks – listening and learning -- had little or no effect on performance, there were significant differences in almost all of the measures of attention when drivers had to reproduce the content of the audio message they had just heard. Drivers also performed other tasks, either live or by phone. One was mental calculus (mentally changing between Euros and Spanish pesetas) either with an experimenter in the car, talking to the driver, or with the driver speaking by hands-free phone. One was a memory task (giving detailed information about where they were and what they were doing at a given day and time). Both tasks significantly impacted on the driver's ability to detect visual targets. In the experimental variation that examined the impact of hands-free phone conversation, message complexity made the difference. The relative safety of low-demand phone conversation -- if hands-free and voice-operated --appeared to be about the same as that of live conversation. The findings also confirm that the risk of internal distraction (one’s own thoughts) is at least as relevant as external distraction.

Goldarecena, M.A.R. & González, L.M.N. 2003. Mental Workload While Driving: Effects on Visual Search, Discrimination and Decision Making. Journal of Experimental Psychology: Applied, 9(2)

http://www.eurekalert.org/pub_releases/2003-06/apa-mcm062403.php

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