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.


[2603] Moreno S, Bialystok E, Barac R, Schellenberg EGlenn, Cepeda NJ, Chau T. Short-Term Music Training Enhances Verbal Intelligence and Executive Function. Psychological Science [Internet]. 2011 ;22(11):1425 - 1433. Available from:

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.

Full text is available at



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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, Wada K, Mouritsen H, Jarvis ED. Molecular Mapping of Movement-Associated Areas in the Avian Brain: A Motor Theory for Vocal Learning Origin. PLoS ONE [Internet]. 2008 ;3(3):e1768 - e1768. Available from:

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

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 KE. Learning from explaining: Does it matter if mom is listening?. Journal of Experimental Child Psychology [Internet]. 2008 ;100(3):215 - 224. Available from:

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 SC, Cook SW, Mitchell Z, Goldin-Meadow S. Making Children Gesture Brings Out Implicit Knowledge and Leads to Learning. Journal of Experimental Psychology: General [Internet]. 2007 ;136(4):539 - 550. Available from:

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

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. What Studies of Actors and Acting Can Tell Us About Memory and Cognitive Functioning. Current Directions in Psychological Science [Internet]. 2006 ;15(1):14 - 18. Available from:

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 SD, Wagner S. Explaining math: gesturing lightens the load. Psychological Science: A Journal of the American Psychological Society / APS [Internet]. 2001 ;12(6):516 - 522. Available from:

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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 PJ, Sekuler AB. Age related differences in learning with the useful field of view. Vision Research [Internet]. 2006 ;46(25):4217 - 4231. Available from:

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 HM, Hooper CJ, Yarger RS. The Development of Nonverbal Working Memory and Executive Control Processes in Adolescents. Child Development. 2005 ;76(3):697 - 712.

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 BS, Casey BJ. Psychosocial stress reversibly disrupts prefrontal processing and attentional control. Proceedings of the National Academy of Sciences [Internet]. 2009 ;106(3):912 - 917. Available from:

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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. Does brain asymmetry allow efficient performance of simultaneous tasks?. Animal Behaviour [Internet]. 2006 ;72(3):523 - 529. Available from:

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 GS, Baker R, McCredden JE, Bain JD. How many variables can humans process?. Psychological Science: A Journal of the American Psychological Society / APS [Internet]. 2005 ;16(1):70 - 76. Available from:

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. Functional magnetic resonance imaging provides new constraints on theories of the psychological refractory period. Psychological Science: A Journal of the American Psychological Society / APS [Internet]. 2004 ;15(6):390 - 396. Available from:

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.

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 AD. From the Cover: Cognitive control in media multitaskers. Proceedings of the National Academy of Sciences [Internet]. 2009 ;106(37):15583 - 15587. Available from:

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 JT, Elliott EM, Eaves SD, Exner AL. The distracting effects of a ringing cell phone: An investigation of the laboratory and the classroom setting. Journal of Environmental Psychology [Internet]. 2009 ;29(4):513 - 521. Available from:

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 HM, Parrott DJ, King TZ. Shooting behaviour: How working memory and negative emotionality influence police officer shoot decisions. Applied Cognitive Psychology [Internet]. 2009 ;9999(9999):n/a - n/a. Available from:

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 CM, Cabeza R, Daselaar SM. When Learning and Remembering Compete: A Functional MRI Study. PLoS Biol [Internet]. 2009 ;7(1):e1000011 - e1000011. Available from:

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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 PE, Ivanoff J, Asplund CL, Marois R. Isolation of a Central Bottleneck of Information Processing with Time-Resolved fMRI. Neuron [Internet]. 2006 ;52(6):1109 - 1120. Available from:

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 BJ, Poldrack RA. Modulation of competing memory systems by distraction. Proceedings of the National Academy of Sciences [Internet]. 2006 ;103(31):11778 - 11783. Available from:

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 MA, Carpenter PA, Keller TA, Emery L, Zajac H, Thulborn KR. Interdependence of Nonoverlapping Cortical Systems in Dual Cognitive Tasks. NeuroImage [Internet]. 2001 ;14(2):417 - 426. Available from:

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 JS, Meyer DE, Evans JE. Executive Control of Cognitive Processes in Task Switching,. Journal of Experimental Psychology: Human Perception and Performance [Internet]. 2001 ;27(4):763 - 797. Available from:

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 CC, Theoret H, Pascual-Leone A. Enhanced visual spatial attention ipsilateral to rTMS-induced 'virtual lesions' of human parietal cortex. Nat Neurosci [Internet]. 2001 ;4(9):953 - 957. Available from:

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. Why Does Language Interfere with Vision-Based Tasks?. Experimental Psychology (formerly "Zeitschrift für Experimentelle Psychologie") [Internet]. 2008 ;55(4):260 - 268. Available from:

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 DL, Drews FA, Crouch DJ. A Comparison of the Cell Phone Driver and the Drunk Driver. Human Factors: The Journal of the Human Factors and Ergonomics Society [Internet]. 2006 ;48(2):381 - 391. Available from:,,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. Central interference in driving: is there any stopping the psychological refractory period?. Psychological Science: A Journal of the American Psychological Society / APS [Internet]. 2006 ;17(3):228 - 235. Available from:

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 TT, Bock K, Dell GS, Garnsey SM, Kramer AF, Mayhugh J. The effects of speech production and speech comprehension on simulated driving performance. Applied Cognitive Psychology [Internet]. 2006 ;20(1):43 - 63. Available from:

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 DL, Drew FA. 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 [Internet]. 2004 ;46(4):640 - 649. Available from:

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)

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When age helps decision making

October, 2011

New study modifies findings that younger adults are better decision-makers by showing older adults are better when the scenarios involve multiple considerations.

Research has shown that younger adults are better decision makers than older adults — a curious result. A new study tried to capture more ‘real-world’ decision-making, by requiring participants to evaluate each result in order to strategize the next choice.

This time (whew!), the older adults did better.

In the first experiment, groups of older (60-early 80s) and younger (college-age) adults received points each time they chose from one of four options and tried to maximize the points they earned.  For this task, the younger adults were more efficient at selecting the options that yielded more points.

In the second experiment, the rewards received depended on the choices made previously.  The “decreasing option” gave a larger number of points on each trial, but caused rewards on future trials to be lower. The “increasing option” gave a smaller reward on each trial but caused rewards on future trials to increase.  In one version of the test, the increasing option led to more points earned over the course of the experiment; in another, chasing the increasing option couldn’t make up for the points that could be accrued grabbing the bigger bite on each trial.

The older adults did better on every permutation.

Understanding more complex scenarios is where experience tells. The difference in performance also may reflect the different ways younger and older adults use their brains. Decision-making can involve two different reward learning systems, according to recent thinking. In the model-based system, a cognitive model is constructed that shows how various actions and their rewards are connected to each other. Decisions are made by simulating how one decision will affect future decisions. In the model-free system, on the other hand, only values associated with each choice are considered.

These systems are rooted in different parts of the brain. The model-based system uses the intraparietal sulcus and lateral prefrontal cortex, while the model-free system uses the ventral striatum. There is some evidence that younger adults use the ventral striatum (involved in habitual, reflexive learning and immediate reward) for decision-making more than older adults, and older adults use the dorsolateral prefrontal cortex (involved in more rational, deliberative thinking) more than younger adults.





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Memory fitness program improves memory abilities of oldest adults

October, 2011

A six-week memory fitness program offered to older adults helped improve their ability to recognize and recall words.

In a study involving 115 seniors (average age 81), those who participated in a six-week, 12-session memory training program significantly improved their verbal memory. 15-20 seniors participated in each hour-long class, which included explanations of how memory works, quick strategies for remembering names, faces and numbers, basic memory strategies such as linking ideas and creating visual images, and information on a healthy lifestyle for protecting and maintaining memory.

Most of the study participants were women, Caucasian and had attained a college degree or higher level of education.



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Errorless learning not always best for older brains

October, 2011

New evidence challenges the view that older adults learn best through errorless learning. Trial-and-error learning can be better if done the right way.

Following a 1994 study that found that errorless learning was better than trial-and-error learning for amnesic patients and older adults, errorless learning has been widely adopted in the rehabilitation industry. Errorless learning involves being told the answer without repeatedly trying to answer the question and perhaps making mistakes. For example, in the 1994 study, participants in the trial-and-error condition could produce up to three errors in answer to the question “I am thinking of a word that begins with QU”, before being told the answer was QUOTE; in contrast, participants in the errorless condition were simply told “I am thinking of a word that begins with QU and it is ‘QUOTE’.”

In a way, it is surprising that errorless learning should be better, given that trial-and-error produces much deeper and richer encoding, and a number of studies with young adults have indeed found an advantage for making errors. Moreover, it’s well established that retrieving an item leads to better learning than passively studying it, even when you retrieve the wrong item. This testing effect has also been found in older adults.

In another way, the finding is not surprising at all, because clearly the trial-and-error condition offers many opportunities for confusion. You remember that QUEEN was mentioned, for example, but you don’t remember whether it was a right or wrong answer. Source memory, as I’ve often mentioned, is particularly affected by age.

So there are good theoretical reasons for both positions regarding the value of mistakes, and there’s experimental evidence for both. Clearly it’s a matter of circumstance. One possible factor influencing the benefit or otherwise of error concerns the type of processing. Those studies that have found a benefit have generally involved conceptual associations (e.g. What’s Canada’s capital? Toronto? No, Ottawa). It may be that errors are helpful to the extent that they act as retrieval cues, and evoke a network of related concepts. Those studies that have found errors harm learning have generally involved perceptual associations, such as word stems and word fragments (e.g., QU? QUeen? No, QUote). These errors are arbitrary, produce interference, and don’t provide useful retrieval cues.

So this new study tested the idea that producing errors conceptually associated with targets would boost memory for the encoding context in which information was studied, especially for older adults who do not spontaneously elaborate on targets at encoding.

In the first experiment, 33 young (average age 21) and 31 older adults (average age 72) were shown 90 nouns presented in three different, intermixed conditions. In the read condition (designed to provide a baseline), participants read aloud the noun fragment presented without a semantic category (e.g., p­_g). In the errorless condition, the semantic category was presented with the target word fragment (e.g. a farm animal  p­_g), and the participants read aloud the category and their answer. The category and target were then displayed. In the trial-and-error condition, the category was presented and participants were encouraged to make two guesses before being shown the target fragment together with the category. The researchers changed the target if it was guessed. Participants were then tested using a list of 70 words, of which 10 came from each of the study conditions, 10 were new unrelated words, and 30 were nontarget exemplars from the TEL categories. Those that the subject had guessed were labeled as learning errors; those that hadn’t come up were labeled as related lures. In addition to an overall recognition test (press “yes” to any word you’ve studied and “no” to any new word), there were two tests that required participants to endorse items that were studied in the TEL condition and reject those studied in the EL condition, and vice versa.

The young adults did better than the older on every test. TEL produced better learning than EL, and both produced better learning than the read condition (as expected). The benefit of TEL was greater for older adults. This is in keeping with the idea that generating exemplars of a semantic category, as occurs in trial-and-error learning, helps produce a richer, more elaborated code, and that this is of greater to older adults, who are less inclined to do this without encouragement.

There was a downside, however. Older adults were also more prone to falsely endorsing prior learning errors or semantically-related lures. It’s worth noting that both groups were more likely to falsely endorse learning errors than related lures.

But the main goal of this first experiment was to disentangle the contributions of recollection and familiarity to the two types of learning. It turns out that there was no difference between young and older adults in terms of familiarity; the difference in performance between the two groups stemmed from recollection. Recollection was a problem for older adults in the errorless condition, but not in the trial-and-error condition (where the recollective component of their performance matched that of young adults). This deficit is clearly closely related to age-related deficits in source memory.

It was also found that familiarity was marginally more important in the errorless condition than the trial-and-error condition. This is consistent with the idea that targets learned without errors acquire greater fluency than those learned with errors (with the downside that they don’t pick up those contextual details that making errors can provide).

In the second experiment, 15 young and 15 older adults carried out much the same procedure, except that during the recognition test they were also required to mention the context in which the words were learned was tested (that is, were the words learned through trial-and-error or not).

Once again, trial-and-error learning was associated with better source memory relative to errorless learning, particularly for the older adults.

These results support the hypothesis that trial-and-error learning is more beneficial than errorless learning for older adults when the trials encourage semantic elaboration. But another factor may also be involved. Unlike other errorless studies, participants were required to attend to errors as well as targets. Explicit attention to errors may help protect against interference.

In a similar way, a recent study involving young adults found that feedback given in increments (thus producing errors) is more effective than feedback given all at once in full. Clearly what we want is to find that balance point, where elaborative benefits are maximized and interference is minimized.


[2496] Cyr A-A, Anderson ND. Trial-and-error learning improves source memory among young and older adults. Psychology and Aging. 2011 :No Pagination Specified - No Pagination Specified.


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Whether couple’s collaborative dialogue helps spouse's memory

September, 2011

A small study suggests that middle-aged couples are more likely to be effective than older couples in helping fill in each other’s memory gaps, but effective collaboration also depends on conversational style.

In my book on remembering what you’re doing and what you intend to do, I briefly discuss the popular strategy of asking someone to remind you (basically, whether it’s an effective strategy depends on several factors, of which the most important is the reliability of the person doing the reminding). So I was interested to see a pilot study investigating the use of this strategy between couples.

The study confirms earlier findings that the extent to which this strategy is effective depends on how reliable the partner's memory is, but expands on that by tying it to age and conversational style.

The study involved 11 married couples, of whom five were middle-aged (average age 52), and six were older adults (average age 73). Participants completed a range of prospective memory tasks by playing the board game "Virtual Week," which encourages verbal interaction among players about completing real life tasks. For each virtual "day" in the game, participants were asked to perform 10 different prospective memory tasks — four that regularly occur (eg, taking medication with breakfast), four that were different each day (eg, purchasing gasoline for the car), and two being time-check tasks that were not based on the activities of the board game (eg, check lung capacity at two specified times).

Overall, the middle-aged group benefited more from collaboration than the older group. But it was also found that those couples who performed best were those who were more supportive and encouraging of each other.

Collaboration in memory tasks is an interesting activity, because it can be both helpful and hindering. Think about how memory works — by association. You start from some point, and if you’re on a good track, more and more should be revealed as each memory triggers another. If another person keeps interrupting your train, you can be derailed. On the other hand, they might help you fill you in gaps that you need, or even point you to the right track, if you’re on the wrong one.

In this small study, it tended to be the middle-aged couples that filled in the gaps more effectively than the older couples. That probably has a lot to do with memory reliability. So it’s not a big surprise (though useful to be aware of). But what I find more interesting (because it’s less obvious, and more importantly, because it’s more under our control) is this idea that our conversational style affects whether memory collaboration is useful or counterproductive. I look forward to results from a larger study.


[2490] Margrett JA, Reese-Melancon C, Rendell PG. Examining Collaborative Dialogue Among Couples. Zeitschrift für Psychologie / Journal of Psychology [Internet]. 2011 ;219:100 - 107. Available from:




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Running faster changes brain rhythms associated with learning

September, 2011

A mouse study finds that gamma waves in the hippocampus, critically involved in learning, grow stronger as mice run faster.

I’ve always felt that better thinking was associated with my brain working ‘in a higher gear’ — literally working at a faster rhythm. So I was particularly intrigued by the findings of a recent mouse study that found that brainwaves associated with learning became stronger as the mice ran faster.

In the study, 12 male mice were implanted with microelectrodes that monitored gamma waves in the hippocampus, then trained to run back and forth on a linear track for a food reward. Gamma waves are thought to help synchronize neural activity in various cognitive functions, including attention, learning, temporal binding, and awareness.

We know that the hippocampus has specialized ‘place cells’ that record where we are and help us navigate. But to navigate the world, to create a map of where things are, we need to also know how fast we are moving. Having the same cells encode both speed and position could be problematic, so researchers set out to find how speed was being encoded. To their surprise and excitement, they found that the strength of the gamma rhythm grew substantially as the mice ran faster.

The results also confirmed recent claims that the gamma rhythm, which oscillates between 30 and 120 times a second, can be divided into slow and fast signals (20-45 Hz vs 45-120 Hz for mice, consistent with the 30-55 Hz vs 45-120 Hz bands found in rats) that originate from separate parts of the brain. The slow gamma waves in the CA1 region of the hippocampus were synchronized with slow gamma waves in CA3, while the fast gamma in CA1 were synchronized with fast gamma waves in the entorhinal cortex.

The two signals became increasingly separated with increasing speed, because the two bands were differentially affected by speed. While the slow waves increased linearly, the fast waves increased logarithmically. This differential effect could have to do with mechanisms in the source regions (CA3 and the medial entorhinal cortex, respectively), or to mechanisms in the different regions in CA1 where the inputs terminate (the waves coming from CA3 and the entorhinal cortex enter CA1 in different places).

In the hippocampus, gamma waves are known to interact with theta waves. Further analysis of the data revealed that the effects of speed on gamma rhythm only occurred within a narrow range of theta phases — but this ‘preferred’ theta phase also changed with running speed, more so for the slow gamma waves than the fast gamma waves (which is not inconsistent with the fact that slow gamma waves are more affected by running speed than fast gamma waves). Thus, while slow and fast gamma rhythms preferred similar phases of theta at low speeds, the two rhythms became increasingly phase-separated with increasing running speed.

What’s all this mean? Previous research has shown that if inputs from CA3 and the entorhinal cortex enter CA1 at the same time, the kind of long-term changes at the synapses that bring about learning are stronger and more likely in CA1. So at low speeds, synchronous inputs from CA3 and the entorhinal cortex at similar theta phases make them more effective at activating CA1 and inducing learning. But the faster you move, the more quickly you need to process information. The stronger gamma waves may help you do that. Moreover, the theta phase separation of slow and fast gamma that increases with running speed means that activity in CA3 (slow gamma source) increasingly anticipates activity in the medial entorhinal cortex (fast gamma source).

What does this mean at the practical level? Well at this point it can only be speculation that moving / exercising can affect learning and attention, but I personally am taking this on board. Most of us think better when we walk. This suggests that if you’re having trouble focusing and don’t have time for that, maybe walking down the hall or even jogging on the spot will help bring your brain cells into order!

Pushing speculation even further, I note that meditation by expert meditators has been associated with changes in gamma and theta rhythms. And in an intriguing comparison of the effect of spoken versus sung presentation on learning and remembering word lists, the group that sang showed greater coherence in both gamma and theta rhythms (in the frontal lobes, admittedly, but they weren’t looking elsewhere).

So, while we’re a long way from pinning any of this down, it may be that all of these — movement, meditation, music — can be useful in synchronizing your brain rhythms in a way that helps attention and learning. This exciting discovery will hopefully be the start of an exploration of these possibilities.



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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 DA, Robertson EM. Preventing interference between different memory tasks. Nat Neurosci [Internet]. 2011 ;14(8):953 - 955. Available from:


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