cerebellum

is the main structure in the hindbrain, situated at the base of the brain, at the top of the spinal cord. The cerebellum controls our balance and postural stability, and is involved in motor coordination - not, it appears, in the initial learning of motor skills, but in the performance and improvement of learned motor skills. Some regions of the cerebellum are especially vulnerable to the effects of chronic alcoholism. The hindbrain, although far from the frontal lobes, is connected to those regions, most especially through the pons and the thalamus. Recent rat studies have also suggested that the cerebellum may be involved in some way in remembering strong emotions, in particular, in the consolidation of long-term memories of fear. There is also growing evidence that the cerebellum might also be involved in processing speech and language.

More support for value of cognitive activities in fighting cognitive decline in old age

September, 2012

Two recent conference presentations add to the evidence for the benefits of ‘brain training’, and of mental stimulation, for holding back age-related cognitive decline.

My recent reports on brain training for older adults (see, e.g., Review of working memory training programs finds no broader benefit; Cognitive training shown to help healthy older adults; Video game training benefits cognition in some older adults) converge on the idea that cognitive training can indeed be beneficial for older adults’ cognition, but there’s little wider transfer beyond the skills being practiced. That in itself can be valuable, but it does reinforce the idea that the best cognitive training covers a number of different domains or skill-sets. A new study adds little to this evidence, but does perhaps emphasize the importance of persistence and regularity in training.

The study involved 59 older adults (average age 84), of whom 33 used a brain fitness program 5 days a week for 30 minutes a day for at least 8 weeks, while the other group of 26 were put on a waiting list for the program. After two months, both groups were given access to the program, and both were encouraged to use it as much or as little as they wanted. Cognitive testing occurred before the program started, at two months, and at six months.

The first group to use the program used the program on average for 80 sessions, compared to an average 44 sessions for the wait-list group.

The higher use group showed significantly higher cognitive scores (delayed memory test; Boston Naming test) at both two and six months, while the lower (and later) use group showed improvement at the end of the six month period, but not as much as the higher use group.

I’m afraid I don’t have any more details (some details of the training program would be nice) because it was a conference presentation, so I only have access to the press release and the abstract. Because we don’t know exactly what the training entailed, we don’t know the extent to which it practiced the same skills that were tested. But we may at least add it to the evidence that you can improve cognitive skills by regular training, and that the length/amount of training (and perhaps regularity, since the average number of sessions for the wait-list group implies an average engagement of some three times a week, while the high-use group seem to have maintained their five-times-a-week habit) matters.

Another interesting presentation at the conference was an investigation into mental stimulating activities and brain activity in older adults.

In this study, 151 older adults (average age 82) from the Rush Memory and Aging Project answered questions about present and past cognitive activities, before undergoing brain scans. The questions concerned how frequently they engaged in mentally stimulating activities (such as reading books, writing letters, visiting a library, playing games) and the availability of cognitive resources (such as books, dictionaries, encyclopedias) in their home, during their lifetime (specifically, at ages 6, 12, 18, 40, and now).

Higher levels of cognitive activity and cognitive resources were also associated with better cognitive performance. Moreover, after controlling for education and total brain size, it was found that frequent cognitive activity in late life was associated with greater functional connectivity between the posterior cingulate cortex and several other regions (right orbital and middle frontal gyrus, left inferior frontal gyrus, hippocampus, right cerebellum, left inferior parietal cortex). More cognitive resources throughout life was associated with greater functional connectivity between the posterior cingulate cortex and several other regions (left superior occipital gyrus, left precuneus, left cuneus, right anterior cingulate, right middle frontal gyrus, and left inferior frontal gyrus).

Previous research has implicated a decline in connectivity with the posterior cingulate cortex in mild cognitive impairment and Alzheimer’s disease.

Cognitive activity earlier in life was not associated with differences in connectivity.

The findings provide further support for the idea “Use it or lose it!”, and suggests that mental activity protects against cognitive decline by maintaining functional connectivity in important neural networks.

Reference: 

Miller, K.J. et al. 2012. Memory Improves With Extended Use of Computerized Brain Fitness Program Among Older Adults. Presented August 3 at the 2012 convention of the American Psychological Association.

Han, S.D. et al. 2012. Cognitive Activity and Resources Are Associated With PCC Functional Connectivity in Older Adults. Presented August 3 at the 2012 convention of the American Psychological Association.

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Sleep learning making a comeback?

August, 2012

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

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

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

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

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

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

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

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

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

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

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

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

The findings are consistent with other research.

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

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Why diabetes is linked to cognitive impairment in older adults

January, 2012
  • The link between diabetes and cognitive impairment in older adults seems to be mediated by the release of molecules that increase inflammation, leading to constricted blood vessels, thus reduced blood flow, and finally loss of gray matter.

Why is diabetes associated with cognitive impairment and even dementia in older adults? New research pinpoints two molecules that trigger a cascade of events that end in poor blood flow and brain atrophy.

The study involved 147 older adults (average age 65), of whom 71 had type 2 diabetes and had been taking medication to manage it for at least five years. Brain scans showed that the diabetic patients had greater blood vessel constriction than the age- and sex-matched controls, and more brain atrophy. The reduction in brain tissue was most marked in the grey matter in the parietal and occipital lobes and cerebellum. Research has found that, at this age, while the average brain shrinks by about 1% annually, a diabetic brain might shrink by as much as 15%. Diabetics also had more white matter hyperintensities in the temporal, parietal and occipital lobes.

Behaviorally, the diabetics also had greater depression, slower walking, and executive dysfunction.

The reduced performance of blood vessels (greater vasoconstriction, blunted vasodilatation), and increased brain atrophy in the frontal, temporal, and parietal lobes, was associated with two adhesion molecules – sVCAM and sICAM. White matter hyperintensities were not associated with the adhesion molecules, inflammatory markers, or blood vessel changes.

It seems that the release of these molecules, probably brought about by chronic hyperglycemia and insulin resistance, produces chronic inflammation, which in turn brings about constricted blood vessels, reduced blood flow, and finally loss of neurons. The blood vessel constriction and the brain atrophy were also linked to higher glucose levels.

The findings suggest that these adhesion molecules provide two biomarkers of vascular health that could enable clinicians to recognize impending brain damage, that could then perhaps be prevented.

The findings also add weight to the growing evidence that diabetes management is crucial in preventing cognitive decline.

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IQ can rise or fall significantly during adolescence

November, 2011

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

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

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

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

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

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

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

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Why spaced practice is better

September, 2011

New mouse research helps explain why the spacing effect occurs.

I’ve spoken often about the spacing effect — that it’s better to spread out your learning than have it all massed in a block. A study in which mice were trained on an eye movement task (the task allowed precise measurement of learning in the brain) compared learning durability after massed training or training spread over various spaced intervals (2.5 hours to 8 days, with 30 minute to one day intervals). In the case of massed training, the learning achieved at the end of training disappeared within 24 hours. However learning gained in spaced training did not.

Moreover, when a region in the cerebellum connected to motor nuclei involved in eye movement (the flocculus) was anesthetized, the learning achieved from one hour of massed training was eliminated, while learning achieved from an hour of training spaced out over four hours was unaffected. This suggests that the memories had been transferred out of the flocculus (to the vestibular nuclei) within four hours.

However, when protein synthesis in the flocculus was blocked, learning from spaced training was impaired, while learning from massed training was not. This suggests that proteins synthesized in the flocculus play a vital part in the transfer to the vestibular nuclei.

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Adolescent binge drinking can damage spatial working memory

August, 2011
  • This study finds that adolescent females are particularly vulnerable to the effects of binge drinking, and points to specific changes in brain activation patterns seen in binge drinkers.

Binge drinking occurs most frequently among young people, and there has been concern that consequences will be especially severe if the brain is still developing, as it is in adolescence. Because of the fact that it is only some parts of the brain — most crucially the prefrontal cortex and the hippocampus — that are still developing, it makes sense that only some functions will be affected.

I recently reported on a finding that binge drinking university students, performed more poorly on tests of verbal memory, but not on a test of visual memory. A new study looks at another function: spatial working memory. This task involves the hippocampus, and animal research has indicated that this region may be especially vulnerable to binge drinking. Spatial working memory is involved in such activities as driving, figural reasoning, sports, and navigation.

The study involved 95 adolescents (aged 16-19) from San Diego-area public schools: 40 binge drinking (27 males, 13 females) and 55 control (31 males, 24 females). Brain scans while performing a spatial working memory task revealed that there were significant gender differences in brain activation patterns for those who engaged in binge drinking. Specifically, in eight regions spanning the frontal cortex, anterior cingulate, temporal cortex, and cerebellum, female binge drinkers showed less activation than female controls, while male bingers exhibited greater activation than male controls. For female binge drinkers, less activation was associated with poorer sustained attention and working memory performances, while for male binge drinkers, greater activation was linked to better spatial performance.

The differences between male binge drinkers and controls were smaller than that seen in the female groups, suggesting that female teens may be particularly vulnerable. This is not the first study to find a gender difference in the brains’ response to excess alcohol. In this case it may have to do, at least partly, with differences in maturity — female brains mature earlier than males’.

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Large brains in mammals first evolved for better sense of smell

July, 2011

High-tech X-ray scans of ancient fossil skulls have revealed that the increase in brain size that began with the first mammals was driven by improvements in smell and touch.

190-million-year-old fossil skulls of Morganucodon and Hadrocodium, two of the earliest known mammal species, has revealed that even at this early stage of mammalian evolution, mammals had larger brains than would be expected for their body size. High-resolution CT scans of the skulls have now shown that this increase in brain size can be attributed to an increase in those regions dealing with smell and touch (mammals have a uniquely well developed ability to sense touch through their fur).

Comparison of these fossils with seven fossils of early reptiles (close relatives of the first mammals), 27 other primitive mammals, and 270 living mammals, has further revealed that the size of the mammalian brain evolved in three major stages. First, an initial increase in the olfactory bulb and related areas (including the cerebellum) by 190 million years ago; then another jump in the size of these regions shortly after that time; and finally an increase in those regions that control neuromuscular coordination by integrating different senses by 65 million years ago.

It’s speculated that the initial increase in smell and touch was driven by early mammals being nocturnal — dinosaurs being active during the day.

Reference: 

[2301] Rowe, T. B., Macrini T. E., & Luo Z-X.
(2011).  Fossil Evidence on Origin of the Mammalian Brain.
Science. 332(6032), 955 - 957.

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The importance of the cerebellum for intelligence and age-related cognitive decline

March, 2011
  • A new study of older adults indicates atrophy of the cerebellum is an important factor in cognitive decline for men, but not women.

Shrinking of the frontal lobe has been associated with age-related cognitive decline for some time. But other brain regions support the work of the frontal lobe. One in particular is the cerebellum. A study involving 228 participants in the Aberdeen Longitudinal Study of Cognitive Ageing (mean age 68.7) has revealed that there is a significant relationship between grey matter volume in the cerebellum and general intelligence in men, but not women.

Additionally, a number of other brain regions showed an association between gray matter and intelligence, in particular Brodmann Area 47, the anterior cingulate, and the superior temporal gyrus. Atrophy in the anterior cingulate has been implicated as an early marker of Alzheimer’s, as has the superior temporal gyrus.

The gender difference was not completely unexpected — previous research has indicated that the cerebellum shrinks proportionally more with age in men than women. More surprising was the fact that there was no significant association between white memory volume and general intelligence. This contrasts with the finding of a study involving older adults aged 79-80. It is speculated that this association may not develop until greater brain atrophy has occurred.

It is also interesting that the study found no significant relationship between frontal lobe volume and general intelligence — although the effect of cerebellar volume is assumed to occur via its role in supporting the frontal lobe.

The cerebellum is thought to play a vital role in three relevant areas: speed of information processing; variability of information processing; development of automaticity through practice.

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Mindfulness meditation training changes brain structure in 8 weeks

February, 2011

After 8 weeks practicing mindfulness meditation, measurable changes occurred in brain regions associated with memory and emotion.

Brain images of 16 participants in an 8-week mindfulness meditation program, taken two weeks before and after the program, have found measurable changes in brain regions associated with memory, sense of self, empathy and stress. Specifically, they showed increased grey-matter density in the left hippocampus, posterior cingulate cortex, temporo-parietal junction, and cerebellum, as well as decreased grey-matter density in the amygdala. Similar brain scans of a control group of non-meditators (those on a waiting list for the program) showed no such changes over time.

Although a number of studies have found differences in the brains of experienced meditators and those who don’t practice meditation, this is the first to demonstrate that those differences are actually produced by meditation.

The Mindfulness-Based Stress Reduction program involved weekly meetings that included practice of mindfulness meditation and audio recordings for guided meditation practice. Participants reported spending an average of 27 minutes each day practicing mindfulness exercises.

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How taking an active role in learning enhances memory

January, 2011

Being actively involved improves learning significantly, and new research shows that the hippocampus is at the heart of this process.

We know active learning is better than passive learning, but for the first time a study gives us some idea of how that works. Participants in the imaging study were asked to memorize an array of objects and their exact locations in a grid on a computer screen. Only one object was visible at a time. Those in the "active study” group used a computer mouse to guide the window revealing the objects, while those in the “passive study” group watched a replay of the window movements recorded in a previous trial by an active subject. They were then tested by having to place the items in their correct positions. After a trial, the active and passive subjects switched roles and repeated the task with a new array of objects.

The active learners learned the task significantly better than the passive learners. Better spatial recall correlated with higher and better coordinated activity in the hippocampus, dorsolateral prefrontal cortex, and cerebellum, while better item recognition correlated with higher activity in the inferior parietal lobe, parahippocampal cortex and hippocampus.

The critical role of the hippocampus was supported when the experiment was replicated with those who had damage to this region — for them, there was no benefit in actively controlling the viewing window.

This is something of a surprise to researchers. Although the hippocampus plays a crucial role in memory, it has been thought of as a passive participant in the learning process. This finding suggests that it is actually part of an active network that controls behavior dynamically.

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