Prefrontal Cortex

A recent study reveals that when we focus on searching for something, regions across the brain are pulled into the search. The study sheds light on how attention works.

In the experiments, brain activity was recorded as participants searched for people or vehicles in movie clips. Computational models showed how each of the roughly 50,000 locations near the cortex responded to each of the 935 categories of objects and actions seen in the movie clips.

When participants searched for humans, relatively more of the cortex was devoted to humans, and when they searched for vehicles, more of the cortex was devoted to vehicles.

Now this might not sound very surprising, but it appears to contradict our whole developing picture of the brain as having specialized areas for specific categories — instead, areas normally involved in recognizing categories such as plants or buildings were being switched to become attuned to humans or vehicles. The changes occurred across the brain, not just in those regions devoted to vision, and in fact, the largest changes were seen in the prefrontal cortex.

What this suggests is that categories are represented in highly organized, continuous maps, a ‘semantic space’, as it were. By increasing the representation of the target category (and related categories) at the expense of other categories, this semantic space is changed. Note that this did not come about in response to the detection of the target; it occurred in response to the direction of attention — the goal setting.

In other words, in the same way that gravity warps the space-time continuum (well, probably not the exact same way!), attention warps your mental continuum.

You can play with an interactive online brain viewer which tries to portray this semantic space.

http://www.futurity.org/science-technology/to-find-whats-lost-brain-forms-search-party/

[3417] Çukur T, Nishimoto S, Huth AG, Gallant JL. Attention during natural vision warps semantic representation across the human brain. Nature Neuroscience [Internet]. 2013 ;advance online publication. Available from: http://www.nature.com/neuro/journal/vaop/ncurrent/full/nn.3381.html

A new finding points to brain reorganization, rather than brain size, as the driver in primate brain evolution. Data from 17 anthropoid primate species (including humans) across 40 million years has found that around three quarters of differences between the brains of species of monkeys and apes are due to internal reorganization that is independent of size. The prefrontal cortex in particular appears to have played the biggest role in explaining the evolutionary changes in primate brains.

http://phys.org/news/2013-03-organisation-trumps-size-primate-brain.html

[3366] Smaers JB, Soligo C. Brain reorganization, not relative brain size, primarily characterizes anthropoid brain evolution. Proceedings of the Royal Society B: Biological Sciences [Internet]. 2013 ;280(1759). Available from: http://rspb.royalsocietypublishing.org/content/280/1759/20130269

Problems with myelin — demyelination (seen most dramatically in MS, but also in other forms of neurodegeneration, including normal aging and depression); failure to develop sufficient myelin (in children and adolescents) — are increasingly being implicated in a wide range of disorders. A new animal study adds to that evidence by showing that social isolation brings about both depression and loss of myelin.

In the study, adult mice were isolated for eight weeks (which is of course longer for a mouse than it is to us) to induce a depressive-like state. They were then introduced to a mouse they hadn’t seen before. Although typically very social animals, those who had been socially isolated didn’t show any interest in interacting with the new mouse — a common pattern in human behavior as well.

Analysis of their brains revealed significantly lower levels of gene transcription for oligodendrocyte cells (the components of myelin) in the prefrontal cortex. This appeared to be caused by a lower production of heterochromatin (tightly packed DNA) in the cell nuclei, producing less mature oligodendrocytes.

Interestingly, even short periods of isolation were sufficient to produce changes in chromatin and myelin, although behavior wasn’t affected.

Happily, however, regardless of length of isolation, myelin production went back to normal after a period of social integration.

The findings add to the evidence that environmental factors can have significant effects on brain development and function, and support the idea that socializing is good for the brain.

A study using data from the Lothian Birth Cohort (people born in Scotland in 1936) has analyzed brain scans of 638 participants when they were 73 years old. Comparing this data with participants’ earlier reports of their exercise and leisure activities at age 70, it was found that those who reported higher levels of regular physical activity showed significantly less brain atrophy than those who did minimal exercise. Participation in social and mentally stimulating activities, on the other hand, wasn’t associated with differences in brain atrophy.

Regular physical exercise was also associated with fewer white matter lesions. While leisure activity was also associated with healthier white matter, this was not significant after factors such as age, social class, and health status were taken into account.

Unfortunately, this study is reported in a journal to which I don’t have access. I would love to have more details about the leisure activities data and the brain scans. However, although the failure to find a positive effect of stimulating activities is disappointing, it’s worth noting another recent study, that produced two relevant findings. First, men with high levels of cognitive activity showed a significant reduction in white matter lesions, while women did not. Women with high levels of cognitive activity, on the other hand, showed less overall brain atrophy — but men did not.

Secondly, both genders showed less atrophy in a particular region of the prefrontal cortex, but there was no effect on the hippocampus — the natural place to look for effects (and the region where physical exercise is known to have positive effects).

In other words, the positive effects of cognitive activity on the brain might be quite different from the positive effects of physical exercise.

The findings do, of course, add to the now-compelling evidence for the benefits of regular physical activity in fighting cognitive decline.

It’s good news, then, that a small study has found that even frail seniors can derive significant benefits from exercise.

The study involved 83 older adults (61-89), some of whom were considered frail. Forty-three took part in group exercises (3 times a week for 12 weeks), while 40 were wait-listed controls. Participants were assessed for physical capacity, quality of life and cognitive health a week before the program began, and at the end.

Those who took part in the exercise program significantly improved their physical capacity, cognitive performance, and quality of life. These benefits were equivalent among frail and non-frail participants.

Frailty is associated with a higher risk of falls, hospitalizations, cognitive decline and psychological distress, and, of course, increases with age. In the U.S, it’s estimated that 7% of seniors aged 65 to 74, 18% of those aged 75 to 84, and 37% of seniors over the age of 85 are frail.

What underlies differences in fluid intelligence? How are smart brains different from those that are merely ‘average’?

Brain imaging studies have pointed to several aspects. One is brain size. Although the history of simplistic comparisons of brain size has been turbulent (you cannot, for example, directly compare brain size without taking into account the size of the body it’s part of), nevertheless, overall brain size does count for something — 6.7% of individual variation in intelligence, it’s estimated. So, something, but not a huge amount.

Activity levels in the prefrontal cortex, research also suggests, account for another 5% of variation in individual intelligence. (Do keep in mind that these figures are not saying that, for example, prefrontal activity explains 5% of intelligence. We are talking about differences between individuals.)

A new study points to a third important factor — one that, indeed, accounts for more than either of these other factors. The strength of the connections from the left prefrontal cortex to other areas is estimated to account for 10% of individual differences in intelligence.

These findings suggest a new perspective on what intelligence is. They suggest that part of intelligence rests on the functioning of the prefrontal cortex and its ability to communicate with the rest of the brain — what researchers are calling ‘global connectivity’. This may reflect cognitive control and, in particular, goal maintenance. The left prefrontal cortex is thought to be involved in (among other things) remembering your goals and any instructions you need for accomplishing those goals.

The study involved 93 adults (average age 23; range 18-40), whose brains were monitored while they were doing nothing and when they were engaged in the cognitively challenging N-back working memory task.

Brain activity patterns revealed three regions within the frontoparietal network that were significantly involved in this task: the left lateral prefrontal cortex, right premotor cortex, and right medial posterior parietal cortex. All three of these regions also showed signs of being global hubs — that is, they were highly connected to other regions across the brain.

Of these, however, only the left lateral prefrontal cortex showed a significant association between its connectivity and individual’s fluid intelligence. This was confirmed by a second independent measure — working memory capacity — which was also correlated with this region’s connectivity, and only this region.

In other words, those with greater connectivity in the left LPFC had greater cognitive control, which is reflected in higher working memory capacity and higher fluid intelligence. There was no correlation between connectivity and crystallized intelligence.

Interestingly, although other global hubs (such as the anterior prefrontal cortex and anterior cingulate cortex) also have strong relationships with intelligence and high levels of global connectivity, they did not show correlations between their levels of connectivity and fluid intelligence. That is, although the activity within these regions may be important for intelligence, their connections to other brain regions are not.

So what’s so important about the connections the LPFC has with the rest of the brain? It appears that, although it connects widely to sensory and motor areas, it is primarily the connections within the frontoparietal control network that are most important — as well as the deactivation of connections with the default network (the network active during rest).

This is not to say that the LPFC is the ‘seat of intelligence’! Research has made it clear that a number of brain regions support intelligence, as do other areas of connectivity. The finding is important because it shows that the left LPFC supports cognitive control and intelligence through a mechanism involving global connectivity and some other as-yet-unknown property. One possibility is that this region is a ‘flexible’ hub — able to shift its connectivity with a number of different brain regions as the task demands.

In other words, what may count is how many different connectivity patterns the left LPFC has in its repertoire, and how good it is at switching to them.

An association between negative connections with the default network and fluid intelligence also adds to evidence for the importance of inhibiting task-irrelevant processing.

All this emphasizes the role of cognitive control in intelligence, and perhaps goes some way to explaining why self-regulation in children is so predictive of later success, apart from the obvious.

I’ve reported before on the evidence suggesting that carriers of the ‘Alzheimer’s gene’, APOE4, tend to have smaller brain volumes and perform worse on cognitive tests, despite being cognitively ‘normal’. However, the research hasn’t been consistent, and now a new study suggests the reason.

The e4 variant of the apolipoprotein (APOE) gene not only increases the risk of dementia, but also of cardiovascular disease. These effects are not unrelated. Apoliproprotein is involved in the transportation of cholesterol. In older adults, it has been shown that other vascular risk factors (such as elevated cholesterol, hypertension or diabetes) worsen the cognitive effects of having this gene variant.

This new study extends the finding, by looking at 72 healthy adults from a wide age range (19-77).

Participants were tested on various cognitive abilities known to be sensitive to aging and the effects of the e4 allele. Those abilities include speed of information processing, working memory and episodic memory. Blood pressure, brain scans, and of course genetic tests, were also performed.

There are a number of interesting findings:

  • The relationship between age and hippocampal volume was stronger for those carrying the e4 allele (shrinkage of this brain region occurs with age, and is significantly greater in those with MCI or dementia).
  • Higher systolic blood pressure was significantly associated with greater atrophy (i.e., smaller volumes), slower processing speed, and reduced working memory capacity — but only for those with the e4 variant.
  • Among those with the better and more common e3 variant, working memory was associated with lateral prefrontal cortex volume and with processing speed. Greater age was associated with higher systolic blood pressure, smaller volumes of the prefrontal cortex and prefrontal white matter, and slower processing. However, blood pressure was not itself associated with either brain atrophy or slower cognition.
  • For those with the Alzheimer’s variant (e4), older adults with higher blood pressure had smaller volumes of prefrontal white matter, and this in turn was associated with slower speed, which in turn linked to reduced working memory.

In other words, for those with the Alzheimer’s gene, age differences in working memory (which underpin so much of age-related cognitive impairment) were produced by higher blood pressure, reduced prefrontal white matter, and slower processing. For those without the gene, age differences in working memory were produced by reduced prefrontal cortex and prefrontal white matter.

Most importantly, these increases in blood pressure that we are talking about are well within the normal range (although at the higher end).

The researchers make an interesting point: that these findings are in line with “growing evidence that ‘normal’ should be viewed in the context of individual’s genetic predisposition”.

What it comes down to is this: those with the Alzheimer’s gene variant (and no doubt other genetic variants) have a greater vulnerability to some of the risk factors that commonly increase as we age. Those with a family history of dementia or serious cognitive impairment should therefore pay particular attention to controlling vascular risk factors, such as hypertension and diabetes.

This doesn’t mean that those without such a family history can safely ignore such conditions! When they get to the point of being clinically diagnosed as problems, then they are assuredly problems for your brain regardless of your genetics. What this study tells us is that these vascular issues appear to be problematic for Alzheimer’s gene carriers before they get to that point of clinical diagnosis.

This is another demonstration of stereotype threat, which is also a nice demonstration of the contextual nature of intelligence. The study involved 70 volunteers (average age 25; range 18-49), who were put in groups of 5. Participants were given a baseline IQ test, on which they were given no feedback. The group then participated in a group IQ test, in which 92 multi-choice questions were presented on a monitor (both individual and group tests were taken from Cattell’s culture fair intelligence test). Each question appeared to each person at the same time, for a pre-determined time. After each question, they were provided with feedback in the form of their own relative rank within the group, and the rank of one other group member. Ranking was based on performance on the last 10 questions. Two of each group had their brain activity monitored.

Here’s the remarkable thing. If you gather together individuals on the basis of similar baseline IQ, then you can watch their IQ diverge over the course of the group IQ task, with some dropping dramatically (e.g., 17 points from a mean IQ of 126). Moreover, even those little affected still dropped some (8 points from a mean IQ of 126).

Data from the 27 brain scans (one had to be omitted for technical reasons) suggest that everyone was initially hindered by the group setting, but ‘high performers’ (those who ended up scoring above the median) managed to largely recover, while ‘low performers’ (those who ended up scoring below the median) never did.

Personality tests carried out after the group task found no significant personality differences between high and low performers, but gender was a significant variable: 10/13 high performers were male, while 11/14 low performers were female (remember, there was no difference in baseline IQ — this is not a case of men being smarter!).

There were significant differences between the high and low performers in activity in the amygdala and the right lateral prefrontal cortex. Specifically, all participants had an initial increase in amygdala activation and diminished activity in the prefrontal cortex, but by the end of the task, the high-performing group showed decreased amygdala activation and increased prefrontal cortex activation, while the low performers didn’t change. This may reflect the high performers’ greater ability to reduce their anxiety. Activity in the nucleus accumbens was similar in both groups, and consistent with the idea that the students had expectations about the relative ranking they were about to receive.

It should be pointed out that the specific feedback given — the relative ranking — was not a factor. What’s important is that it was being given at all, and the high performers were those who became less anxious as time went on, regardless of their specific ranking.

There are three big lessons here. One is that social pressure significantly depresses talent (meetings make you stupid?), and this seems to be worse when individuals perceive themselves to have a lower social rank. The second is that our ability to regulate our emotions is important, and something we should put more energy into. And the third is that we’ve got to shake ourselves loose from the idea that IQ is something we can measure in isolation. Social context matters.

The olfactory bulb is in the oldest part of our brain. It connects directly to the amygdala (our ‘emotion center’) and our prefrontal cortex, giving smells a more direct pathway to memory than our other senses. But the olfactory bulb is only part of the system processing smells. It projects to several other regions, all of which are together called the primary olfactory cortex, and of which the most prominent member is the piriform cortex. More recently, however, it has been suggested that it would be more useful to regard the olfactory bulb as the primary olfactory cortex (primary in the sense that it is first), while the piriform cortex should be regarded as association cortex — meaning that it integrates sensory information with ‘higher-order’ (cognitive, contextual, and behavioral) information.

Testing this hypothesis, a new rat study has found that, when rats were given training to distinguish various odors, each smell produced a different pattern of electrical activity in the olfactory bulb. However, only those smells that the rat could distinguish from others were reflected in distinct patterns of brain activity in the anterior piriform cortex, while smells that the rat couldn’t differentiate produced identical brain activity patterns there. Interestingly, the smells that the rats could easily distinguish were ones in which one of the ten components in the target odor had been replaced with a new component. The smells they found difficult to distinguish were those in which a component had simply been deleted.

When a new group of rats was given additional training (8 days vs the 2 days given the original group), they eventually learned to discriminate between the odors the first animals couldn’t distinguish, and this was reflected in distinct patterns of brain activity in the anterior piriform cortex. When a third group were taught to ignore the difference between odors the first rats could readily distinguish, they became unable to tell the odors apart, and similar patterns of brain activity were produced in the piriform cortex.

The effects of training were also quite stable — they were still evident after two weeks.

These findings support the idea of the piriform cortex as association cortex. It is here that experience modified neuronal activity. In the olfactory bulb, where all the various odors were reflected in different patterns of activity right from the beginning (meaning that this part of the brain could discriminate between odors that the rat itself couldn’t distinguish), training made no difference to the patterns of activity.

Having said that, it should be noted that this is not entirely consistent with previous research. Several studies have found that odor training produces changes in the representations in the olfactory bulb. The difference may lie in the method of neural recording.

How far does this generalize to the human brain? Human studies have suggested that odors are represented in the posterior piriform cortex rather than the anterior piriform cortex. They have also suggested that the anterior piriform cortex is involved in expectations relating to the smells, rather than representing the smells themselves. Whether these differences reflect species differences, task differences, or methodological differences, remains to be seen.

But whether or not the same exact regions are involved, there are practical implications we can consider. The findings do suggest that one road to olfactory impairment is through neglect — if you learn to ignore differences between smells, you will become increasingly less able to do so. An impaired sense of smell has been found in Alzheimer’s disease, Parkinson's disease, schizophrenia, and even normal aging. While some of that may well reflect impairment earlier in the perception process, some of it may reflect the consequences of neglect. The burning question is, then, would it be possible to restore smell function through odor training?

I’d really like to see this study replicated with old rats.

The study involved 1,292 children followed from birth, whose cortisol levels were assessed at 7, 15, and 24 months. Three tests related to executive functions were given at age 3. Measures of parenting quality (maternal sensitivity, detachment, intrusiveness, positive regard, negative regard, and animation, during interaction with the child) and household environment (household crowding, safety and noise levels) were assessed during the home visits.

Earlier studies have indicated that a poor environment in and of itself is stressful to children, and is associated with increased cortisol levels. Interestingly, in one Mexican study, preschool children in poor homes participating in a conditional cash transfer scheme showed reduced cortisol levels.

This study found that children in lower-income homes received less positive parenting and had higher levels of cortisol in their first two years than children in slightly better-off homes. Higher levels of cortisol were associated with lower levels of executive function abilities, and to a lesser extent IQ, at 3 years.

African American children were more affected than White children on every measure. Cortisol levels were significantly higher; executive function and IQ significantly lower; ratings of positive parenting significantly lower and ratings of negative parenting significantly higher. Maternal education was significantly lower, poverty greater, homes more crowded and less safe.

The model derived from this data shows executive function negatively predicted by cortisol, while the effect on IQ is marginal. However, both executive function and IQ are predicted by negative parenting, positive parenting, and household risk (although this last variable has a greater effect on IQ than executive function). Neither executive function nor IQ was directly predicted by maternal education, ethnicity, or poverty level. Cortisol level was inversely related to positive parenting, but was not directly related to negative parenting or household risk.

Indirectly (according to this best-fit model), poverty was related to executive function through negative parenting; maternal education was related to executive function through negative parenting and to a lesser extent positive parenting; both poverty and maternal education were related to IQ through positive parenting, negative parenting, and household risk; African American ethnicity was related to executive function through negative parenting and positive parenting, and to IQ through negative parenting, positive parenting, and household risk. Cortisol levels were higher in African American children and this was unrelated to poverty level or maternal education.

Executive function (which includes working memory, inhibitory control, and attention shifting) is vital for self-regulation and central to early academic achievement. A link between cortisol level and executive function has previously been shown in preschool children, as well as adults. The association partly reflects the fact that stress hormone levels affect synaptic plasticity in the prefrontal cortex, where executive functions are carried out. This is not to say that this is the only brain region so affected, but it is an especially sensitive one. Chronic levels of stress alter the stress response systems in ways that impair flexible regulation.

What is important about this study is this association between stress level and cognitive ability at an early age, that the effect of parenting on cortisol is associated with positive aspects rather than negative ones, and that the association between poverty and cognitive ability is mediated by both cortisol and parenting behavior — both positive and negative aspects.

A final word should be made on the subject of the higher cortisol levels in African Americans. Because of the lack of high-income African Americans in the sample (a reflection of the participating communities), it wasn’t possible to directly test whether the effect is accounted for by poverty. So this remains a possibility. It is also possible that there is some genetic difference. But it also might reflect other sources of stress, such as that relating to prejudice and stereotype threat.

Based on mother’s ethnic status, 58% of the families were Caucasian and 42% African American. Two-thirds of the participants had an income-to-need ratio (estimated total household income divided by the 2005 federal poverty threshold adjusted for number of household members) less than 200% of poverty. Just over half of the mothers weren’t married, and most of them (89%) had never been married. The home visits at 7, 15, and 24 months lasted at least an hour, and include a videotaped free play or puzzle completion interaction between mother and child. Cortisol samples were taken prior to an emotion challenge task, and 20 minutes and 40 minutes after peak emotional arousal.

Long-term genetic effects of childhood environment

The long-term effects of getting off to a poor start are deeper than you might believe. A DNA study of forty 45-year-old males in a long-running UK study has found clear differences in gene methylation between those who experienced either very high or very low standards of living as children or adults (methylation of a gene at a significant point in the DNA reduces the activity of the gene). More than twice as many methylation differences were associated with the combined effect of the wealth, housing conditions and occupation of parents (that is, early upbringing) than were associated with the current socio-economic circumstances in adulthood (1252 differences as opposed to 545).

The findings may explain why the health disadvantages known to be associated with low socio-economic position can remain for life, despite later improvement in living conditions. The methylation profiles associated with childhood family living conditions were clustered together in large stretches of DNA, which suggests that a well-defined epigenetic pattern is linked to early socio-economic environment. Adult diseases known to be associated with early life disadvantage include coronary heart disease, type 2 diabetes and respiratory disorders.

[2589] Blair C, Granger DA, Willoughby M, Mills-Koonce R, Cox M, Greenberg MT, Kivlighan KT, Fortunato CK, the Investigators FLP. Salivary Cortisol Mediates Effects of Poverty and Parenting on Executive Functions in Early Childhood. Child Development [Internet]. 2011 :no - no. Available from: http://dx.doi.org/10.1111/j.1467-8624.2011.01643.x

Fernald, L. C., & Gunnar, M. R. (2009). Poverty-alleviation program participation and salivary cortisol in very low-income children. Social Science and Medicine, 68, 2180–2189.

[2590] Borghol N, Suderman M, McArdle W, Racine A, Hallett M, Pembrey M, Hertzman C, Power C, Szyf M. Associations with early-life socio-economic position in adult DNA methylation. International Journal of Epidemiology [Internet]. 2011 . Available from: http://ije.oxfordjournals.org/content/early/2011/10/18/ije.dyr147.abstract

Research into the effects of cannabis on cognition has produced inconsistent results. Much may depend on extent of usage, timing, and perhaps (this is speculation) genetic differences. But marijuana abuse is common among sufferers of schizophrenia and recent studies have shown that the psychoactive ingredient of marijuana can induce some symptoms of schizophrenia in healthy volunteers.

Now new research helps explain why marijuana is linked to schizophrenia, and why it might have detrimental effects on attention and memory.

In this rat study, a drug that mimics the psychoactive ingredient of marijuana (by activating the cannabinoid receptors) produced significant disruption in brain networks, with brain activity becoming uncoordinated and inaccurate.

In recent years it has become increasingly clear that synchronized brainwaves play a crucial role in information processing — especially that between the hippocampus and prefrontal cortex (see, for example, my reports last month on theta waves improving retrieval and the effect of running on theta and gamma rhythms). Interactions between the hippocampus and prefrontal cortex seem to be involved in working memory functions, and may provide the mechanism for bringing together memory and decision-making during goal-directed behaviors.

Consistent with this, during decision-making on a maze task, hippocampal theta waves and prefrontal gamma waves were impaired, and the theta synchronization between the two was disrupted. These effects correlated with impaired performance on the maze task.

These findings are consistent with earlier findings that drugs that activate the cannabinoid receptors disrupt the theta rhythm in the hippocampus and impair spatial working memory. This experiment extends that result to coordinated brainwaves beyond the hippocampus.

Similar neural activity is observed in schizophrenia patients, as well as in healthy carriers of a genetic risk variant.

The findings add to the evidence that working memory processes involve coordination between the prefrontal cortex and the hippocampus through theta rhythm synchronization. The findings are consistent with the idea that items are encoded and indexed along the phase of the theta wave into episodic representations and transferred from the hippocampus to the neocortex as a theta phase code. By disrupting that code, cannabis makes it more difficult to retain and index the information relevant to the task at hand.

A ten-year study involving 7,239 older adults (65+) has found that each common health complaint increased dementia risk by an average of about 3%, and that these individual risks compounded. Thus, while a healthy older adult had about an 18% chance of developing dementia after 10 years, those with a dozen of these health complaints had, on average, closer to a 40% chance.

It’s important to note that these complaints were not for serious disorders that have been implicated in Alzheimer’s. The researchers constructed a ‘frailty’ index, involving 19 different health and wellbeing factors: overall health, eyesight, hearing, denture fit, arthritis/rheumatism, eye trouble, ear trouble, stomach trouble, kidney trouble, bladder control, bowel control, feet/ankle trouble, stuffy nose/sneezing, bone fractures, chest problems, cough, skin problems, dental problems, other problems.

Not all complaints are created equal. The most common complaint — arthritis/rheumatism —was only slightly higher among those with dementia. Two of the largest differences were poor eyesight (3% of the non-demented group vs 9% of those with dementia) and poor hearing (3% and 6%).

At the end of the study, 4,324 (60%) were still alive, and of these, 416 (9.6%) had Alzheimer's disease, 191 (4.4%) had another sort of dementia and 677 (15.7%) had other cognitive problems (but note that 1,023 were of uncertain cognitive ability).

While these results need to be confirmed in other research — the study used data from broader health surveys that weren’t specifically designed for this purpose, and many of those who died during the study will have probably had dementia — they do suggest the importance of maintaining good general health.

Common irregular heartbeat raises risk of dementia

In another study, which ran from 1994 to 2008 and followed 3,045 older adults (mean age 74 at study start), those with atrial fibrillation were found to have a significantly greater risk of developing Alzheimer’s.

At the beginning of the study, 4.3% of the participants had atrial fibrillation (the most common kind of chronically irregular heartbeat); a further 12.2% developed it during the study. Participants were followed for an average of seven years. Over this time, those with atrial fibrillation had a 40-50% higher risk of developing dementia of any type, including probable Alzheimer's disease. Overall, 18.8% of the participants developed some type of dementia during the course of the study.

While atrial fibrillation is associated with other cardiovascular risk factors and disease, this study shows that atrial fibrillation increases dementia risk more than just through this association. Possible mechanisms for this increased risk include:

  • weakening the heart's pumping ability, leading to less oxygen going to the brain;
  • increasing the chance of tiny blood clots going to the brain, causing small, clinically undetected strokes;
  • a combination of these plus other factors that contribute to dementia such as inflammation.

The next step is to see whether any treatments for atrial fibrillation reduce the risk of developing dementia.

Stress may increase risk for Alzheimer's disease

And a rat study has shown that increased release of stress hormones leads to cognitive impairment and that characteristic of Alzheimer’s disease, tau tangles. The rats were subjected to stress for an hour every day for a month, by such means as overcrowding or being placed on a vibrating platform. These rats developed increased hyperphosphorylation of tau protein in the hippocampus and prefrontal cortex, and these changes were associated with memory deficits and impaired behavioral flexibility.

Previous research has shown that stress leads to that other characteristic of Alzheimer’s disease: the formation of beta-amyloid.

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.

In the study, two rhesus monkeys were given a standard human test of working memory capacity: an array of colored squares, varying from two to five squares, was shown for 800 msec on a screen. After a delay, varying from 800 to 1000 msec, a second array was presented. This array was identical to the first except for a change in color of one item. The monkey was rewarded if its eyes went directly to this changed square (an infra-red eye-tracking system was used to determine this). During all this, activity from single neurons in the lateral prefrontal cortex and the lateral intraparietal area — areas critical for short-term memory and implicated in human capacity limitations — was recorded.

As with humans, the more squares in the array, the worse the performance (from 85% correct for two squares to 66.5% for 5). Their working memory capacity was calculated at 3.88 objects — i.e. the same as that of humans.

That in itself is interesting, speaking as it does to the question of how human intelligence differs from other animals. But the real point of the exercise was to watch what is happening at the single neuron level. And here a surprise occurred.

That total capacity of around 4 items was composed of two independent, smaller capacities in the right and left halves of the visual space. What matters is how many objects are in the hemifield an eye is covering. Each hemifield can only handle two objects. Thus, if the left side of the visual space contains three items, and the right side only one, information about the three items from the left side will be degraded. If the left side contains four items and the right side two, those two on the right side will be fine, but information from the four items on the left will be degraded.

Notice that the effect of more items than two in a hemifield is to decrease the total information from all the items in the hemifield — not to simply lose the additional items.

The behavioral evidence correlated with brain activity, with object information in LPFC neurons decreasing with increasing number of items in the same hemifield, but not the opposite hemifield, and the same for the intraparietal neurons (the latter are active during the delay; the former during the presentation).

The findings resolve a long-standing debate: does working memory function like slots, which we fill one by one with items until all are full, or as a pool that fills with information about each object, with some information being lost as the number of items increases? And now we know why there is evidence for both views, because both contain truth. Each hemisphere might be considered a slot, but each slot is a pool.

Another long-standing question is whether the capacity limit is a failure of perception or  memory. These findings indicate that the problem is one of perception. The neural recordings showed information about the objects being lost even as the monkeys were viewing them, not later as they were remembering what they had seen.

All of this is important theoretically, but there are also immediate practical applications. The work suggests that information should be presented in such a way that it’s spread across the visual space — for example, dashboard displays should spread the displays evenly on both sides of the visual field; medical monitors that currently have one column of information should balance it in right and left columns; security personnel should see displays scrolled vertically rather than horizontally; working memory training should present information in a way that trains each hemisphere separately. The researchers are forming collaborations to develop these ideas.

[2335] Buschman TJ, Siegel M, Roy JE, Miller EK. Neural substrates of cognitive capacity limitations. Proceedings of the National Academy of Sciences [Internet]. 2011 . Available from: http://www.pnas.org/content/early/2011/06/13/1104666108.abstract

In the study, 18 children (aged 7-8), 20 adolescents (13-14), and 20 young adults (20-29) were shown pictures and asked to decide whether it was a new picture or one they had seen earlier. Some of the pictures were of known objects and others were fanciful figures (this was in order to measure the effects of novelty in general). After a 10-minute break, they resumed the task — with the twist that any pictures that had appeared in the first session should be judged “new” if that was the first appearance in the second session. EEG measurements (event-related potentials — ERPs) were taken during the sessions.

ERPs at the onset of a test stimulus (each picture) are different for new and old (repeated) stimuli. Previous studies have established various old/new effects that reflect item and source memory in adults. In the case of item memory, recognition is thought to be based on two processes — familiarity and recollection — which are reflected in ERPs of different timings and location (familiarity: mid-frontal at 300-500 msec; recollection: parietal at 400-70 msec). Familiarity is seen as a fast assessment of similarity, while recollection varies according to the amount of retrieved information.

Source memory appears to require control processes that involve the prefrontal cortex. Given that this region is the slowest to mature, it would not be surprising if source memory is a problematic memory task for the young. And indeed, previous research has found that children do have particular difficulty in sourcing memories when the sources are highly similar.

In the present study, children performed more poorly than adolescents and adults on both item memory and source memory. Adolescents performed more poorly than adults on item memory but not on source memory. Children performed more poorly on source memory than item memory, but adolescents and adults showed no difference between the two tasks.

All groups responded faster to new items than old, and ERP responses to general novelty were similar across the groups — although children showed a left-frontal focus that may reflect the transition from analytic to a more holistic processing approach.

ERPs to old items, however, showed a difference: for adults, they were especially pronounced at frontal sites, and occurred at around 350-450 msec; for children and adolescents they were most pronounced at posterior sites, occurring at 600-800 msec for children and 400-600 msec for adolescents. Only adults showed the early midfrontal response that is assumed to reflect familiarity processing. On the other hand, the late old/new effect occurring at parietal sites and thought to reflect recollection, was similar across all age groups. The early old/new effect seen in children and adolescents at central and parietal regions is thought to reflect early recollection.

In other words, only adults showed the brain responses typical of familiarity as well as recollection. Now, some research has found evidence of familiarity processing in children, so this shouldn’t be taken as proof against familiarity processing in the young. What seems most likely is that children are less likely to use such processing. Clearly the next step is to find out the factors that affect this.

Another interesting point is the early recollective response shown by children and adolescents. It’s speculated that these groups may have used more retrieval cues — conceptual as well as perceptual — that facilitated recollection. I’m reminded of a couple of studies I reported on some years ago, that found that young children were better than adults on a recognition task in some circumstances — because children were using a similarity-based process and adults a categorization-based one. In these cases, it had more to do with knowledge than development.

It’s also worth noting that, in adults, the recollective response was accentuated in the right-frontal area. This suggests that recollection was overlapping with post-retrieval monitoring. It’s speculated that adults’ greater use of familiarity produces a greater need for monitoring, because of the greater uncertainty.

What all this suggests is that preadolescent children are less able to strategically recollect source information, and that strategic recollection undergoes an important step in early adolescence that is probably related to improvements in cognitive control. But this process is still being refined in adolescents, in particular as regards monitoring and coping with uncertainty.

Interestingly, source memory is also one of the areas affected early in old age.

Failure to remember the source of a memory has many practical implications, in particular in the way it renders people more vulnerable to false memories.

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’.

I’ve always been intrigued by neurofeedback training. But when it first raised its head, technology was far less sophisticated. Now a new study has used real-time functional Magnetic Resonance Imaging (fMRI) feedback from the rostrolateral prefrontal cortex to improve people's ability to control their thoughts and focus their attention.

In the study, participants performed tasks that either raised or lowered mental introspection in 30-second intervals over four six-minute sessions. Those with access to real-time fMRI feedback could see their RLPFC activity increase during introspection and decrease during non-introspective thoughts, such as mental tasks that focused on body sensations. These participants became significantly better at controlling their thoughts and performing the mental tasks. Moreover, the improved regulation was reflected only in activity in the rostrolateral prefrontal cortex. Those given inaccurate or no brain feedback showed no such improvement.

The findings point to a means of improving attentional control, and also raise hope for clinical treatments of conditions that can benefit from improved awareness and regulation of one's thoughts, including depression, anxiety, and obsessive-compulsive disorders.

We learn from what we read and what people tell us, and we learn from our own experience. Although you would think that personal experience would easily trump other people’s advice, we in fact tend to favor abstract information against our own experience. This is seen in the way we commonly distort what we experience in ways that match what we already believe. But there is probably good reason for this tendency (reflected in confirmation bias), even if it sometimes goes wrong.

But of course individuals vary in the extent to which they persist with bad advice. A new study points to genes as a critical reason. Different brain regions are involved in the processing of these two information sources (advice vs experience): the prefrontal cortex and the striatum. Variants in the genes DARPP-32 and DRD2 affect the response to dopamine in the striatum. Variation in the gene COMT, on the other hand, affects dopamine response in the prefrontal cortex.

In the study, over 70 people performed a computerized learning task in which they had to pick the "correct" symbol, which they learned through trial and error. For some symbols, subjects were given advice, and sometimes that advice was wrong.

COMT gene variants were predictive of the degree to which participants persisted in responding in accordance with prior instructions even as evidence against their correctness grew. Variants in DARPP-32 and DRD2 predicted learning from positive and negative outcomes, and the degree to which such learning was overly inflated or neglected when outcomes were consistent or inconsistent with prior instructions.

Binge drinking is, unfortunately, most common among adolescents (12-20 years). But this is a time when brains are still developing. Does this make them more vulnerable to the detrimental effects of excessive alcohol?

A study involving adolescent mice has revealed that not only did an alcoholic binge reduce the activity of many neurotransmitter genes, but that gene expression in adulthood was even more seriously reduced. Although this deficit didn’t translate into problems with spatial learning, adult mice that had been exposed to excess alcohol in adolescence were significantly worse on a reversal learning task. Moreover, certain brain regions (the olfactory bulb and basal forebrain) were smaller.

In humans, it is thought that these impairments might translate into greater difficulty in adapting to changed situations, in evaluating consequences and controlling impulses.

Similarly, another recent study involving teenagers (15-21) has found that activity in the prefrontal cortex varied according to how heavily they smoked, with those who smoked most heavily having the least activity.

The 25 smokers and 25 non-smokers were tested on a Stop-Signal Task, which tests a person’s ability to inhibit an action. Despite the differences in activity level, smokers and non-smokers performed similarly on the task, suggesting that other brain areas are in some way compensating for the impaired prefrontal cortex. Nevertheless, reduced activity in the prefrontal cortex, which is still developing in adolescence, does suggest long-term consequences for decision-making and cognitive control.

In a study involving 44 young adults given a rigorous memorizing task at noon and another such task at 6pm, those who took a 90-minute nap during the interval improved their ability to learn on the later task, while those who stayed awake found it harder to learn.

The degree to which the nappers were refreshed correlated with the amount of stage 2 non-REM sleep they experienced. This sleep phase is characterized by sleep spindles, which are associated with brain activity between the hippocampus and prefrontal cortex. Spindle-rich sleep occurs mostly in the second half of the night, so those who don’t get their quota of sleep are probably getting less.

The finding confirms the idea that learning ability decreases the more time you spend awake.

A study involving 171 sedentary, overweight 7- to 11-year-old children has found that those who participated in an exercise program improved both executive function and math achievement. The children were randomly selected either to a group that got 20 minutes of aerobic exercise in an after-school program, one that got 40 minutes of exercise in a similar program, or a group that had no exercise program. Those who got the greater amount of exercise improved more. Brain scans also revealed increased activity in the prefrontal cortex and reduced activity in the posterior parietal cortex, for those in the exercise group.

The program lasted around 13 weeks. The researchers are now investigating the effects of continuing the program for a full year. Gender, race, socioeconomic factors or parental education did not change the impact of the exercise program.

The effects are consistent with other studies involving older adults. It should be emphasized that these were sedentary, overweight children. These findings are telling us what the lack of exercise is doing to young minds. I note the report just previous, about counteracting what we have regarded as “normal” brain atrophy in older adults by the simple action of walking for 40 minutes three times a week. Children and older adults might be regarded as our canaries in the coal mine, more vulnerable to many factors that can affect the brain. We should take heed.

When stroke or brain injury damages a part of the brain controlling movement or sensation or language, other parts of the brain can learn to compensate for this damage. It’s been thought that this is a case of one region taking over the lost function. Two new studies show us the story is not so simple, and help us understand the limits of this plasticity.

In the first study, six stroke patients who have lost partial function in their prefrontal cortex, and six controls, were briefly shown a series of pictures to test the ability to remember images for a brief time (visual working memory) while electrodes recorded their EEGs. When the images were shown to the eye connected to the damaged hemisphere, the intact prefrontal cortex (that is, the one not in the hemisphere directly receiving that visual input) responded within 300 to 600 milliseconds.

Visual working memory involves a network of brain regions, of which the prefrontal cortex is one important element, and the basal ganglia, deep within the brain, are another. In the second study, the researchers extended the experiment to patients with damage not only to the prefrontal cortex, but also to the basal ganglia. Those with basal ganglia damage had problems with visual working memory no matter which part of the visual field was shown the image.

In other words, basal ganglia lesions caused a more broad network deficit, while prefrontal cortex lesions resulted in a more limited, and recoverable, deficit. The findings help us understand the different roles these brain regions play in attention, and emphasize how memory and attention are held in networks. They also show us that the plasticity compensating for brain damage is more dynamic and flexible than we realized, with intact regions stepping in on a case by case basis, very quickly, but only when the usual region fails.

Last month I reported on a finding that toddlers with autism spectrum disorder showed a strong preference for looking at moving shapes rather than active people. This lower interest in people is supported by a new imaging study involving 62 children aged 4-17, of whom 25 were diagnosed with autistic spectrum disorder and 20 were siblings of children with ASD.

In the study, participants were shown point-light displays (videos created by placing lights on the major joints of a person and filming them moving in the dark). Those with ASD showed reduced activity in specific regions (right amygdala, ventromedial prefrontal cortex, right posterior superior temporal sulcus, left ventrolateral prefrontal cortex, and the fusiform gyri) when they were watching a point-light display of biological motion compared with a display of moving dots. These same regions have also been implicated in previous research with adults with ASD.

Moreover, the severity of social deficits correlated with degrees of activity in the right pSTS specifically. More surprisingly, other brain regions (left dorsolateral prefrontal cortex, right inferior temporal gyrus, and a different part of the fusiform gyri) showed reduced activity in both the siblings group and the ASD group compared to controls. The sibling group also showed signs of compensatory activity, with some regions (right posterior temporal sulcus and a different part of the ventromedial prefrontal cortex) working harder than normal.

The implications of this will be somewhat controversial, and more research will be needed to verify these findings.

The issue of “mommy brain” is a complex one. Inconsistent research results make it clear that there is no simple answer to the question of whether or not pregnancy and infant care change women’s brains. But a new study adds to the picture.

Brain scans of 19 women two to four weeks and three to four months after they gave birth showed that grey matter volume increased by a small but significant amount in the midbrain (amygdala, substantia nigra, hypothalamus), prefrontal cortex, and parietal lobe. These areas are involved in motivation and reward, emotion regulation, planning, and sensory perception.

Mothers who were most enthusiastic about their babies were significantly more likely to show this increase in the midbrain regions. The authors speculated that the “maternal instinct” might be less of an instinctive response and more of a result of active brain building. Interestingly, while the brain’s reward regions don’t usually change as a result of learning, one experience that does have this effect is that of addiction.

While the reasons may have to do with genes, personality traits, infant behavior, or present circumstances, previous research has found that mothers who had more nurturing in their childhood had more grey matter in those brain regions involved in empathy and reading faces, which also correlated with the degree of activation in those regions when their baby cried.

A larger study is of course needed to confirm these findings.

Metamemory or metacognition — your ability to monitor your own cognitive processes — is central to efficient and effective learning. Research has also shown that, although we customarily have more faith in person’s judgment the more confident they are in it, a person’s accuracy and their confidence in their accuracy are two quite separate things (which is not to say it’s not a useful heuristic; just that it’s far from infallible). A new study involving 32 participants has looked at individual differences in judging personal accuracy when assessing a geometric image, comparing these differences to differences in the brain.

The perceptual test used simple stimuli, and each one was customized to the individual's level of skill in order to achieve a score of 71%. In keeping with previous research, there was considerable variation in the participants’ accuracy in assessing their own responses. But the intriguing result was that these differences were reflected in differences in the volume of gray matter in the right anterior prefrontal cortex. Moreover, those who were better at judging their own performance not only had more neurons in that region, but also tended to have denser connections between the region and the white matter connected to it. The anterior prefrontal cortex is associated with various executive functions, and seems to be more developed in humans compared to other animals.

The finding should not be taken to indicate a genetic basis for metacognitive ability. The finding implies nothing about whether the physical differences are innate or achieved by training and experience. However it seems likely that, like most skills and abilities, a lot of it is training.

Children’s ability to remember past events improves as they get older. This has been thought by many to be due to the slow development of the prefrontal cortex. But now brain scans from 60 children (8-year-olds, 10- to 11-year-olds, and 14-year-olds) and 20 young adults have revealed marked developmental differences in the activity of the mediotemporal lobe.

The study involved the participants looking at a series of pictures (while in the scanner), and answering a different question about the image, depending on whether it was drawn in red or green ink. Later they were shown the pictures again, in black ink and mixed with new ones. They were asked whether they had seen them before and whether they had been red or green.

While the adolescents and adults selectively engaged regions of the hippocampus and posterior parahippocampal gyrus to recall event details, the younger children did not, with the 8-year-olds indiscriminately using these regions for both detail recollection and item recognition, and the 10- to 11-year-olds showing inconsistent activation. It seems that the hippocampus and posterior parahippocampal gyrus become increasingly specialized for remembering events, and these changes may partly account for long-term memory improvements during childhood.

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

September 2009

New insights into memory without conscious awareness

An imaging study in which participants were shown a previously studied scene along with three previously studied faces and asked to identify the face that had been paired with that scene earlier has found that hippocampal activity was closely tied to participants' tendency to view the associated face, even when they failed to identify it. Activity in the lateral prefrontal cortex, an area required for decision making, was sensitive to whether or not participants had responded correctly and communication between the prefrontal cortex and the hippocampus was increased during correct, but not incorrect, trials. The findings suggest that conscious memory may depend on interactions between the hippocampus and the prefrontal cortex.

Hannula, D.E. & Ranganath, C. 2009. The Eyes Have It: Hippocampal Activity Predicts Expression of Memory in Eye Movements. Neuron, 63 (5), 592-599.

http://www.eurekalert.org/pub_releases/2009-09/cp-ycb090309.php

August 2009

Alcoholics show abnormal brain activity when processing facial expressions

Excessive chronic drinking is known to be associated with deficits in comprehending emotional information, such as recognizing different facial expressions. Now an imaging study of abstinent long-term alcoholics has found that they show decreased and abnormal activity in the amygdala and hippocampus when looking at facial expressions. They also show increased activity in the lateral prefrontal cortex, perhaps in an attempt to compensate for the failure of the limbic areas. The finding is consistent with other studies showing alcoholics invoking additional and sometimes higher-order brain systems to accomplish a relatively simple task at normal levels. The study compared 15 abstinent long-term alcoholics and 15 healthy, nonalcoholic controls, matched on socioeconomic backgrounds, age, education, and IQ.

Marinkovic, K. et al. 2009. Alcoholism and Dampened Temporal Limbic Activation to Emotional Faces. Alcoholism: Clinical and Experimental Research, Published Online: Aug 10 2009

http://www.eurekalert.org/pub_releases/2009-08/ace-edc080509.php
http://www.eurekalert.org/pub_releases/2009-08/bumc-rfa081109.php

June 2009

Study finds autistics better at problem-solving

A study involving 15 autistics and 18 non-autistics, aged 14 to 36 and IQ-matched, has found that while both groups completed patterns in a complex problem-solving test (the widely-used Raven's Standard Progressive Matrices) with equal accuracy, the autistics responded significantly faster, and showed a different pattern of brain activity. Specifically, they showed increased activity in extrastriate areas, and decreased activity in the lateral prefrontal cortex and the medial posterior parietal cortex — suggesting visual processing mechanisms may play a more prominent role in reasoning in autistics. The differences between groups did not appear when participants performed a simpler pattern-matching task.

Soulières, I. et al. 2009. Enhanced visual processing contributes to matrix reasoning in autism. Human Brain Mapping, Published Online June 15.

http://www.eurekalert.org/pub_releases/2009-06/uom-sfa061609.php

May 2009

Brain's problem-solving function at work when we daydream

An imaging study has revealed that daydreaming is associated with an increase in activity in numerous brain regions, especially those regions associated with complex problem-solving. Until now it was thought that the brain's "default network" (which includes the medial prefrontal cortex, the posterior cingulate cortex and the temporoparietal junction) was the only part of the brain active when our minds wander. The new study has found that the "executive network" (including the lateral prefrontal cortex and the dorsal anterior cingulate cortex) is also active. Before this, it was thought that these networks weren’t active at the same time. It may be that mind wandering evokes a unique mental state that allows otherwise opposing networks to work in cooperation. It was also found that greater activation was associated with less awareness on the part of the subject that there mind was wandering.

Christoff, K. et al. 2009. Experience sampling during fMRI reveals default network and executive system contributions to mind wandering. Proceedings of the National Academy of Sciences, 106 (21), 8719-8724.

http://www.eurekalert.org/pub_releases/2009-05/uobc-bpf051109.php

February 2009

Brain activity linked to anticipation revealed

Brain scans of students listening to their favorite music CDs has revealed plenty of neural activity during the silence between songs — activity that is absent in those listening to music they had never heard in sequence before. Such anticipatory activity probably occurs whenever we expect any particular action to happen. In this case, the activity took the form of excitatory signals passing from the prefrontal cortex (where planning takes place) to the nearby premotor cortex (which is involved in preparing the body to act).

Leaver, A.M. et al. 2009. Brain Activation during Anticipation of Sound Sequences. Journal of Neuroscience, 29, 2477-2485.

http://www.eurekalert.org/pub_releases/2009-02/gumc-rcw022509.php

December 2008

Prefrontal cortex activity in poor children like that of stroke victim

An imaging study of 26 normal 9- and 10-year-olds differing only in socioeconomic status has revealed detectable differences in the response of their prefrontal cortex. While not invariant, those from lower socioeconomic levels were more likely to have low frontal lobe response. This is consistent with earlier studies, but is the first to demonstrate the effect when there is no issue of task complexity (the task was very simple; the measure was how fast the child responded to an unexpected novel picture — the response of many from low socioeconomic backgrounds was similar to the response of adults who have had a portion of their frontal lobe destroyed by a stroke). The effect is thought to be due to growing up in cognitively-impoverished and stressful environments, since these have been found to affect the prefrontal cortex in animal studies. Further research is looking into whether these brain differences can be eliminated by training.

Kishiyama, M.M. et al. 2008. Socioeconomic Disparities Affect Prefrontal Function in Children. Journal of Cognitive Neuroscience

http://www.eurekalert.org/pub_releases/2008-12/uoc--esb120208.php

September 2008

Patients who recover well from head injury 'work harder' to perform at same level as healthy people

People who make a full recovery from head injury often report "mental fatigue" and feeling "not quite the same" – even though they scored well on standard cognitive tests. Now brain imaging reveals that even with recovered head injury patients performing as well as matched controls on a series of working memory tests, their brains were working harder — specifically, showing more activity in regions of the prefrontal cortex and posterior cortices. All the patients had diffuse axonal injury, the most common consequence of head injuries resulting from motor vehicle accidents, falls, combat-related blast injuries, and other situations where the brain is rattled violently inside the skull causing widespread disconnection of brain cells.

Turner, G.R. & Levine, B. 2008. Augmented neural activity during executive control processing following diffuse axonal injury. Neurology, 71, 812-818.

http://www.eurekalert.org/pub_releases/2008-09/bcfg-pwr090308.php

April 2008

Intelligence and rhythmic accuracy go hand in hand

And in another perspective on the nature of intelligence, a new study has demonstrated a correlation between general intelligence and the ability to tap out a simple regular rhythm. The correlation between high intelligence and a good ability to keep time, was also linked to a high volume of white matter in the parts of the frontal lobes involved in problem solving, planning and managing time. The finding suggests that the long-established correlation of general intelligence with the mean and variability of reaction time in elementary cognitive tasks, as well as with performance on temporal judgment and discrimination tasks, is a bottom-up connection, stemming from connectivity in the prefrontal regions.

Ullén, F. et al. 2008. Intelligence and variability in a simple timing task share neural substrates in the prefrontal white matter. The Journal of Neuroscience, 28(16), 4238-4243.

http://www.eurekalert.org/pub_releases/2008-04/ki-iar041608.php

August 2007

Maturity brings richer memories

New research suggests adults can remember more contextual details than children, and that this is related to the development of the prefrontal cortex. While in a MRI scanner, 49 volunteers aged eight to 24 were shown pictures of 250 common scenes and told they would be tested on their memory of these scenes. In both children and adults, correct recognition of a scene was associated with higher activation in several areas of the prefrontal cortex and the medial temporal lobe when they were studying the pictures. However, the older the volunteers, the more frequently their correct answers were enriched with contextual detail. These more detailed memories correlated with more intense activation in a specific region of the PFC. A number of studies have suggested that the PFC develops later than other brain regions.

The report appeared in the August 5 advance online edition of Nature Neuroscience.

http://www.eurekalert.org/pub_releases/2007-08/miot-msm080107.php

June 2007

Brain's voluntary chain-of-command ruled by not 1 but 2 captains

Previous research has shown a large number of brain regions (39) that are consistently active when people prepare for a mental task. It’s been assumed that all these regions work together under the command of one single region. A new study, however, indicates that there are actually two independent networks operating. The cingulo-opercular network (including the dorsal anterior cingulate/medial superior frontal cortex, anterior insula/frontal operculum, and anterior prefrontal cortex) is linked to a "sustain" signal — it turns on at the beginning, hums away constantly during the task, then turns off at dorsolateral prefrontal cortex and intraparietal sulcus) is active at the start of mental tasks and during the correction of errors. The findings may help efforts to understand the effects of brain injury and develop new strategies to treat such injuries.

Dosenbach, N.U.F. et al. 2007. Distinct brain networks for adaptive and stable task control in humans. Proceedings of the National Academy of Sciences, 104 (26), 11073-11078.

http://news.wustl.edu/news/Pages/9639.aspx

March 2007

Prefrontal cortex loses neurons during adolescence

A rat study has found that adolescents lose neurons in the ventral prefrontal cortex in adolescence, with females losing about 13% more neurons than males. Human studies have found gradual reductions in the volume of gray matter in the prefrontal cortex from adolescence to adulthood, but this finding that neurons are actually dying is new, and indicates that the brain reorganizes in a very fundamental way in adolescence. The number of neurons in the dorsal prefrontal cortex didn’t change, although the number of glial cells increased there (while remaining stable in the ventral area). The finding could have implications for understanding disorders that often arise in late adolescence, such as schizophrenia and depression, and why addictions that start in adolescence are harder to overcome than those that begin in adulthood.

Markham, J.A., Morris, J.R. & Juraska, J.M. 2007. Neuron number decreases in the rat ventral, but not dorsal, medial prefrontal cortex between adolescence and adulthood. Neuroscience, 144 (3), 961-968.

http://www.sciencedaily.com/releases/2007/03/070314093257.htm

Disentangling attention

A new study provides more evidence that the ability to deliberately focus your attention is physically separate in the brain from the part that helps you filter out distraction. The study trained monkeys to take attention tests on a video screen in return for a treat of apple juice. When the monkeys voluntarily concentrated (‘top-down’ attention), the prefrontal cortex was active, but when something distracting grabbed their attention (‘bottom-up’ attention), the parietal cortex became active. The electrical activity in these two areas vibrated in synchrony as they signaled each other, but top-down attention involved synchrony that was stronger in the lower-frequencies and bottom-up attention involved higher frequencies. These findings may help us develop treatments for attention disorders.

Buschman, T.J. & Miller, E.K. 2007. Top-Down Versus Bottom-Up Control of Attention in the Prefrontal and Posterior Parietal Cortices. Science, 315 (5820), 1860-1862.

February 2007

Common gene version optimizes thinking but carries a risk

On the same subject, another study has found that the most common version of DARPP-32, a gene that shapes and controls a circuit between the striatum and prefrontal cortex, optimizes information filtering by the prefrontal cortex, thus improving working memory capacity and executive control (and thus, intelligence). However, the same version was also more prevalent among people who developed schizophrenia, suggesting that a beneficial gene variant may translate into a disadvantage if the prefrontal cortex is impaired. In other words, one of the things that make humans more intelligent as a species may also make us more vulnerable to schizophrenia.

Meyer-Lindenberg,A. et al. 2007. Genetic evidence implicating DARPP-32 in human frontostriatal structure, function, and cognition. Journal of Clinical Investigation, 117 (3), 672-682.

http://www.sciencedaily.com/releases/2007/02/070208230059.htm
http://www.eurekalert.org/pub_releases/2007-02/niom-cgv020707.php

January 2007

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.

Dux, P.E. et al. 2006. Isolation of a Central Bottleneck of Information Processing with Time-Resolved fMRI. Neuron, 52, 1109-1120.

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

November 2006

Hormone replacement therapy may improve visual memory of postmenopausal women

A study of 10 postmenopausal women (aged 50-60) found that those taking combined estrogen-progestin hormone therapy for four weeks showed significantly increased activity in the prefrontal cortex when engaged in a visual matching task, compared with those on placebo.

Smith, Y.R. et al. 2006. Impact of Combined Estradiol and Norethindrone Therapy on Visuospatial Working Memory Assessed by Functional Magnetic Resonance Imaging. The Journal of Clinical Endocrinology & Metabolism, 91 (11), 4476-4481.

http://www.eurekalert.org/pub_releases/2006-11/uomh-hrt111606.php

July 2006

Brain Imaging Identifies Best Memorization Strategies

Why do some people remember things better than others? An imaging study has revealed that the brain regions activated when learning vary depending on the strategy adopted. The study involved 29 right-handed, healthy young adults, ages 18-31, all of whom had normal or corrected-to-normal vision and reported no significant neurological history. Participants were given interacting object pair images (such as a turkey seated atop a horse and a banana positioned in the back of a dump truck) and told to study them in anticipation of a memory test. Earlier studies had indicated that while individuals use a variety of strategies to help them memorize new information, the following four strategies were the main strategies:

1) A visual inspection strategy in which participants carefully studied the visual appearance of objects.

2) A verbal elaboration strategy in which individuals constructed sentences about the objects to remember them.

3) A mental imagery strategy in which participants formed interactive mental images of the objects.

4) A memory retrieval strategy in which they thought about the meaning of the objects and/or personal memories associated with the objects.

Both visual inspection and verbal elaboration resulted in improved recall. Imaging revealed that people who often used verbal elaboration had greater activity in a network of regions that included prefrontal regions associated with controlled verbal processing compared to people who used this strategy less frequently. People who often used a visual inspection strategy had greater activity in a network of regions that included an extrastriate region associated with object processing compared to people who used this strategy less frequently.

Kirchhoff, B.A. & Buckner, R.L. 2006. Functional-Anatomic Correlates of Individual Differences in Memory. Neuron, 51, 263-274.

http://www.sciencedaily.com/releases/2006/08/060809082610.htm

May 2006

Planning is goal-, not action-, oriented

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

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

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

January 2006

Morning grogginess worse for cognition than sleep deprivation

People who awaken after eight hours of sound sleep have more impaired thinking and memory skills than they do after being deprived of sleep for more than 24 hours. The impairment is worst in the first three minutes, and the most severe effects have generally dissipated by ten minutes, but measurable effects can last up to two hours. This is consistent with reports indicating that cortical areas like the prefrontal cortex take longer to come “online” after sleep than other parts of the brain. The findings have implications for medical, safety and transportation workers who are often called upon to perform critical tasks immediately after waking, as well as for anyone abruptly woken to face an emergency situation.

Wertz, A.T., Ronda, J.M., Czeisler, C.A. & Wright, K.P.Jr. 2006. Effects of Sleep Inertia on Cognition. Journal of the American Medical Association, 295,163-164.

http://www.eurekalert.org/pub_releases/2006-01/uoca-mgm121905.php

Fitness counteracts cognitive decline from hormone-replacement therapy

A study of 54 postmenopausal women (aged 58 to 80) suggests that being physically fit offsets cognitive declines attributed to long-term hormone-replacement therapy. It was found that gray matter in four regions (left and right prefrontal cortex, left parahippocampal gyrus and left subgenual cortex) was progressively reduced with longer hormone treatment, with the decline beginning after more than 10 years of treatment. Therapy shorter than 10 years was associated with increased tissue volume. Higher fitness scores were also associated with greater tissue volume. Those undergoing long-term hormone therapy had more modest declines in tissue loss if their fitness level was high. Higher fitness levels were also associated with greater prefrontal white matter regions and in the genu of the corpus callosum. The findings need to be replicated with a larger sample, but are in line with animal studies finding that estrogen and exercise have similar effects: both stimulate brain-derived neurotrophic factor.

Erickson, K.I., Colcombe, S.J., Elavsky, S., McAuley, E., Korol, D., Scalf, P.E. & Kramer, A.F. 2006. Interactive effects of fitness and hormone treatment on brain health in postmenopausal women. Neurobiology of Aging, In Press, Corrected Proof, Available online 6 January 2006

http://www.eurekalert.org/pub_releases/2006-01/uoia-fcc012406.php

September 2005

Memory of fear more complex than supposed

It seems that fear memory is more complex than has been thought. A new mouse study has shown that not only the hippocampus and amygdala are involved, but that the prefrontal cortex is also critical. The development of the fear association doesn’t occur immediately after a distressing event, but develops over time. The process, it now seems, depends directly on a protein called NR2B.

Zhao, M-G. et al. 2005. Roles of NMDA NR2B Subtype Receptor in Prefrontal Long-Term Potentiation and Contextual Fear Memory. Neuron, 47, 859-872.

http://www.eurekalert.org/pub_releases/2005-09/uot-sco091505.php

June 2005

How sleep improves memory

While previous research has been conflicting, it does now seem clear that sleep consolidates learning of motor skills in particular. A new imaging study involving 12 young adults taught a sequence of skilled finger movements has found a dramatic shift in activity pattern when doing the task in those who were allowed to sleep during the 12 hour period before testing. Increased activity was found in the right primary motor cortex, medial prefrontal lobe, hippocampus and left cerebellum — this is assumed to support faster and more accurate motor output. Decreased activity was found in the parietal cortices, the left insular cortex, temporal pole and fronto-polar region — these are assumed to reflect less anxiety and a reduced need for conscious spatial monitoring. It’s suggested that this is one reason why infants need so much sleep — motor skill learning is a high priority at this age. The findings may also have implications for stroke patients and others who have suffered brain injuries.

Walker, M.P., Stickgold, R., Alsop, D., Gaab, N. & Schlaug, G. 2005. Sleep-dependent motor memory plasticity in the human brain.Neuroscience, 133 (4) , 911-917.

http://www.eurekalert.org/pub_releases/2005-06/bidm-ssh062805.php

March 2005

Primitive brain learns faster than the "thinking" part of our brain

A study of monkeys has revealed that a primitive region of the brain known as the basal ganglia learns rules first, then “trains” the prefrontal cortex, which learns more slowly. The findings turn our thinking about how rules are learned on its head — it has been assumed that the smarter areas of our brain work things out; instead it seems that primitive brain structures might be driving even our most high-level learning.

Pasupathy, A. &Miller, E.K. 2005. Different time courses of learning-related activity in the prefrontal cortex and striatum. Nature, 433, 873-876.

http://news.mit.edu/2005/basalganglia

February 2005

How the brain creates false memories

An imaging study has shed new light on how false memories are formed. The study involved participants watching series of 50 photographic slides that told a story. A little later, the subjects were shown what they thought was the same sequence of slides but in fact containing a misleading item and differing in small ways from the original. Two days later, the subjects’ memories were tested. It was found that, during the original encoding (the 1st set of slides), activity in the hippocampus and perirhinal cortex was greater for true than for false memories, while during the misinformation phase (2nd set), the activity there was greater for false memories. In other regions, such as the prefrontal cortex, activity for false memories tended to be greater during the original event. Activity in the prefrontal cortex may be correlated to encoding the source, or context, of the memory. Thus, weak prefrontal cortex activity during the misinformation phase indicates that the details of the second experience were poorly placed in a learning context, and as a result more easily embedded in the context of the first event, creating false memories.

Okado, Y. & Stark, C.E.L. 2005. Neural activity during encoding predicts false memories created by misinformation. Learning & Memory, 12, 3-11.

http://www.eurekalert.org/pub_releases/2005-02/cshl-htb012805.php

October 2004

How false memories are formed

An imaging study has attempted to pinpoint how people form a memory for something that didn't actually happen. The study measured brain activity in people who looked at pictures of objects or imagined other objects they were asked to visualize. Three brain areas (precuneus, right inferior parietal cortex and anterior cingulate) showed greater responses in the study phase to words that would later be falsely remembered as having been presented with photos, compared to words that were not later misremembered as having been presented with photos. Brain activity produced in response to viewed pictures also predicted which pictures would be subsequently remembered. Two brain regions in particular -- the left hippocampus and the left prefrontal cortex -- were activated more strongly for pictures that were later remembered than for pictures that were forgotten. The new findings directly showed that different brain areas are critical for accurate memories for visual objects than for false remembering -- for forming a memory for an imagined object that is later remembered as a perceived object.

Gonsalves, B., Reber, P.J., Gitelman, D.R., Parrish, T.B., Mesulam, M-M. & Paller, K.A. 2004. Neural Evidence That Vivid Imagining Can Lead to False Remembering. Psychological Science, 15 (10), 655-660.

http://www.eurekalert.org/pub_releases/2004-10/nu-nrp101404.php
http://www.northwestern.edu/newscenter/stories/2004/10/kenneth.html

Development of working memory with age

An imaging study of 20 healthy 8- to 30-year-olds has shed new light on the development of working memory. The study found that pre-adolescent children relied most heavily on the prefrontal cortex and parietal regions of the brain during the working memory task; adolescents used those regions plus the anterior cingulate; and in adults, a third area of the brain, the medial temporal lobe, was brought in to support the functions of the other areas. Adults performed best. The results support the view that a person's ability to have voluntary control over behavior improves with age because with development, additional brain processes are used.

http://www.eurekalert.org/pub_releases/2004-10/uopm-dow102104.php

September 2004

New technique sheds light on autobiographical memory

A new technique for studying autobiographical memory has revealed new findings about autobiographical memory, and may prove useful in studying age-related cognitive impairment. Previous inconsistencies between controlled laboratory studies of memory (typically, subjects are asked to remember items they have previously seen in the laboratory, such as words presented on a computer screen) and studies of autobiographical memory have seemed to indicate that the brain may function differently in the two processes. However, such differences might instead reflect how the memories are measured. In an effort to provide greater control over the autobiographical memories, volunteer subjects were given cameras and instructed to take pictures of campus scenes. The subjects were also instructed to remember the taking of each picture as an individual event, noting the physical conditions and their psychological state, such as their mood and associations with the subject of the images. The subjects were then shown a selection of campus photos they had not taken. While their brains were scanned, they were then shown a mix of their own photos with those they had not taken, and asked to indicate whether each photo was new, seen earlier in the lab, or one they had taken themselves. The researchers found that recalling the autobiographical memories activated many of the same brain areas as laboratory memories (the medial temporal lobe and the prefrontal cortex); however, they also activated brain areas associated with "self-referential processing" (processing information about one's self), and regions associated with retrieval of visual and spatial information, as well as showing a higher level of activity in the recollection areas in the hippocampus.

The report appeared in the November issue of the Journal of Cognitive Neuroscience.

http://www.eurekalert.org/pub_releases/2004-09/du-blm092904.php

March 2004

Different brain regions for arousing and non-arousing words

An imaging study has found that words representing arousing events (e.g., “rape”, “slaughter”) activate cells in the amygdala, while nonarousing words (e.g., “sorrow”, “mourning”) activated cells in the prefrontal cortex. The hippocampus was active for both type of words. On average, people remembered more of the arousing words than the others, suggesting stress hormones, released as part of the response to emotionally arousing events, are responsible for enhancing memories of those events.

Kensinger, E.A. & Corkin, S. 2004. Two routes to emotional memory: Distinct neural processes for valence and arousal. PNAS, 101, 3310-3315. Published online before print February 23 2004, 10.1073/pnas.0306408101

http://www.eurekalert.org/pub_releases/2004-03/miot-mlu030104.php

January 2004

More evidence for active forgetting

In an imaging study involving 24 people aged 19 to 31, participants were given pairs of words and told to remember some of the matched pairs but forget others. Trying to shut out memory appeared more demanding than remembering, in that some areas of the brain were significantly more when trying to suppress memory. Both the prefrontal cortex and the hippocampus were active. Those whose prefrontal cortex and hippocampus were most active during this time were most successful at suppressing memory.

Anderson, M.C., Ochsner, K.N., Kuhl, B., Cooper, J., Robertson, E., Gabrieli, S.W., Glover, G.H. & Gabrieli, J.D.E. 2004. Neural Systems Underlying the Suppression of Unwanted Memories. Science, 303 (5655), 232-235.

http://www.eurekalert.org/pub_releases/2004-01/su-rrb010604.php

August 2002

How emotions interfere with staying focused

In a new imaging study, Duke University researchers have shown how emotional stimuli and "attentional functions" like driving move in parallel streams through the brain before being integrated in a specific part of the brain's prefrontal cortex (the anterior cingulate, which is located between the right and left halves). Emotional stimuli are thus more likely than simple distractions to interfere with a person's efforts to focus on a task such as driving. These findings may help us understand the neural dynamics underlying emotional distractibility on attentional tasks in affective disorders.

Yamasaki, H., LaBar, K.S. & McCarthy, G. Dissociable prefrontal brain systems for attention and emotion. Proc. Natl. Acad. Sci. USA, 99(17), 11447-51.

http://www.pnas.org/content/99/17/11447.abstract

December 2001

Age-related changes in brain dopamine may underpin the normal cognitive problems of aging

A new model suggests why and how many cognitive abilities decline with age, and offers hope for prevention. Research in the past few years has clarified and refined our ideas about the ways in which cognitive abilities decline with age, and one of these ways is in a reduced ability to recall the context of memories. Thus, for example, an older person is less likely to be able to remember where she has heard something. According to this new model, context processing is involved in many cognitive functions — including some once thought to be independent — and therefore a reduction in the ability to remember contextual information can have wide-reaching implications for many aspects of cognition. The model suggests that context processing occurs in the prefrontal cortex and requires a certain level of the brain chemical dopamine. It may be that in normal aging, dopamine levels become low or erratic. Changes in dopamine have also been implicated in Alzheimer’s, as well as other brain-based diseases.

Braver, T.S., Barch, D.M., Keys, B.A., Carter, C.S., Cohen, J.D., Kaye, J.A., Janowsky, J.S., Taylor, S.F., Yesavage, J.A., Mumenthaler, M.S., Jagust, W.J., & Reed, B.R. 2001. Context Processing in Older Adults: Evidence for a Theory Relating Cognitive Control to Neurobiology in Healthy Aging. Journal of Experimental Psychology –General, 130(4)

http://www.eurekalert.org/pub_releases/2001-12/apa-ocf121701.php

November 2001

Physical brain changes with advancing age

Many of the cognitive deficits associated with advancing age are related to functions of the prefrontal cortex such as working memory, decision-making, planning and judgement. Postmortem examination of 20 brains ranging in age from 25 to 83 years, confirm that prefrontal regions may be particularly sensitive to the effects of aging. It also appears that white matter decreases at a faster rate than grey matter with age.

Kigar, D.L., Walter, A.L., Stoner-Beresh, H.J. & Witelson, S.F. 2001. Age and volume of the human prefrontal cortex: a postmortem study. Paper presented to the annual Society for Neuroscience meeting in San Diego, US.

October 2001

Role of prefrontal cortical regions in goal-directed behaviour

Goal-directed behaviour depends on keeping relevant information in mind (working memory) and irrelevant information out of mind (behavioural inhibition or interference resolution). Prefrontal cortex is essential for both working memory and for interference resolution, but it is unknown whether these two mental abilities are mediated by common or distinct prefrontal regions. An imaging study found there was a high degree of overlap between the regions activated by load and interference, while no region was activated exclusively by interference. The findings suggest that, within the circuitry engaged by this task, some regions are more critically involved in the resolution of interference whereas others are more involved in the resolution of an increase in load.

Bunge, S.A., Ochsner, K.N., Desmond, J.E., Glover, G.H. & Gabrieli J.D.E. (2001). Prefrontal regions involved in keeping information in and out of mind. Brain, 124 (10), 2074-2086.

http://brain.oupjournals.org/cgi/content/abstract/124/10/2074

Left prefrontal cortex

January 2009

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 theorised: 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.

Huijbers, W., Pennartz, C.M., Cabeza, R. & Daselaar, S.M. 2009. When learning and remembering compete: A functional MRI study. PLoS Biology, 7(1), e1000011. doi:10.1371/ journal.pbio.1000011

http://www.eurekalert.org/pub_releases/2009-01/plos-sit010909.php

January 2003

Learning a sequence with explicit knowledge of that sequence involves same

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

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

November 2001

Differential effects of encoding strategy on brain activity patterns

Encoding and recognition of unfamiliar faces in young adults were examined using PET imaging to determine whether different encoding strategies would lead to differences in brain activity. It was found that encoding activated a primarily ventral system including bilateral temporal and fusiform regions and left prefrontal cortices, whereas recognition activated a primarily dorsal set of regions including right prefrontal and parietal areas. The type of encoding strategy produced different brain activity patterns. There was no effect of encoding strategy on brain activity during recognition. The left inferior prefrontal cortex was engaged during encoding regardless of strategy.

Bernstein, L.J., Beig, S., Siegenthaler, A.L. & Grady, C.L. 2002. The effect of encoding strategy on the neural correlates of memory for faces. Neuropsychologia, 40 (1), 86 - 98.

Medial prefrontal cortex

May 2009

Brain's problem-solving function at work when we daydream

An imaging study has revealed that daydreaming is associated with an increase in activity in numerous brain regions, especially those regions associated with complex problem-solving. Until now it was thought that the brain's "default network" (which includes the medial prefrontal cortex, the posterior cingulate cortex and the temporoparietal junction) was the only part of the brain active when our minds wander. The new study has found that the "executive network" (including the lateral prefrontal cortex and the dorsal anterior cingulate cortex) is also active. Before this, it was thought that these networks weren’t active at the same time. It may be that mind wandering evokes a unique mental state that allows otherwise opposing networks to work in cooperation. It was also found that greater activation was associated with less awareness on the part of the subject that there mind was wandering.

Christoff, K. et al. 2009. Experience sampling during fMRI reveals default network and executive system contributions to mind wandering. Proceedings of the National Academy of Sciences, 106 (21), 8719-8724.

http://www.eurekalert.org/pub_releases/2009-05/uobc-bpf051109.php

February 2009

Brain hub links music and autobiographical memory

We all know that songs from our youth can evoke strong autobiographical memories. Now a new study explains why. Brain scans of students listening to excerpts of 30 different popular tunes found that a student recognized on average about 17 of the 30 excerpts, and of these, about 13 were moderately or strongly associated with an autobiographical memory. The strength of that memory was reflected in the amount of activity in the upper (dorsal) part of the medial prefrontal cortex, a region critically involved in integrating sensory information with self-knowledge and the retrieval of autobiographical information. Moreover, mapping the tones of each excerpt showed that the brain was tracking these tonal progressions in the same region as it was experiencing the memories: in the dorsal part of the medial prefrontal cortex, and the regions immediately adjacent to it. Again, the stronger the autobiographical memory, the greater the tracking activity. The finding explains why memory for autobiographically important music lingers in Alzheimer’s sufferers — the area is one of the last to be affected.

Janata, P. 2009. The Neural Architecture of Music-Evoked Autobiographical Memories. Cerebral Cortex, Advance Access published on February 24.

http://www.eurekalert.org/pub_releases/2009-02/uoc--sfb021809.php

May 2008

Brain region involved in false memories identified

We’re all susceptible to false memories, but brain damage can produce false memories beyond the normal level. The pathological production of false memories is known as confabulation, and because the patients who suffer this have showed damage to various parts of the brain, the cause has been unclear until now. But a new study of 50 patients has found the common element: all those who confabulated shared damage to the inferior medial prefrontal cortex.

Turner, M.S. et al. 2008. Confabulation: Damage to a specific inferior medial prefrontal system. Cortex, 44 (6), 637-648.

http://www.eurekalert.org/pub_releases/2008-05/e-wym052808.php

March 2007

Social memory localized

An imaging study has identified the medial prefrontal cortex as being the key structure in remembering social information (involving people and their interactions) from a picture. Previous studies have implicated this region with thinking about one’s self and others. This finding reveals that the region is involved not only in processing social information, but also storing it. The finding may help us understand disorders which affect social and relational skills, such as schizophrenia and autism.

Harvey, P.O., Fossati, P. & Lepage, M. 2007. Modulation of memory formation by stimulus content: specific role of the medial prefrontal cortex in the successful encoding of social pictures. Journal of Cognitive Neuroscience, 19, 351-362.

http://www.eurekalert.org/pub_releases/2007-03/c-tfo033007.php

May 2005

How the brain handles sarcasm

A study involving people with prefrontal lobe damage, people with posterior-lobe damage and healthy controls, found that those with prefrontal damage were impaired in comprehending sarcasm, whereas the people in the other two groups had no such problem. Within the prefrontal group, people with damage in the right ventromedial area had the most trouble in comprehending sarcasm. The researchers suggest that the frontal lobes process the context, identifying the contradiction between the literal meaning and the social/emotional context, while the ventromedial prefrontal cortex integrates the literal meaning with the social/emotional knowledge of the situation and previous situations.

Shamay-Tsoory, S.G., Tomer, R. & Aharon-Peretz, J. 2005. The Neuroanatomical Basis of Understanding Sarcasm and Its Relationship to Social Cognition. Neuropsychology, 19 (3)

http://www.eurekalert.org/pub_releases/2005-05/apa-tao051705.php

October 2004

Can't place a name to the face you just saw?

We’re all familiar with that “I know I know it, I just can’t bring it to mind” feeling. Among researchers, this is known as FOK — “feeling of knowing”. It is a common phenomenon, that occurs more frequently as we age. A new imaging study involving a dozen people aged 22 to 32, has investigated the FOK state using pictures of 300 famous and not-so-famous faces. They found that the medial prefrontal cortex showed activity during the FOK state, but not when the subjects either knew or did not know a face. Possibly this reflects a state in which subjects were evaluating the correctness of retrieved information. Additionally, the anterior cingulate area became activated both in the FOK state and when subjects successfully retrieved a name but with some effort. The anterior cingulate area is associated with cognitive conflict processes which allow a person to detect errors in automatic behavior responses. The results suggest that, during a FOK state, the brain may be enlisting additional processes to aid in recalling accurate memories.

http://www.eurekalert.org/pub_releases/2004-10/uoa-cpa102604.php