Anterior Cingulate

An online study open to anyone, that ended up involving over 100,000 people of all ages from around the world, put participants through 12 cognitive tests, as well as questioning them about their background and lifestyle habits. This, together with a small brain-scan data set, provided an immense data set to investigate the long-running issue: is there such a thing as ‘g’ — i.e. is intelligence accounted for by just a single general factor; is it supported by just one brain network? — or are there multiple systems involved?

Brain scans of 16 healthy young adults who underwent the 12 cognitive tests revealed two main brain networks, with all the tasks that needed to be actively maintained in working memory (e.g., Spatial Working Memory, Digit Span, Visuospatial Working Memory) loading heavily on one, and tasks in which information had to transformed according to logical rules (e.g., Deductive Reasoning, Grammatical Reasoning, Spatial Rotation, Color-Word Remapping) loading heavily on the other.

The first of these networks involved the insula/frontal operculum, the superior frontal sulcus, and the ventral part of the anterior cingulate cortex/pre-supplementary motor area. The second involved the inferior frontal sulcus, inferior parietal lobule, and the dorsal part of the ACC/pre-SMA.

Just a reminder of individual differences, however — when analyzed by individual, this pattern was observed in 13 of the 16 participants (who are not a very heterogeneous bunch — I strongly suspect they are college students).

Still, it seems reasonable to conclude, as the researchers do, that at least two functional networks are involved in ‘intelligence’, with all 12 cognitive tasks using both networks but to highly variable extents.

Behavioral data from some 60,000 participants in the internet study who completed all tasks and questionnaires revealed that there was no positive correlation between performance on the working memory tasks and the reasoning tasks. In other words, these two factors are largely independent.

Analysis of this data revealed three, rather than two, broad components to overall cognitive performance: working memory; reasoning; and verbal processing. Re-analysis of the imaging data in search of the substrate underlying this verbal component revealed that the left inferior frontal gyrus and temporal lobes were significantly more active on tasks that loaded on the verbal component.

These three components could also be distinguished when looking at other factors. For example, while age was the most significant predictor of cognitive performance, its effect on the verbal component was much later and milder than it was for the other two components. Level of education was more important for the verbal component than the other two, while the playing of computer games had an effect on working memory and reasoning but not verbal. Chronic anxiety affected working memory but not reasoning or verbal. Smoking affected working memory more than the others. Unsurprisingly, geographical location affected verbal more than the other two components.

A further test, involving 35 healthy young adults, compared performance on the 12 tasks and score on the Cattell Culture Fair test (a classic pen and paper IQ test). The working memory component correlated most with the Cattell score, followed by the reasoning component, with the Verbal component (unsurprisingly, given that this is designed to be a ‘culture-fair’ test) showing the smallest correlation.

All of this is to say that this is decided evidence that what is generally considered ‘intelligence’ is based on the functioning of multiple brain networks rather than a single ‘g’, and that these networks are largely independent. Thus, the need to focus on and maintain task-relevant information maps onto one particular brain network, and is one strand. Another network specializes in transforming information, regardless of source or type. These, it would seem, are the main processes involved in fluid intelligence, while the Verbal component most likely reflects crystallized intelligence. There are also likely to be other networks which are not perhaps typically included in ‘general intelligence’, but are nevertheless critical for task performance (the researchers suggest the ability to adapt plans based on outcomes might be one such function).

The obvious corollary of all this is that similar IQ scores can reflect different abilities for these strands — e.g., even if your working memory capacity is not brilliant, you can develop your reasoning and verbal abilities. All this is consistent with the growing evidence that, although fundamental WMC might be fixed (and I use the word ‘fundamental’ deliberately, because WMC can be measured in a number of different ways, and I do think you can, at the least, effectively increase your WMC), intelligence (because some of its components are trainable) is not.

If you want to participate in this research, a new version of the tests is available at http://www.cambridgebrainsciences.com/theIQchallenge

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.

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

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

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

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

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

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

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

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

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

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

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

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

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

Another study adds to the evidence that changes in the brain that may lead eventually to Alzheimer’s begin many years before Alzheimer’s is diagnosed. The findings also add to the evidence that what we regard as “normal” age-related cognitive decline is really one end of a continuum of which the other end is dementia.

In the study, brain scans were taken of 137 highly educated people aged 30-89 (participants in the Dallas Lifespan Brain Study). The amount of amyloid-beta (characteristic of Alzheimer’s) was found to increase with age, and around a fifth of those over 60 had significantly elevated levels of the protein. These higher amounts were linked with worse performance on tests of working memory, reasoning and processing speed.

More specifically, across the whole sample, amyloid-beta levels affected processing speed and fluid intelligence (in a dose-dependent relationship — that is, as levels increased, these functions became more impaired), but not working memory, episodic memory, or crystallized intelligence. Among the elevated-levels group, increased amyloid-beta was significantly associated with poorer performance for processing speed, working memory, and fluid intelligence, but not episodic memory or crystallized intelligence. Among the group without elevated levels of the protein, increasing amyloid-beta only affected fluid intelligence.

These task differences aren’t surprising: processing speed, working memory, and fluid intelligence are the domains that show the most decline in normal aging.

Those with the Alzheimer’s gene APOE4 were significantly more likely to have elevated levels of amyloid-beta. While 38% of the group with high levels of the protein had the risky gene variant, only 15% of those who didn’t have high levels carried the gene.

Note that, while the prevalence of carriers of the gene variant matched population estimates (24%), the proportion was higher among those in the younger age group — 33% of those under 60, compared to 19.5% of those aged 60 or older. It seems likely that many older carriers have already developed MCI or Alzheimer’s, and thus been ineligible for the study.

The average age of the participants was 64, and the average years of education 16.4.

Amyloid deposits varied as a function of age and region: the precuneus, temporal cortex, anterior cingulate and posterior cingulate showed the greatest increase with age, while the dorsolateral prefrontal cortex, orbitofrontal cortex, parietal and occipital cortices showed smaller increases with age. However, when only those aged 60+ were analyzed, the effect of age was no longer significant. This is consistent with previous research, and adds to evidence that age-related cognitive impairment, including Alzheimer’s, has its roots in damage occurring earlier in life.

In another study, brain scans of 408 participants in the Mayo Clinic Study of Aging also found that higher levels of amyloid-beta were associated with poorer cognitive performance — but that this interacted with APOE status. Specifically, carriers of the Alzheimer’s gene variant were significantly more affected by having higher levels of the protein.

This may explain the inconsistent findings of previous research concerning whether or not amyloid-beta has significant effects on cognition in normal adults.

As the researchers of the first study point out, what’s needed is information on the long-term course of these brain changes, and they are planning to follow these participants.

In the meantime, all in all, the findings do provide more strength to the argument that your lifestyle in mid-life (and perhaps even younger) may have long-term consequences for your brain in old age — particularly for those with a genetic susceptibility to Alzheimer’s.

A certain level of mental decline in the senior years is regarded as normal, but some fortunate few don’t suffer from any decline at all. The Northwestern University Super Aging Project has found seniors aged 80+ who match or better the average episodic memory performance of people in their fifties. Comparison of the brains of 12 super-agers, 10 cognitively-normal seniors of similar age, and 14 middle-aged adults (average age 58) now reveals that the brains of super-agers also look like those of the middle-aged. In contrast, brain scans of cognitively average octogenarians show significant thinning of the cortex.

The difference between the brains of super-agers and the others was particularly marked in the anterior cingulate cortex. Indeed, the super agers appeared to have a much thicker left anterior cingulate cortex than the middle-aged group as well. Moreover, the brain of a super-ager who died revealed that, although there were some plaques and tangles (characteristic, in much greater quantities, of Alzheimer’s) in the mediotemporal lobe, there were almost none in the anterior cingulate. (But note an earlier report from the researchers)

Why this region should be of special importance is somewhat mysterious, but the anterior cingulate is part of the attention network, and perhaps it is this role that underlies the superior abilities of these seniors. The anterior cingulate also plays a role error detection and motivation; it will be interesting to see if these attributes are also important.

While the precise reason for the anterior cingulate to be critical to retaining cognitive abilities might be mysterious, the lack of cortical atrophy, and the suggestion that super-agers’ brains have much reduced levels of the sort of pathological damage seen in most older brains, adds weight to the growing evidence that cognitive aging reflects clinical problems, which unfortunately are all too common.

Sadly, there are no obvious lifestyle factors involved here. The super agers don’t have a lifestyle any different from their ‘cognitively average’ counterparts. However, while genetics might be behind these people’s good fortune, that doesn’t mean that lifestyle choices don’t make a big difference to those of us not so genetically fortunate. It seems increasingly clear that for most of us, without ‘super-protective genes’, health problems largely resulting from lifestyle choices are behind much of the damage done to our brains.

It should be emphasized that these unpublished results are preliminary only. This conference presentation reported on data from only 12 of 48 subjects studied.

Harrison, T., Geula, C., Shi, J., Samimi, M., Weintraub, S., Mesulam, M. & Rogalski, E. 2011. Neuroanatomic and pathologic features of cognitive SuperAging. Presented at a poster session at the 2011 Society for Neuroscience conference.

Obesity has been linked to cognitive decline, but a new study involving 300 post-menopausal women has found that higher BMI was associated with higher cognitive scores.

Of the 300 women (average age 60), 158 were classified as obese (waist circumference of at least 88cm, or BMI of over 30). Cognitive performance was assessed in three tests: The Mini-Mental Statement Examination (MMSE), a clock-drawing test, and the Boston Abbreviated Test.

Both BMI and waist circumference were positively correlated with higher scores on both the MMSE and a composite cognitive score from all three tests. It’s suggested that the estrogen produced in a woman’s fat cells help protect cognitive function.

Interestingly, a previous report from the same researchers challenged the link found between metabolic syndrome and poorer cognitive function. This study, using data from a large Argentinean Cardiovascular Prevention Program, found no association between metabolic syndrome and cognitive decline — but the prevalence of metabolic syndrome and cognitive decline was higher in males than females. However, high inflammatory levels were associated with impairment of executive functions, and higher systolic blood pressure was associated with cognitive decline.

It seems clear that any connection between BMI and cognitive decline is a complex one. For example, two years ago I reported that, among older adults, higher BMI was associated with more brain atrophy (replicated below; for more recent articles relating obesity to cognitive impairment, click on the obesity link at the end of this report). Hypertension, inflammation, and diabetes have all been associated with greater risk of impairment and dementia. It seems likely that the connection between BMI and impairment is mediated through these and other factors. If your fat stores are not associated with such health risk factors, then the fat in itself is not likely to be harmful to your brain function — and may (if you’re a women) even help.

Previous:

Overweight and obese elderly have smaller brains

Analysis of brain scans from 94 people in their 70s who were still "cognitively normal" five years after the scan has revealed that people with higher body mass indexes had smaller brains on average, with the frontal and temporal lobes particularly affected (specifically, in the frontal lobes, anterior cingulate gyrus, hippocampus, and thalamus, in obese people, and in the basal ganglia and corona radiate of the overweight). The brains of the 51 overweight people were, on average, 6% smaller than those of the normal-weight participants, and those of the 14 obese people were 8% smaller. To put it in more comprehensible, and dramatic terms: "The brains of overweight people looked eight years older than the brains of those who were lean, and 16 years older in obese people." However, overall brain volume did not differ between overweight and obese persons. As yet unpublished research by the same researchers indicates that exercise protects these same brain regions: "The most strenuous kind of exercise can save about the same amount of brain tissue that is lost in the obese."

Zilberman, J.M., Del Sueldo, M., Cerezo, G., Castellino, S., Theiler, E. & Vicario, A. 2011. Association Between Menopause, Obesity, and Cognitive Impairment. Presented at the Physiology of Cardiovascular Disease: Gender Disparities conference, October 12, at the University of Mississippi in Jackson.

Vicario, A., Del Sueldo, M., Zilberman, J. & Cerezo, G.H. 2011. The association between metabolic syndrome, inflammation and cognitive decline. Presented at the European Society of Hypertension (ESH) 2011: 21st European Meeting on Hypertension, June 17 - 20, Milan, Italy.

[733] Thompson PM, Raji CA, Ho AJ, Parikshak NN, Becker JT, Lopez OL, Kuller LH, Hua X, Leow AD, Toga AW. Brain structure and obesity. Human Brain Mapping [Internet]. 2010 ;31(3):353 - 364. Available from: http://dx.doi.org/10.1002/hbm.20870

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’.

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

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

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

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

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

Following on from previous studies showing that drinking beet juice can lower blood pressure, a study involving 14 older adults (average age 75) has found that after two days of eating a high-nitrate breakfast, which included 16 ounces of beet juice, blood flow to the white matter of the frontal lobes (especially between the dorsolateral prefrontal cortex and anterior cingulate cortex) had increased. This area is critical for executive functioning.

Poor blood flow in the brain is thought to be a factor in age-related cognitive decline and dementia.

High concentrations of nitrates are found in beets, as well as in celery, cabbage and other leafy green vegetables like spinach and some lettuce. When you eat high-nitrate foods, good bacteria in the mouth turn nitrate into nitrite. Research has found that nitrites can help open up the blood vessels in the body, increasing blood flow and oxygen specifically to places that are lacking oxygen.

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

August 2009

Overweight and obese elderly have smaller brains

Analysis of brain scans from 94 people in their 70s who were still "cognitively normal" five years after the scan has revealed that people with higher body mass indexes had smaller brains on average, with the frontal and temporal lobes particularly affected (specifically, in the frontal lobes, anterior cingulate gyrus, hippocampus, and thalamus, in obese people, and in the basal ganglia and corona radiate of the overweight). The brains of the 51 overweight people were, on average, 6% smaller than those of the normal-weight participants, and those of the 14 obese people were 8% smaller. To put it in more comprehensible, and dramatic terms: "The brains of overweight people looked eight years older than the brains of those who were lean, and 16 years older in obese people." However, overall brain volume did not differ between overweight and obese persons. As yet unpublished research by the same researchers indicates that exercise protects these same brain regions: "The most strenuous kind of exercise can save about the same amount of brain tissue that is lost in the obese."

Raji, C.A. et al. 2009. Brain structure and obesity. Human Brain Mapping, Published Online: Aug 6 2009

http://www.newscientist.com/article/mg20327222.400-expanding-waistlines-may-cause-shrinking-brains

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

September 2008

From 12 years onward you learn differently

Behavioral studies have found eight-year-olds learn primarily from positive feedback, with negative feedback having little effect. Twelve-year-olds, however, are better able to process negative feedback, and use it to learn from their mistakes. Now brain imaging reveals that the brain regions responsible for cognitive control (specifically, the dorsolateral prefrontal cortex and superior parietal cortex, and the pre-supplementary motor area/anterior cingulate cortex) react strongly to positive feedback and scarcely respond at all to negative feedback in children of eight and nine, but the opposite is the case in children of 11 to 13 years, and also in adults.

van Duijvenvoorde, A.C.K. et al. 2008. Evaluating the Negative or Valuing the Positive? Neural Mechanisms Supporting Feedback-Based Learning across Development. The Journal of Neuroscience, 28, 9495-9503.

http://www.eurekalert.org/pub_releases/2008-09/lu-f1y092508.php
http://www.physorg.com/news141554842.html

December 2006

Neurons targeted by dementing illness may have evolved for complex social cognition

Special elongated nerve cells called spindle neurons, also known as Von Economo neurons (VENs), are found in two parts of the cerebral cortex known to be associated with social behavior, consciousness, and emotion (the anterior cingulate and fronto-insular cortex). They have only been found in humans and great apes, and, recently, whales. Because of this link with social behaviour, and because these brain regions are targeted by frontotemporal dementia, a recent study investigated whether VENs play a role in this type of dementia that causes people to lose inhibition in social situations. Autopsies revealed that among FTD sufferers, the anterior cingulate cortex had a dramatic reduction in the number of VENs compared to controls. In contrast, Alzheimer's patients had only a small and statistically insignificant reduction.

Seeley, W.W. et al. 2006. Early Frontotemporal Dementia Targets Neurons Unique to Apes and Humans. Annals of Neurology, published online ahead of print Decumber 22

http://sciencenow.sciencemag.org/cgi/content/full/2006/1222/1?etoc
http://www.sciencedaily.com/releases/2006/12/061222090935.htm
http://www.eurekalert.org/pub_releases/2006-12/uoc--wih122106.htm

May 2006

Master planners in brain may coordinate other areas' roles in cognitive tasks

Scans of 183 subjects have identified 3 brain areas most consistently active during a variety of cognitive tasks — the dorsal anterior cingulate and the left and right frontal operculum. It’s suggested that these regions coordinate the activities of specialized regions. In a rather lovely analogy, researchers suggested that if the brain in action can be compared to a symphony, with specialized sections required to pitch in at the right time to produce the desired melody, then the regions highlighted by the new study may be likened to conductors. Until now, the function of the opercula has been a mystery; the findings also suggest a rethinking of the role of the cingulate.

Dosenbach, N.U.F. et al. 2006. A core system for the implementation of task sets. Neuron, 50(5), 799-812.

http://www.sciencedaily.com/releases/2006/05/060531165250.htm
http://www.eurekalert.org/pub_releases/2006-05/wuso-mpi053006.php

April 2006

AIDS-related cognitive impairment exists in two separate forms

Cognitive impairment in people with AIDS is caused when the HIV virus attacks the brain and can be a complicated syndrome resulting in deficits in mood, behavior, motor coordination and thought processes. While the incidence of severe dementia in people with AIDS has decreased significantly, a greater number of people are living with a milder form of cognitive impairment. A study of 54 participants with AIDS and 23 HIV-negative control subjects has found that cognitive impairment in people with AIDS exists in two forms -- one mild, another severe -- each affecting different areas of the brain. Of the 54 participants with AIDS, 17 demonstrated some level of mental impairment. The mild impairment group only showed problems in the area of psychomotor speed, and demonstrated atrophy in the frontal and anterior cingulate cortices. Those in the severe impairment group showed impairments in memory and visual-spatial processing as well as psychomotor speed, and had more significant atrophy that was located in the caudate and putamen.

The findings were presented April 5 at the American Academy of Neurology 58th Annual Meeting in San Diego.

http://www.eurekalert.org/pub_releases/2006-04/uopm-aci040306.php

February 2006

A single memory is processed in three separate parts of the brain

A rat study has demonstrated that a single experience is indeed processed differently in separate parts of the brain. They found that when the rats were confined in a dark compartment of a familiar box and given a mild shock, the hippocampus was involved in processing memory for context, while the anterior cingulate cortex was responsible for retaining memories involving unpleasant stimuli, and the amygdala consolidated memories more broadly and influenced the storage of both contextual and unpleasant information.

Malin, E.L. & McGaugh, J.L. 2006. Differential involvement of the hippocampus, anterior cingulate cortex, and basolateral amygdala in memory for context and footshock. Proceedings of the National Academy of Sciences, 103 (6), 1959-1963.

http://www.eurekalert.org/pub_releases/2006-02/uoc--urp020106.php

November 2005

Coffee jump-starts short-term memory

An imaging study of 15 males aged 26-47 has found that after consuming caffeine, all showed improved reaction times, and increased activity in part of the frontal lobe and in the anterior cingulate cortex. The findings are consistent with earlier research showing caffeine improves attention.

Koppelstätter, F. et al. 2005. Presented at the annual meeting of the Radiological Society of North America in Chicago.

http://www.eurekalert.org/pub_releases/2005-11/rson-cjs112005.php

August 2005

Insight into the processes of 'positive' and 'negative' learners

An intriguing study of the electrical signals emanating from the brain has revealed two types of learners. A brainwave event called an "event-related potential" (ERP) is important in learning; a particular type of ERP called "error-related negativity" (ERN), is associated with activity in the anterior cingulate cortex. This region is activated during demanding cognitive tasks, and ERNs are typically more negative after participants make incorrect responses compared to correct choices. Unexpectedly, studies of this ERN found a difference between "positive" learners, who perform better at choosing the correct response than avoiding the wrong one, and "negative" learners, who learn better to avoid incorrect responses. The negative learners showed larger ERNs, suggesting that "these individuals are more affected by, and therefore learn more from, their errors.” Positive learners had larger ERNs when faced with high-conflict win/win decisions among two good options than during lose/lose decisions among two bad options, whereas negative learners showed the opposite pattern.

Frank, M.J., Woroch, B.S. & Curran, T. 2005. Error-Related Negativity Predicts Reinforcement Learning and Conflict Biases. Neuron, 47, 495-501.

http://www.eurekalert.org/pub_releases/2005-08/cp-iit081205.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 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

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

April 2004

How we retrieve distant memories

We know that recent memories are stored in the hippocampus, but these memories do not remain there forever. It has been less clear how we retrieve much older memories. Now studies of mice genetically altered to be unable to recall old memories have demonstrated that a part of the cortex called the anterior cingulate is critical for this process. It is suggested that, rather than this structure being the storage site for old memories, the anterior cingulate assembles signals of an old memory from different sites in the brain. Dementia may result from a malfunction in this assembling process, leaving the memory too fragmented to make proper sense. Both ageing and certain aspects of Alzheimer's disease and other dementias are all accompanied by reduced activity in the anterior cingulate.

Frankland, P.W., Bontempi, B., Talton, L.E., Kaczmarek, L. & Silva, A.J. 2004. The Involvement of the Anterior Cingulate Cortex in Remote Contextual Fear Memory. Science, 304, 881-883.

http://news.bbc.co.uk/2/hi/health/3689335.stm

August 2002

Identity memory area localized

An imaging study investigating brain activation when people were asked to answer yes or no to statements about themselves (e.g. 'I forget important things', 'I'm a good friend', 'I have a quick temper'), found consistent activation in the anterior medial prefrontal and posterior cingulate. This is consistent with lesion studies, and suggests that these areas of the cortex are involved in self-reflective thought.

Johnson, S.C., Baxter, L.C., Wilder, L.S., Pipe, J.G., Heiserman, J.E. & Prigatano, G.P. 2002. Neural correlates of self-reflection. Brain, 125 (8), 1808-14.

http://brain.oupjournals.org/cgi/content/abstract/125/8/1808