Temporal Lobe

A pilot study involving 17 older adults with mild cognitive impairment and 18 controls (aged 60-88; average age 78) has found that a 12-week exercise program significantly improved performance on a semantic memory task, and also significantly improved brain efficiency, for both groups.

The program involved treadmill walking at a moderate intensity. The semantic memory tasks involved correctly recognizing names of celebrities well known to adults born in the 1930s and 40s (difficulty in remembering familiar names is one of the first tasks affected in Alzheimer’s), and recalling words presented in a list. Brain efficiency was demonstrated by a decrease in the activation intensity in the 11 brain regions involved in the memory task. The brain regions with improved efficiency corresponded to those involved in Alzheimer's disease, including the precuneus region, the temporal lobe, and the parahippocampal gyrus.

Participants also improved their cardiovascular fitness, by about 10%.


Smith, J.C. et al. 2013. Semantic Memory Functional MRI and Cognitive Function After Exercise Intervention in Mild Cognitive Impairment. Journal of Alzheimer’s Disease, 37 (1), 197-215.

11 new genetic susceptibility factors for Alzheimer’s identified

The largest international study ever conducted on Alzheimer's disease (I-GAP) has identified 11 new genetic regions that increase the risk of late-onset Alzheimer’s, plus 13 other genes yet to be validated. Genetic data came from 74,076 patients and controls from 15 countries.

Eleven genes for Alzheimer's disease have previously been identified.

Some of the newly associated genes confirm biological pathways already known to be involved, including the amyloid (SORL1, CASS4 ) and tau (CASS4 , FERMT2 ) pathways. The role of the immune response and inflammation (HLA-DRB5/DRB1 , INPP5D , MEF2C ) already implied by previous work (CR1, TREM2) is reinforced, as are the importance of cell migration (PTK2B), lipid transport and endocytosis (SORL1 ). New hypotheses have also emerged related to hippocampal synaptic function (MEF2C , PTK2B), the cytoskeleton and axonal transport (CELF1 , NME8, CASS4) as well as myeloid and microglial cell functions (INPP5D).

All this reinforces the idea that there are several paths to Alzheimer's, and no single treatment approach is likely to be successful.


[3586] Lambert J-C, Ibrahim-Verbaas CA, Harold D, Naj AC, Sims R, Bellenguez C, Jun G, DeStefano AL, Bis JC, Beecham GW, et al. Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease. Nature Genetics [Internet]. 2013 ;45(12):1452 - 1458. Available from: http://www.nature.com/ng/journal/v45/n12/full/ng.2802.html

ADAM10 mutations increase risk of Alzheimer's

Mouse studies have found that two mutations in a gene called ADAM10 (which codes for an enzyme involved in processing the amyloid precursor protein) impaired the folding of the gene, resulting in an increase in toxic amyloid-beta, and reduced neurogenesis in the hippocampus. Previous research had found that either of these mutations was associated with an increased risk of Alzheimer’s in seven families with the late-onset form of the disease.

The finding suggests that increasing ADAM10 activity might be a potential therapeutic approach.


[3610] Suh J, Choi SH, Romano DM, Gannon MA, Lesinski AN, Kim DY, Tanzi RE. ADAM10 Missense Mutations Potentiate β-Amyloid Accumulation by Impairing Prodomain Chaperone Function. Neuron [Internet]. 2013 ;80(2):385 - 401. Available from: http://www.cell.com/article/S0896627313007940/abstract

TREM2 gene variant has dramatic effect on brain atrophy

Back in January 2013, a study (initially involving 2261 Icelanders, but then repeated on data from the U.S., Norway, the Netherlands, and Germany) reported on a rare genetic variant (TREM2) that nearly trebled Alzheimer’s risk. The variant was found in 0.46% of controls aged 85+. Carriers (aged 85-100) without Alzheimer’s also had poorer cognitive function than non-carriers.

TREM2 is thought to have an anti-inflammatory role, and so it’s thought that this rare mutation reduces its effectiveness.

In a more recent study, brain scans of 478 older adults (average age 76), of whom 100 had Alzheimer's, 221 had MCI and 157 were healthy controls, found that those carrying the TREM2 mutation lost 1.4-3.3% more of their brain tissue than non-carriers, and twice as fast. The loss appeared to be concentrated in the temporal lobe and hippocampus. Those carrying the TREM2 mutation may develop the disease three years earlier than expected.


[3581] Jonsson T, Stefansson H, Steinberg S, Jonsdottir I, Jonsson PV, Snaedal J, Bjornsson S, Huttenlocher J, Levey AI, Lah JJ, et al. Variant of TREM2 Associated with the Risk of Alzheimer's Disease. New England Journal of Medicine [Internet]. 2013 ;368(2):107 - 116. Available from: http://www.nejm.org/doi/full/10.1056/NEJMoa1211103

Rajagopalan, P., Hibar, D.P., & Thompson, P.M. (2013). TREM2 and neurodegenerative disease. The New England Journal of Medicine, 369(16), 1564-1567. Published online Oct. 16, 2013; doi:10.1056/NEJMc1306509

Recent research has suggested that sleep problems might be a risk factor in developing Alzheimer’s, and in mild cognitive impairment. A new study adds to this gathering evidence by connecting reduced slow-wave sleep in older adults to brain atrophy and poorer learning.

The study involved 18 healthy young adults (mostly in their 20s) and 15 healthy older adults (mostly in their 70s). Participants learned 120 word- nonsense word pairs and were tested for recognition before going to bed. Their brain activity was recorded while they slept. Brain activity was also measured in the morning, when they were tested again on the word pairs.

As has been found previously, older adults showed markedly less slow-wave activity (both over the whole brain and specifically in the prefrontal cortex) than the younger adults. Again, as in previous studies, the biggest difference between young and older adults in terms of gray matter volume was found in the medial prefrontal cortex (mPFC). Moreover, significant differences were also found in the insula and posterior cingulate cortex. These regions, like the mPFC, have also been associated with the generation of slow waves.

When mPFC volume was taken into account, age no longer significantly predicted the extent of the decline in slow-wave activity — in other words, the decline in slow-wave activity appears to be due to the brain atrophy in the medial prefrontal cortex. Atrophy in other regions of the brain (precuneus, hippocampus, temporal lobe) was not associated with the decline in slow-wave activity when age was considered.

Older adults did significantly worse on the delayed recognition test than young adults. Performance on the immediate test did not predict performance on the delayed test. Moreover, the highest performers on the immediate test among the older adults performed at the same level as the lowest young adult performers — nevertheless, these older adults did worse the following day.

Slow-wave activity during sleep was significantly associated with performance on the next day’s test. Moreover, when slow-wave activity was taken into account, neither age nor mPFC atrophy significantly predicted test performance.

In other words, age relates to shrinkage of the prefrontal cortex, this shrinkage relates to a decline in slow-wave activity during sleep, and this decline in slow-wave sleep relates to poorer cognitive performance.

The findings confirm the importance of slow-wave brainwaves for memory consolidation.

All of this suggests that poorer sleep quality contributes significantly to age-related cognitive decline, and that efforts should be made to improve quality of sleep rather than just assuming lighter, more disturbed sleep is ‘natural’ in old age!

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.

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.


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’.

Following on from research showing that long-term meditation is associated with gray matter increases across the brain, an imaging study involving 27 long-term meditators (average age 52) and 27 controls (matched by age and sex) has revealed pronounced differences in white-matter connectivity between their brains.

The differences reflect white-matter tracts in the meditators’ brains being more numerous, more dense, more myelinated, or more coherent in orientation (unfortunately the technology does not yet allow us to disentangle these) — thus, better able to quickly relay electrical signals.

While the differences were evident among major pathways throughout the brain, the greatest differences were seen within the temporal part of the superior longitudinal fasciculus (bundles of neurons connecting the front and the back of the cerebrum) in the left hemisphere; the corticospinal tract (a collection of axons that travel between the cerebral cortex of the brain and the spinal cord), and the uncinate fasciculus (connecting parts of the limbic system, such as the hippocampus and amygdala, with the frontal cortex) in both hemispheres.

These findings are consistent with the regions in which gray matter increases have been found. For example, the tSLF connects with the caudal area of the temporal lobe, the inferior temporal gyrus, and the superior temporal gyrus; the UNC connects the orbitofrontal cortex with the amygdala and hippocampal gyrus

It’s possible, of course, that those who are drawn to meditation, or who are likely to engage in it long term, have fundamentally different brains from other people. However, it is more likely (and more consistent with research showing the short-term effects of meditation) that the practice of meditation changes the brain.

The precise mechanism whereby meditation might have these effects can only be speculated. However, more broadly, we can say that meditation might induce physical changes in the brain, or it might be protecting against age-related reduction. Most likely of all, perhaps, both processes might be going on, perhaps in different regions or networks.

Regardless of the mechanism, the evidence that meditation has cognitive benefits is steadily accumulating.

The number of years the meditators had practiced ranged from 5 to 46. They reported a number of different meditation styles, including Shamatha, Vipassana and Zazen.

Twice a week for four weeks, female hamsters were subjected to six-hour time shifts equivalent to a New York-to-Paris airplane flight. Cognitive tests taken during the last two weeks of jet lag and a month after recovery from it revealed difficulty learning simple tasks that control hamsters achieved easily. Furthermore, the jet-lagged hamsters had only half the number of new neurons in the hippocampus that the control hamsters had.

The findings support earlier research indicating that chronic jet lag impairs memory and learning and reduces the size of the temporal lobe, and points to the loss of brain tissue as being due to reduced neurogenesis in the hippocampus. Although further research is needed to clarify this, indications are that the problem is not so much fewer neurons being created, but fewer new cells maturing into working cells, or perhaps new cells dying prematurely.

Hamsters are excellent subjects for circadian rhythm research because their rhythms are so precise.

Over the years I’ve reported on a number of studies investigating the effect of chemotherapy on the brain. A new study uses brain imaging, before and after treatment for breast cancer, to show that there is an anatomic basis for “chemobrain” complaints. The study, involving 17 breast cancer patients treated with chemotherapy after surgery, 12 women with breast cancer who did not undergo chemotherapy after surgery, and 18 women without breast cancer, found that gray matter density decreased in the frontal lobe, temporal lobe, cerebellum and right thalamus, shortly after chemotherapy.

The areas affected are consistent with memory and executive functions like multi-tasking and processing speed being the most typically affected functions. Post-surgery scans were carried out at one month, and at one year. Gray matter density in most women had improved by one year after chemotherapy ended.

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

September 2009

Tetris increases gray matter and improves brain efficiency

In a study in which 26 adolescent girls played the computer game Tetris for half an hour every day for three months, their brains compared to controls increased grey matter in Brodmann Area 6 in the left frontal lobe and BAs 22 and 38 in the left temporal lobe — areas involved in planning complex coordinated movements, and coordinating sensory information. Their brains also showed greater efficiency, but in different areas — ones associated with critical thinking, reasoning, and language, mostly in the right frontal and parietal lobes. The finding points to improved efficiency being unrelated to grey matter increases.

Haier, R.J. et al. 2009. MRI assessment of cortical thickness and functional activity changes in adolescent girls following three months of practice on a visual-spatial task. BMC Research Notes, 2, 174. 
Text available at http://www.biomedcentral.com/1756-0500/2/174/abstract


Neural changes produced by learning to read revealed

Understanding how our brain structures change as we learn to read is difficult because of the confounding with age and the learning of other skills. Studying adult learners is also problematic because in most educated societies adult illiteracy is typically the result of learning impairments or poor health. Now a new study involving 20 former guerrillas in Colombia who are learning to read for the first time as adults has found that these late-literates showed a number of significant brain differences compared to matched adult illiterates, including more white matter between various regions, and more grey matter in various left temporal and occipital regions important for recognizing letter shapes and translating letters into speech sounds and their meanings. Particularly important were connections between the left and right angular gyri in the parietal lobe. While this area has long been known as important for reading, its function turns out to have been misinterpreted — it now appears its main role is in anticipating what we will see. The findings will help in understanding the causes of dyslexia.

Carreiras, M. et al. 2009. An anatomical signature for literacy. Nature, 461 (7266), 983-986.


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


April 2009

Object recognition fast and early in processing

We see through our eye and with our brain. Visual information flows from the retina through a hierarchy of visual areas in the brain until it reaches the temporal lobe, which is ultimately responsible for our visual perceptions, and also sends information back along the line, solidifying perception. This much we know, but how much processing goes on at each stage, and how important feedback is compared to ‘feedforward’, is still under exploration. A new study involving children about to undergo surgery for epilepsy (using invasive electrode techniques) reveals that feedback from the ‘smart’ temporal lobe is less important than we thought, that the brain can recognize objects under a variety of conditions very rapidly, at a very early processing stage. It appears that certain areas of the visual cortex selectively respond to specific categories of objects.

Liu, H. et al. 2009. Timing, Timing, Timing: Fast Decoding of Object Information from Intracranial Field Potentials in Human Visual Cortex. Neuron, 62 (2), 281-290.


Research suggests words are seen as units and processed quickly

What exactly is going on in our brain when we read? Two new studies suggest the process is quicker and more direct than we thought. One study revealed that a region of the brain in the fusiform gyrus called the visual word form area (VWFA) recognizes words as whole units rather than letter by letter – words that differed in only one letter (e.g., "farm" and "form") produced changes in brain activity that were as profound as between completely different words (e.g., "farm" and "coat"), while incremental changes occurred in response to single-letter changes in made-up words. In another study, it was revealed that, rather than processing words in a slow, hierarchical way, we seem to process words quickly, through direct connections between visual and speech-processing systems. The first area to respond to text was the text recognition area in the occipito-temporal cortex, but it was followed within 15msec by both the VWFA and Broca's area (involved in speech processing). The results provide support for the idea that the brain has two rapid reading pathways (simultaneous rather than sequential): a lexical route using the VWFA and a sublexical route through Broca's area to the motor areas that control sound production (allowing us to sound out unfamiliar words).

Glezer, L.S., Jiang, X. & Riesenhuber, M. 2009. Evidence for Highly Selective Neuronal Tuning to Whole Words in the Visual Word Form Area. Neuron, 62 (2), 199-204.
Cornelissen, P.L. et al. 2009. Activation of the Left Inferior Frontal Gyrus in the First 200 ms of Reading: Evidence from Magnetoencephalography (MEG). PLoS ONE, 4(4), e5359. doi:10.1371/journal.pone.0005359


October 2007

Brain activity distinguishes false from true recollection

Although memory confidence and accuracy tend to be positively correlated, people sometimes remember with high confidence events that never happened. A new imaging study reveals that, in cases of high confidence, responses were associated with greater activity in the medial temporal lobe when the event really happened, but with greater activity in the frontoparietal region when the memory was false. Both of these regions are involved in event memory, but the medial temporal lobe focuses on specific facts about the event, while the fronto-parietal network is more likely to process the global gist of the event.

Kim, H. & Cabeza, R. 2007. Trusting Our Memories: Dissociating the Neural Correlates of Confidence in Veridical versus Illusory Memories. Journal of Neuroscience, 27, 12190–12197.


September 2007

Why music training helps language

Several studies have come out in recent years suggesting that giving children music training can improve their language skills. A new study supports these findings by showing how. The latest study shows that music triggers changes in the brain stem, a very early stage in the processing pathway for both music and language. It has previously been thought that the automatic processing occurring at this level was not particularly malleable, and the strength of neuron connections there was fixed.

And in another study, researchers have found evidence for more commonality in the brain networks involved in music and language. One network, based in the temporal lobes, helps us memorize information in both language and music— for example, words and meanings in language and familiar melodies in music. The other network, based in the frontal lobes, helps us unconsciously learn and use the rules that underlie both language and music, such as the rules of syntax in sentences, and the rules of harmony in music.

Musacchia, G., Sams, M., Skoe, E. & Kraus, N. 2007. Musicians have enhanced subcortical auditory and audiovisual processing of speech and music. Proceedings of the National Academy of Sciences USA, 104, 15894-15898.
Miranda, R.A. & Ullman, M.T. 2007. Double dissociation between rules and memory in music: An event-related potential study. NeuroImage, 38 (2), 331-345.

http://www.sciam.com/article.cfm?chanID=sa003&articleID=39568C58-E7F2-99DF-32A49429C2B356CD&sc=WR_20071002 (1st)
http://www.sciencedaily.com/releases/2007/09/070926123908.htm (1st)
http://www.eurekalert.org/pub_releases/2007-09/gumc-tat092707.php (2nd)

June 2006

How does the bilingual brain distinguish between languages?

Studies of bilingual people have found that the same brain regions, particularly parts of the left temporal cortex, are similarly activated by both languages. But there must be some part of the brain that knows one language from another. A new imaging study reveals that this region is the left caudate — a finding supported by case studies of bilingual patients with damage to the left caudate, who are prone to switch languages involuntarily.

Crinion, J. et al. 2006. Language Control in the Bilingual Brain. Science, 312 (5779), 1537–1540.


April 2006

Specific brain region for reading

Although a number of imaging studies have provided support for the idea that there’s a specific area of the brain that enables us to read efficiently by allowing us to process the visual image of entire words, the question is still debated — partly because the same area also seems to be involved in the recognition of other objects and partly because damage in this region has never been confined to this region alone. Now the experience of an epileptic requiring removal of a small area next to the so-called visual word-form area (VWFA) in the left occipito-temporal cortex has provided evidence of the region's importance for reading. After the operation, the patient’s ability to comprehend words was dramatically slower, and the results were consistent with him reading letter by letter. A brain scan confirmed that the VWFA no longer lit up when words were read, perhaps because the surgery severed its connection to other parts of the brain.

Gaillard, R. et. al. 2006. Direct Intracranial, fMRI, and Lesion Evidence for the Causal Role of Left Inferotemporal Cortex in Reading. Neuron, 50, 191-204.


March 2005

How higher education protects older adults from cognitive decline

Research has indicated that higher education helps protect older adults from cognitive decline. Now an imaging study helps us understand how. The study compared adults from two age groups: 18-30, and over 65. Years of education ranged from 11 to 20 years for the younger group, and 8 to 21 for the older. Participants carried out several memory tasks while their brain was scanned. In young adults performing the memory tasks, more education was associated with less use of the frontal lobes and more use of the temporal lobes. For the older adults doing the same tasks, more education was associated with less use of the temporal lobes and more use of the frontal lobes. Previous research has indicated frontal activity is greater in old adults, compared to young; the new study suggests that this effect is related to the educational level in the older participants. The higher the education, the more likely the older adult is to recruit frontal regions, resulting in a better memory performance.

Springer, M.V., McIntosh, A.R., Winocur, G. & Grady, C.L. 2005. The Relation Between Brain Activity During Memory Tasks and Years of Education in Young and Older adults. Neuropsychology and Aging, 19 (2).


January 2005

IQ-related brain areas may differ in men and women

An imaging study of 48 men and women between 18 and 84 years old found that, although men and women performed equally on the IQ tests, the brain structures involved in intelligence appeared distinct. Compared with women, men had more than six times the amount of intelligence-related gray matter, while women had about nine times more white matter involved in intelligence than men did. Women also had a large proportion of their IQ-related brain matter (86% of white and 84% of gray) concentrated in the frontal lobes, while men had 90% of their IQ-related gray matter distributed equally between the frontal lobes and the parietal lobes, and 82% of their IQ-related white matter in the temporal lobes. The implications of all this are not clear, but it is worth noting that the volume of gray matter can increase with learning, and is thus a product of environment as well as genes. The findings also demonstrate that no single neuroanatomical structure determines general intelligence and that different types of brain designs are capable of producing equivalent intellectual performance.

Haier, R.J., Jung, R.E., Yeo, R.A., Head, K. & Alkire, M.T. 2005. The neuroanatomy of general intelligence: sex matters. NeuroImage, In Press, Corrected Proof, Available online 16 January 2005


July 2004

Intelligence based on the volume of gray matter in certain brain regions

Confirming earlier suggestions, the most comprehensive structural brain-scan study of intelligence to date supports an association between general intelligence and the volume of gray matter tissue in certain regions of the brain. Because these regions are located throughout the brain, a single "intelligence center" is unlikely. It is likely that a person's mental strengths and weaknesses depend in large part on the individual pattern of gray matter across his or her brain. Although gray matter amounts are vital to intelligence levels, only about 6% of the brain’s gray matter appears related to IQ — intelligence seems related to an efficient use of relatively few structures. The structures that are important for intelligence are the same ones implicated in memory, attention and language. There are also age differences: in middle age, more of the frontal and parietal lobes are related to IQ; less frontal and more temporal areas are related to IQ in the younger adults. Previous research has shown the regional distribution of gray matter in humans is highly heritable. The findings also challenge the recent view that intelligence may be a reflection of more subtle characteristics of the brain, such as the speed at which nerve impulses travel in the brain, or the number of neuronal connections present. It may of course be that all of these are factors.

Haier, R.J., Jung, R.E., Yeo, R.A., Head, K. & Alkire, M.T. 2004. Structural brain variation and general intelligence. Neuroimage. In press. http://dx.doi.org/10.1016/j.neuroimage.2004.04.025


November 2003

Maturation of the human brain mapped

The progressive maturation of the human brain in childhood and adolescence has now been mapped. The initial overproduction of synapses in the gray matter that occurs after birth, is followed, for the most part just before puberty, with their systematic pruning. The mapping has confirmed that this maturation process occurs in different regions at different times, and has found that the normal gray matter loss begins first in the motor and sensory parts of the brain, and then slowly spreads downwards and forwards, to areas involved in spatial orientation, speech and language development, and attention (upper and lower parietal lobes), then to the areas involved in executive functioning, attention or motor coordination (frontal lobes), and finally to the areas that integrate these functions (temporal lobe). "The surprising thing is that the sequence in which the cortex matures appears to agree with regionally relevant milestones in cognitive development, and also reflects the evolutionary sequence in which brain regions were formed."


November 2001

Separate brain regions for living vs nonliving categories

Lobectomy patients were compared to normal control subjects on a variety of category naming and matching tasks. Patients were disproportionately impaired for naming living things relative to nonliving things. The authors argue that damage to the temporal lobe impairs lexical retrieval most strongly for living things and that the anterior temporal cortices are convergence zones particularly necessary for retrieving the names of living things.

Luckhurst,L. & Lloyd-Jones, T.J. 2001. A Selective Deficit for Living Things after Temporal Lobectomy for Relief of Epileptic Seizures. Brain and Language, 79 (2), 266-296.

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.


inferior temporal gyrus

May 2009

Meditation may increase gray matter

Adding to the increasing evidence for the cognitive benefits of meditation, a new imaging study of 22 experienced meditators and 22 controls has revealed that meditators showed significantly larger volumes of the right hippocampus and the right orbitofrontal cortex, and to a lesser extent the right thalamus and the left inferior temporal gyrus. There were no regions where controls had significantly more gray matter than meditators. These areas of the brain are all closely linked to emotion, and may explain meditators' improved ability in regulating their emotions.

Luders, E. et al. 2009. The underlying anatomical correlates of long-term meditation: Larger hippocampal and frontal volumes of gray matter. NeuroImage, 45 (3), 672-678.


February 2004

Special training may help people with autism recognize faces

People with autism tend to activate object-related brain regions when they are viewing unfamiliar faces, rather than a specific face-processing region. They also tend to focus on particular features, such as a mustache or a pair of glasses. However, a new study has found that when people with autism look at a picture of a very familiar face, such as their mother's, their brain activity is similar to that of control subjects – involving the fusiform gyrus, a region in the brain's temporal lobe that is associated with face processing, rather than the inferior temporal gyrus, an area associated with objects. Use of the fusiform gyrus in recognizing faces is a process that starts early with non-autistic people, but does take time to develop (usually complete by age 12). The study indicates that the fusiform gyrus in autistic people does have the potential to function normally, but may need special training to operate properly.

Aylward, E. 2004. Functional MRI studies of face processing in adolescents and adults with autism: Role of experience. Paper presented February 14 at the annual meeting of the American Association for the Advancement of Science in Seattle.
Dawson, G. & Webb, S. 2004. Event related potentials reveal early abnormalities in face processing autism. Paper presented February 14 at the annual meeting of the American Association for the Advancement of Science in Seattle.


Anterior temporal cortex

December 2004

How the brain recognizes a face

Face recognition involves at least three stages. An imaging study has now localized these stages to particular regions of the brain. It was found that the inferior occipital gyrus was particularly sensitive to slight physical changes in faces. The right fusiform gyrus (RFG), appeared to be involved in making a more general appraisal of the face and compares it to the brain's database of stored memories to see if it is someone familiar. The third activated region, the anterior temporal cortex (ATC), is believed to store facts about people and is thought to be an essential part of the identifying process.

Rotshtein, P., Henson, R.N.A., Treves, A., Driver, J. & Dolan, R.J. 2005. Morphing Marilyn into Maggie dissociates physical and identity face representations in the brain. Nature Neuroscience, 8, 107-113.


Temporal pole

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.


Lateral temporal cortex

May 2005

Brain networks change according to cognitive task

Using a newly released method to analyze functional magnetic resonance imaging, researchers have demonstrated that the interconnections between different parts of the brain are dynamic and not static. Moreover, the brain region that performs the integration of information shifts depending on the task being performed. The study involved two language tasks, in which subjects were asked to read individual words and then make a spelling or rhyming judgment. Imaging showed that the lateral temporal cortex (LTC) was active for the rhyming task, while the intraparietal sulcus (IPS) was active for the spelling task. The inferior frontal gyrus (IFG) and the fusiform gyrus (FG) were engaged by both tasks. However, Dynamic Causal Modeling (the new method for analyzing imaging data) revealed that the network took different configurations depending on the goal of the task, with each task preferentially strengthening the influences converging on the task-specific regions (LTC for rhyming, IPS for spelling). This suggests that task specific regions serve as convergence zones that integrate information from other parts of the brain. Additionally, switching between tasks led to changes in the influence of the IFG on the task-specific regions, suggesting the IFG plays a pivotal role in making task-specific regions more or less sensitive. This is consistent with previous studies showing that the IFG is active in many different language tasks and plays a role in integrating brain regions.

Bitan, T., Booth, J.R., Choy, J., Burman, D.D., Gitelman, D.R. & Mesulam, M-M. 2005. Shifts of Effective Connectivity within a Language Network during Rhyming and Spelling. Journal of Neuroscience, 25, 5397-5403.


Superior temporal gyrus

March 2009

Unraveling the roots of dyslexia

There is some evidence that dyslexia is distinguished by a basic deficit in phonological processing, characterized by difficulties in segmenting spoken words into their minimally discernable speech segments (speech sounds, or phonemes). A new study investigating brain activity of dyslexics and normal adult readers when presented with letters, speech sounds, or a matching or non-matching combination of the two, has revealed that dyslexic adults showed lower activation of the superior temporal cortex when needing to integrate letter and speech sounds. The findings point to reading failure being caused by a neural deficit in integrating letters with their speech sounds.

Blau, V. et al. 2009. Reduced Neural Integration of Letters and Speech Sounds Links Phonological and Reading Deficits in Adult Dyslexia. Current Biology, 19 (6), 503-508.


April 2004

Brain region involved in insight localized

An imaging study has revealed a unique neural signature of those “Aha!” moments of sudden insight. Participants were given word problems which can be solved quickly with or without insight, and asked to press a button to indicate whether they had solved the problem using insight, which they had been told leads to an Aha! experience characterized by suddenness and obviousness. While several regions in the cerebral cortex showed about the same heightened activity for both insight and noninsight-derived solutions, only an area known as the anterior superior temporal gyrus in the right hemisphere showed a robust insight effect. The researchers also found that 0.3 seconds before the subjects indicated solutions achieved through insight, there was a burst of neural activity of one particular type: high-frequency (gamma band) activity that is often thought to reflect complex cognitive processing. This supports the view that the insight process involves integration of distantly related information.

Jung-Beeman, M., Bowden, E.M., Haberman, J., Frymiare, J.L., Arambel-Liu, S. et al. 2004. Neural activity when people solve verbal problems with insight. PLoS Biol 2(4): e97 DOI: 10.1371/journal.pbio.0020097
Full text available at http://www.plosbiology.org/plosonline/?request=get-document&doi=10.1371/journal.pbio.0020097