a fold in the lower area of the temporal lobe. The area is involved in object recognition.
A study involving 159 older adults (average age 76) has confirmed that the amount of brain tissue in specific regions is a predictor of Alzheimer’s disease development. Of the 159 people, 19 were classified as at high risk on the basis of the smaller size of nine small regions previously shown to be vulnerable to Alzheimer's), and 24 as low risk. The regions, in order of importance, are the medial temporal, inferior temporal, temporal pole, angular gyrus, superior parietal, superior frontal, inferior frontal cortex, supramarginal gyrus, precuneus.
There was no difference between the three risk groups at the beginning of the study on global cognitive measures (MMSE; Alzheimer’s Disease Assessment Scale—cognitive subscale; Clinical Dementia Rating—sum of boxes), or in episodic memory. The high-risk group did perform significantly more slowly on the Trail-making test part B, with similar trends on the Digit Symbol and Verbal Fluency tests.
After three years, 125 participants were re-tested. Nine met the criteria for cognitive decline. Of these, 21% were from the small high-risk group (3/14) and 7% from the much larger average-risk group (6/90). None were from the low-risk group.
The results were even more marked when less stringent criteria were used. On the basis of an increase on the Clinical Dementia Rating, 28.5% of the high-risk group and 9.7% of the average-risk group showed decline. On the basis of declining at least one standard deviation on any one of the three neuropsychological tests, half the high-risk group, 35% of the average risk group, and 14% (3/21) of the low-risk group showed decline. (The composite criteria required both of these criteria.)
Analysis estimated that every standard deviation of cortical thinning (reduced brain tissue) was associated with a nearly tripled risk of cognitive decline.
The 84 individuals for whom amyloid-beta levels in the cerebrospinal fluid were available also revealed that 60% of the high-risk group had levels consistent with the presence of Alzheimer's pathology, compared to 36% of those at average risk and 19% of those at low risk.
The findings extend and confirm the evidence that brain atrophy in specific regions is a biomarker for developing Alzheimer’s.
 Dickerson, B. C., & Wolk D. A.
(2012). MRI cortical thickness biomarker predicts AD-like CSF and cognitive decline in normal adults.
Neurology. 78(2), 84 - 90.
Dickerson BC, Bakkour A, Salat DH, et al. 2009. The cortical signature of Alzheimer’s disease: regionally specific cortical thinning relates to symptom severity in very mild to mild AD dementia and is detectable in asymptomatic amyloidpositive individuals. Cereb Cortex;19:497–510.
Another study adds to the weight of evidence that meditating has cognitive benefits. The latest finding points to brain-wide improvements in connectivity.
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.
 Luders, E., Clark K., Narr K. L., & Toga A. W.
(2011). Enhanced brain connectivity in long-term meditation practitioners.
NeuroImage. 57(4), 1308 - 1316.
An imaging study has found three different brain signatures discriminating children with autistic spectrum disorders, siblings of children with ASD, and other typically-developing children.
Last month I reported on a finding that toddlers with autism spectrum disorder showed a strong preference for looking at moving shapes rather than active people. This lower interest in people is supported by a new imaging study involving 62 children aged 4-17, of whom 25 were diagnosed with autistic spectrum disorder and 20 were siblings of children with ASD.
In the study, participants were shown point-light displays (videos created by placing lights on the major joints of a person and filming them moving in the dark). Those with ASD showed reduced activity in specific regions (right amygdala, ventromedial prefrontal cortex, right posterior superior temporal sulcus, left ventrolateral prefrontal cortex, and the fusiform gyri) when they were watching a point-light display of biological motion compared with a display of moving dots. These same regions have also been implicated in previous research with adults with ASD.
Moreover, the severity of social deficits correlated with degrees of activity in the right pSTS specifically. More surprisingly, other brain regions (left dorsolateral prefrontal cortex, right inferior temporal gyrus, and a different part of the fusiform gyri) showed reduced activity in both the siblings group and the ASD group compared to controls. The sibling group also showed signs of compensatory activity, with some regions (right posterior temporal sulcus and a different part of the ventromedial prefrontal cortex) working harder than normal.
The implications of this will be somewhat controversial, and more research will be needed to verify these findings.
 Kaiser, M. D., Hudac C. M., Shultz S., Lee S. M., Cheung C., Berken A. M., et al.
(2010). Neural signatures of autism.
Proceedings of the National Academy of Sciences.
Full text available at http://www.pnas.org/content/early/2010/11/05/1010412107.full.pdf+html
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