A study involving older adults has found that diabetes was associated with higher levels of tau protein and greater brain atrophy.
The study involved 816 older adults (average age 74), of whom 397 had mild cognitive impairment, 191 had Alzheimer's disease, and 228 people had no cognitive problems. Fifteen percent (124) had diabetes.
Those with diabetes had greater levels of tau protein in the spinal and brain fluid regardless of cognitive status. Tau tangles are characteristic of Alzheimer's.
Those with diabetes also had cortical tissue that was an average of 0.03 millimeter less than those who didn't have diabetes, regardless of their cognitive status. This greater brain atrophy in the frontal and parietal cortices may be partly related to the increase in tau protein.
There was no link between diabetes and amyloid-beta, the other main pathological characteristic of Alzheimer's.
Previous research has indicated that people with type 2 diabetes have double the risk of developing dementia. Previous research has also found that those who had been diabetic for longer had a greater degree of brain atrophy
The findings support the idea that type 2 diabetes may have a negative effect on cognition independent of dementia, and that this effect may be driven by an increase in tau phosphorylation.
(2015). Type 2 diabetes mellitus and biomarkers of neurodegeneration.
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.
(2012). Β-Amyloid Burden in Healthy Aging Regional Distribution and Cognitive Consequences.
Neurology. 78(6), 387 - 395.
(2012). APOE modifies the association between Aβ load and cognition in cognitively normal older adults.
Neurology. 78(4), 232 - 240.
Why is diabetes associated with cognitive impairment and even dementia in older adults? New research pinpoints two molecules that trigger a cascade of events that end in poor blood flow and brain atrophy.
The study involved 147 older adults (average age 65), of whom 71 had type 2 diabetes and had been taking medication to manage it for at least five years. Brain scans showed that the diabetic patients had greater blood vessel constriction than the age- and sex-matched controls, and more brain atrophy. The reduction in brain tissue was most marked in the grey matter in the parietal and occipital lobes and cerebellum. Research has found that, at this age, while the average brain shrinks by about 1% annually, a diabetic brain might shrink by as much as 15%. Diabetics also had more white matter hyperintensities in the temporal, parietal and occipital lobes.
Behaviorally, the diabetics also had greater depression, slower walking, and executive dysfunction.
The reduced performance of blood vessels (greater vasoconstriction, blunted vasodilatation), and increased brain atrophy in the frontal, temporal, and parietal lobes, was associated with two adhesion molecules – sVCAM and sICAM. White matter hyperintensities were not associated with the adhesion molecules, inflammatory markers, or blood vessel changes.
It seems that the release of these molecules, probably brought about by chronic hyperglycemia and insulin resistance, produces chronic inflammation, which in turn brings about constricted blood vessels, reduced blood flow, and finally loss of neurons. The blood vessel constriction and the brain atrophy were also linked to higher glucose levels.
The findings suggest that these adhesion molecules provide two biomarkers of vascular health that could enable clinicians to recognize impending brain damage, that could then perhaps be prevented.
The findings also add weight to the growing evidence that diabetes management is crucial in preventing cognitive decline.
(2011). Adhesion Molecules, Altered Vasoreactivity, and Brain Atrophy in Type 2 Diabetes.
Diabetes Care. 34(11), 2438 - 2441.
The issue of “mommy brain” is a complex one. Inconsistent research results make it clear that there is no simple answer to the question of whether or not pregnancy and infant care change women’s brains. But a new study adds to the picture.
Brain scans of 19 women two to four weeks and three to four months after they gave birth showed that grey matter volume increased by a small but significant amount in the midbrain (amygdala, substantia nigra, hypothalamus), prefrontal cortex, and parietal lobe. These areas are involved in motivation and reward, emotion regulation, planning, and sensory perception.
Mothers who were most enthusiastic about their babies were significantly more likely to show this increase in the midbrain regions. The authors speculated that the “maternal instinct” might be less of an instinctive response and more of a result of active brain building. Interestingly, while the brain’s reward regions don’t usually change as a result of learning, one experience that does have this effect is that of addiction.
While the reasons may have to do with genes, personality traits, infant behavior, or present circumstances, previous research has found that mothers who had more nurturing in their childhood had more grey matter in those brain regions involved in empathy and reading faces, which also correlated with the degree of activation in those regions when their baby cried.
A larger study is of course needed to confirm these findings.
(2010). The plasticity of human maternal brain: Longitudinal changes in brain anatomy during the early postpartum period..
Behavioral Neuroscience. 124(5), 695 - 700.
Older news items (pre-2010) brought over from the old website
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.
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.
Sex difference on spatial skill test linked to brain structure
It’s been well established that men (as a group) consistently out-perform women on spatial tasks. Research has also established that the parietal lobes in women tend to have proportionally more gray matter. Now a new study shows that the thicker cortex in the parietal lobe in women is associated with poorer mental rotation ability. It also reveals that the surface area of the parietal lobe is increased in men, compared to women, and this is directly related to better performance on mental rotation tasks. It also appears that, perhaps because the brain structure is different between men and women, the way the brain performs the task is different. While men appear able to globally rotate an object in space, women seem to do it piecemeal.
Koscik, T. et al. 2008. Sex differences in parietal lobe morphology: Relationship to mental rotation performance. Brain and Cognition, Article in Press
A new study provides more evidence that the ability to deliberately focus your attention is physically separate in the brain from the part that helps you filter out distraction. The study trained monkeys to take attention tests on a video screen in return for a treat of apple juice. When the monkeys voluntarily concentrated (‘top-down’ attention), the prefrontal cortex was active, but when something distracting grabbed their attention (‘bottom-up’ attention), the parietal cortex became active. The electrical activity in these two areas vibrated in synchrony as they signaled each other, but top-down attention involved synchrony that was stronger in the lower-frequencies and bottom-up attention involved higher frequencies. These findings may help us develop treatments for attention disorders.
Buschman, T.J. & Miller, E.K. 2007. Top-Down Versus Bottom-Up Control of Attention in the Prefrontal and Posterior Parietal Cortices. Science, 315 (5820), 1860-1862.
Right parietal lobe implicated in dyscalculia
By temporarily knocking out an area in the right parietal lobe (the right intraparietal sulcus), researchers have induced dyscalculia in normal subjects, providing strong evidence that dyscalculia is caused by malfunction in this area. These findings were further validated by testing participants suffering from developmental dyscalculia. Although less well-known, dyscalculia is as prevalent as dyslexia and attention deficit hyperactivity disorder (around 5%).
Kadosh, R.C. et al. 2007. Virtual Dyscalculia Induced by Parietal-Lobe TMS Impairs Automatic Magnitude Processing. Current Biology, online ahead of print March 22
Fast language learners have more white matter in auditory region
An imaging study has found that fast language learners have more white matter in a region of the brain that’s critical for processing sound. The study involved 65 French adults in their twenties, who were asked to distinguish two closely related sounds (the French 'da' sound from the Hindi 'da' sound). There was considerable variation in people’s ability to learn to tell these sounds apart — the fastest could do it within 8 minutes; the slowest were still guessing randomly after 20 minutes. The 11 fastest and 10 slowest learners were then given brain scans, revealing that the fastest learners had, on average, 70% more white matter in the left Heschl's gyrus than the slowest learners, as well as a greater asymmetry in the parietal lobe (the left being bigger than the right).
Golestani, N., Molko, N., Dehaene, S., LeBihan, D. & Pallier, C. 2006. Brain Structure Predicts the Learning of Foreign Speech Sounds. Cerebral Cortex, Advance Access published on April 7, 2006
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.
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
Development of working memory with age
An imaging study of 20 healthy 8- to 30-year-olds has shed new light on the development of working memory. The study found that pre-adolescent children relied most heavily on the prefrontal cortex and parietal regions of the brain during the working memory task; adolescents used those regions plus the anterior cingulate; and in adults, a third area of the brain, the medial temporal lobe, was brought in to support the functions of the other areas. Adults performed best. The results support the view that a person's ability to have voluntary control over behavior improves with age because with development, additional brain processes are used.
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
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."
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.