Selective increase of cortical thickness in high-performing elderly--structural indices of optimal cognitive aging.
ABSTRACT The aim of this study was to identify cortical areas important for optimal cognitive aging. 74 participants (20-88 years) went through neuropsychological tests and two MR sessions. The sample was split into two age groups. In each, every participant was classified as "high" or "average" on fluid ability tests and on neuropsychological tests related to executive function. The groups were compared with regard to thickness on a point-by-point basis across the entire cortical mantle. The old high fluid performers had thicker cortex than the average performers in large areas of cortex, while there was minimal difference between the groups of high vs. average executive function. Furthermore, the old group with high fluid function had thicker cortex than the young participants in the posterior cingulate and adjacent areas. Further analyses showed that the latter was a result of a complex aging pattern, differing between the two performance groups, with decades of cortical thickening and subsequent thinning.
Full-textDOI: · Available from: Anders M Dale, Jul 01, 2015
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ABSTRACT: We report that preexisting individual differences in the cortical thickness of brain areas involved in a perceptual learning task predict the subsequent perceptual learning rate. Participants trained in a motion-discrimination task involving visual search for a "V"-shaped target motion trajectory among inverted "V"-shaped distractor trajectories. Motion-sensitive area MT+ (V5) was functionally identified as critical to the task: after 3 weeks of training, activity increased in MT+ during task performance, as measured by functional magnetic resonance imaging. We computed the cortical thickness of MT+ from anatomical magnetic resonance imaging volumes collected before training started, and found that it significantly predicted subsequent perceptual learning rates in the visual search task. Participants with thicker neocortex in MT+ before training learned faster than those with thinner neocortex in that area. A similar association between cortical thickness and training success was also found in posterior parietal cortex (PPC). © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: email@example.com.Cerebral Cortex 01/2015; DOI:10.1093/cercor/bhu309 · 8.31 Impact Factor
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ABSTRACT: We present a spiking neural model capable of solving a popular test of intelligence, Raven's Advanced Progressive Matrices (RPM). The central features of this model are its ability to dynamically generate the rules needed to solve the RPM and its biologically detailed implementation in spiking neurons. We describe the rule generation processes, and demonstrate the model's ability to use the resulting rules to solve the RPM with similar performance and error patterns to human subjects. Investigating the rules in more detail, we show that they successfully capture abstract patterns in the data, enabling them to generalize to novel matrices. We also show that the same model can be used to solve a separate reasoning task, and demonstrates the expected positive correlation in performance across tasks. Finally, we demonstrate the advantages of the biologically detailed implementation by using the model to connect behavioral and neurophysiological data. Specifically, we investigate two neurophysiological explanations of cognitive decline in aging: neuron loss and representational “dedifferentiation”. We show that manipulations to the model that reflect these neurophysiological hypotheses result in performance changes that match observed human behavioral data.Intelligence 01/2014; 42:53-82. DOI:10.1016/j.intell.2013.10.003 · 2.67 Impact Factor
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ABSTRACT: It is "normal" for old age to be associated with gradual decline in memory and brain mass. However, there are anecdotal reports of individuals who seem immune to age-related memory impairment, but these individuals have not been studied systematically. This study sought to establish that such cognitive SuperAgers exist and to determine if they were also resistant to age-related loss of cortical brain volume. SuperAgers were defined as individuals over age 80 with episodic memory performance at least as good as normative values for 50- to 65-year-olds. Cortical morphometry of the SuperAgers was compared to two cognitively normal cohorts: age-matched elderly and 50- to 65-year-olds. The SuperAgers' cerebral cortex was significantly thicker than their healthy age-matched peers and displayed no atrophy compared to the 50- to 65-year-old healthy group. Unexpectedly, a region of left anterior cingulate cortex was significantly thicker in the SuperAgers than in both elderly and middle-aged controls. Our findings identify cognitive and neuroanatomical features of a cohort that appears to resist average age-related changes of memory capacity and cortical volume. A better understanding of the underlying factors promoting this potential trajectory of unusually successful aging may provide insight for preventing age-related cognitive impairments or the more severe changes associated with Alzheimer's disease. (JINS, 2012, 18, 1-5).Journal of the International Neuropsychological Society 11/2012; 18(6):1081-5. DOI:10.1017/S1355617712000847 · 3.01 Impact Factor