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Previous studies have consistently reported age-related changes in cognitive abilities and brain structure. Previous studies also suggest compensatory roles for specialized training, skill, and years of education in the age-related decline of cognitive function. The Stanford/VA Aviation Study examines the influence of specialized training and skill level (expertise) on age-related changes in cognition and brain structure. This preliminary report examines the effect of aviation expertise, years of education, age, and brain size on flight simulator performance in pilots aged 45–68 years. Fifty-one pilots were studied with structural magnetic resonance imaging, flight simulator, and processing speed tasks. There were significant main effects of age (p < .01) and expertise (p < .01), but not of whole brain size (p > .1) or education (p > .1), on flight simulator performance. However, even though age and brain size were correlated (r = −0.41), age differences in flight simulator performance were not explained by brain size. Both aviation expertise and education were involved in an interaction with brain size in predicting flight simulator performance (p < .05). These results point to the importance of examining measures of expertise and their interactions to assess age-related cognitive changes. (JINS, 2010, 16, 412–423.)
Major advances in understanding the physiology and genetics of circadian rhythm in the past decade challenge the researcher of sleep/wake disorders in Alzheimer's disease (AD) to distinguish patient characteristics stable across the course of illness (“traits”) from characteristics that vary with stage of illness (“states”). A components-of-variance approach with a repeated measures model was used to examine the between-subjects variance over time (“trait”) vs. within-subjects (“state”) variance in 42 patients with probable AD followed, on average, over 2 years on actigraphic sleep/wake measures. Mental status scores indexed stage of illness. Actigraphic measures of sleep efficiency and circadian rhythmicity appeared predominantly “trait,” with between-individual differences accounting for over 55% of variance compared to the less than 5% of variance related to stage of cognitive impairment. We discuss how “state-trait” analyses can be helpful in identifying areas of assessment most likely to be fruitful objectives of physiologic and genetic research on sleep/wake disturbance in AD.
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