The overall goal of this research is to examine the association of brain structural changes with attentional deficits in healthy aging. The speed with which attentional resources can be allocated and re-allocated affects the speed of sensory processing and behavioral responding, both of which are slowed with aging. A number of the brain regions that have been identified as important to spatial attentional function, including prefrontal and parietal cortex, the thalamus, and most recently the cerebellum, have, in fact, been reported to show age-related change. We propose to use structural and functional imaging methods to examine whether structural changes and subsequent functional inefficiency in these cortical and subcortical regions, particularly the cerebellum, may underlie attention deficits in aging. Specifically, we propose 1) to identify brain structural changes occurring with healthy aging in cross-sectional samples, 2) to identify behavioral and EEG changes in aging associated with shifting or orienting of attention, and 3) to test the hypothesis that age-related loss in the posterior cerebellum may affect both an anterior attention orienting system, and a posterior spatial attention mapping system. Reduced efficiency in these brain networks would result in slowed attentional shifting and orienting, and associated changes in brain electrophysiological dynamics. We will study 120 males and females aged 21-85. All subjects will receive: (1) neuropsychological evaluation; (2) MR imaging with quantification of gray and white matter and CSF in cortical and subcortical regions of interest, and hyperintensities in intracranial space; (3) attention shift tasks designed to allow separation of electrophysiological and hemodynamic activities linked to sensory, motor, and attentional processes. Behavioral, event-related potential (ERP), and functional magnetic imaging (fMRI) data recorded during these tasks will be compared with neuroanatomic results to address our research hypotheses. New analytic techniques based on Independent Component Analysis will allow us to identify both correlated fMRI signal changes throughout the brain, and overlapping patterns of coherent EEG from ERP data. The proposed experiments will yield convergent evidence concerning the neurologic bases of dynamic attention deficits in aging. These data will also provide methods as well as a baseline dataset of neuroanatomic measures that could be used in future clinical studies.
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