AGING OF VISUAL-COGNITIVE MECHANISMS ON A NEURAL NETWORK

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The overall aim of this project is to specify the mechanisms that are responsible for age-related changes in visual-cognitive performance. Age-related change in several types of visualcognitive performance will be described and explicated in terms of empirically-derived neural network models of aging. Specifically, the factors that contribute to general and task-specific interindividual and intraindividual variability in healthy young, middle-aged, and older adults will be identified and modeled. The proposed neural network models have the unique property that their constituent interconnections can be adjusted so as to represent time-related and practice-related change in the encoding and subsequent transformation of visual information. During the three years of this project, about 400 men and women between the ages of 19 years and 80 years will be tested on measures of 1) perceptual closure or figure completion, and 2) the perception of apparent motion. For each visual-cognitive task, several neurologically plausible network models will be developed, tested, and contrasted with each other in terms of their ability to simulate general and task-specific differences in the distributions of response times and errors for young adults, middle-aged adults, and older adults. The outcome of this line of investigation will have clear implications for the understanding of the mechanisms responsible for effective cognitive functioning during the middle and later years of life.