Adult age differences in frontostriatal representation of prediction error but not reward outcome.
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Emerging evidence from decision neuroscience suggests that although younger and older adults show similar frontostriatal representations of reward magnitude, older adults often show deficits in feedback-driven reinforcement learning. In the present study, healthy adults completed reward-based tasks that did or did not depend on probabilistic learning, while undergoing functional neuroimaging. We observed reductions in the frontostriatal representation of prediction errors during probabilistic learning in older adults. In contrast, we found evidence for stability across adulthood in the representation of reward outcome in a task that did not require learning. Together, the results identify changes across adulthood in the dynamic coding of relational representations of feedback, in spite of preserved reward sensitivity in old age. Overall, the results suggest that the neural representation of prediction error, but not reward outcome, is reduced in old age. These findings reveal a potential dissociation between cognition and motivation with age and identify a potential mechanism for explaining changes in learning-dependent decision making in old adulthood.
Aged, 80 and over
Image Processing, Computer-Assisted
Magnetic Resonance Imaging
Predictive Value of Tests
Published Version (Please cite this version)10.3758/s13415-014-0297-4
Publication InfoSamanez-Larkin, Gregory Russell; Worthy, DA; Mata, R; McClure, SM; & Knutson, B (2014). Adult age differences in frontostriatal representation of prediction error but not reward outcome. Cogn Affect Behav Neurosci, 14(2). pp. 672-682. 10.3758/s13415-014-0297-4. Retrieved from https://hdl.handle.net/10161/13717.
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Assistant Professor of Psychology and Neuroscience
Research in our lab examines how individual and age differences in motivation and cognition influence decision making and health behavior across the life span. Our research is at the intersection of a number of subfields within psychology, neuroscience, and economics including human development, affective science, cognitive neuroscience, behavioral economics, and finance. We use a combination of behavioral and neuroimaging techniques ranging from detailed measurement of functional brain activity