Adult age differences in frontostriatal representation of prediction error but not reward outcome.

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2014-06

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Abstract

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.

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10.3758/s13415-014-0297-4

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Samanez-Larkin, Gregory R, Darrell A Worthy, Rui Mata, Samuel M McClure and Brian Knutson (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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Samanez-Larkin

Gregory Russell Samanez-Larkin

Jerry G. and Patricia Crawford Hubbard Professor

Research in our lab examines how motivation, emotion, 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 consumer finance. We use a combination of behavioral and neuroimaging techniques ranging from detailed measurement of functional brain activity (fMRI) and neuroreceptors (PET) in the laboratory to experience sampling measures of experience and behavior in everyday life, wearable measures physical activity and sleep, and real-world measures of financial management. The goal of our translational research is to make discoveries using the tools of basic science that could inform the development of interventions, products, or services that would enhance health and well being across the life span.

In the classroom, I teach quantitative research methods and statistics, applications of neuroscience research for everyday life, and evidence-based course design in higher education.


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