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Changes in corticostriatal connectivity during reinforcement learning in humans
Authors:Rachel Marsh  Xuejun Hao  Dongrong Xu  Yunsuo Duan  Gregory Z. Tau  Barbara Graniello  Zhishun Wang  Alayar Kangarlu  Diana Martinez  Mark G. Packard  Bradley S. Peterson
Affiliation:1. Department of Psychiatry, New York State Psychiatric Institute and College of Physicians and Surgeons, Columbia University, New York, New York;2. Department of Psychology, Texas A&M University, College Station, Texas;3. Institute for the Developing Mind at Children's Hospital Los Angeles and the Keck School of MedicineUniversity of Southern California
Abstract:
Many computational models assume that reinforcement learning relies on changes in synaptic efficacy between cortical regions representing stimuli and striatal regions involved in response selection, but this assumption has thus far lacked empirical support in humans. We recorded hemodynamic signals with fMRI while participants navigated a virtual maze to find hidden rewards. We fitted a reinforcement‐learning algorithm to participants' choice behavior and evaluated the neural activity and the changes in functional connectivity related to trial‐by‐trial learning variables. Activity in the posterior putamen during choice periods increased progressively during learning. Furthermore, the functional connections between the sensorimotor cortex and the posterior putamen strengthened progressively as participants learned the task. These changes in corticostriatal connectivity differentiated participants who learned the task from those who did not. These findings provide a direct link between changes in corticostriatal connectivity and learning, thereby supporting a central assumption common to several computational models of reinforcement learning. Hum Brain Mapp 36:793–803, 2015. © 2014 Wiley Periodicals, Inc .
Keywords:reinforcement learning  computational model‐based fMRI  functional connectivity  putamen
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