Generalization of value in reinforcement learning by humans

Description: Group-level SPM for the contrasts: 1) Reward prediction error, 2) Reward prediction error due to generalization, 3) Choice probability Here, we used functional magnetic resonance imaging and computational model-based analyses to examine the joint contributions of the reinforcement learning and generalization. Humans performed a reinforcement learning task with added relational structure, modeled after tasks used to isolate hippocampal contributions to memory. We observed blood oxygen level-dependent (BOLD) activity related to learning in the striatum and also in the hippocampus. By comparing a basic reinforcement learning model to one augmented to allow feedback to generalize between correlated options, we tested whether choice behavior and BOLD activity were influenced by the opportunity to generalize across correlated options. Although such generalization goes beyond standard computational accounts of reinforcement learning and striatal BOLD, both choices and striatal BOLD activity were better explained by the augmented model. Consistent with the hypothesized role for the hippocampus in this generalization, functional connectivity between the ventral striatum and hippocampus was modulated, across participants, by the ability of the augmented model to capture participants' choice.

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Add DateFeb. 15, 2017, 7:03 p.m.
Uploaded bygewimmer
Related article DOI10.1111/j.1460-9568.2012.08017.x
Related article authorsG. Elliott Wimmer, Nathaniel D. Daw and Daphna Shohamy
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