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Differential representations for affective and informative components of reward in the striatum and hippocampus

Xinxu SheniD, Kainan S. Wang, Vishnu P. MurtyiD, Mauricio R. DelgadoiD, David Victor SmithiD

Abstract

Receipt of a reward is composed of affective and informative components, which are often intertwined in most reward-processing and decision-making tasks. Our previous work allowed us to identify regions that were more strongly engaged for the affective and informative components of reward upon receipt (Smith et al., 2016) and showed that the ventral striatum responds to both affective and informative components of reward processing. However, the limited spatial resolution and coarse analytical approaches made it hard to understand how these different components of reward were represented in the brain, wherein similar engagement may not necessitate similar representations. In our current study, we used high-resolution functional magnetic resonance imaging (voxel size: 1.75 mm3) and representational similarity analysis to investigate the representation of affective and informative components of reward receipt in the striatum and the hippocampus, another region that is sensitive to reward information. We found a differential representation of affective and informative components of reward receipt in the striatum and the hippocampus, with no difference in representation between the two structures. However, in the dorsal striatum, we found that representations were stronger for affective rather than the informative components of reward receipt. Finally, we observed that the ventral striatum was sensitive to the predictiveness of information, such that across-run pattern similarity in the ventral striatum increased with the predictiveness of information. In sum, our results provide evidence of how affective and informative components of rewards are represented in the striatum and the hippocampus, potentially indicating a differential coding schema for the dorsal and the ventral striatum.

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02 /Specification & Classification

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