Multiple associative structures created by reinforcement and incidental statistical learning mechanisms

Miriam C. Klein-Flügge (), Marco K. Wittmann, Anna Shpektor, Daria E. A. Jensen and Matthew F. S. Rushworth
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Miriam C. Klein-Flügge: University of Oxford
Marco K. Wittmann: University of Oxford
Anna Shpektor: West Wing, John Radcliffe Hospital
Daria E. A. Jensen: University of Oxford
Matthew F. S. Rushworth: University of Oxford

Nature Communications, 2019, vol. 10, issue 1, 1-15

Abstract: Abstract Learning the structure of the world can be driven by reinforcement but also occurs incidentally through experience. Reinforcement learning theory has provided insight into how prediction errors drive updates in beliefs but less attention has been paid to the knowledge resulting from such learning. Here we contrast associative structures formed through reinforcement and experience of task statistics. BOLD neuroimaging in human volunteers demonstrates rigid representations of rewarded sequences in temporal pole and posterior orbito-frontal cortex, which are constructed backwards from reward. By contrast, medial prefrontal cortex and a hippocampal-amygdala border region carry reward-related knowledge but also flexible statistical knowledge of the currently relevant task model. Intriguingly, ventral striatum encodes prediction error responses but not the full RL- or statistically derived task knowledge. In summary, representations of task knowledge are derived via multiple learning processes operating at different time scales that are associated with partially overlapping and partially specialized anatomical regions.

Date: 2019
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DOI: 10.1038/s41467-019-12557-z

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