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Feature-specific prediction errors and surprise across macaque fronto-striatal circuits

Mariann Oemisch (), Stephanie Westendorff, Marzyeh Azimi, Seyed Alireza Hassani, Salva Ardid, Paul Tiesinga and Thilo Womelsdorf ()
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Mariann Oemisch: York University
Stephanie Westendorff: York University
Marzyeh Azimi: York University
Seyed Alireza Hassani: York University
Salva Ardid: Boston University
Paul Tiesinga: Radboud University Nijmegen
Thilo Womelsdorf: York University

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

Abstract: Abstract To adjust expectations efficiently, prediction errors need to be associated with the precise features that gave rise to the unexpected outcome, but this credit assignment may be problematic if stimuli differ on multiple dimensions and it is ambiguous which feature dimension caused the outcome. Here, we report a potential solution: neurons in four recorded areas of the anterior fronto-striatal networks encode prediction errors that are specific to feature values of different dimensions of attended multidimensional stimuli. The most ubiquitous prediction error occurred for the reward-relevant dimension. Feature-specific prediction error signals a) emerge on average shortly after non-specific prediction error signals, b) arise earliest in the anterior cingulate cortex and later in dorsolateral prefrontal cortex, caudate and ventral striatum, and c) contribute to feature-based stimulus selection after learning. Thus, a widely-distributed feature-specific eligibility trace may be used to update synaptic weights for improved feature-based attention.

Date: 2019
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-018-08184-9

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DOI: 10.1038/s41467-018-08184-9

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