Interactions between frontal and posterior oscillatory dynamics support adjustment of stimulus processing during reinforcement learning

Irene van de Vijver*, Joram van Driel, Arjan Hillebrand, Michael X Cohen

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Reinforcement learning (RL) in humans is subserved by a network of striatal and frontal brain areas. The electrophysiological signatures of feedback evaluation are increasingly well understood, but how those signatures relate to the use of feedback to guide subsequent behavioral adjustment remains unclear. One mechanism for post-feedback behavioral optimization is the modulation of sensory processing. We used source-reconstructed MEG to test whether feedback affects the interactions between sources of oscillatory activity in the learning network and task-relevant stimulus-processing areas. Participants performed a probabilistic RL task in which they learned associations between colored faces and response buttons using trial-and-error feedback. Delta-band (2-4 Hz) and theta-band (4-8 Hz) power in multiple frontal regions were sensitive to feedback valence. Low and high beta-band power (12-20 and 20-30 Hz) in occipital, parietal, and temporal regions differentiated between color and face information. Consistent with our hypothesis, single-trial power-power correlations between frontal and posterior-sensory areas were modulated by the interaction between feedback valence and the relevant stimulus characteristic (color versus identity). These results suggest that long-range oscillatory coupling supports post-feedback updating of stimulus processing.

Original languageEnglish
Pages (from-to)170-181
Number of pages12
JournalNeuroImage
Volume181
Early online date7 Jul 2018
DOIs
Publication statusPublished - 1 Nov 2018

Funding

IvdV, JvD, and MXC were supported by a Vidi grant ( 452-09-003 ) from the Netherlands Organization for Scientific Research (NWO) to MXC. Appendix A

FundersFunder number
Netherlands Organization for Scientific Research
Horizon 2020 Framework Programme638589
Nederlandse Organisatie voor Wetenschappelijk Onderzoek452-09-003

    Keywords

    • Beamforming
    • MEG
    • Oscillations
    • Power-power correlations
    • Reinforcement learning

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