Spatiotemporal neural characterization of prediction error valence and surprise during reward learning in humans

Abstract Reward learning depends on accurate reward associations with potential choices. These associations can be attained with reinforcement learning mechanisms using a reward prediction error (RPE) signal (the difference between actual and expected rewards) for updating future reward expectations...

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Autores principales:	Elsa Fouragnan, Filippo Queirazza, Chris Retzler, Karen J. Mullinger, Marios G. Philiastides
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/4fa880931362431c9df34eb547d1c2dd
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spelling	oai:doaj.org-article:4fa880931362431c9df34eb547d1c2dd2021-12-02T11:40:31ZSpatiotemporal neural characterization of prediction error valence and surprise during reward learning in humans10.1038/s41598-017-04507-w2045-2322https://doaj.org/article/4fa880931362431c9df34eb547d1c2dd2017-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-04507-whttps://doaj.org/toc/2045-2322Abstract Reward learning depends on accurate reward associations with potential choices. These associations can be attained with reinforcement learning mechanisms using a reward prediction error (RPE) signal (the difference between actual and expected rewards) for updating future reward expectations. Despite an extensive body of literature on the influence of RPE on learning, little has been done to investigate the potentially separate contributions of RPE valence (positive or negative) and surprise (absolute degree of deviation from expectations). Here, we coupled single-trial electroencephalography with simultaneously acquired fMRI, during a probabilistic reversal-learning task, to offer evidence of temporally overlapping but largely distinct spatial representations of RPE valence and surprise. Electrophysiological variability in RPE valence correlated with activity in regions of the human reward network promoting approach or avoidance learning. Electrophysiological variability in RPE surprise correlated primarily with activity in regions of the human attentional network controlling the speed of learning. Crucially, despite the largely separate spatial extend of these representations our EEG-informed fMRI approach uniquely revealed a linear superposition of the two RPE components in a smaller network encompassing visuo-mnemonic and reward areas. Activity in this network was further predictive of stimulus value updating indicating a comparable contribution of both signals to reward learning.Elsa FouragnanFilippo QueirazzaChris RetzlerKaren J. MullingerMarios G. PhiliastidesNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-18 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Elsa Fouragnan Filippo Queirazza Chris Retzler Karen J. Mullinger Marios G. Philiastides Spatiotemporal neural characterization of prediction error valence and surprise during reward learning in humans
description	Abstract Reward learning depends on accurate reward associations with potential choices. These associations can be attained with reinforcement learning mechanisms using a reward prediction error (RPE) signal (the difference between actual and expected rewards) for updating future reward expectations. Despite an extensive body of literature on the influence of RPE on learning, little has been done to investigate the potentially separate contributions of RPE valence (positive or negative) and surprise (absolute degree of deviation from expectations). Here, we coupled single-trial electroencephalography with simultaneously acquired fMRI, during a probabilistic reversal-learning task, to offer evidence of temporally overlapping but largely distinct spatial representations of RPE valence and surprise. Electrophysiological variability in RPE valence correlated with activity in regions of the human reward network promoting approach or avoidance learning. Electrophysiological variability in RPE surprise correlated primarily with activity in regions of the human attentional network controlling the speed of learning. Crucially, despite the largely separate spatial extend of these representations our EEG-informed fMRI approach uniquely revealed a linear superposition of the two RPE components in a smaller network encompassing visuo-mnemonic and reward areas. Activity in this network was further predictive of stimulus value updating indicating a comparable contribution of both signals to reward learning.
format	article
author	Elsa Fouragnan Filippo Queirazza Chris Retzler Karen J. Mullinger Marios G. Philiastides
author_facet	Elsa Fouragnan Filippo Queirazza Chris Retzler Karen J. Mullinger Marios G. Philiastides
author_sort	Elsa Fouragnan
title	Spatiotemporal neural characterization of prediction error valence and surprise during reward learning in humans
title_short	Spatiotemporal neural characterization of prediction error valence and surprise during reward learning in humans
title_full	Spatiotemporal neural characterization of prediction error valence and surprise during reward learning in humans
title_fullStr	Spatiotemporal neural characterization of prediction error valence and surprise during reward learning in humans
title_full_unstemmed	Spatiotemporal neural characterization of prediction error valence and surprise during reward learning in humans
title_sort	spatiotemporal neural characterization of prediction error valence and surprise during reward learning in humans
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/4fa880931362431c9df34eb547d1c2dd
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_version_	1718395580603957248

Spatiotemporal neural characterization of prediction error valence and surprise during reward learning in humans

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