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Sci Rep. 2017 Jul 6;7(1):4762. doi: 10.1038/s41598-017-04507-w.

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

Author information

1
Institute of Neuroscience & Psychology, University of Glasgow, Glasgow, UK. elsa.fouragnan@psy.ox.ac.uk.
2
Department of Experimental Psychology, University of Oxford, Oxford, UK. elsa.fouragnan@psy.ox.ac.uk.
3
Institute of Neuroscience & Psychology, University of Glasgow, Glasgow, UK.
4
Department of Behavioural & Social Sciences, University of Huddersfield, Huddersfield, UK.
5
Sir Peter Mansfield Magnetic Resonance Center, School of Physics and Astronomy, University of Nottingham, Nottingham, UK.
6
Birmingham University Imaging Centre, School of Psychology, University of Birmingham, Birmingham, UK.
7
Institute of Neuroscience & Psychology, University of Glasgow, Glasgow, UK. Marios.Philiastides@glasgow.ac.uk.

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.

PMID:
28684734
PMCID:
PMC5500565
DOI:
10.1038/s41598-017-04507-w
[Indexed for MEDLINE]
Free PMC Article

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