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research article

Risk prediction error signaling: A two-component response?

Lauffs, Marc M.  
•
Geoghan, Sophie A.
•
Favrod, Ophélie  
Show more
2020
NeuroImage

Organisms use rewards to navigate and adapt to (uncertain) environments. Error-based learning about rewards issupported by the dopaminergic system, which is thought to signal reward prediction errors to make adjustmentsto past predictions. More recently, the phasic dopamine response was suggested to have two components: thefirstrapid component is thought to signal the detection of a potentially rewarding stimulus; the second, slightly latercomponent characterizes the stimulus by its reward prediction error. Error-based learning signals have also beenfound for risk. However, whether the neural generators of these signals employ a two-component coding schemelike the dopaminergic system is unknown. Here, using human high density EEG, we ask whether risk learning, ormore generally speaking surprise-based learning under uncertainty, is similarly comprised of two temporallydissociable components. Using a simple card game, we show that the risk prediction error is reflected in theamplitude of the P3b component. This P3b modulation is preceded by an earlier component, that is modulated bythe stimulus salience. Source analyses are compatible with the idea that both the early salience signal and the laterrisk prediction error signal are generated in insular, frontal, and temporal cortex. The identified sources are partsof the risk processing network that receives input from noradrenergic cells in the locus coeruleus. Finally, the P3bamplitude modulation is mirrored by an analogous modulation of pupil size, which is consistent with the idea thatboth the P3b and pupil size indirectly reflect locus coeruleus activity.

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Type
research article
DOI
10.1016/j.neuroimage.2020.116766
Author(s)
Lauffs, Marc M.  
Geoghan, Sophie A.
Favrod, Ophélie  
Herzog, Michael H.  
Preuschoff, Kerstin
Date Issued

2020

Published in
NeuroImage
Volume

214

Start page

1

End page

10, 116766

Subjects

This is an open access article under the CC BY license.

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LPSY  
FunderGrant Number

FNS-NCCR

51NF40-158776

Available on Infoscience
June 25, 2020
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/169641
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