en
Scientific article
Open access
English

Robust valence-induced biases on motor response and confidence in human reinforcement learning

Published inCognitive, affective & behavioral neuroscience, vol. 20, no. 6, p. 1184-1199
Publication date2020-09-01
First online date2020-09-01
Abstract

In simple instrumental-learning tasks, humans learn to seek gains and to avoid losses equally well. Yet, two effects of valence are observed. First, decisions in loss-contexts are slower. Second, loss contexts decrease individuals' confidence in their choices. Whether these two effects are two manifestations of a single mechanism or whether they can be partially dissociated is unknown. Across six experiments, we attempted to disrupt the valence-induced motor bias effects by manipulating the mapping between decisions and actions and imposing constraints on response times (RTs). Our goal was to assess the presence of the valence-induced confidence bias in the absence of the RT bias. We observed both motor and confidence biases despite our disruption attempts, establishing that the effects of valence on motor and metacognitive responses are very robust and replicable. Nonetheless, within- and between-individual inferences reveal that the confidence bias resists the disruption of the RT bias. Therefore, although concomitant in most cases, valence-induced motor and confidence biases seem to be partly dissociable. These results highlight new important mechanistic constraints that should be incorporated in learning models to jointly explain choice, reaction times and confidence.

eng
Keywords
  • Confidence
  • Meta-cognition
  • Reinforcement-leaning
  • Valence-induced bias
Citation (ISO format)
TING, Chih-Chung et al. Robust valence-induced biases on motor response and confidence in human reinforcement learning. In: Cognitive, affective & behavioral neuroscience, 2020, vol. 20, n° 6, p. 1184–1199. doi: 10.3758/s13415-020-00826-0
Main files (1)
Article (Published version)
Secondary files (1)
Identifiers
ISSN of the journal1530-7026
94views
36downloads

Technical informations

Creation10/04/2021 1:14:00 PM
First validation10/04/2021 1:14:00 PM
Update time03/16/2023 1:32:12 AM
Status update03/16/2023 1:32:10 AM
Last indexation08/31/2023 2:01:06 AM
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack