Humans perseverate on punishment avoidance goals in multigoal reinforcement learning.
anxiety
human
multitask
neuroscience
reinforcement learning
Journal
eLife
ISSN: 2050-084X
Titre abrégé: Elife
Pays: England
ID NLM: 101579614
Informations de publication
Date de publication:
24 02 2022
24 02 2022
Historique:
received:
03
10
2021
accepted:
21
02
2022
pubmed:
25
2
2022
medline:
30
4
2022
entrez:
24
2
2022
Statut:
epublish
Résumé
Managing multiple goals is essential to adaptation, yet we are only beginning to understand computations by which we navigate the resource demands entailed in so doing. Here, we sought to elucidate how humans balance reward seeking and punishment avoidance goals, and relate this to variation in its expression within anxious individuals. To do so, we developed a novel multigoal pursuit task that includes trial-specific instructed goals to either pursue reward (without risk of punishment) or avoid punishment (without the opportunity for reward). We constructed a computational model of multigoal pursuit to quantify the degree to which participants could disengage from the pursuit goals when instructed to, as well as devote less model-based resources toward goals that were less abundant. In general, participants (
Identifiants
pubmed: 35199640
doi: 10.7554/eLife.74402
pii: 74402
pmc: PMC8912924
doi:
pii:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Wellcome Trust
ID : 098362/Z/12/Z
Pays : United Kingdom
Commentaires et corrections
Type : ErratumIn
Informations de copyright
© 2022, Sharp et al.
Déclaration de conflit d'intérêts
PS, ER, QH, RD, EE No competing interests declared
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