Individual Differences in Reward-Based Learning Predict Fluid Reasoning Abilities.
Basal ganglia
Cognitive architectures
Computational modeling
Dopamine
Fluid reasoning
Reinforcement learning
Reward processing
fMRI
Journal
Cognitive science
ISSN: 1551-6709
Titre abrégé: Cogn Sci
Pays: United States
ID NLM: 7708195
Informations de publication
Date de publication:
02 2021
02 2021
Historique:
received:
07
09
2018
revised:
30
12
2020
accepted:
04
01
2021
entrez:
23
2
2021
pubmed:
24
2
2021
medline:
18
9
2021
Statut:
ppublish
Résumé
The ability to reason and problem-solve in novel situations, as measured by the Raven's Advanced Progressive Matrices (RAPM), is highly predictive of both cognitive task performance and real-world outcomes. Here we provide evidence that RAPM performance depends on the ability to reallocate attention in response to self-generated feedback about progress. We propose that such an ability is underpinned by the basal ganglia nuclei, which are critically tied to both reward processing and cognitive control. This hypothesis was implemented in a neurocomputational model of the RAPM task, which was used to derive novel predictions at the behavioral and neural levels. These predictions were then verified in one neuroimaging and two behavioral experiments. Furthermore, an effective connectivity analysis of the neuroimaging data confirmed a role for the basal ganglia in modulating attention. Taken together, these results suggest that individual differences in a neural circuit related to reward processing underpin human fluid reasoning abilities.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e12941Informations de copyright
© 2021 Cognitive Science Society, Inc.
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