Cognitive-attentional mechanisms of cooperation-with implications for attention-deficit hyperactivity disorder and cognitive neuroscience.
Attention-deficit hyperactivity disorder
Bayesian hierarchical modeling
Computational modeling
Computational psychiatry
Cooperation
Experimental economics
Eye-tracking
Game theory
Social cognition
Journal
Cognitive, affective & behavioral neuroscience
ISSN: 1531-135X
Titre abrégé: Cogn Affect Behav Neurosci
Pays: United States
ID NLM: 101083946
Informations de publication
Date de publication:
Dec 2023
Dec 2023
Historique:
accepted:
13
09
2023
medline:
29
11
2023
pubmed:
3
10
2023
entrez:
2
10
2023
Statut:
ppublish
Résumé
People's cooperativeness depends on many factors, such as their motives, cognition, experiences, and the situation they are in. To date, it is unclear how these factors interact and shape the decision to cooperate. We present a computational account of cooperation that not only provides insights for the design of effective incentive structures but also redefines neglected social-cognitive characteristics associated with attention-deficit hyperactivity disorder (ADHD). Leveraging game theory, we demonstrate that the source and magnitude of conflict between different motives affected the speed and frequency of cooperation. Integrating eye-tracking to measure motivation-based information processing during decision-making shows that participants' visual fixations on the gains of cooperation rather than its costs and risks predicted their cooperativeness on a trial-by-trial basis. Using Bayesian hierarchical modeling, we find that a situation's prosociality and participants' past experience each bias the decision-making process distinctively. ADHD characteristics explain individual differences in responsiveness across contexts, highlighting the clinical importance of experimentally studying reactivity in social interactions. We demonstrate how the use of eye-tracking and computational modeling can be used to experimentally investigate social-cognitive characteristics in clinical populations. We also discuss possible underlying neural mechanisms to be investigated in future studies.
Identifiants
pubmed: 37783876
doi: 10.3758/s13415-023-01129-w
pii: 10.3758/s13415-023-01129-w
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1545-1567Subventions
Organisme : National Center for Translational Sciences to the Ohio State University
ID : Clinical
Organisme : National Center for Translational Sciences to the Ohio State University
ID : Translational Science award 8UL18TR00
Organisme : Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
ID : P1SKP1_184033
Informations de copyright
© 2023. The Psychonomic Society, Inc.
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