Header

UZH-Logo

Maintenance Infos

Bayesian modelling captures inter-individual differences in social belief computations in the putamen and insula


Henco, Lara; Brandi, Marie-Luise; Lahnakoski, Juha M; Diaconescu, Andreea O; Mathys, Christoph; Schilbach, Leonhard (2020). Bayesian modelling captures inter-individual differences in social belief computations in the putamen and insula. Cortex, 131:221-236.

Abstract

Computational models of social learning and decision-making provide mechanistic tools to investigate the neural mechanisms that are involved in understanding other people. While most studies employ explicit instructions to learn from social cues, everyday life is characterized by the spontaneous use of such signals (e.g., the gaze of others) to infer on internal states such as intentions. To investigate the neural mechanisms of the impact of gaze cues on learning and decision-making, we acquired behavioural and fMRI data from 50 participants performing a probabilistic task, in which cards with varying winning probabilities had to be chosen. In addition, the task included a computer-generated face that gazed towards one of these cards providing implicit advice. Participants’ individual belief trajectories were inferred using a hierarchical Gaussian filter (HGF) and used as predictors in a linear model of neuronal activation. During learning, social prediction errors were correlated with activity in inferior frontal gyrus and insula. During decision-making, the belief about the accuracy of the social cue was correlated with activity in inferior temporal gyrus, putamen and pallidum while the putamen and insula showed activity as a function of individual differences in weighting the social cue during decision-making. Our findings demonstrate that model-based fMRI can give insight into the behavioural and neural aspects of spontaneous social cue integration in learning and decision-making. They provide evidence for a mechanistic involvement of specific components of the basal ganglia in subserving these processes.

Abstract

Computational models of social learning and decision-making provide mechanistic tools to investigate the neural mechanisms that are involved in understanding other people. While most studies employ explicit instructions to learn from social cues, everyday life is characterized by the spontaneous use of such signals (e.g., the gaze of others) to infer on internal states such as intentions. To investigate the neural mechanisms of the impact of gaze cues on learning and decision-making, we acquired behavioural and fMRI data from 50 participants performing a probabilistic task, in which cards with varying winning probabilities had to be chosen. In addition, the task included a computer-generated face that gazed towards one of these cards providing implicit advice. Participants’ individual belief trajectories were inferred using a hierarchical Gaussian filter (HGF) and used as predictors in a linear model of neuronal activation. During learning, social prediction errors were correlated with activity in inferior frontal gyrus and insula. During decision-making, the belief about the accuracy of the social cue was correlated with activity in inferior temporal gyrus, putamen and pallidum while the putamen and insula showed activity as a function of individual differences in weighting the social cue during decision-making. Our findings demonstrate that model-based fMRI can give insight into the behavioural and neural aspects of spontaneous social cue integration in learning and decision-making. They provide evidence for a mechanistic involvement of specific components of the basal ganglia in subserving these processes.

Statistics

Citations

Dimensions.ai Metrics
3 citations in Web of Science®
3 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

2 downloads since deposited on 08 Jan 2021
2 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Institute of Biomedical Engineering
Dewey Decimal Classification:170 Ethics
610 Medicine & health
Scopus Subject Areas:Social Sciences & Humanities > Neuropsychology and Physiological Psychology
Social Sciences & Humanities > Experimental and Cognitive Psychology
Life Sciences > Cognitive Neuroscience
Uncontrolled Keywords:Experimental and Cognitive Psychology, Cognitive Neuroscience, Neuropsychology and Physiological Psychology
Language:English
Date:1 October 2020
Deposited On:08 Jan 2021 12:22
Last Modified:09 Jan 2021 21:01
Publisher:Elsevier
ISSN:0010-9452
OA Status:Hybrid
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1016/j.cortex.2020.02.024
PubMed ID:32571519
Project Information:
  • : FunderSNSF
  • : Grant IDPZ00P3_167952
  • : Project TitleNeurocomputational Modelling of Delusions and its Clinical Utility for Psychosis

Download

Hybrid Open Access

Download PDF  'Bayesian modelling captures inter-individual differences in social belief computations in the putamen and insula'.
Preview
Content: Published Version
Filetype: PDF
Size: 1MB
View at publisher
Licence: Creative Commons: Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)