Neural mechanisms of predicting individual preferences based on group membership
Publication year
2021Number of pages
12 p.
Source
Social Cognitive and Affective Neuroscience, 16, 9, (2021), pp. 1006-1017ISSN
Publication type
Article / Letter to editor
Related publications
Display more detailsDisplay less details
Organization
SW OZ DCC SMN
SW OZ DCC CO
Journal title
Social Cognitive and Affective Neuroscience
Volume
vol. 16
Issue
iss. 9
Languages used
English (eng)
Page start
p. 1006
Page end
p. 1017
Subject
Action, intention, and motor controlAbstract
Successful social interaction requires humans to predict others' behavior. To do so, internal models of others are generated based on previous observations. When predicting others' preferences for objects, for example, observations are made at an individual level (5-year old Rosie often chooses a pencil), or at a group level (kids often choose pencils). But previous research has focused either on already established group knowledge, i.e., stereotypes, or on the neural correlates of predicting traits and preferences of individuals. We identified the neural mechanisms underlying predicting individual behavior based on learned group knowledge using fMRI. We show that applying learned group knowledge hinges on both a network of regions commonly referred to as the mentalizing network, and a network of regions implicated in representing social-knowledge. Additionally, we provide evidence for the presence of a gradient in the posterior temporal cortex and the medial frontal cortex, catering to different functions while applying learned group knowledge. This process is characterized by an increased connectivity between medial prefrontal cortex and other mentalizing network regions, and increased connectivity between anterior temporal lobe and other social-knowledge regions. Our study provides insights into the neural mechanisms underlying the application of learned group knowledge.
This item appears in the following Collection(s)
- Academic publications [246936]
- Electronic publications [134293]
- Faculty of Social Sciences [30577]
- Open Access publications [107816]
Upload full text
Use your RU credentials (u/z-number and password) to log in with SURFconext to upload a file for processing by the repository team.