Corrigendum to: Neural mechanisms of predicting individual preferences based on group membership

Neural mechanisms of predicting individual preferences based on group membership

Social Cognitive and Affective Neuroscience ◽

10.1093/scan/nsaa136 ◽

2020 ◽

Author(s):

Suhas Vijayakumar ◽

Egbert Hartstra ◽

Rogier B Mars ◽

Harold Bekkering

Keyword(s):

Group Membership ◽

Temporal Cortex ◽

Neural Correlates ◽

Neural Mechanisms ◽

Social Knowledge ◽

Group Level ◽

Individual Level ◽

Individual Preferences ◽

Group Knowledge ◽

Do So

Abstract 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.

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John Ludbrook APPS Symposium Neural Mechanisms In The Cardiovascular Responses To Acute Central Hypovolaemia

Clinical and Experimental Pharmacology and Physiology ◽

10.1046/j.1440-1681.2001.3473.x ◽

2001 ◽

Vol 28 (5-6) ◽

pp. 479-487

Author(s):

Roger G Evans ◽

Sabatino Ventura ◽

Roger Al Dampney ◽

John Ludbrook

Keyword(s):

Cardiovascular Responses ◽

Neural Mechanisms ◽

Central Hypovolaemia

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Does the Name-Race Implicit Association Test Measure Racial Prejudice?

Experimental Psychology (formerly Zeitschrift für Experimentelle Psychologie) ◽

10.1027/1618-3169/a000093 ◽

2011 ◽

Vol 58 (4) ◽

pp. 271-277 ◽

Cited By ~ 26

Author(s):

Don van Ravenzwaaij ◽

Han L. J. van der Maas ◽

Eric-Jan Wagenmakers

Keyword(s):

Diffusion Model ◽

Implicit Association Test ◽

Alternative Explanation ◽

Group Membership ◽

Racial Prejudice ◽

Decision Time ◽

Association Test ◽

Implicit Association ◽

Model Decomposition ◽

Test Measure

Research using the Implicit Association Test (IAT) has shown that names labeled as Caucasian elicit more positive associations than names labeled as non-Caucasian. One interpretation of this result is that the IAT measures latent racial prejudice. An alternative explanation is that the result is due to differences in in-group/out-group membership. In this study, we conducted three different IATs: one with same-race Dutch names versus racially charged Moroccan names; one with same-race Dutch names versus racially neutral Finnish names; and one with Moroccan names versus Finnish names. Results showed equivalent effects for the Dutch-Moroccan and Dutch-Finnish IATs, but no effect for the Finnish-Moroccan IAT. This suggests that the name-race IAT-effect is not due to racial prejudice. A diffusion model decomposition indicated that the IAT-effects were caused by changes in speed of information accumulation, response conservativeness, and non-decision time.

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