Information flow between interacting human brains: Identification, validation, and relationship to social expertise
Identifieur interne : 000802 ( Main/Exploration ); précédent : 000801; suivant : 000803Information flow between interacting human brains: Identification, validation, and relationship to social expertise
Auteurs : Edda Bilek ; Matthias Ruf ; Axel Sch Fer ; Ceren Akdeniz ; Vince D. Calhoun ; Christian Schmahl ; Charmaine Demanuele ; Heike Tost ; Peter Kirsch [Allemagne] ; Andreas Meyer-LindenbergSource :
- Proceedings of the National Academy of Sciences of the United States of America [ 0027-8424 ] ; 2015.
Abstract
Social interaction is the likely driver of human brain evolution, critical for health, and underlies phenomena as varied as childhood development, stock market behavior, and much of what is studied in the humanities. However, appropriate experimental methods to study the underlying brain processes are still developing and technically challenging. Here, we extend previous pioneering approaches in neuroimaging [functional MRI (fMRI) hyperscanning] to provide a method for studying information flow between interacting humans in a two-person approach. A scan environment enabling synchronized data acquisition and interaction-based fMRI tasks is described. We provide a generally applicable analysis method to identify interacting brain systems. Specific social brain systems are identified as drivers of interaction in humans, and we find a link to a measure of social expertise.
Url:
DOI: 10.1073/pnas.1421831112
PubMed: 25848050
PubMed Central: 4413334
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en"><title>Significance</title>
<p>Social interaction is the likely driver of human brain evolution, critical for health, and underlies phenomena as varied as childhood development, stock market behavior, and much of what is studied in the humanities. However, appropriate experimental methods to study the underlying brain processes are still developing and technically challenging. Here, we extend previous pioneering approaches in neuroimaging [functional MRI (fMRI) hyperscanning] to provide a method for studying information flow between interacting humans in a two-person approach. A scan environment enabling synchronized data acquisition and interaction-based fMRI tasks is described. We provide a generally applicable analysis method to identify interacting brain systems. Specific social brain systems are identified as drivers of interaction in humans, and we find a link to a measure of social expertise.</p>
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<name sortKey="Schmahl, Christian" sort="Schmahl, Christian" uniqKey="Schmahl C" first="Christian" last="Schmahl">Christian Schmahl</name>
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