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How Dynamic Brain Networks Tune Social Behavior in Real Time

Silston, Brian and Bassett, Danielle S. and Mobbs, Dean (2018) How Dynamic Brain Networks Tune Social Behavior in Real Time. Current Directions in Psychological Science, 27 (6). pp. 413-421. ISSN 0963-7214.

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During social interaction, the brain has the enormous task of interpreting signals that are fleeting, subtle, contextual, abstract, and often ambiguous. Despite the signal complexity, the human brain has evolved to be highly successful in the social landscape. Here, we propose that the human brain makes sense of noisy dynamic signals through accumulation, integration, and prediction, resulting in a coherent representation of the social world. We propose that successful social interaction is critically dependent on a core set of highly connected hubs that dynamically accumulate and integrate complex social information and, in doing so, facilitate social tuning during moment-to-moment social discourse. Successful interactions, therefore, require adaptive flexibility generated by neural circuits composed of highly integrated hubs that coordinate context-appropriate responses. Adaptive properties of the neural substrate, including predictive and adaptive coding, and neural reuse, along with perceptual, inferential, and motivational inputs, provide the ingredients for pliable, hierarchical predictive models that guide our social interactions.

Item Type:Article
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Mobbs, Dean0000-0003-1175-3772
Additional Information:© 2019 by SAGE Publications. Article first published online: October 30, 2018; Issue published: December 1, 2018.
Subject Keywords:dynamic-integration theory, adaptive flexibility, temporal dynamics, social interaction, prediction
Record Number:CaltechAUTHORS:20190102-084504270
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Official Citation:Silston, B., Bassett, D. S., & Mobbs, D. (2018). How Dynamic Brain Networks Tune Social Behavior in Real Time. Current Directions in Psychological Science, 27(6), 413–421.
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:91964
Deposited By: Tony Diaz
Deposited On:02 Jan 2019 16:51
Last Modified:02 Jan 2019 16:51

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