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• W2899153561 abstract "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." @default.
• W2899153561 created "2018-11-09" @default.
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• W2899153561 date "2018-10-30" @default.
• W2899153561 modified "2023-10-16" @default.
• W2899153561 title "How Dynamic Brain Networks Tune Social Behavior in Real Time" @default.
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• W2899153561 doi "https://doi.org/10.1177/0963721418773362" @default.
• W2899153561 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6715321" @default.
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• W2899153561 hasPublicationYear "2018" @default.
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