Directed coupling in multi-brain networks underlies generalized synchrony during social exchange

神经科学 背景(考古学) 心理学 大脑活动与冥想 社会神经科学 因果模型 脑功能 认知心理学 人脑 计算机科学 认知科学 社会认知 脑电图 认知 生物 数学 统计 古生物学
作者
Edda Bilek,Peter Zeidman,Peter Kirsch,Heike Tost,Andreas Meyer‐Lindenberg,Karl J. Friston
出处
期刊:NeuroImage [Elsevier]
卷期号:252: 119038-119038 被引量:25
标识
DOI:10.1016/j.neuroimage.2022.119038
摘要

Advances in social neuroscience have made neural signatures of social exchange measurable simultaneously across people. This has identified brain regions differentially active during social interaction between human dyads, but the underlying systems-level mechanisms are incompletely understood. This paper introduces dynamic causal modeling and Bayesian model comparison to assess the causal and directed connectivity between two brains in the context of hyperscanning (h-DCM). In this setting, correlated neuronal responses become the data features that have to be explained by models with and without between-brain (effective) connections. Connections between brains can be understood in the context of generalized synchrony, which explains how dynamical systems become synchronized when they are coupled to each another. Under generalized synchrony, each brain state can be predicted by the other brain or a mixture of both. Our results show that effective connectivity between brains is not a feature within dyads per se but emerges selectively during social exchange. We demonstrate a causal impact of the sender's brain activity on the receiver of information, which explains previous reports of two-brain synchrony. We discuss the implications of this work; in particular, how characterizing generalized synchrony enables the discovery of between-brain connections in any social contact, and the advantage of h-DCM in studying brain function on the subject level, dyadic level, and group level within a directed model of (between) brain function.

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