亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

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.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
曦鸽子完成签到,获得积分10
1秒前
幽默的访冬完成签到,获得积分10
3秒前
syalonyui完成签到,获得积分10
4秒前
内啡呔发布了新的文献求助10
5秒前
缓慢思枫发布了新的文献求助10
9秒前
香蕉觅云应助糊涂虫采纳,获得10
10秒前
13秒前
阿米娅发布了新的文献求助10
16秒前
威武寒松关注了科研通微信公众号
17秒前
清秀网络完成签到,获得积分10
18秒前
19秒前
陈词丶发布了新的文献求助10
20秒前
墙雨轩完成签到 ,获得积分10
22秒前
百里守约完成签到 ,获得积分10
26秒前
CodeCraft应助koalafish采纳,获得10
29秒前
33秒前
852应助陈词丶采纳,获得10
34秒前
35秒前
酷波er应助听闻采纳,获得10
38秒前
无限鸵鸟完成签到 ,获得积分10
38秒前
小巧幼蓉发布了新的文献求助10
39秒前
39秒前
41秒前
威武寒松发布了新的文献求助10
42秒前
43秒前
糖醋里脊完成签到,获得积分10
43秒前
土豪的摩托完成签到 ,获得积分10
43秒前
Orange应助houy采纳,获得30
46秒前
糖醋里脊发布了新的文献求助50
48秒前
糊涂虫发布了新的文献求助10
48秒前
大个应助yeah采纳,获得10
50秒前
53秒前
53秒前
Adrenaline发布了新的文献求助10
59秒前
1分钟前
SciGPT应助含蓄凡柔采纳,获得10
1分钟前
丘比特应助小巧幼蓉采纳,获得10
1分钟前
听闻发布了新的文献求助10
1分钟前
1分钟前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Handbook of pharmaceutical excipients, Ninth edition 5000
Aerospace Standards Index - 2026 ASIN2026 3000
Signals, Systems, and Signal Processing 610
Discrete-Time Signals and Systems 610
Principles of town planning : translating concepts to applications 500
Wearable Exoskeleton Systems, 2nd Edition 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6058165
求助须知:如何正确求助?哪些是违规求助? 7890883
关于积分的说明 16296629
捐赠科研通 5203241
什么是DOI,文献DOI怎么找? 2783828
邀请新用户注册赠送积分活动 1766484
关于科研通互助平台的介绍 1647087