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同步行为中人际策略的瞬态脑网络。

Transient brain networks underlying interpersonal strategies during synchronized action.

机构信息

Center for Music in the Brain, Aarhus University & The Royal Academy of Music Aarhus/Aalborg, Aarhus, Denmark.

SINe Lab, Section for Cognitive Systems, DTU Compute, Technical University of Denmark, Kongens Lyngby, Denmark.

出版信息

Soc Cogn Affect Neurosci. 2021 Jan 18;16(1-2):19-30. doi: 10.1093/scan/nsaa056.

Abstract

Interpersonal coordination is a core part of human interaction, and its underlying mechanisms have been extensively studied using social paradigms such as joint finger-tapping. Here, individual and dyadic differences have been found to yield a range of dyadic synchronization strategies, such as mutual adaptation, leading-leading, and leading-following behaviour, but the brain mechanisms that underlie these strategies remain poorly understood. To identify individual brain mechanisms underlying emergence of these minimal social interaction strategies, we contrasted EEG-recorded brain activity in two groups of musicians exhibiting the mutual adaptation and leading-leading strategies. We found that the individuals coordinating via mutual adaptation exhibited a more frequent occurrence of phase-locked activity within a transient action-perception-related brain network in the alpha range, as compared to the leading-leading group. Furthermore, we identified parietal and temporal brain regions that changed significantly in the directionality of their within-network information flow. Our results suggest that the stronger weight on extrinsic coupling observed in computational models of mutual adaptation as compared to leading-leading might be facilitated by a higher degree of action-perception network coupling in the brain.

摘要

人际协调是人类互动的核心部分,其潜在机制已通过社交范式(如联合手指敲击)得到广泛研究。在这里,个体和双体差异产生了一系列的双体同步策略,例如相互适应、领先-领先和领先-跟随行为,但这些策略背后的大脑机制仍知之甚少。为了确定这些最小社交互动策略出现的个体大脑机制,我们对比了表现出相互适应和领先-领先策略的两组音乐家的 EEG 记录的大脑活动。我们发现,通过相互适应进行协调的个体在短暂的动作感知相关脑网络中表现出更频繁的 alpha 范围内的锁相活动,与领先-领先组相比。此外,我们还确定了顶叶和颞叶脑区,它们在网络内信息流的方向上发生了显著变化。我们的结果表明,与领先-领先相比,相互适应计算模型中观察到的外部耦合更强的权重可能是由大脑中更高程度的动作感知网络耦合促成的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/094f/7812620/d80b93993627/nsaa056f1.jpg

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