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社会同步的阿尔法波段特征。

Alpha band signatures of social synchrony.

机构信息

Department of Psychology, Assumption College, Worcester, MA, USA.

Department of Psychology, Brandeis University, Waltham, MA, USA; Eunice Kennedy Shriver Center, Department of Psychiatry, University of Massachusetts Medical School, Worcester, MA, USA.

出版信息

Neurosci Lett. 2019 Apr 23;699:24-30. doi: 10.1016/j.neulet.2019.01.037. Epub 2019 Jan 23.

Abstract

Previous research has reported changes in mu rhythm, the central rhythm of the alpha frequency band, in both intentional and spontaneous interpersonal coordination. The current study was designed to extend existing findings on social synchrony to the pendulum swinging task and simultaneously measured time unfolding behavioral synchrony and EEG estimation of mu activity during spontaneous, intentional in-phase and intentional anti-phase interpersonal coordination. As expected, the behavioral measures of synchrony demonstrated the expected pattern of weak synchronization for spontaneous coordination, moderate synchronization for intentional anti-phase coordination, and strong synchronization for in-phase coordination. With respect to the EEG measures, we found evidence for mu enhancement for spontaneous coordination in contrast to mu suppression for intentional coordination (both in phase and anti-phase), with higher levels of synchronization associated with higher levels of mu suppression in the right hemisphere. The implications of the research findings and methodology for understanding the underlying mechanisms contributing to social problems in psychological disorders, leader-follower relationships, and inter-brain dynamics are discussed.

摘要

先前的研究报告称,在有意和自发的人际协调中,mu 节律(alpha 频带的中枢节律)发生了变化。本研究旨在将现有的社会同步研究结果扩展到钟摆摆动任务,并同时测量自发、有意同相和有意反相人际协调期间时间展开的行为同步和 EEG 估计的 mu 活动。正如预期的那样,行为同步的测量结果显示了自发协调的弱同步预期模式、有意反相协调的中等同步和同相协调的强同步。关于 EEG 测量,我们发现与有意协调(同相和反相)相比,自发协调存在 mu 增强的证据,而与右半球的 mu 抑制水平更高相关的同步水平更高。讨论了研究结果和方法对理解导致心理障碍、领导-跟随关系和脑间动力学中的社会问题的潜在机制的意义。

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Frontal alpha oscillations distinguish leaders from followers: multivariate decoding of mutually interacting brains.
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