Literature DB >> 35903785

Interpersonal Physiological Synchrony Predicts Group Cohesion.

Alon Tomashin1,2, Ilanit Gordon1,2, Sebastian Wallot3,4.   

Abstract

A key emergent property of group social dynamic is synchrony-the coordination of actions, emotions, or physiological processes between group members. Despite this fact and the inherent nested structure of groups, little research has assessed physiological synchronization between group members from a multi-level perspective, thus limiting a full understanding of the dynamics between members. To address this gap of knowledge we re-analyzed a large dataset (N = 261) comprising physiological and psychological data that were collected in two laboratory studies that involved two different social group tasks. In both studies, following the group task, members reported their experience of group cohesion via questionnaires. We utilized a non-linear analysis method-multidimensional recurrence quantification analysis that allowed us to represent physiological synchronization in cardiological interbeat intervals between group members at the individual-level and at the group-level. We found that across studies and their conditions, the change in physiological synchrony from baseline to group interaction predicted a psychological sense of group cohesion. This result was evident both at the individual and the group levels and was not modified by the context of the interaction. The individual- and group-level effects were highly correlated. These results indicate that the relationship between synchrony and cohesion is a multilayered construct. We re-affirm the role of physiological synchrony for cohesion in groups. Future studies are needed to crystallize our understanding of the differences and similarities between synchrony at the individual-level and synchrony at the group level to illuminate under which conditions one of these levels has primacy, or how they interact.
Copyright © 2022 Tomashin, Gordon and Wallot.

Entities:  

Keywords:  cohesion; group-level synchrony; individual-level-synchrony; physiological synchrony; recurrence quantification analysis

Year:  2022        PMID: 35903785      PMCID: PMC9314573          DOI: 10.3389/fnhum.2022.903407

Source DB:  PubMed          Journal:  Front Hum Neurosci        ISSN: 1662-5161            Impact factor:   3.473


  44 in total

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10.  Calculation of Average Mutual Information (AMI) and False-Nearest Neighbors (FNN) for the Estimation of Embedding Parameters of Multidimensional Time Series in Matlab.

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