Physiological Group Synchrony Captures Individual Perceptions of Trust and Cohesion and Collective Performance through Multi-Channel Network Analysis
- 1University of Trento
Abstract
Humans coordinate in groups, yet much of what we know about coordination comes from dyadic interaction. In groups, however, knowing how much people synchronize may not be enough. Pairwise synchrony can be distributed across teammates: who synchronizes with whom, and how these connections are distributed, may carry distinct social information. Here, we tested whether physiological group synchrony can be understood as a network topology of interpersonal coordination rather than as an aggregate of dyadic alignments. A total of 33 groups (N = 161 participants) completed cooperative and competitive joint drumming tasks while cardiac inter-beat intervals (IBI) and electrodermal activity (EDA) were recorded simultaneously. Pairwise physiological synchrony was estimated using lagged cross-correlation and used to construct synchrony-based networks. IBI-based networks showed stronger and broader cardiac connectivity during cooperation, with cardiac coupling also increasing during competitive drumming relative to baseline. EDA-based networks also showed task-sensitive changes in node-level connectivity and captured social and behavioral dimensions of group interaction, linking trust and cohesion to node-level connectivity, and collective behavioral synchrony to lower clustering and higher local efficiency. Together, these findings show that the social meaning of physiological group synchrony lies not only in how much individuals align, but in how physiological alignment is distributed across people, relationships, and biological systems. By preserving this configuration, synchrony-based network analysis captures information about group experience that is lost when synchrony is reduced to an average dyadic score, providing a route toward understanding group synchrony as a flexible, selective, and distributed property of social coordination.
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BibTeX
@misc{carollo2026physiological,
title = {{Physiological Group Synchrony Captures Individual Perceptions of Trust and Cohesion and Collective Performance through Multi-Channel Network Analysis}},
author = {A. Carollo and M. Sabag and N. Golbez and O. Porat and E. Cohen and A. Bizzego and I. Gordon},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.18.752699},
url = {https://www.biorxiv.org/content/10.64898/2026.09.18.752699v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Physiological Group Synchrony Captures Individual Perceptions of Trust and Cohesion and Collective Performance through Multi-Channel Network Analysis
AU - A. Carollo
AU - M. Sabag
AU - N. Golbez
AU - O. Porat
AU - E. Cohen
AU - A. Bizzego
AU - I. Gordon
PY - 2026
DA - 2026/09/18
PB - bioRxiv
DO - 10.64898/2026.09.18.752699
UR - https://www.biorxiv.org/content/10.64898/2026.09.18.752699v1
AB - Humans coordinate in groups, yet much of what we know about coordination comes from dyadic interaction. In groups, however, knowing how much people synchronize may not be enough. Pairwise synchrony can be distributed across teammates: who synchronizes with whom, and how these connections are distributed, may carry distinct social information. Here, we tested whether physiological group synchrony can be understood as a network topology of interpersonal coordination rather than as an aggregate of dyadic alignments. A total of 33 groups (N = 161 participants) completed cooperative and competitive joint drumming tasks while cardiac inter-beat intervals (IBI) and electrodermal activity (EDA) were recorded simultaneously. Pairwise physiological synchrony was estimated using lagged cross-correlation and used to construct synchrony-based networks. IBI-based networks showed stronger and broader cardiac connectivity during cooperation, with cardiac coupling also increasing during competitive drumming relative to baseline. EDA-based networks also showed task-sensitive changes in node-level connectivity and captured social and behavioral dimensions of group interaction, linking trust and cohesion to node-level connectivity, and collective behavioral synchrony to lower clustering and higher local efficiency. Together, these findings show that the social meaning of physiological group synchrony lies not only in how much individuals align, but in how physiological alignment is distributed across people, relationships, and biological systems. By preserving this configuration, synchrony-based network analysis captures information about group experience that is lost when synchrony is reduced to an average dyadic score, providing a route toward understanding group synchrony as a flexible, selective, and distributed property of social coordination.
ER -