An embedded and embodied neuroscience of interpersonal synchrony
Abstract
Interpersonal synchrony provides a powerful framework for understanding how coordinated behaviour emerges across interacting individuals. While neuroscientific advances have extended this work to the neural level, they risk reducing synchrony to isolated mechanisms without an appropriate conceptual framework. We argue for an embedded and embodied approach in which neural, physiological, and behavioural processes are treated as co-constitutive components of coupled systems. Within this perspective, neural activity both constrains and is constrained by the dynamics of interaction. We highlight key challenges, including isolating genuine neural signals, developing multi-level dynamical models, and identifying collective variables linking scales. We also set out criteria for identifying such variables and predictions by which the framework can be tested. Rather than abandoning mechanism, this approach redefines it as multilevel and dynamical, providing a principled basis for a more integrative science of interpersonal synchrony.
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BibTeX
@article{varlet2026embedded,
title = {{An embedded and embodied neuroscience of interpersonal synchrony}},
author = {Manuel Varlet and Michael J Richardson},
journal = {Oxford Open Neuroscience},
year = {2026},
month = oct,
doi = {10.1093/oons/kvag017},
url = {https://doi.org/10.1093/oons/kvag017},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - An embedded and embodied neuroscience of interpersonal synchrony
AU - Manuel Varlet
AU - Michael J Richardson
PY - 2026
DA - 2026/10/27
JO - Oxford Open Neuroscience
DO - 10.1093/oons/kvag017
UR - https://doi.org/10.1093/oons/kvag017
AB - Interpersonal synchrony provides a powerful framework for understanding how coordinated behaviour emerges across interacting individuals. While neuroscientific advances have extended this work to the neural level, they risk reducing synchrony to isolated mechanisms without an appropriate conceptual framework. We argue for an embedded and embodied approach in which neural, physiological, and behavioural processes are treated as co-constitutive components of coupled systems. Within this perspective, neural activity both constrains and is constrained by the dynamics of interaction. We highlight key challenges, including isolating genuine neural signals, developing multi-level dynamical models, and identifying collective variables linking scales. We also set out criteria for identifying such variables and predictions by which the framework can be tested. Rather than abandoning mechanism, this approach redefines it as multilevel and dynamical, providing a principled basis for a more integrative science of interpersonal synchrony.
SN - 2753-149X
ER -