Bilek, Edda;
Zeidman, Peter;
Kirsch, Peter;
Tost, Heike;
Meyer-Lindenberg, Andreas;
Friston, Karl;
(2022)
Directed coupling in multi-brain networks underlies generalized synchrony during social exchange.
Neuroimage
, 252
, Article 119038. 10.1016/j.neuroimage.2022.119038.
Preview |
Text
1-s2.0-S1053811922001677-main.pdf - Published Version Download (1MB) | Preview |
Abstract
Advances in social neuroscience have made neural signatures of social exchange measurable simultaneously across people. This has identified brain regions differentially active during social interaction between human dyads, but the underlying systems-level mechanisms are incompletely understood. This paper introduces dynamic causal modeling and Bayesian model comparison to assess the causal and directed connectivity between two brains in the context of hyperscanning (h-DCM). In this setting, correlated neuronal responses become the data features that have to be explained by models with and without between-brain (effective) connections. Connections between brains can be understood in the context of generalized synchrony, which explains how dynamical systems become synchronized when they are coupled to each another. Under generalized synchrony, each brain state can be predicted by the other brain or a mixture of both. Our results show that effective connectivity between brains is not a feature within dyads per se but emerges selectively during social exchange. We demonstrate a causal impact of the sender's brain activity on the receiver of information, which explains previous reports of two-brain synchrony. We discuss the implications of this work; in particular, how characterizing generalized synchrony enables the discovery of between-brain connections in any social contact, and the advantage of h-DCM in studying brain function on the subject level, dyadic level, and group level within a directed model of (between) brain function.
| Type: | Article |
|---|---|
| Title: | Directed coupling in multi-brain networks underlies generalized synchrony during social exchange |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.neuroimage.2022.119038 |
| Publisher version: | https://doi.org/10.1016/j.neuroimage.2022.119038 |
| Language: | English |
| Additional information: | © 2021 Published by Elsevier Ltd. This is an open access article under the CC BY 4.0 license Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/) |
| Keywords: | Dynamic causal modeling, Hyperscanning, Joint attention, Social interaction, h-DCM |
| UCL classification: | UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10144944 |
Archive Staff Only
 |
View Item |
