Social attachment shapes interbrain synchrony

Neural synchrony, or correlated neural activity across interacting individuals, scales with relationship quality in humans, yet how it evolves during social bond formation remains unknown. Using fiber photometry in monogamous prairie voles, we track prefrontal cortex synchrony across pair bond formation. Bonded voles show stronger synchrony with partners than strangers, mirroring human findings. A linear mixed model reveals that synchrony is jointly shaped by bond strength, inter-animal distance, and time since interaction onset, with relationship type modulating how each factor contributes. Using a machine-learning behavioral classification pipeline we developed for freely interacting voles, we demonstrate that the coupling between specific behaviors and synchrony depends on the nature of the dyadic relationship. These findings establish that neural synchrony is not a simple function of proximity or interaction time but is fundamentally shaped by relationship history-a conclusion with direct implications for understanding the synchrony in human social attachment.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-04-16
DOI
https://doi.org/10.64898/2026.04.15.718291
Primary Topic
Neuroendocrine regulation and behavior
Type
article
Field-Weighted Citation Impact
0.00

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article

Social attachment shapes interbrain synchrony

Zoe R. Donaldson, Liza E. Brusman, Yevgenia Kozorovitskiy, Kathleen Murphy
bioRxiv (Cold Spring Harbor Laboratory)
Neuroendocrine regulation and behavior
article

Social attachment shapes interbrain synchrony

Zoe R. Donaldson, Liza E. Brusman, Yevgenia Kozorovitskiy, Kathleen Murphy
article en

Abstract

Neural synchrony, or correlated neural activity across interacting individuals, scales with relationship quality in humans, yet how it evolves during social bond formation remains unknown. Using fiber photometry in monogamous prairie voles, we track prefrontal cortex synchrony across pair bond formation. Bonded voles show stronger synchrony with partners than strangers, mirroring human findings. A linear mixed model reveals that synchrony is jointly shaped by bond strength, inter-animal distance, and time since interaction onset, with relationship type modulating how each factor contributes. Using a machine-learning behavioral classification pipeline we developed for freely interacting voles, we demonstrate that the coupling between specific behaviors and synchrony depends on the nature of the dyadic relationship. These findings establish that neural synchrony is not a simple function of proximity or interaction time but is fundamentally shaped by relationship history-a conclusion with direct implications for understanding the synchrony in human social attachment.

bioRxiv (Cold Spring Harbor Laboratory)
Northwestern University (US), University of Colorado Boulder (US)
National Institutes of Health
Reduced inequalities
Openalex Percentile: Top 22%
Neuroendocrine regulation and behavior
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