Making new connections: An fNIRS machine learning classification study of inter-brain synchrony in the default mode network.
Grace Qiyuan Miao, Ian J. Lieberman, Ashley L. Binnquist, Agnieszka Pluta, Bear M. Goldstein, Rick Dale, Matthew D. Lieberman
Social Cognitive and Affective Neuroscience June 9, 2026 DOI: 10.1093/scan/nsag044 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Observational cohort Peer reviewed |
|---|---|
| Sample size | 140 |
| Population | Stranger dyads |
| Topics | Default mode network |
| Keywords | Communication Inter-brain synchrony Social connection |
| Key findings | Greater feelings of connection during deep conversations are associated with increased DMN synchrony, with the right TPJ subregion emerging as the strongest predictor. |
Abstract
Little is known about the neurocognitive underpinnings of forming social connections. In this study, we tested whether default mode network (DMN) inter-brain synchrony (which prior work has linked to interpersonal alignment, or 'seeing eye-to-eye') predicts feelings of connection during conversations. Seventy pairs of strangers engaged in shallow or deep conversations while brain activity was measured with functional near infrared spectroscopy (fNIRS). Stranger dyads in the deep condition felt more connected than those in the shallow condition. Greater feelings of connection were associated with increased DMN synchrony, with the right temporoparietal junction (TPJ) subregion of the DMN emerging as the strongest individual predictor across regression analyses and machine learning classification. These findings suggest that DMN synchrony in general and TPJ synchrony in particular may play a key role in strangers coming to 'see eye-to-eye' during face-to-face interactions and feeling more socially connected.