ArticleSocial cognitive and affective neuroscience2026
Making new connections: an fNIRS machine learning classification study of inter-brain synchrony in the default mode network.
Article in Social cognitive and affective neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- DrSVision: A Machine Learning Tool for Cortical Region-Specific fNIRS Calibration Based on Cadaveric Head MRI.Sensors (Basel, Switzerland) · 2025Article
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7 authors.
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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.
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