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Abstract #0203

Mapping inter-brain synchrony in awake, socially interacting mice using SORDINO hyperscanning

Tzu-Hao Harry Chao1,2,3, Sheng Song1,2,3, Martin MacKinnon1,2,3,4, Sung-Ho Lee1,2,3, Li-Ming Hsu1,2,3,5, Randy Nonneman1,2,3, and Yen-Yu Ian Shih1,2,3
1Center for Animal MRI, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States, 2Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States, 3Department of Neurology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States, 4National Institute of Neurological Disorders and Stroke, National Institute of Health, Bethesda, MD, United States, 5Department of Radiology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States

Synopsis

Keywords: Functional Connectivity, Functional Connectivity, Brain Connectivity; fMRI Acquisition; Neuroscience; Preclinical

Motivation: Inter-brain synchronization enables shared understanding and coordinated behavior in social interactions, with disruptions linked to neuropsychiatric disorders. However, its underlying neuronal mechanisms remain unclear due to limitations of current imaging techniques.

Goal(s): Develop a hyperscanning-fMRI platform to measure inter-brain synchronization and identify key brain hubs engaged in mouse social interactions.

Approach: Using silent, motion-insensitive SORDINO-fMRI, we simultaneously imaged the brains of two interacting mice, comparing inter-brain connectivity before and after divider removal.

Results: Social interaction post-divider removal elicited robust inter-brain synchronization among retrosplenial, cingulate, prelimbic, anterior insula (default mode and salience networks), and motor cortices, but not somatosensory cortex.

Impact: We demonstrated a robust large-scale inter-brain synchronization in socially interacting mice using a novel, silent, motion-insensitive SORDINO-fMRI hyperscanning method, enabling future exploration of neural circuit- and network-level mechanisms behind inter-brain synchronization that are challenging to investigate with conventional approaches.

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Keywords