Single-cell resolution functional networks during unconsciousness are segregated into spatially intermixed modules
2026.02.09
Highlights
● Cellular-resolution wide-field calcium imaging enables multi-scale network analysis
● Cellular-scale networks in sleep and anesthesia are more segregated than wakefulness
● Segregation is apparent only at the cellular level but not at the mesoscale
● Modules are intermixed at the cellular scale but localized at the mesoscale
The common neural mechanisms underlying the reduction of consciousness during sleep and anesthesia remain unclear. Previous studies have examined changes in network structure by only using recordings with limited spatial resolution, which has hindered the investigation of the critical spatial scales for the reduction of consciousness. To address this issue, we recorded calcium signals from approximately 10,000 neurons across multiple cortical regions in awake, sleeping, and anesthetized mice and compared network structure at different spatial scales by leveraging single-cell resolution and wide-field two-photon microscopy. At the single-cell scale, both sleep and anesthesia exhibit higher network modularity than an awake state, indicating a segregated network, but modules are spatially intermixed in all three states. In contrast, at the mesoscale, there are no consistent differences in modularity between states, and modules are spatially localized. Our multi-scale analysis challenges the traditional view of network segregation during unconsciousness and indicates a scale-dependent network organization.
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Jun Kitazono
Associate Professor
School of Data Science, Yokohama City University, 22-2 Seto, Kanazawa-ku, Yokohama-shi, Kanagawa 236-0027, Japan
Associate Professor
School of Data Science, Yokohama City University, 22-2 Seto, Kanazawa-ku, Yokohama-shi, Kanagawa 236-0027, Japan