Abstract
Throughout each day, the brain displays transient changes in state, as evidenced by shifts in behavior and vigilance. While the electrophysiological correlates of brain states have been studied for some time, it remains unclear how large-scale cortico-cortical functional connectivity systematically reconfigures across states. Here, we investigate state-dependent shifts in cortical functional connectivity by recording local field potentials (LFPs) during spontaneous behavioral transitions in the ferret using chronically implanted micro-electrocorticographic (µECoG) arrays positioned over occipital, parietal, and temporal cortical regions. To objectively classify brain state, we describe a data-driven approach that projects time-varying LFP spectral properties into brain state space. Distinct brain states displayed markedly different patterns of cross-frequency phase-amplitude coupling and inter-electrode phase synchronization across several LFP frequency bands. The largest across-state differences in functional connectivity were observed between periods of presumed slow-wave and rapid-eye-movement-sleep/active-state, which were characterized by the contrasting phenomena of cortical network fragmentation and global synchronization, respectively. Collectively, our data provide strong evidence that large-scale functional interactions in the brain dynamically reconfigure across behavioral states.
Highlights
Across the sleep/wake cycle we typically transition between states of varying vigilance and unconsciousness
To assess large-scale cortical dynamics associated with spontaneous brain state transitions, animals were recorded across multiple sessions with a minimum length of 2 hours each
While animals were alert and moving about, local field potentials (LFPs) spectra were typically characterized by theta (4–6 Hz) oscillations coupled with relatively low delta oscillation power (0.8–3 Hz)
Summary
Across the sleep/wake cycle we typically transition between states of varying vigilance and unconsciousness. To test this hypothesis, we recorded LFPs during spontaneous behavior, including movement, quiet awake, and sleep periods, using custom micro-electrocorticographic (μECoG) arrays chronically implanted in ferrets. We recorded LFPs during spontaneous behavior, including movement, quiet awake, and sleep periods, using custom micro-electrocorticographic (μECoG) arrays chronically implanted in ferrets The advantage of this approach was that, in contrast to humans, ferrets alternate relatively quickly across sleep, resting, and awake states[16, 17]. Brain states in this study were exclusively classified based on electrophysiological signatures of neural activity detected in cortex This state-classification method enabled the examination of how patterns of large-scale cortical functional connectivity evolve as animals traverse through brain state space. Our data reveal that patterns of cortical synchronization systematically reconfigure across brain states, with the most striking across-state changes occurring between periods of presumed slow-wave and rapid eye movement sleep
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