Dataset Information

Sleep-wake dynamics pre- and post-exposure to chronic social stress.

ABSTRACT: An analytical approach combining the statistical distributions of the sleep-wake bouts and the Markov transition matrix is used to explain the under-examined association between the microarchitecture of the sleep-wake cycle and susceptibility to chronic social stress in C57BL/6J mice. We separated the sleep-wake transitions into distinct sleep-wake sequences, NREM↔Wake and NREM→REM→Wake, which are controlled by independent neural circuits. Our findings imply greater pull toward the wake leading to early termination and fragmentation of the sleep bouts in the light in both sleep-wake sequences pre- and post-stress. Moreover, the stability of NREM in the NREM↔Wake transition was lower, and the probability of transitioning to wake was higher in susceptible relative to resilient or stress-naïve mice pre- and post-stress. Our findings help elucidate the mechanistic interplay between sleep and mood by suggesting the potential neural underpinnings of sleep disturbances responsible the aberrant transitions of sleep-wake bouts exhibited by the stress-susceptible phenotype.

SUBMITTER: Radwan B

PROVIDER: S-EPMC8524188 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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Sleep-wake dynamics pre- and post-exposure to chronic social stress.

Radwan Basma B Jansen Gloria G Chaudhury Dipesh D

iScience 20211002 10

An analytical approach combining the statistical distributions of the sleep-wake bouts and the Markov transition matrix is used to explain the under-examined association between the microarchitecture of the sleep-wake cycle and susceptibility to chronic social stress in C57BL/6J mice. We separated the sleep-wake transitions into distinct sleep-wake sequences, NREM↔Wake and NREM→REM→Wake, which are controlled by independent neural circuits. Our findings imply greater pull toward the wake leading ...[more]

PMID: 34703999

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Project description:ObjectivesConventional scoring of sleep provides little information about the process of transitioning between vigilance states. We applied the state space technique (SST) using frequency band ratios to follow normal maturation of different sleep/wake states, velocities of movements, and transitions between states of juvenile (postnatal day 34, P34) and young adult rats (P71).Design24-h sleep recordings of eight P34 and nine P71 were analyzed using conventional scoring criteria and SST one week following implantation of telemetric transmitter. SST is a non-categorical approach that allows novel quantitative and unbiased examination of vigilance-states dynamics and state transitions. In this approach, behavioral changes are described in a 2-dimensional state space that is derived from spectral characteristics of the electroencephalography.Measurements and resultsWith maturation sleep intensity declines, the duration of deep slow wave sleep (DSWS) and light slow wave sleep (LSWS) decreases and increases, respectively. Vigilance state determination, as a function of frequency, is not constant; there is a substantial shift to higher ratio 1 in all vigilance states except DSWS. Deep slow wave sleep decreases in adult relative to juvenile animals at all frequencies. P71 animals have 400% more trajectories from Wake to LSWS (p = 0.005) and vice versa (p = 0.005), and 100% more micro-arousals (p = 0.021), while trajectories from LSWS to DSWS (p = 0.047) and vice versa (p = 0.033) were reduced by 60%. In both juvenile and adult animals, no significant changes were found in sleep velocity at all regions of the 2-dimensional state space plot; suggesting that maturation has a partial effect on sleep stability.ConclusionsHere, we present novel and original evidence that SST enables visualization of vigilance-state intensity, transitions, and velocities that were not evident by traditional scoring methods. These observations provide new perspectives in sleep state dynamics and highlight the usefulness of this technique in exploring the development of sleep-wake activity.

Project description:BackgroundScale-invariant neuronal avalanches have been observed in cell cultures and slices as well as anesthetized and awake brains, suggesting that the brain operates near criticality, i.e. within a narrow margin between avalanche propagation and extinction. In theory, criticality provides many desirable features for the behaving brain, optimizing computational capabilities, information transmission, sensitivity to sensory stimuli and size of memory repertoires. However, a thorough characterization of neuronal avalanches in freely-behaving (FB) animals is still missing, thus raising doubts about their relevance for brain function.Methodology/principal findingsTo address this issue, we employed chronically implanted multielectrode arrays (MEA) to record avalanches of action potentials (spikes) from the cerebral cortex and hippocampus of 14 rats, as they spontaneously traversed the wake-sleep cycle, explored novel objects or were subjected to anesthesia (AN). We then modeled spike avalanches to evaluate the impact of sparse MEA sampling on their statistics. We found that the size distribution of spike avalanches are well fit by lognormal distributions in FB animals, and by truncated power laws in the AN group. FB data surrogation markedly decreases the tail of the distribution, i.e. spike shuffling destroys the largest avalanches. The FB data are also characterized by multiple key features compatible with criticality in the temporal domain, such as 1/f spectra and long-term correlations as measured by detrended fluctuation analysis. These signatures are very stable across waking, slow-wave sleep and rapid-eye-movement sleep, but collapse during anesthesia. Likewise, waiting time distributions obey a single scaling function during all natural behavioral states, but not during anesthesia. Results are equivalent for neuronal ensembles recorded from visual and tactile areas of the cerebral cortex, as well as the hippocampus.Conclusions/significanceAltogether, the data provide a comprehensive link between behavior and brain criticality, revealing a unique scale-invariant regime of spike avalanches across all major behaviors.

Dataset Information

Sleep-wake dynamics pre- and post-exposure to chronic social stress.

Publications

Sleep-wake dynamics pre- and post-exposure to chronic social stress.

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