Fig 1.
Representative data illustrating dark/light modulation of sleep-wake behavior in C57Bl/6 mouse.
A i-ii) Hypnogram was generated by automatic sleep scoring of wk, nrem and rem sleep states. B) Long (-) and brief (*) wk bouts were identified based on the frequency pattern of cortex and hippocampal eeg activity (i-ii). iii) raw eeg during brief wk.
Fig 2.
Statistics of wk, nrem and rem bout duration as a function of dark/light periods.
A) Bouts duration histogram showed a clear bimodal density distribution of wake (brief- and long-wk) while nrem and rem distribution was unimodal; only the density of long-wk varied during circadian rhythm, lasting longer in the dark (active) than light (inactive) phase. B) Cumulative wk showed by Kaplan-Meyer survival curves exhibited a biexponential distribution (wkb and wkl, vertical bar) with a significant increment of wkl duration in dark phase. C) Mean bout durations of wkl nrem rem and wkb; duration increased in wkl during dark in comparison with light phase. Clear differences in duration distribution during light and dark period are shown (*, Anova and Log-Rank Test for Kaplan-Meier analysis p < 0.05).
Fig 3.
Spectral analysis of sleep stages normalized to the total spectrum of the signal in 24 hours.
A) Hippocampal spectral content of long and brief wake is different (in red; cortex in blue); i and ii, long wake epochs had an augmented theta band with a characteristic 8 Hz peak (θ2 band; arrow a), whereas in the brief wake a lower frequency theta peak activity was at 6 Hz (θ1 band; arrow b); in addition, the power of fast gamma hippocampal frequencies in long wake epochs is significantly increased compared to brief wake. During nrem sleep a predominance of delta and beta power, and a reduction of gamma band were observed (iii) and in rem there was a predominance of theta (iv; arrow a) with low delta and beta, and an increased gamma band with respect to nrem. B) Long vs. brief wake spectrums; hippocampal, but not cortical, fast gamma and theta power (θ2) and EMG tone were decreased in brief-wk (p < 0.001).
Table 1.
Probability matrix of transitions between states and of remaining in a state for discrete time steps of 5 seconds applying a four-state Markov model to fit the mouse sleep-wake dynamics along 12/12h dark/light cycle.
Dark filled cells, dark period; light filled cells, light period.
Fig 4.
Diagram of four-state Markov model accounting for the wk-sleep dynamics across dark/light cycle.
Circular arrows correspond to the probability of maintaining a state (i.e., the time spent in the corresponding state or bout duration), and straight arrows to transitions between states; arrows thickness are proportional to the corresponding probabilities (from Table 1), and the dark and light periods are represented in black and grey. The sleep-wake model of four states comprises of two wk states (with spectral differences, see text): a long-wk (wkl) and a brief-wk (wkb); and of nrem and rem sleep states. States of wkl and nrem were more stable than rem and wkb, while state transitions wkb to nrem and rem to nrem were the most probable. Circadian modulation increased the stability of wkl mainly by reducing the transitions from wkl to nrem during dark active period (*, p < 0.05; and **, p < 0.01).