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Updated: Mar 7, 2026

Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice
Published on: August 2, 2017
Sleep/wake movement velocities, trajectories and micro-arousals during maturation in rats
Gideon Gradwohl1,2, Nadja Olini1, Reto Huber3,4,5
1Child Development Center, University Children's Hospital Zurich, Zurich, Switzerland.
Background:
Sleep is regulated by two main processes. The circadian process provides a 24-h rhythm and the homeostatic process reflects sleep pressure, which increases in the course of wakefulness and decreases during sleep. Both of these processes undergo major changes during development. For example, sleep homeostasis, measured by means of electroencephalogram (EEG) slow-wave activity (SWA, EEG power between 0.5 and 4.5 Hz), peaks around puberty and decreases during adolescence. In humans and rats these changes have been related to cortical maturation. We aimed to explore whether additional parameters as state dynamic (dynamic of sleep/wake behavior) parameters of movement velocity, trajectories and micro-arousals provide markers of rat maturation. The state dynamics reflect the stability of sleep within a specific sleep stage. We applied a state space technique (SST), a quantitative and unbiased method, based on frequency band ratios of the EEG to analyze the development of different sleep/wake states and state dynamics between vigilance states. EEG of recording electrodes at the frontal and parietal lobe were analyzed using conventional scoring criteria and SST.
Results:
We found that movement velocity, trajectories between sleep states and micro-arousals changed as an inverse U-shaped curve across maturation. At all ages, movement velocity over the frontal lobe is higher compared to the parietal lobe, while the number of trajectories and micro-arousals are reduced. Furthermore, we showed that SWA correlates negatively with movement velocity and the number of micro-arousals. The velocity in the parietal lobe correlates positively with the number of micro-arousals. As for SWA, trajectories seem primarily to depend on sleep homeostasis regulatory mechanisms while the movement velocity seems to be modulated by other sleep regulators like the circadian rhythms.
Conclusions:
New insights in sleep/wake state dynamics are established with the SST, because trajectories, micro-arousals and velocities are not evident by traditional scoring methods. These dynamic measures may represent new indicators for changes in sleep regulatory processes across maturation.
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