Abstract
Understanding the inherent dynamics of the EEG associated to sleep-waking can provide insights into its basic neural regulation. By characterizing the local properties of the EEG using power spectrum, empirical mode decomposition (EMD) and Hilbert-spectral analysis, we can examine the dynamics over a range of time-scales. We analyzed rat EEG during wake, NREMS and REMS using these methods. The average instantaneous phase, power spectral density (PSD) of intrinsic mode functions (IMFs) and the energy content in various frequency bands show characteristic changes in each of the vigilance states. The 2nd and 7th IMFs show changes in PSD for wake and REMS, suggesting that those modes may carry wake- and REMS-associated cognitive, conscious and behavior-specific information of an individual even though the EEG may appear similar. The energy content in θ2 (6Hz-9Hz) band of the 1st IMF for REMS is larger than that of wake. The decrease in the phase function of IMFs from wake to REMS to NREMS indicates decrease of the mean frequency in these states, respectively. The rate of information processing in waking state is more in the time scale described by the first three IMFs than in REMS state. However, for IMF5-IMF7, the rate is more for REMS than that for wake. We obtained Hilbert-Huang spectral entropy, which is a suitable measure of information processing in each of these state-specific EEG. It is possible to evaluate the complex dynamics of the EEG in each of the vigilance states by applying measures based on EMD and Hilbert-transform. Our results suggest that the EMD based nonlinear measures of the EEG can provide useful estimates of the information possessed by various oscillations associated with the vigilance states. Further, the EMD-based spectral measures may have implications in understanding anatamo-physiological correlates of sleep-waking behavior and clinical diagnosis of sleep-pathology.
Highlights
Since its discovery by Berger [1], the electroencephalogram (EEG) has been recognized as an important tool in psychobehavioral studies and sleep research
Characteristic changes are observed in the power spectral density (PSD) of the vigilance states, with the average trend being that the power densities in non-rapid eye movement sleep (NREMS) are more than wake and rapid eye movement sleep (REMS)
Closer inspection reveals that the PSD of IMF2 in waking state is higher than in REMS
Summary
Since its discovery by Berger [1], the electroencephalogram (EEG) has been recognized as an important tool in psychobehavioral studies and sleep research. It is the commonest and the most characteristic feature for objectively defining various stages of sleep-waking. Cortical activation is shown by EEG desynchronization, while sleep-spindles and slow waves (0.4Hz-4Hz) are the hallmark of EEG during behavioral arousal (wakefulness) and non-rapid eye movement sleep (NREMS) respectively. During NREMS the neuronal firing patterns change from rapid firing, characteristic of arousal, to low frequency synchronized rhythms [2]. Stages of sleep are characterized by the presence of α-waves (7Hz-14Hz) in the EEG, which changes to slow oscillations (0.1Hz-4Hz) as sleep deepens. Analyzing the dynamical properties of the EEG can provide insights into understanding the mechanism of its basic regulation [12]
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