Generalized information equilibrium approaches to EEG sleep stage discrimination (Q519793)

Summary: Recent advances in neuroscience have raised the hypothesis that the underlying pattern of neuronal activation which results in electroencephalography (EEG) signals is via power-law distributed neuronal avalanches, while EEG signals are nonstationary. Therefore, spectral analysis of EEG may miss many properties inherent in such signals. A complete understanding of such dynamical systems requires knowledge of the underlying nonequilibrium thermodynamics. In recent work by \textit{P. Fielitz} and \textit{G. Borchardt} [``A generalized concept of information transfer'', Phys. Essays 24, No. 3, 350--363 (2011; \url{doi:10.4006/1.3601352}); ``A general concept of natural information equilibrium: from the ideal gas law to the K-Trumpler effect'', Preprint, \url{arXiv:0905.0610}], the concept of information equilibrium (IE) in information transfer processes has successfully characterized many different systems far from thermodynamic equilibrium. We utilized a publicly available database of polysomnogram EEG data from fourteen subjects with eight different one-minute tracings of sleep stage 2 and waking and an overlapping set of eleven subjects with eight different one-minute tracings of sleep stage 3. We applied principles of IE to model EEG as a system that transfers (equilibrates) information from the time domain to scalp-recorded voltages. We find that waking consciousness is readily distinguished from sleep stages 2 and 3 by several differences in mean information transfer constants. Principles of IE applied to EEG may therefore prove to be useful in the study of changes in brain function more generally.