Systemic Modeling of Chaotic EEG During Human Sleep

One of the most challenging discussions about EEG is the chaotic nature of this biological signal. In the present study, we attempt to provide an analysis to demonstrate sleep EEG chaoticity. We model changes of sleep attractor dynamic in phase space by exponential regression. Our model demonstrates that the sleep attractor is the sleep cycle attractor whose size shrinks during successive cycles by presenting a new definition of the sleep cycle. We study the EEG dynamics of different sleep stages by presenting two new features based on phase space properties. We show that each stage has a unique chaotic attractor. We model geometric changes of these attractors during successive sleep cycles. Our model achieves an accuracy, sensitivity, and specificity of 89.15%, 82.84%, and 81.62% classifying sleep stages.

Human cerebral cortex networks use expanding and contracting state dynamic to shape cortical functions

SummaryWe lack viable explanations of how collective activities of neurons in networks produce brain functions. We recorded field potentials from many local networks in the human cerebral cortex during a wide variety of brain functions. The network dynamics showed that each local cortical network produced fluctuating attractor states. The state trajectories continuously stretched and contracted during all brain functions, leaving no stable patterns. Different local networks all produced this dynamic, despite different architectures. Single trial stimuli and tasks modified the stretching and contractions. These modified fluctuations cross-correlated among particular networks during specific brain functions. Spontaneous activity, rest, sensory, motor and cognitive functions all emerged from this dynamic. Its mathematical structure provides a general theoretical model of cortical dynamics that can be tested experimentally. This universal dynamic is a simple functional organizing principle for brain functions at the mm3 scale that is distinct from existing frameworks.Graphical abstractIn briefWillumsen et al. developed a method to show that local cortical networks contribute to sensory, motor and cognitive functions by stretching and contracting the trajectory of the multidimensional field potential. In single trials the networks communicate by cross-correlating the stretching and contracting. This ubiquitous attractor dynamic forms a departure from existing models of how postsynaptic dynamics contribute to sensory, motor and cognitive brain functions.HighlightsCortical fluctuating expanding and contacting attractor dynamics (FECAT) drive collective postsynaptic operations at the mm3 scaleFECAT dynamic accounted for all behavioral conditions and all tested cortical areasCortical states show no stationary patterns, but continuously expand and contract with a stable attractor dynamicOur method reveals multi-dimensional cortical dynamics in field potentials, also useful for EEG and MEG