Proceedings of the National Academy of Sciences · 2022 · 145 citations · 107 references
Life SciencesNeurobiologyNeuroscienceCognitive NeuroscienceElectrophysiologyNeurophysiologyChaos TheoryConsciousnessCortical PhysiologyElectroencephalographyNeural Circuit DynamicsNeuronal DynamicsCortical Circuit DynamicsCortical DynamicsCortical Evoked ResponsesCortical Signal ProcessingCritical DynamicsCriticality In Neural SystemsElectrophysiological RecordingsNeural Correlates Of Consciousness
Mounting evidence suggests that during conscious states, the electrodynamics of the cortex are poised near a critical point or phase transition and that this near-critical behavior supports the vast flow of information through cortical networks during conscious states. Here, we empirically identify a mathematically specific critical point near which waking cortical oscillatory dynamics operate, which is known as the edge-of-chaos critical point, or the boundary between stability and chaos. We do so by applying the recently developed modified 0-1 chaos test to electrocorticography (ECoG) and magnetoencephalography (MEG) recordings from the cortices of humans and macaques across normal waking, generalized seizure, anesthesia, and psychedelic states. Our evidence suggests that cortical information processing is disrupted during unconscious states because of a transition of low-frequency cortical electric oscillations away from this critical point; conversely, we show that psychedelics may increase the information richness of cortical activity by tuning low-frequency cortical oscillations closer to this critical point. Finally, we analyze clinical electroencephalography (EEG) recordings from patients with disorders of consciousness (DOC) and show that assessing the proximity of slow cortical oscillatory electrodynamics to the edge-of-chaos critical point may be useful as an index of consciousness in the clinical setting.
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On the Complexity of Finite Sequences
A. Lempel, J. Ziv · IEEE Transactions on Information Theory · 1976 · 2.7K citations
Parameterizing neural power spectra into periodic and aperiodic components
Thomas Donoghue, Matar Haller, Erik Peterson et al. · Nature Neuroscience · 2020 · 2.4K citations · Full text