title: Percolation Model of Sensory Transmission and Loss of Consciousness Under General Anesthesia.
abstract: Neurons communicate with each other dynamically; how such communications lead to consciousness remains unclear. Here, we present a theoretical model to understand the dynamic nature of sensory activity and information integration in a hierarchical network, in which edges are stochastically defined by a single parameter p representing the percolation probability of information transmission. We validate the model by comparing the transmitted and original signal distributions, and we show that a basic version of this model can reproduce key spectral features clinically observed in electroencephalographic recordings of transitions from conscious to unconscious brain activities during general anesthesia. As p decreases, a steep divergence of the transmitted signal from the original was observed, along with a loss of signal synchrony and a sharp increase in information entropy in a critical manner; this resembles the precipitous loss of consciousness during anesthesia. The model offers mechanistic insights into the emergence of information integration from a stochastic process, laying the foundation for understanding the origin of cognition.
authors.affiliation: Department of Anesthesiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15260, USA.|Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA.
authors.forename: David W
authors.initials: DW
authors.lastname: Zhou
authors.affiliation: Department of Anesthesiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15260, USA.|Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15260, USA.
authors.forename: David D
authors.initials: DD
authors.lastname: Mowrey
authors.affiliation: Department of Anesthesiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15260, USA.|Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15260, USA.|Department of Pharmacology and Chemical Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15260, USA.
authors.forename: Pei
authors.initials: P
authors.lastname: Tang
authors.affiliation: Department of Anesthesiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15260, USA.|Department of Pharmacology and Chemical Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15260, USA.|Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15260, USA.
authors.forename: Yan
authors.initials: Y
authors.lastname: Xu
mesh_terms: D000344:Afferent Pathways / Q000502:physiology; D000768:Anesthesia, General; D002540:Cerebral Cortex / Q000166:cytology / Q000502:physiology; D003243:Consciousness / Q000502:physiology*; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology; D009474:Neurons / Q000502:physiology*; D009435:Synaptic Transmission / Q000502:physiology*; D013788:Thalamus / Q000166:cytology / Q000502:physiology