Nonlinear dynamics captures brain states at different levels of consciousness in patients anesthetized with propofol

Autor: Divya Chander, Christina Reynolds, Sarah L. Eagleman, M. Bruce MacIver, Nicholas T. Ouellette
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Male
Brain activity and meditation
Physiology
Electroencephalography
Pathology and Laboratory Medicine
Systems Science
0302 clinical medicine
Level of consciousness
030202 anesthesiology
Anesthesiology
Medicine and Health Sciences
Anesthesia
Propofol
media_common
Clinical Neurophysiology
Aged
80 and over
Brain Mapping
Multidisciplinary
medicine.diagnostic_test
Pharmaceutics
Unconsciousness
Information processing
Drugs
Brain
Signal Processing
Computer-Assisted
Middle Aged
Electrophysiology
Bioassays and Physiological Analysis
Brain Electrophysiology
Ellipses
Physical Sciences
Medicine
Female
medicine.symptom
Psychology
medicine.drug
Research Article
Adult
Computer and Information Sciences
Consciousness
Imaging Techniques
Science
media_common.quotation_subject
Cognitive Neuroscience
Neurophysiology
Geometry
Neuroimaging
Surgical and Invasive Medical Procedures
Research and Analysis Methods
Syncope
03 medical and health sciences
Young Adult
Signs and Symptoms
Drug Therapy
Diagnostic Medicine
medicine
Pain Management
Humans
Anesthetics
Aged
Retrospective Studies
Pharmacology
Electrophysiological Techniques
Biology and Life Sciences
Brain Waves
Nonlinear system
Nonlinear Dynamics
Cognitive Science
Clinical Medicine
Neuroscience
030217 neurology & neurosurgery
Mathematics
Zdroj: PLoS ONE
PLoS ONE, Vol 14, Iss 10, p e0223921 (2019)
ISSN: 1932-6203
Popis: The information processing capability of the brain decreases during unconscious states. Capturing this decrease during anesthesia-induced unconsciousness has been attempted using standard spectral analyses as these correlate relatively well with breakdowns in corticothalamic networks. Much of this work has involved the use of propofol to perturb brain activity, as it is one of the most widely used anesthetics for routine surgical anesthesia. Propofol administration alone produces EEG spectral characteristics similar to most hypnotics; however, inter-individual and drug variation render spectral measures inconsistent. Complexity measures of EEG signals could offer better measures to distinguish brain states, because brain activity exhibits nonlinear behavior at several scales during transitions of consciousness. We tested the potential of complexity analyses from nonlinear dynamics to identify loss and recovery of consciousness at clinically relevant timepoints. Patients undergoing propofol general anesthesia for various surgical procedures were identified as having changes in states of consciousness by the loss and recovery of response to verbal stimuli after induction and upon cessation of anesthesia, respectively. We demonstrate that nonlinear dynamics analyses showed more significant differences between consciousness states than spectral measures. Notably, attractors in conscious and anesthesia-induced unconscious states exhibited significantly different shapes. These shapes have implications for network connectivity, information processing, and the total number of states available to the brain at these different levels. They also reflect some of our general understanding of the network effects of consciousness in a way that spectral measures cannot. Thus, complexity measures could provide a universal means for reliably capturing depth of consciousness based on EEG changes at the beginning and end of anesthesia administration.
Databáze: OpenAIRE
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