A Computational, Neurobiological and Clinical Study of Cortical Connectivity During Consciousness & Anesthesia

University Of Michigan At Ann Arbor, Ann Arbor MI

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Abstract

? DESCRIPTION (provided by applicant): Although the field of anesthesiology has played a leadership role in promoting patient safety, there is still no standard monitor for the target orga of general anesthesia: the brain. The lack of reliable neurophysiologic monitoring can result in patient complications because of insufficient anesthesia (e.g., awareness and post- traumatic stress disorder) as well as excessive anesthesia (e.g., delayed emergence, delirium, neurotoxicity). A number of commercially-available brain monitors are currently used in the operating room, but such devices have shown limited utility and are often based on proprietary or empirical algorithms. Recent advances in neurobiology herald the possibility of a more sophisticated era of brain monitoring and improved patient safety. What is needed is the identification of measurable neurophysiological features of general anesthesia that are informed by the neurobiology of consciousness. We have gathered compelling data in human surgical patients that frontal-to-parietal connectivity in the brain is suppressed by all major classes of anesthetics. However, important questions remain regarding the measurement of information transfer in the brain, the underlying neural mechanisms of this suppressed connectivity and the clinical relevance of the findings. The objective for this application is a deeper understanding of the neurobiological principles of cortical connectivity patterns during consciousness and anesthesia as well as the relevance of such patterns for clinical care. We will achieve this objective by conducting innovative studies with computational brain network models, mechanistic experiments in the non-human primate brain, and a clinical study of surgical patients throughout the perioperative period. These studies will have a positive impact by advancing the neurobiology of anesthetic mechanisms, advancing network science in general, and making a key translational step toward novel brain monitoring strategies for surgical and critical care patients.