Calculations of consciousness: electroencephalography analyses to determine anesthetic depth

Purpose of review Electroencephalography (EEG) was introduced into anesthesia practice in the 1990s as a tool to titrate anesthetic depth. However, limitations in current analysis techniques have called into question whether these techniques improve standard of care, or instead call for improved, more ubiquitously applicable measures to assess anesthetic transitions and depth. This review highlights emerging analytical approaches and techniques from neuroscience research that have the potential to better capture anesthetic transitions to provide better measurements of anesthetic depth. Recent findings Since the introduction of electroencephalography, neuroscientists, engineers, mathematicians, and clinicians have all been developing new ways of analyzing continuous electrical signals. Collaborations between these fields have proliferated several analytical techniques that demonstrate how anesthetics affect brain dynamics and conscious transitions. Here, we review techniques in the following categories: network science, integration and information, nonlinear dynamics, and artificial intelligence. Summary Up-and-coming techniques have the potential to better clinically define and characterize altered consciousness time points. Such new techniques used alongside traditional measures have the potential to improve depth of anesthesia measurements and enhance an understanding of how the brain is affected by anesthetic agents. However, new measures will be needed to be tested for robustness in real-world environments and on diverse experimental protocols. Correspondence to Sarah L. Eagleman, PhD, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Grant Building, 300 Pasteur Dr, S288, Palo Alto, CA 94305–5117, USA. Tel: +650 725 5851; fax: +650 725 8544; e-mail: seagle@stanford.edu Copyright © 2018 YEAR Wolters Kluwer Health, Inc. All rights reserved.

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