Spatiotemporal Changes of Neuronal Responses in the Primary Somatosensory Cortex to Noxious Tail Stimulation in Awake and Pentobarbital-Anesthetized Rats

Understanding the Effects of Anesthesia on Cortical Electrophysiological Recordings: A Scoping Review

General anesthesia in animal experiments is an ethical must and is required for all the procedures that are likely to cause more than slight or momentary pain. As anesthetics are known to deeply affect experimental findings, including electrophysiological recordings of brain activity, understanding their mechanism of action is of paramount importance. It is widely recognized that the depth and type of anesthesia introduce significant bias in electrophysiological measurements by affecting the shape of both spontaneous and evoked signals, e.g., modifying their latency and relative amplitude. Therefore, for a given experimental protocol, it is relevant to identify the appropriate anesthetic, to minimize the impact on neuronal circuits and related signals under investigation. This review focuses on the effect of different anesthetics on cortical electrical recordings, examining their molecular mechanisms of action, their influence on neuronal microcircuits and, consequently, their impact on cortical measurements.

Mechanisms underlying brain monitoring during anesthesia: limitations, possible improvements, and perspectives

Currently, anesthesiologists use clinical parameters to directly measure the depth of anesthesia (DoA). This clinical standard of monitoring is often combined with brain monitoring for better assessment of the hypnotic component of anesthesia. Brain monitoring devices provide indices allowing for an immediate assessment of the impact of anesthetics on consciousness. However, questions remain regarding the mechanisms underpinning these indices of hypnosis. By briefly describing current knowledge of the brain's electrical activity during general anesthesia, as well as the operating principles of DoA monitors, the aim of this work is to simplify our understanding of the mathematical processes that allow for translation of complex patterns of brain electrical activity into dimensionless indices. This is a challenging task because mathematical concepts appear remote from clinical practice. Moreover, most DoA algorithms are proprietary algorithms and the difficulty of exploring the inner workings of mathematical models represents an obstacle to accurate simplification. The limitations of current DoA monitors — and the possibility for improvement — as well as perspectives on brain monitoring derived from recent research on corticocortical connectivity and communication are also discussed.