Neural Correlates of Anesthesia in Newborn Mice and Humans

Overview

Journal Front Neural Circuits

Date 2019 Jun 14

PMID 31191258

Citations 14

Authors

Mattia Chini

Sabine Gretenkord

Johanna K Kostka

Jastyn A Popplau

Laura Cornelissen

Charles B Berde

Ileana L Hanganu-Opatz

Sebastian H Bitzenhofer

Affiliations

Soon will be listed here.

Abstract

Monitoring the hypnotic component of anesthesia during surgeries is critical to prevent intraoperative awareness and reduce adverse side effects. For this purpose, electroencephalographic (EEG) methods complementing measures of autonomic functions and behavioral responses are in use in clinical practice. However, in human neonates and infants existing methods may be unreliable and the correlation between brain activity and anesthetic depth is still poorly understood. Here, we characterized the effects of different anesthetics on brain activity in neonatal mice and developed machine learning approaches to identify electrophysiological features predicting inspired or end-tidal anesthetic concentration as a proxy for anesthetic depth. We show that similar features from EEG recordings can be applied to predict anesthetic concentration in neonatal mice and humans. These results might support a novel strategy to monitor anesthetic depth in human newborns.

Citing Articles

Generation and propagation of bursts of activity in the developing basal ganglia.

Klavinskis-Whiting S, Bitzenhofer S, Hanganu-Opatz I, Ellender T Cereb Cortex. 2023; 33(20):10595-10613.

PMID: 37615347 PMC: 10560579. DOI: 10.1093/cercor/bhad307.

Use of artificial intelligence in paediatric anaesthesia: a systematic review.

Antel R, Sahlas E, Gore G, Ingelmo P BJA Open. 2023; 5:100125.

PMID: 37587993 PMC: 10430814. DOI: 10.1016/j.bjao.2023.100125.

Activity in developing prefrontal cortex is shaped by sleep and sensory experience.

Gomez L, Dooley J, Blumberg M Elife. 2023; 12.

PMID: 36745108 PMC: 9901933. DOI: 10.7554/eLife.82103.

Network instability dynamics drive a transient bursting period in the developing hippocampus in vivo.

Graf J, Rahmati V, Majoros M, Witte O, Geis C, Kiebel S Elife. 2022; 11.

PMID: 36534089 PMC: 9762703. DOI: 10.7554/eLife.82756.

Machine learning reveals interhemispheric somatosensory coherence as indicator of anesthetic depth.

Schmidt D, English G, Gent T, Yanik M, von der Behrens W Front Neuroinform. 2022; 16:971231.

PMID: 36172256 PMC: 9510780. DOI: 10.3389/fninf.2022.971231.

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