From index to insight: clinical perspectives on electroencephalographic spectrogram-guided anesthesia—a narrative review

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Authors: Akira Mukai, Jen-Ting Yang, Shao‐Chun Wu, Tzu-Chun Wang, F. Lin, Chun-Yu Wu
Cited by: 1
References: 94

Abstract

Processed electroencephalogram (EEG) indices, such as the Bispectral Index, have markedly influenced anesthesia practice as they translate brain activity into simple numerical indices. Nevertheless, as the manufacturing algorithms are not disclosed, the underlying neurophysiology remains obscured. Additionally, these indices are often affected by electromyographic contamination, pharmacological variability, and patient-specific EEG heterogeneity. In contrast, an EEG spectrogram, or density spectral array, preserves the frequency- and time-resolved structures of cortical oscillations. This information is presented in a form that is both physiologically meaningful and clinically interpretable. In this review, we trace the evolution of anesthesia from an index-based to a spectrogram-guided approach, and summarize the clinical rationale for adopting the latter. Key applications of this approach include the use of frontal alpha power as a biomarker of cortical stability and postoperative brain health, the identification of nociceptive arousal through alpha dropout and beta or delta arousal patterns, and individualized titration of multimodal or age-specific anesthetic management. Although current devices lack standardized quantitative alpha metrics and have limited sensitivity for low-frequency brain wave components, structured EEG education programs have proven to be effective in terms of fostering spectrogram literacy among anesthesiologists. By combining neurophysiological precision with bedside practicality, the EEG spectrogram represents a pivotal advance toward individualized, mechanism-based, and brain-protective anesthesia, transforming anesthetic monitoring from mere algorithmic abstraction to cortical insight.

Fields of Study & Subjects

Anesthesia and Sedative Agents EEG and Brain-Computer Interfaces Music Therapy and Health

Publication details

Journal / source
Korean Journal of Anesthesiology
Publisher
The Korean Society of Anesthesiologists
Volume
79
Issue
2
Pages
139–151
Publication date
3 February 2026
Language
EN