Gamma and beta power and the 1/f slope vary across a spectrum of depression severity

Depression is a highly prevalent mental disorder that impacts an individual's functioning, societal productivity, and quality of life. It is associated with disrupted neural activity (e.g., balance of excitation-inhibition) across networks implicated in emotional processing, such as between prefrontal and limbic regions. Gamma and beta activity measured with electroencephalography (EEG) differ between healthy individuals and those with depression, and predict treatment outcomes following pharmacological intervention. However, to date research has focussed on binary comparisons between individuals with a clinical depression diagnosis relative to healthy control populations, providing limited insight into how these measures may shift as a function of illness severity. To establish the utility of EEG measures as potential biomarkers for depression, an improved understanding across the spectrum of symptom profiles is required. Here, we aimed to bridge this gap and investigate changes in beta and gamma power and the 1/f slope in resting-state EEG across a spectrum of mild to severe depression symptom presentations. In line with expectations, we demonstrate graded alterations to gamma and beta power and the 1/f slope across a spectrum of depression severity. Our findings provide critical new insights into the neurophysiological signature of depression symptoms, and highlight the utility of EEG markers to inform future precision psychiatry approaches to more effectively assess and treat depression.

Authors

Institutions

Publication Details

Journal
Translational Psychiatry
Published
2026-07-16
DOI
https://doi.org/10.1038/s41398-026-04268-z
Primary Topic
Treatment of Major Depression
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Gamma and beta power and the 1/f slope vary across a spectrum of depression severity

James P. Coxon, Juliet Hosler, Joshua Hendrikse
Translational Psychiatry
Treatment of Major Depression
article

Gamma and beta power and the 1/f slope vary across a spectrum of depression severity

James P. Coxon, Juliet Hosler, Joshua Hendrikse
article en

Abstract

Depression is a highly prevalent mental disorder that impacts an individual's functioning, societal productivity, and quality of life. It is associated with disrupted neural activity (e.g., balance of excitation-inhibition) across networks implicated in emotional processing, such as between prefrontal and limbic regions. Gamma and beta activity measured with electroencephalography (EEG) differ between healthy individuals and those with depression, and predict treatment outcomes following pharmacological intervention. However, to date research has focussed on binary comparisons between individuals with a clinical depression diagnosis relative to healthy control populations, providing limited insight into how these measures may shift as a function of illness severity. To establish the utility of EEG measures as potential biomarkers for depression, an improved understanding across the spectrum of symptom profiles is required. Here, we aimed to bridge this gap and investigate changes in beta and gamma power and the 1/f slope in resting-state EEG across a spectrum of mild to severe depression symptom presentations. In line with expectations, we demonstrate graded alterations to gamma and beta power and the 1/f slope across a spectrum of depression severity. Our findings provide critical new insights into the neurophysiological signature of depression symptoms, and highlight the utility of EEG markers to inform future precision psychiatry approaches to more effectively assess and treat depression.

Translational Psychiatry
Monash University (AU)
Department of Education and Training, Australian Research Council, Centre of Excellence for Integrative Brain Function, Australian Research Council
Climate action
Openalex Percentile: Top 10%
Treatment of Major Depression
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.