Reduced alpha power predicts recurrence risk in major depressive disorder

Background A high proportion of individuals with major depressive disorder (MDD) develop recurrent episodes. A better understanding and the identification of markers of recurrence risk are needed to develop prophylactic treatments and to support treatment decisions. Electroencephalography (EEG) is a scalable approach to identifying potential markers. Alpha band (8-13Hz) power and frontal alpha asymmetry (FAA) have been implicated in the pathophysiology of depression, however prospective studies of recurrence risk are sparse. Here, we investigated frontal alpha power and FAA in remitted MDD patients, to assess their potential as predictors of future depressive episodes. Methods In total, 84 participants (n = 53 medication-free remitted MDD, n = 31 control participants with no family history of MDD) completed resting EEG testing. Remitted MDD patients were followed up clinically to determine recurrence over 14 months. Resting frontal alpha power and FAA were compared between groups (controls, stable remission, subclinical symptoms, recurrent episode) and binary logistic regression models were used to predict recurrence risk in remitted MDD patients. Results Patients who developed a recurring episode showed reduced frontal alpha power at baseline compared to controls and patients who remained in stable remission. No group effect was found for FAA. When combining clinical predictors with frontal alpha power, prediction accuracy for recurring episodes was 88%. Conclusions This study demonstrates that reduced frontal alpha power has the potential to be further developed as a marker for recurrence risk in MDD, and could contribute to recurrence risk prediction models. This calls for larger studies using cross-validated prediction modelling techniques.

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Publication Details

Journal
Neuroimage Reports
Published
2026-05-22
DOI
https://doi.org/10.1016/j.ynirp.2026.100357
Primary Topic
Neural and Behavioral Psychology Studies
Type
article
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article

Reduced alpha power predicts recurrence risk in major depressive disorder

Jennifer A. Gethin, Gráinne McLoughlin, Amy Tong, Wael El-Deredy et al.
Neuroimage Reports
Neural and Behavioral Psychology Studies
article

Reduced alpha power predicts recurrence risk in major depressive disorder

Jennifer A. Gethin, Gráinne McLoughlin, Amy Tong, Wael El-Deredy, Jason Palmer, Roland Zahn
article en

Abstract

Background A high proportion of individuals with major depressive disorder (MDD) develop recurrent episodes. A better understanding and the identification of markers of recurrence risk are needed to develop prophylactic treatments and to support treatment decisions. Electroencephalography (EEG) is a scalable approach to identifying potential markers. Alpha band (8-13Hz) power and frontal alpha asymmetry (FAA) have been implicated in the pathophysiology of depression, however prospective studies of recurrence risk are sparse. Here, we investigated frontal alpha power and FAA in remitted MDD patients, to assess their potential as predictors of future depressive episodes. Methods In total, 84 participants (n = 53 medication-free remitted MDD, n = 31 control participants with no family history of MDD) completed resting EEG testing. Remitted MDD patients were followed up clinically to determine recurrence over 14 months. Resting frontal alpha power and FAA were compared between groups (controls, stable remission, subclinical symptoms, recurrent episode) and binary logistic regression models were used to predict recurrence risk in remitted MDD patients. Results Patients who developed a recurring episode showed reduced frontal alpha power at baseline compared to controls and patients who remained in stable remission. No group effect was found for FAA. When combining clinical predictors with frontal alpha power, prediction accuracy for recurring episodes was 88%. Conclusions This study demonstrates that reduced frontal alpha power has the potential to be further developed as a marker for recurrence risk in MDD, and could contribute to recurrence risk prediction models. This calls for larger studies using cross-validated prediction modelling techniques.

Neuroimage ReportsVol. 6(2)
West Virginia University (US), King's College London (GB), South London and Maudsley NHS Foundation Trust (GB), Manchester Academic Health Science Centre (GB), University of Valparaíso (CL)
Good health and well-being
Openalex Percentile: Top 5%
Neural and Behavioral Psychology Studies
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