SynthesisNeuroImage. Clinical2026
Resting-state EEG activity in depression: a systematic review and meta-analysis.
Synthesis in NeuroImage. Clinical, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Brain rhythms of depression: A predictive processing perspective.Trends in neurosciences · 2026Review
- Rethinking EEG biomarkers of brain disorders: a transdiagnostic dimensional view.Translational psychiatry · 2026Review
- Interpretable machine-learning for depression classification based on a three-component EEG marker.Frontiers in computational neuroscience · 2026Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Depression is a highly prevalent and disabling disorder affecting approximately 5% of the adult population worldwide. Despite its impact, the underlying pathophysiology remains insufficiently understood, and current treatments are only partially effective. Understanding electrophysiological correlates of depression offers promise for a better grasp of the underlying brain mechanisms and might even guide novel treatment approaches, including neuromodulation. EEG is particularly attractive for this purpose due to its wide availability, cost-effectiveness, and potential for direct neuromodulatory targeting. We conducted a PROSPERO-registered systematic review in accordance with PRISMA guidelines to assess resting-state EEG activity in adult patients with depression, diagnosed according to DSM-IV/V or ICD-10/11. Included studies reported cross-sectional or correlational data on well-established quantitative EEG measures such as power, cordance, peak frequency, and alpha asymmetry. Semiquantitative analyses using modified albatross plots and meta-analyses were performed. Study quality was assessed with a modified Newcastle-Ottawa Scale. Fifty-two studies met the inclusion criteria. Semiquantitative findings showed a trend for increased low-frequency (delta and theta) and high-frequency (beta and gamma) power, as well as left frontal alpha asymmetry, in depressed patients compared to healthy controls. However, meta-analysis only confirmed a significant increase in beta power. Results regarding disease severity correlations and data on peak alpha frequency and cordance were insufficient for interpretation. Risk of bias across studies was high. Our results support a potential role for increased beta oscillations in depression. These oscillations may reflect disrupted corticolimbic control and reward processing and partially overlap with mechanisms implicated in chronic pain and fatigue. Further investigation is warranted into their potential as a diagnostic tool or even a biomarker, as well as their potential use as a neuromodulatory treatment target.
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Registered trials
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