ReviewFrontiers in psychiatry2018
Quantitative Electroencephalography in Guiding Treatment of Major Depression.
Review in Frontiers in psychiatry, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 36 citations in OpenAlex.
- Electroencephalographic Parameters Differentiating Melancholic Depression, Non-melancholic Depression, and Healthy Controls. A Systematic Review.Frontiers in psychiatry · 2021Pooled it
- Cortical Connectivity Moderators of Antidepressant vs Placebo Treatment Response in Major Depressive Disorder: Secondary Analysis of a Randomized Clinical Trial.JAMA psychiatry · 2020Trial
- Impaired emotional response inhibition among adolescents with bipolar depression: evidence from event-related potentials and behavioral performance.BMC psychiatry · 2025Article
- Symptom-based depression subtypes: brain dynamic specificity and its association with gene expression profiles.Translational psychiatry · 2025Article
- Editorial: Recent advances on the multimodal search for markers of treatment response in affective disorders: from bench to bedside, volume II.Frontiers in psychiatry · 2025Article
- Quantitative and qualitative electroencephalography in the diagnosis and monitoring of depression. A modern approach to clinical neurophysiology.Frontiers in human neuroscience · 2025Review
- Retrospective analysis of quantitative electroencephalography changes in a dissimulating patient after dying by suicide: A single case report.Frontiers in psychiatry · 2023Article
- Alpha peak activity in resting-state EEG is associated with depressive score.Frontiers in neuroscience · 2023Article
- A review of critical brain oscillations in depression and the efficacy of transcranial magnetic stimulation treatment.Frontiers in psychiatry · 2023Review
- Machine learning in biosignals processing for mental health: A narrative review.Frontiers in psychology · 2022Review
- The Changes of qEEG Approximate Entropy during Test of Variables of Attention as a Predictor of Major Depressive Disorder.Brain sciences · 2020Article
- Baseline Difference in Quantitative Electroencephalography Variables Between Responders and Non-Responders to Low-Frequency Repetitive Transcranial Magnetic Stimulation in Depression.Frontiers in psychiatry · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper reviews significant contributions to the evidence for the use of quantitative electroencephalography features as biomarkers of depression treatment and examines the potential of such technology to guide pharmacotherapy. Frequency band abnormalities such as alpha and theta band abnormalities have shown promise as have combinatorial measures such as cordance (a measure combining alpha and theta power) and the Antidepressant Treatment Response Index in predicting medication treatment response. Nevertheless, studies have been hampered by methodological problems and inconsistencies, and these approaches have ultimately failed to elicit any significant interest in actual clinical practice. More recent machine learning approaches such as the Psychiatric Encephalography Evaluation Registry (PEER) technology and other efforts analyze large datasets to develop variables that may best predict response rather than test a priori hypotheses. PEER is a technology that may go beyond predicting response to a particular antidepressant and help to guide pharmacotherapy.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.