Beyond the label “major depressive disorder” - detailed characterization of study population matters for EEG-biomarker research
Introduction: Major Depressive Disorder (MDD) is a prevalent, multi-faceted psychiatric disorder influenced by a plethora of physiological and environmental factors. Neuroimaging biomarkers such as diagnosis support systems based on electroencephalography (EEG) recordings have the potential to subst...
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| Main Authors: | , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
17 June 2025
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| In: |
Frontiers in neuroscience
Year: 2025, Volume: 19, Pages: 1-14 |
| ISSN: | 1662-453X |
| DOI: | 10.3389/fnins.2025.1595221 |
| Online Access: | Verlag, kostenfrei, Volltext: https://doi.org/10.3389/fnins.2025.1595221 Verlag, kostenfrei, Volltext: https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2025.1595221/full 
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| Author Notes: | Roman Mähler and Alexandra Reichenbach |
| Summary: | Introduction: Major Depressive Disorder (MDD) is a prevalent, multi-faceted psychiatric disorder influenced by a plethora of physiological and environmental factors. Neuroimaging biomarkers such as diagnosis support systems based on electroencephalography (EEG) recordings have the potential to substantially improve its diagnostic procedure. Research on these biomarkers, however, provides inconsistent findings regarding the robustness of specific markers. One potential source of these contradictions that is frequently neglected may arise from the variability in study populations. Methods: This study systematically reviews 66 original studies from the last 5 years that investigate resting-state EEG-biomarker for MDD detection or diagnosis. The study populations are compared regarding demographic factors, diagnostic procedures and medication, as well as neuropsychological characteristics. Furthermore, we investigate the impact these factors have on the biomarkers, if they were included in the analysis. Finally, we provide further insights into the impact of diagnostic choices and the heterogeneity of a study population based on exploratory analyses in two publicly available data sets. Results: We find indeed a large variability in the study populations with respect to all factors included in the review. Furthermore, these factors are often neglected in analyses even though the studies that include them tend to find effects. Discussion: In light of the variability in diagnostic procedures and heterogeneity in neuropsychological characteristics of the study populations, we advocate for more differentiated target variables in biomarker research then simply MDD and healthy control. Furthermore, the study populations need to be more extensively described and analyses need to include this information in order to provide comparable findings. |
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| Item Description: | Veröffentlicht: 17. Juni 2025 Gesehen am 30.10.2025 |
| Physical Description: | Online Resource |
| ISSN: | 1662-453X |
| DOI: | 10.3389/fnins.2025.1595221 |