ArticleScientific reports2023
Brainwave activities reflecting depressed mood: a pilot study.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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.
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Who cites it
3 citing papers in PubMed.
- Correlation of physical activity with positive and negative affect and frontal lateralization in college students with depressive symptoms.Scientific reports · 2026Article
- Portable electroencephalography in early detection of depression: Progress and future directions.World journal of psychiatry · 2025Review
- Resting-state EEG features modulated by depressive state in healthy individuals: insights from theta PSD, theta-beta ratio, frontal-parietal PLV, and sLORETA.Frontiers in human neuroscience · 2024Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Early diagnosis and treatment of depression are desirable but currently difficult due to a lack of established biomarkers. Although biomarkers for depression based on electroencephalogram (EEG) data have long been explored, most existing methods are thought to capture cognitive decline caused by depression and are unsuccessful in detecting signs of depression. Here we report that some brainwave activities involving phase resetting reflect the depressed mood at the time, which can be easily monitored by measuring the resting EEG with eyes closed for 1 min with a few electrodes. We instructed 10 participants (nine healthy and one diagnosed with depression, aged 18-34) to record their EEG for 14-26 days. We found that indicators of depressed mood were correlated with the occurrence frequency of EEG phase resetting. For most participants, the correlation coefficients swung systematically between large positive and large negative values with respect to EEG frequency; however, the frequencies at which they were maximum or minimum differed among participants. Although this study is in the pilot phase and needs further experimentation, the results are expected to lead to innovative biomarkers for early detection of depression and may contribute to a better understanding and treatment of depression.
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