| Autor: |
Xinyu Liu, Haoran Zhang, Yi Cui, Tong Zhao, Bin Wang, Xiaomeng Xie, Sixiang Liang, Sha Sha, Yuxiang Yan, Xixi Zhao, Ling Zhang |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
Frontiers in Neuroscience, Vol 18 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
1662-453X |
| DOI: |
10.3389/fnins.2024.1362111 |
| Popis: |
BackgroundMajor Depressive Disorder (MDD) is a pervasive mental health issue with significant diagnostic challenges. Electroencephalography (EEG) offers a non-invasive window into the neural dynamics associated with MDD, yet the diagnostic efficacy is contingent upon the appropriate selection of EEG features and brain regions.MethodsIn this study, resting-state EEG signals from both eyes-closed and eyes-open conditions were analyzed. We examined band power across various brain regions, assessed the asymmetry of band power between the hemispheres, and integrated these features with clinical characteristics of MDD into a diagnostic regression model.ResultsRegression analysis found significant predictors of MDD to be beta2 (16–24 Hz) power in the Prefrontal Cortex (PFC) with eyes open (B = 20.092, p = 0.011), beta3 (24–40 Hz) power in the Medial Occipital Cortex (MOC) (B = −12.050, p |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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