Adolescent depression recognition and symptom prediction based on multi-view EEG network: an exploratory study
Yanli Zhao, Haitao Chen, Xiaoxiao Ma, Xiaoyue Li, Kai Li, Zihao Wei, Jiaqi Song, Yan Chen, Wen Xin, Guimei Yin, Shuping Tan · 2026
Read Adolescent depression recognition and symptom prediction based on multi-view EEG network: an exploratory study by Yanli Zhao, Haitao Chen, Xiaoxiao Ma, Xiaoyue Li, Kai Li, Zihao Wei, Jiaqi Song, Yan Chen, Wen Xin, Guimei Yin, Shuping Tan (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/PMC13472816.txt.
Description
Zhao and colleagues present a 2026 study of an EEG-based network model to recognize depression in adolescents, whose diagnosis now rests on subjective questionnaires. The team recorded resting brain waves from 44 adolescents with major depression and 30 healthy peers. Their model reads the brain as a network and fuses three views of how regions synchronize, using a graph learning method that weighs the views adaptively.
The model's classification was compared head-to-head with machine learning built on the standard questionnaires. The team also explored whether the model's brain network features relate to psychological resilience, the capacity to recover from stress. Small samples mean accuracy must be proven on new groups first.
Catalog record
| CREATOR | Yanli Zhao, Haitao Chen, Xiaoxiao Ma, Xiaoyue Li, Kai Li, Zihao Wei, Jiaqi Song, Yan Chen, Wen Xin, Guimei Yin, Shuping Tan |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 52 KB |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |