Using deep learning to decode abnormal brain neural activity in MDD from single-trial EEG signals

Mengmeng Liu, Jianling Tan, Yuhao Jiang, Yin Tian

Open source

DOI: 10.1080/27706710.2022.2075242
Published: 2022-05-26
Container: Brain-Apparatus Communication: A Journal of Bacomics
Publisher: Informa UK Limited
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1080/27706710.2022.2075242,
  title = {Using deep learning to decode abnormal brain neural activity in MDD from single-trial EEG signals},
  author = {Mengmeng Liu and Jianling Tan and Yuhao Jiang and Yin Tian},
  year = {2022},
  journal = {Brain-Apparatus Communication: A Journal of Bacomics},
  doi = {10.1080/27706710.2022.2075242},
  url = {https://doi.org/10.1080/27706710.2022.2075242}
}

RIS

TY  - JOUR
TI  - Using deep learning to decode abnormal brain neural activity in MDD from single-trial EEG signals
AU  - Mengmeng Liu
AU  - Jianling Tan
AU  - Yuhao Jiang
AU  - Yin Tian
PY  - 2022
JO  - Brain-Apparatus Communication: A Journal of Bacomics
DO  - 10.1080/27706710.2022.2075242
UR  - https://doi.org/10.1080/27706710.2022.2075242
ER  -

APA

Liu, M., Tan, J., Jiang, Y., & Tian, Y. (2022). Using deep learning to decode abnormal brain neural activity in MDD from single-trial EEG signals. Brain-Apparatus Communication: A Journal of Bacomics. https://doi.org/10.1080/27706710.2022.2075242

Source records

crossref · retrieved 2026-11-10T15:07:55.641Z