A self-supervised reconstruction framework for segment-level detection of task-induced deviations in multi-channel EEG.

Saavedra LA, Quintero-Rincón A, Batatia H

DOI: 10.1371/journal.pone.0361586
Published: 2026
Container: PloS one
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1371/journal.pone.0361586,
  title = {A self-supervised reconstruction framework for segment-level detection of task-induced deviations in multi-channel EEG.},
  author = {Saavedra LA and Quintero-Rincón A and Batatia H},
  year = {2026},
  journal = {PloS one},
  doi = {10.1371/journal.pone.0361586},
  url = {https://doi.org/10.1371/journal.pone.0361586}
}

RIS

TY  - JOUR
TI  - A self-supervised reconstruction framework for segment-level detection of task-induced deviations in multi-channel EEG.
AU  - Saavedra LA
AU  - Quintero-Rincón A
AU  - Batatia H
PY  - 2026
JO  - PloS one
DO  - 10.1371/journal.pone.0361586
UR  - https://doi.org/10.1371/journal.pone.0361586
ER  -

APA

LA, S., A, Q., & H, B. (2026). A self-supervised reconstruction framework for segment-level detection of task-induced deviations in multi-channel EEG.. PloS one. https://doi.org/10.1371/journal.pone.0361586

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pubmed · retrieved 2026-11-10T10:56:22.090Z