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Parkinson's disease classification using optimized attention-based deep learning from EEG signals with interpretable sub-band topography.

Overview

Authors: Khosro Rezaee1, Hossein Ghayoumi Zadeh2, Ali Fayazi2
  1. Department of Biomedical Engineering, Meybod University, Meybod, Iran
  2. Department of Electrical Engineering, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran
Institutions: Vali Asr University of Rafsanjan (Iran)
Journal: Brain informatics, volume 13, issue 1, article 29
Dates: received 3 August 2025; accepted 22 June 2026; published online 1 July 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1186/s40708-026-00317-x · PMID 42384288 · PMCID PMC13337974 · OpenAlex W7166869136
Open access: gold, a free copy (OpenAlex)
Status: code on request
Categories: EEG (modality), Parkinson's (population), clinical / translational (subfield)
Methods: Spectral & time-frequency, Statistics, Smoothing, state filtering, decompositions, Machine learning, Connectivity, Preprocessing, Graphs, Complexity
Keywords: Parkinson disease, Electroencephalography, Deep learning, Early diagnosis, Attention mechanism, Optimization algorithm
Topic: EEG and Brain-Computer Interfaces (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Citations: not cited yet (Europe PMC); 33 references in the paper

Abstract

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Code

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Read it in the paper: doi.org/10.1186/s40708-026-00317-x.

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Data

Datasets cited

Data availability statement

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Read it in the paper: doi.org/10.1186/s40708-026-00317-x.

Versions

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Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 3 authors, 6 keywords, 33 references.

Cite

This paper

Rezaee, K., Ghayoumi Zadeh, H., & Fayazi, A. (2026). Parkinson's disease classification using optimized attention-based deep learning from EEG signals with interpretable sub-band topography. Brain informatics, 13(1), 29. https://doi.org/10.1186/s40708-026-00317-x

BibTeX

@article{rezaee2026parkinson,
author = {Rezaee, Khosro and Ghayoumi Zadeh, Hossein and Fayazi, Ali},
title = {{Parkinson's disease classification using optimized attention-based deep learning from EEG signals with interpretable sub-band topography}},
journal = {Brain informatics},
year = {2026},
month = jul,
volume = {13},
number = {1},
pages = {29},
publisher = {Springer},
issn = {2198-4018},
doi = {10.1186/s40708-026-00317-x},
url = {https://doi.org/10.1186/s40708-026-00317-x},
pmid = {42384288},
pmcid = {PMC13337974}
}

RIS

TY - JOUR
AU - Rezaee, Khosro
AU - Ghayoumi Zadeh, Hossein
AU - Fayazi, Ali
TI - Parkinson's disease classification using optimized attention-based deep learning from EEG signals with interpretable sub-band topography
T2 - Brain informatics
J2 - Brain Inform
PY - 2026
DA - 2026/07/01
VL - 13
IS - 1
SP - 29
SN - 2198-4018
PB - Springer
DO - 10.1186/s40708-026-00317-x
UR - https://doi.org/10.1186/s40708-026-00317-x
LA - en
ER -

CSL-JSON

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