Probabilistic and explainable modeling of Phase–Phase Cross-Frequency Coupling patterns in EEG. Application to dyslexia diagnosis
| dc.centro | E.T.S.I. Telecomunicación | es_ES |
| dc.contributor.author | Castillo-Barnes, Diego | |
| dc.contributor.author | Gallego-Molina, Nicolás J. | |
| dc.contributor.author | Formoso, Marco A. | |
| dc.contributor.author | Ortiz-García, Andrés | |
| dc.contributor.author | Figueiredo, Patrícia | |
| dc.contributor.author | Luque-Vilaseca, Juan Luis | |
| dc.date.accessioned | 2024-10-24T11:25:03Z | |
| dc.date.available | 2024-10-24T11:25:03Z | |
| dc.date.issued | 2024 | |
| dc.departamento | Ingeniería de Comunicaciones | |
| dc.description.abstract | This work explores the intricate neural dynamics associated with dyslexia through the lens of Cross-Frequency Coupling (CFC) analysis applied to electroencephalography (EEG) signals evaluated from 48 seven-year-old Spanish readers from the LEEDUCA research platform. The analysis focuses on CFS (Cross-Frequency phase Synchronization) maps, capturing the interaction between different frequency bands during low-level auditory processing stimuli. Then, making use of Gaussian Mixture Models (GMMs), CFS activations are quantified and classified, offering a compressed representation of EEG activation maps. The study unveils promising results specially at the Theta-Gamma coupling (Area Under the Curve = 0.821), demonstrating the method’s sensitivity to dyslexia-related neural patterns and highlighting potential applications in the early identification of dyslexic individuals. | es_ES |
| dc.description.sponsorship | Funding for open access charge: Universidad de Málaga / CBUA. This research is part of the PID2022-137461NB-C32 funded by MICIU/AEI/10.13039/501100011033 and by ERDF/EU. Work by D.C.-B. is part of the grant FJC2021-048082-I funded by MICIU/AEI/10.13039/501100011033 and by European Union NextGenerationEU/PRTR. M.-A.F. grant PRE2019087350 funded by MICIU/AEI/10.13039/501100011033 by “ESF Investing in your future”. LARSyS funding (DOI: 10.54499/LA/P/0083/2020, 10.54499/UIDP/50009/2020, and the 10.54499/UIDB/50009/2020). | es_ES |
| dc.identifier.citation | Diego Castillo-Barnes, Nicolás J. Gallego-Molina, Marco A. Formoso, Andrés Ortiz, Patrícia Figueiredo, Juan L. Luque, Probabilistic and explainable modeling of Phase–Phase Cross-Frequency Coupling patterns in EEG. Application to dyslexia diagnosis, Biocybernetics and Biomedical Engineering, Volume 44, Issue 4, 2024, Pages 814-823, ISSN 0208-5216, https://doi.org/10.1016/j.bbe.2024.09.003. (https://www.sciencedirect.com/science/article/pii/S0208521624000688) | es_ES |
| dc.identifier.doi | https://doi.org/10.1016/j.bbe.2024.09.003 | |
| dc.identifier.uri | https://hdl.handle.net/10630/34896 | |
| dc.language.iso | eng | es_ES |
| dc.publisher | Elsevier | es_ES |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
| dc.rights.accessRights | open access | es_ES |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
| dc.subject | Dislexia | es_ES |
| dc.subject | Procesamiento de señales | es_ES |
| dc.subject.other | Mixture models | es_ES |
| dc.subject.other | Cross-Frequency Coupling | es_ES |
| dc.subject.other | EEG | es_ES |
| dc.subject.other | Signal processing | es_ES |
| dc.subject.other | Explainable machine learning | es_ES |
| dc.subject.other | Dyslexia | es_ES |
| dc.title | Probabilistic and explainable modeling of Phase–Phase Cross-Frequency Coupling patterns in EEG. Application to dyslexia diagnosis | es_ES |
| dc.type | journal article | es_ES |
| dc.type.hasVersion | VoR | es_ES |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 5d9e81fc-5f53-42ea-82c8-809b9defd772 | |
| relation.isAuthorOfPublication | ae01056f-b4bd-452b-9139-f397c289666f | |
| relation.isAuthorOfPublication.latestForDiscovery | 5d9e81fc-5f53-42ea-82c8-809b9defd772 |
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