Characterization of the non-stationary nature of steady-state visual evoked potentials using echo state networks

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• dc.contributor.author Ibáñez Soria, David, 1983-
• dc.contributor.author Soria Frisch, Aureli
• dc.contributor.author García Ojalvo, Jordi
• dc.contributor.author Ruffini, Giulio
• dc.date.accessioned 2019-09-10T14:10:03Z
• dc.date.available 2019-09-10T14:10:03Z
• dc.date.issued 2019
• dc.description.abstract State Visual Evoked Potentials (SSVEPs) arise from a resonance phenomenon in the visual cortex that is produced by a repetitive visual stimulus. SSVEPs have long been considered a steady-state response resulting from purely oscillatory components phase locked with the stimulation source, matching the stimulation frequency and its harmonics. Here we explore the dynamical character of the SSVEP response by proposing a novel non-stationary methodology for SSVEP detection based on an ensemble of Echo State Networks (ESN). The performance of this dynamical approach is compared to stationary canonical correlation analysis (CCA) for the detection of 6 visual stimulation frequencies ranging from 12 to 22 Hz. ESN-based methodology outperformed CCA, achieving an average information transfer rate of 47 bits/minute when simulating a BCI system of 6 degrees of freedom. However, for some subjects and stimulation frequencies the detection accuracy of CCA exceeds that of ESN. The comparison suggests that each methodology captures different features of the SSVEP response: while CCA captures purely stationary patterns, the ESN-based approach presented here is capable of detecting the non-stationary nature of the SSVEP.
• dc.description.sponsorship This work was partly supported by the European Commission through the STIPED project under the Horizon 2020 Program (H2020, Grant agreement number 731827) and the AsTeRICS project under the 7th Framework Program (FP7, Grant agreement number 247730), the ICREA Academia program and the Spanish Ministry of Economy and Competitiveness and FEDER (project FIS2015-66503-C3-1-P and Maria de Maeztu Programme for Units of Excellence in R&D, MDM-2014-0370). The funder, Starlab, provided support in the form of salaries for authors DIS, ASF and GR, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section. Co-author GR is employed by Neuroelectrics Corporation. Neuroelectrics Barcelona provided support in the form of salaries for GR but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.
• dc.format.mimetype application/pdf
• dc.identifier.citation Ibáñez-Soria D, Soria-Frisch A, Garcia-Ojalvo J, Ruffini G. Characterization of the non-stationary nature of steady-state visual evoked potentials using echo state networks. PLoS One. 2019;14(7):e0218771. DOI: 10.1371/journal.pone.0218771
• dc.identifier.doi http://dx.doi.org/10.1371/journal.pone.0218771
• dc.identifier.issn 1932-6203
• dc.identifier.uri http://hdl.handle.net/10230/42259
• dc.language.iso eng
• dc.publisher Public Library of Science (PLoS)
• dc.relation.ispartof PLoS One. 2019;14(7):e0218771
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/731827
• dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/247730
• dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/FIS2015-66503-C3-1-P
• dc.rights © 2019 Ibáñez-Soria et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword Electroencephalography
• dc.subject.keyword Functional electrical stimulation
• dc.subject.keyword Bandpass filters
• dc.subject.keyword Operator theory
• dc.subject.keyword Man-computer interface
• dc.subject.keyword Vision
• dc.subject.keyword Dynamical systems
• dc.subject.keyword Evoked potentials
• dc.title Characterization of the non-stationary nature of steady-state visual evoked potentials using echo state networks
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion