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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.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.issn 1932-6203
dc.identifier.uri http://hdl.handle.net/10230/42259
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.language.iso eng
dc.publisher Public Library of Science (PLoS)
dc.relation.ispartof PLoS One. 2019; 14(7):e0218771
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.uri http://creativecommons.org/licenses/by/4.0/
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.identifier.doi http://dx.doi.org/10.1371/journal.pone.0218771
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.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.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion


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