SSVEP modulation via non-volitional neurofeedback: an in silico proof of concept

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dc.contributor.authorEstiveira, João
dc.contributor.authorSoares, Ernesto
dc.contributor.authorPires, Gabriel
dc.contributor.authorNunes, Urbano J.
dc.contributor.authorSousa, Teresa
dc.contributor.authorRibeiro, Sidarta Tollendal Gomes
dc.contributor.authorCastelo-Branco, Miguel
dc.date.accessioned2024-11-25T17:02:24Z
dc.date.available2024-11-25T17:02:24Z
dc.date.issued2024-11
dc.description.resumoObjective Neuronal oscillatory patterns are believed to underpin multiple cognitive mechanisms. Accordingly, compromised oscillatory dynamics were shown to be associated with neuropsychiatric conditions. Therefore, the possibility of modulating, or controlling, oscillatory components of brain activity as a therapeutic approach has emerged. Typical non-invasive brain-computer interfaces (BCI) based on EEG have been used to decode volitional motor brain signals for interaction with external devices. Here we aimed at feedback through visual stimulation which returns directly back to the visual cortex. Approach Our architecture permits the implementation of feedback control-loops capable of controlling, or at least modulating, visual cortical activity. As this type of neurofeedback depends on early visual cortical activity, mainly driven by external stimulation it is called non-volitional or implicit neurofeedback. Because retino-cortical 40-100ms delays in the feedback loop severely degrade controller performance, we implemented a predictive control system, called a Smith-Predictor (SP) controller, which compensates for fixed delays in the control loop by building an internal model of the system to be controlled, in this case the EEG response to stimuli in the visual cortex. Main Results Response models were obtained by analyzing, EEG data (n=8) of experiments using periodically inverting stimuli causing prominent parieto-occipital oscillations, the Steady-State Visual Evoked Potentials (SSVEPs). Averaged subject-specific SSVEPs, and associated retina-cortical delays, were subsequently used to obtain the SP controler's Linear, Time-Invariant (LTI) models of individual responses. The SSVEP models were first successfully validated against the experimental data. When placed in closed loop with the designed SP controller configuration, the SSVEP amplitude level oscillated around several reference values, accounting for inter-individual variability. Significance In silico and in vivo data matched, suggesting model's robustness, paving the way for the experimental validation of this non-volitional neurofeedback system to control the amplitude of abnormal brain oscillations in autism and attention and hyperactivity deficitspt_BR
dc.identifier.citationESTIVEIRA, João; SOARES, Ernesto; PIRES, Gabriel; NUNES, Urbano J.; SOUSA, Teresa; RIBEIRO, Sidarta; CASTELO-BRANCO, Miguel. SSVEP modulation via non-volitional neurofeedback: an in silico proof of concept. Journal of Neural Engineering, [S. l.], nov. 2024. Doi: http://dx.doi.org/10.1088/1741-2552/ad94a5. Disponível em: https://iopscience.iop.org/article/10.1088/1741-2552/ad94a5. Acesso em: 25 nov. 2024pt_BR
dc.identifier.doi10.1088/1741-2552/ad94a5
dc.identifier.urihttps://repositorio.ufrn.br/handle/123456789/60666
dc.languageenpt_BR
dc.publisherIOP Publishingpt_BR
dc.rightsAttribution 3.0 Brazil*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/br/*
dc.subjectBrain-computer interfaces (BCI)pt_BR
dc.subjectNon-volitional neurofeedbackpt_BR
dc.subjectSteady-State Visual Evoked Potentials (SSVEPs)pt_BR
dc.subjectComputer simulationpt_BR
dc.titleSSVEP modulation via non-volitional neurofeedback: an in silico proof of conceptpt_BR
dc.typearticlept_BR

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