dc.contributor.authorVij, Nikhil
dc.contributor.authorZuobin, Wu
dc.contributor.authorBjornsdotter, Malin
dc.contributor.authorDauwels, Justin
dc.contributor.authorVialatte, François-Benoît
dc.date.accessioned2013-12-02T07:22:09Z
dc.date.available2013-12-02T07:22:09Z
dc.date.copyright2013en_US
dc.date.issued2013
dc.identifier.citationVij, N., Wu, Z., Bjornsdotter, M., Dauwels, J., & Vialatte, F.-B. (2013). A multimodal approach to analysis of steady state visually evoked potentials. 2013 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 183-188.en_US
dc.identifier.urihttp://hdl.handle.net/10220/17967
dc.description.abstractSteady state visually evoked potentials (SSVEPs), recorded from the central nervous system of humans using electroencephalography (EEG) in response to visual stimuli, have recently gained attention in cognitive and clinical neuroscience [1]. Here, we fuse EEG SSVEPs with recordings from functional magnetic resonance imaging data (fMRI) utilizing the millisecond temporal resolution of the former and the excellent spatial resolution of the latter. In particular, we propose a spatio-frequency EEG/fMRI fusion framework to recover the frequency content from the EEG and spatial information from the fMRI to enhance our understanding of SSVEPs. Notably, we consider fused analysis of fMRI and EEG data collected independently. We demonstrate that the proposed approach is a practical data-driven method to achieve spatio-frequency fusion of EEG and fMRI SSVEP responses.en_US
dc.language.isoenen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering
dc.titleA multimodal approach to analysis of steady state visually evoked potentialsen_US
dc.typeConference Paper
dc.contributor.conferenceIEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (2013 : Singapore)en_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.identifier.doihttp://dx.doi.org/10.1109/CIBCB.2013.6595406


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