Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/105843
Title: A multimodal approach to analysis of steady state visually evoked potentials
Authors: Vij, Nikhil
Zuobin, Wu
Bjornsdotter, Malin
Dauwels, Justin
Vialatte, François-Benoît
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2013
Source: Vij, 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.
Conference: IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (2013 : Singapore)
Abstract: Steady 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.
URI: https://hdl.handle.net/10356/105843
http://hdl.handle.net/10220/17967
DOI: 10.1109/CIBCB.2013.6595406
Schools: School of Electrical and Electronic Engineering 
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Conference Papers

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