A multimodal approach to analysis of steady state visually evoked potentials

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 m...

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Main Authors: Vij, Nikhil, Zuobin, Wu, Bjornsdotter, Malin, Dauwels, Justin, Vialatte, François-Benoît
Other Authors: School of Electrical and Electronic Engineering
Format: Conference or Workshop Item
Language:English
Published: 2013
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Online Access:https://hdl.handle.net/10356/105843
http://hdl.handle.net/10220/17967
http://dx.doi.org/10.1109/CIBCB.2013.6595406
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1058432019-12-06T21:59:09Z A multimodal approach to analysis of steady state visually evoked potentials Vij, Nikhil Zuobin, Wu Bjornsdotter, Malin Dauwels, Justin Vialatte, François-Benoît School of Electrical and Electronic Engineering IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (2013 : Singapore) DRNTU::Engineering::Electrical and electronic engineering 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. 2013-12-02T07:22:09Z 2019-12-06T21:59:09Z 2013-12-02T07:22:09Z 2019-12-06T21:59:09Z 2013 2013 Conference Paper 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. https://hdl.handle.net/10356/105843 http://hdl.handle.net/10220/17967 http://dx.doi.org/10.1109/CIBCB.2013.6595406 en
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Vij, Nikhil
Zuobin, Wu
Bjornsdotter, Malin
Dauwels, Justin
Vialatte, François-Benoît
A multimodal approach to analysis of steady state visually evoked potentials
description 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.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Vij, Nikhil
Zuobin, Wu
Bjornsdotter, Malin
Dauwels, Justin
Vialatte, François-Benoît
format Conference or Workshop Item
author Vij, Nikhil
Zuobin, Wu
Bjornsdotter, Malin
Dauwels, Justin
Vialatte, François-Benoît
author_sort Vij, Nikhil
title A multimodal approach to analysis of steady state visually evoked potentials
title_short A multimodal approach to analysis of steady state visually evoked potentials
title_full A multimodal approach to analysis of steady state visually evoked potentials
title_fullStr A multimodal approach to analysis of steady state visually evoked potentials
title_full_unstemmed A multimodal approach to analysis of steady state visually evoked potentials
title_sort multimodal approach to analysis of steady state visually evoked potentials
publishDate 2013
url https://hdl.handle.net/10356/105843
http://hdl.handle.net/10220/17967
http://dx.doi.org/10.1109/CIBCB.2013.6595406
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