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Conference Paper: Joint Source Separation of Simultaneous EEG-fMRI Recording in Two Experimental Conditions Using Common Spatial Patterns

TitleJoint Source Separation of Simultaneous EEG-fMRI Recording in Two Experimental Conditions Using Common Spatial Patterns
Authors
Issue Date2015
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000269
Citation
The 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’15), Milan, Italy, 25-29 August 2015. How to Cite?
AbstractSimultaneous collection of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data has become increasingly popular in neuroscientific studies, because it can provide neural information with both high spatial and temporal resolution. In order to maximally utilize the information contained in simultaneous EEG-fMRI recording, many sophisticated multimodal data-mining methods, such as joint ICA, have been developed. However, these methods normally deal with data recorded in one experimental condition, and they cannot effectively extract information on activities that are distinct in two conditions. In this paper, a new data decomposition method called joint common spatial pattern (jCSP) is proposed. Compared with previous methods, the jCSP method exploits inter-conditional difference in the strength of brain source activities to achieve source separation, and is able to uncover the source activities with the strongest discriminative power. A group analysis based on clustering is further proposed to reveal distinctive jCSP patterns at group level. We applied joint CSP to a simultaneous EEG-fMRI dataset collected from 21 subjects under two different resting-state conditions (eyes-closed and eyes-open). Results show a distinct dynamic pattern shared by EEG alpha power and fMRI signal during eyes-open resting-state.
Persistent Identifierhttp://hdl.handle.net/10722/214830
ISSN

 

DC FieldValueLanguage
dc.contributor.authorTan, A-
dc.contributor.authorFu, Z-
dc.contributor.authorTu, Y-
dc.contributor.authorHung, YS-
dc.contributor.authorZhang, Z-
dc.date.accessioned2015-08-21T11:57:54Z-
dc.date.available2015-08-21T11:57:54Z-
dc.date.issued2015-
dc.identifier.citationThe 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’15), Milan, Italy, 25-29 August 2015.-
dc.identifier.issn1049-3565-
dc.identifier.urihttp://hdl.handle.net/10722/214830-
dc.description.abstractSimultaneous collection of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data has become increasingly popular in neuroscientific studies, because it can provide neural information with both high spatial and temporal resolution. In order to maximally utilize the information contained in simultaneous EEG-fMRI recording, many sophisticated multimodal data-mining methods, such as joint ICA, have been developed. However, these methods normally deal with data recorded in one experimental condition, and they cannot effectively extract information on activities that are distinct in two conditions. In this paper, a new data decomposition method called joint common spatial pattern (jCSP) is proposed. Compared with previous methods, the jCSP method exploits inter-conditional difference in the strength of brain source activities to achieve source separation, and is able to uncover the source activities with the strongest discriminative power. A group analysis based on clustering is further proposed to reveal distinctive jCSP patterns at group level. We applied joint CSP to a simultaneous EEG-fMRI dataset collected from 21 subjects under two different resting-state conditions (eyes-closed and eyes-open). Results show a distinct dynamic pattern shared by EEG alpha power and fMRI signal during eyes-open resting-state.-
dc.languageeng-
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000269-
dc.relation.ispartofIEEE Engineering in Medicine and Biology Society Annual Conference Proceedings-
dc.rightsIEEE Engineering in Medicine and Biology Society. Annual Conference. Proceedings. Copyright © IEEE.-
dc.rights©2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.titleJoint Source Separation of Simultaneous EEG-fMRI Recording in Two Experimental Conditions Using Common Spatial Patterns-
dc.typeConference_Paper-
dc.identifier.emailHung, YS: yshung@hkucc.hku.hk-
dc.identifier.emailZhang, Z: zhangzg@hku.hk-
dc.identifier.authorityHung, YS=rp00220-
dc.identifier.authorityZhang, Z=rp01565-
dc.identifier.hkuros249929-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 151005 - proceedings nyp-

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