A temporally constrained spatial ICA for separation of seizure bold from FMRI

Min Jing, Saeid Sanei

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Application of spatial Independent Component Analysis (ICA) to functional magnetic resonance imaging (fMRI) subject to the simultaneously recorded electroencephalography (EEG) signals as constraint, has been investigated in this work. In this novel approach, the closeness between the time course of spatial independent components of fMRI and EEG signals during epileptic seizure period is introduced as the constraint to the separation process. The performance of the algorithm has been tested on a set of simultaneous EEG and fMRI data and the results show a more accurate localization of the blood-oxygenated level-dependence (BOLD) regions, better algorithm convergence, and a higher correlation between the time course of spatial components and the seizure EEG signals than the conventional ICA method.
LanguageEnglish
Title of host publicationEuropean Signal Processing Conference (EUSIPCO-2008)
Publication statusPublished - 2008
EventThe 16th European Signal Processing Conference (EUSIPCO 2008) - , Switzerland
Duration: 25 Aug 2008 → …

Conference

ConferenceThe 16th European Signal Processing Conference (EUSIPCO 2008)
CountrySwitzerland
Period25/08/08 → …

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seizure
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Cite this

Jing, M., & Sanei, S. (2008). A temporally constrained spatial ICA for separation of seizure bold from FMRI. In European Signal Processing Conference (EUSIPCO-2008)
Jing, Min ; Sanei, Saeid. / A temporally constrained spatial ICA for separation of seizure bold from FMRI. European Signal Processing Conference (EUSIPCO-2008). 2008.
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title = "A temporally constrained spatial ICA for separation of seizure bold from FMRI",
abstract = "Application of spatial Independent Component Analysis (ICA) to functional magnetic resonance imaging (fMRI) subject to the simultaneously recorded electroencephalography (EEG) signals as constraint, has been investigated in this work. In this novel approach, the closeness between the time course of spatial independent components of fMRI and EEG signals during epileptic seizure period is introduced as the constraint to the separation process. The performance of the algorithm has been tested on a set of simultaneous EEG and fMRI data and the results show a more accurate localization of the blood-oxygenated level-dependence (BOLD) regions, better algorithm convergence, and a higher correlation between the time course of spatial components and the seizure EEG signals than the conventional ICA method.",
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Jing, M & Sanei, S 2008, A temporally constrained spatial ICA for separation of seizure bold from FMRI. in European Signal Processing Conference (EUSIPCO-2008). The 16th European Signal Processing Conference (EUSIPCO 2008), Switzerland, 25/08/08.

A temporally constrained spatial ICA for separation of seizure bold from FMRI. / Jing, Min; Sanei, Saeid.

European Signal Processing Conference (EUSIPCO-2008). 2008.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - A temporally constrained spatial ICA for separation of seizure bold from FMRI

AU - Jing, Min

AU - Sanei, Saeid

PY - 2008

Y1 - 2008

N2 - Application of spatial Independent Component Analysis (ICA) to functional magnetic resonance imaging (fMRI) subject to the simultaneously recorded electroencephalography (EEG) signals as constraint, has been investigated in this work. In this novel approach, the closeness between the time course of spatial independent components of fMRI and EEG signals during epileptic seizure period is introduced as the constraint to the separation process. The performance of the algorithm has been tested on a set of simultaneous EEG and fMRI data and the results show a more accurate localization of the blood-oxygenated level-dependence (BOLD) regions, better algorithm convergence, and a higher correlation between the time course of spatial components and the seizure EEG signals than the conventional ICA method.

AB - Application of spatial Independent Component Analysis (ICA) to functional magnetic resonance imaging (fMRI) subject to the simultaneously recorded electroencephalography (EEG) signals as constraint, has been investigated in this work. In this novel approach, the closeness between the time course of spatial independent components of fMRI and EEG signals during epileptic seizure period is introduced as the constraint to the separation process. The performance of the algorithm has been tested on a set of simultaneous EEG and fMRI data and the results show a more accurate localization of the blood-oxygenated level-dependence (BOLD) regions, better algorithm convergence, and a higher correlation between the time course of spatial components and the seizure EEG signals than the conventional ICA method.

M3 - Conference contribution

BT - European Signal Processing Conference (EUSIPCO-2008)

ER -

Jing M, Sanei S. A temporally constrained spatial ICA for separation of seizure bold from FMRI. In European Signal Processing Conference (EUSIPCO-2008). 2008