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Simultaneous EEG and fMRIRecording, Analysis, and Application$
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Markus Ullsperger and Stefan Debener

Print publication date: 2010

Print ISBN-13: 9780195372731

Published to Oxford Scholarship Online: May 2010

DOI: 10.1093/acprof:oso/9780195372731.001.0001

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Parallel EEG-fMRI ICA Decomposition

Parallel EEG-fMRI ICA Decomposition

Chapter:
(p.175) 3.5 Parallel EEG-fMRI ICA Decomposition
Source:
Simultaneous EEG and fMRI
Author(s):

Tom Eichele

Vince D. Calhoun

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780195372731.003.0012

This chapter introduces and applies the concept of parallel spatial and temporal unmixing with group independent component analysis (ICA) for concurrent electroencephalography-functional magnetic resonance imaging (EEG-fMRI). Hemodynamic response function (HRF) deconvolution and single-trial estimation in the fMRI data were employed, and the single-trial weights were used as predictors for the amplitude modulation in the EEG. For illustration, data from a previously published performance-monitoring experiment were analyzed, in order to identify error-preceding activity in the EEG modality. EEG components that displayed such slow trends, and which were coupled to the corresponding fMRI components, are described. Parallel ICA for analysis of concurrent EEG-fMRI on a trial-by-trial basis is a very useful addition to the toolbelt of researchers interested in multimodal integration.

Keywords:   electroencephalography, functional magnetic resonance, independent component analysis, covariation

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