Parallel EEG-fMRI ICA Decomposition

Tom Eichele, Vince D. Calhoun

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

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.

Original languageEnglish (US)
Title of host publicationSimultaneous EEG and fMRI
Subtitle of host publicationRecording, Analysis, and Application
PublisherOxford University Press
Volume9780195372731
ISBN (Electronic)9780199776283
ISBN (Print)9780195372731
DOIs
StatePublished - May 1 2010
Externally publishedYes

Keywords

  • Covariation
  • Electroencephalography
  • Functional magnetic resonance
  • Independent component analysis

ASJC Scopus subject areas

  • Neuroscience(all)

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  • Cite this

    Eichele, T., & Calhoun, V. D. (2010). Parallel EEG-fMRI ICA Decomposition. In Simultaneous EEG and fMRI: Recording, Analysis, and Application (Vol. 9780195372731). Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195372731.003.0012