Examining associations between fMRI and EEG data using canonical correlation analysis

Nicolle Correa, Yi Ou Li, Tülay Adal, Vince D. Calhoun

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

Abstract

Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) provide complementary information about the brain function. We propose a novel scheme to examine associations between these two modalities using canonical correlation analysis (CCA). Our multimodal canonical correlation analysis (mCCA) scheme utilizes inter-subject covariations to quantitatively link the two modalities and to estimate the spatio-temporal areas of association. We evaluate the performance of mCCA using simulated fMRI- and EEG-like data and note its ability to effectively identify associations across modalities. Also, our experiments on actual data from an auditory oddball task reveals associations of the temporal and motor areas with the N2 and P3 peaks, a finding that is consistent with previous studies. Additionally, we compare the performance of mCCA to the recently introduced joint-ICA technique for estimating spatio-temporal connections from multimodal data and discuss the advantages and limitations of each.

Original languageEnglish (US)
Title of host publication2008 5th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, Proceedings, ISBI
Pages1251-1254
Number of pages4
DOIs
StatePublished - Sep 10 2008
Externally publishedYes
Event2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI - Paris, France
Duration: May 14 2008May 17 2008

Publication series

Name2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI

Other

Other2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI
CountryFrance
CityParis
Period5/14/085/17/08

Keywords

  • Biomedical signal analysis
  • Canonical correlation analysis
  • Electroencephalography
  • Magnetic resonance
  • Multimodal analysis

ASJC Scopus subject areas

  • Biomedical Engineering

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