Abstract
Different imaging modalities are sensitive to different aspects of brain activity, and integrating information from multiple modalities can provide an improved picture of brain dynamics. Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are often integrated since they make up for each other's limitations. FMRI can reveal localized intrinsic networks whose BOLD signals have periods from 100 s to about 10 s. EEG recordings, in contrast, reflect cortical electrical fluctuations with periods up to 20 ms or higher. The following chapter surveys the physiological differences between EEG and fMRI recordings and the implications and results of their integration. EEG-fMRI findings are reviewed in cases where individuals do not participate in an explicit task (e.g. during rest). The results are discussed in the context of different methodological approaches to EEG-fMRI integration, including correlation and GLM-based analysis, and ICA decomposition of group EEG-fMRI datasets. The resulting EEG-fMRI networks capture a broader range of brain dynamics compared to EEG or fMRI alone, and can serve as a reference for studies integrating MEG and fMRI.
Original language | English (US) |
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Title of host publication | Magnetoencephalography |
Subtitle of host publication | From Signals to Dynamic Cortical Networks |
Publisher | Springer-Verlag Berlin Heidelberg |
Pages | 213-235 |
Number of pages | 23 |
Volume | 9783642330452 |
ISBN (Electronic) | 9783642330452 |
ISBN (Print) | 3642330444, 9783642330445 |
DOIs | |
State | Published - Jul 1 2014 |
Externally published | Yes |
Keywords
- BOLD fMRI
- Data fusion
- EEG
- ERP
- Intrinsic connectivity
- Networks
- Oscillations
- Source separation
- Spatiotemporal dynamics
ASJC Scopus subject areas
- Engineering(all)