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- Title
Multimodal Functional Network Connectivity: An EEG-fMRI Fusion in Network Space.
- Authors
Xu Lei; Ostwald, Dirk; Jiehui Hu; Chuan Qiu; Porcaro, Camillo; Bagshaw, Andrew P.; Dezhong Yao
- Abstract
EEG and fMRI recordings measure the functional activity of multiple coherent networks distributed in the cerebral cortex. Identifying network interaction from the complementary neuroelectric and hemodynamic signals may help to explain the complex relationships between different brain regions. In this paper, multimodal functional network connectivity (mFNC) is proposed for the fusion of EEG and fMRI in network space. First, functional networks (FNs) are extracted using spatial independent component analysis (ICA) in each modality separately. Then the interactions among FNs in each modality are explored by Granger causality analysis (GCA). Finally, fMRI FNs are matched to EEG FNs in the spatial domain using networkbased source imaging (NESOI). Investigations of both synthetic and real data demonstrate that mFNC has the potential to reveal the underlying neural networks of each modality separately and in their combination. With mFNC, comprehensive relationships among FNs might be unveiled for the deep exploration of neural activities and metabolic responses in a specific task or neurological state.
- Subjects
ELECTROENCEPHALOGRAPHY; CEREBRAL cortex; MAGNETIC resonance imaging of the brain; BIOLOGICAL neural networks; BRAIN function localization; HEMODYNAMICS; INDEPENDENT component analysis; GRANGER causality test
- Publication
PLoS ONE, 2011, Vol 6, Issue 9, p1
- ISSN
1932-6203
- Publication type
Article
- DOI
10.1371/journal.pone.0024642