Multimodal functional network connectivity: An EEG-fMRI fusion in network space

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 network-based 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. © 2011 Lei et al.

Publication type: 
Articolo
Author or Creator: 
Lei, Xu
Ostwald, Dirk
Hu, Jiehui
Qiu, Chuan
Porcaro, Camillo
Bagshaw, Andrew P.
Yao, Dezhong
Publisher: 
Public Library of Science, San Francisco, CA , Stati Uniti d'America
Source: 
PloS one 6 (2011). doi:10.1371/journal.pone.0024642
info:cnr-pdr/source/autori:Lei, Xu; Ostwald, Dirk; Hu, Jiehui; Qiu, Chuan; Porcaro, Camillo; Bagshaw, Andrew P.; Yao, Dezhong/titolo:Multimodal functional network connectivity: An EEG-fMRI fusion in network space/doi:10.1371/journal.pone.0024642/rivista:P
Date: 
2011
Resource Identifier: 
http://www.cnr.it/prodotto/i/296758
https://dx.doi.org/10.1371/journal.pone.0024642
info:doi:10.1371/journal.pone.0024642
http://www.scopus.com/record/display.url?eid=2-s2.0-80053082587&origin=inward
Language: 
Eng
ISTC Author: 
Camillo Porcaro's picture
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