Journal
JOURNAL OF INTEGRATIVE NEUROSCIENCE
Volume 11, Issue 3, Pages 313-337Publisher
IMR PRESS
DOI: 10.1142/S0219635212500203
Keywords
EEG; fMRI; neuroimaging; fusion; ICA; Bayesian; STEFF
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Funding
- 973 project [2011CB707803]
- National Nature Science Foundation of China [31070881, 31170953, 81071222, 31200857]
- 111 Project for neuroinformation of the Ministry of Education of China
- Fundamental Research Funds for the Central Universities [SWU1209319]
- National Key Discipline of Basic Psychology at Southwest University [NSKD11047]
- Humanity and Social Science Youth foundation of Ministry of Education of China [12YJC190015]
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Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) provide complementary noninvasive information of brain activity, and EEG/fMRI fusion can achieve higher spatiotemporal resolution than each modality separately. This focuses on independent component analysis (ICA)-based EEG/fMRI fusion. In order to appreciate the issues, we first describe the potential and limitations of the developed fusion approaches: fMRI-constrained EEG imaging, EEG-informed fMRI analysis, and symmetric fusion. We then outline some newly developed hybrid fusion techniques using ICA and the combination of data-/model-driven methods, with special mention of the spatiotemporal EEG/fMRI fusion (STEFF). Finally, we discuss the current trend in methodological development and the existing limitations for extrapolating neural dynamics.
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