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Abstract #5406

Multimodal functional imaging using modified fMRI-weighted minimum-norm estimation

Jing Xu1, Tianyi Qian2, Thomas Beck3, and Jia-Hong Gao1

1Center for MRI Research, Peking University, Beijing, People's Republic of China, 2MR Collaborations NE Asia, Siemens Healthcare, Beijing, People's Republic of China, 3Application Development, Siemens Healthcare, Erlangen, Germany

Multimodal functional neuroimaging by combining fMRI and EEG has been studied to achieve high-resolution reconstruction of the spatiotemporal cortical current density (CCD) distribution. Although fMRI-constrained EEG/MEG source imaging can enhance spatiotemporal resolution of functional neuroimaging, it has been reported that hard fMRI constraint can result in misidentification of neuronal sources if mismatches exist between fMRI activations and EEG/MEG sources. In this study, we propose a new method modified fMRI-weighted minimum-norm estimation (mfMNE) to solve the problem of fMRI–EEG integrated source imaging. This method may be a promising option for solving the mismatches between fMRI and EEG/MEG in the fMRI-constrained EEG/MEG source imaging.

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