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The aim is to develop an high-resolution spatiotemporal imaging technique to map the cerebral connectome using simultaneous EEG-fMRI. These two neuroimaging  techniques combines two complementary information, that could allow to establish more accurate multimodal functional biomarkers of neurological diseases. But, in this setup, the EEG signals are usually contaminated by many artifacts hampering the estimation of the connectivity. To overcome that, we propose to develop an innovative multimodal connectivity estimation using an accurate denoising method with carbon-wire loops.