Simultaneous MRI-EEG during a motor imagery neurofeedback task: an open access brain imaging dataset for multi-modal data integration.

Combining EEG and fMRI allows for integration of fine spatial and accurate temporal resolution yet presents numerous challenges, noticeably if performed in real-time to implement a Neurofeedback (NF) loop. Here we describe a multimodal dataset of EEG and fMRI acquired simultaneously during a motor imagery NF task, supplemented with MRI structural data. The study involved 30 healthy volunteers undergoing five training sessions. We showed the potential and merit of simultaneous EEG-fMRI NF in previous work. Here we illustrate the type of information that can be extracted from this dataset and show its potential use. Our group is the second in the world to have integrated EEG and fMRI for NF, therefore this dataset is unique of its kind. We believe that it will be a valuable tool to 1. Advance and test methodologies to integrate complementary neuroimaging techniques (design and validation of methods of multi-modal data integration at various scales) 2. Improve the quality of Neurofeedback provided 3. Improve methodologies for de-noising EEG acquired under MRI 4. Investigate the neuromarkers of motor-imagery using multi-modal information