Simultaneous EEG-fMRI during a neurofeedback task, a brain imaging dataset for multimodal data integration

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作者
Giulia Lioi
Claire Cury
Lorraine Perronnet
Marsel Mano
Elise Bannier
Anatole Lécuyer
Christian Barillot
机构
[1] Univ Rennes,
[2] Inria,undefined
[3] CNRS,undefined
[4] Inserm,undefined
[5] IRISA UMR 6074,undefined
[6] CHU Rennes,undefined
[7] Service de Radiologie,undefined
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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. This represents one of the first simultaneous recording of EEG and fMRI for NF and here we present the first open access bi-modal NF dataset integrating EEG and fMRI. We believe that it will be a valuable tool to (1) advance and test methodologies for multi-modal data integration, (2) improve the quality of NF provided, (3) improve methodologies for de-noising EEG acquired under MRI and (4) investigate the neuromarkers of motor-imagery using multi-modal information.
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