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Hybrid EEG and fMRI platform for multi-modal neurofeedback

Marsel Mano 1, 2 Elise Bannier 1, 3 Lorraine Perronnet 1, 2 Anatole Lécuyer 2 Christian Barillot 1, * 
* Corresponding author
1 VisAGeS - Vision, Action et Gestion d'informations en Santé
INSERM - Institut National de la Santé et de la Recherche Médicale : U1228, Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
2 Hybrid - 3D interaction with virtual environments using body and mind
Inria Rennes – Bretagne Atlantique , IRISA-D6 - MEDIA ET INTERACTIONS
Abstract : Neurofeedback (NFB) relies on neurosignals for the estimation of brain activity. There exist a wide variety of NFB applications that use one type of neurosignals like fMRI or electroencephalography (EEG). Recently, the combination of two or more neurosignals has been receiving a lot of attention in the research community, but still very few multi-modal NFB applications exist. This is primarily because of the lack of commercial multi-modal NFB systems and the associated technical difficulties in building them. Here we are going to describe a bi-modal EEG and fMRI NFB platform that we have build in our lab. Our platform is designed to maximize modularity and parallel processing in order to be able to provide real-time NFB with high level of synchronization and minimal delays. We have successfully used our platform to conduct over 100 uni-modal and bi-modal NFB experiments with more than 30 healthy subjects.
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Submitted on : Monday, August 28, 2017 - 11:59:44 AM
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  • HAL Id : inserm-01577442, version 1


Marsel Mano, Elise Bannier, Lorraine Perronnet, Anatole Lécuyer, Christian Barillot. Hybrid EEG and fMRI platform for multi-modal neurofeedback. International Society of Magnetic Resonance in Medicine, ISMRM, Apr 2017, Honolulu, United States. pp.4550. ⟨inserm-01577442⟩



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