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Conference Papers Year : 2017

Hybrid EEG and fMRI platform for multi-modal neurofeedback

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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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Dates and versions

inserm-01577442 , version 1 (28-08-2017)

Licence

Public Domain

Identifiers

  • HAL Id : inserm-01577442 , version 1

Cite

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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