EEG-fMRI neurofeedback of a motor imagery task

Lorraine Perronnet (1) , Anatole Lécuyer (1) , Marsel Mano (2, 1) , Elise Bannier (2, 3) , Fabien Lotte (4, 5) , Maureen Clerc (6, 7) , Christian Barillot (2)

1 Hybrid - 3D interaction with virtual environments using body and mind
2 VisAGeS - Vision, Action et Gestion d'informations en Santé
3 Département de Radiologie [CHU de Rennes]
4 LaBRI - Laboratoire Bordelais de Recherche en Informatique
5 Potioc - Popular interaction with 3d content
6 ATHENA - Computational Imaging of the Central Nervous System
7 COMUE UCA - COMUE Université Côte d'Azur (2015-2019)

EEG-fMRI-neurofeedback(NF) has been introduced for the first time by Zotev et al [1]. The authors hypothesized that bimodal EEG-fMRI-NF could be more efficient than unimodal EEG-NF or fMRI-NF performed alone. A recent study identified the fMRI signature of motor imagery during EEG-NF [3]. However to our knowledge EEG-fMRI-NF, EEG-NF and fMRI-NF have never been compared before. In the present work, we propose an EEG-fMRI-NF protocol of a motor imagery (MI) task and compare the cross-modal effects of EEG-NF, fMRI-NF and EEG-fMRI-NF. We hypothesized that: • EEG activations : EEG-NF ≥ EEG-fMRI-NF > fMRI-NF • fMRI activations : fMRI-NF ≥ EEG-fMRI-NF > EEG-NF As compared to [1] in which EEG and fMRI were represented with two separate gauges, our feedback metaphor integrates both EEG and fMRI signal in a single bi-dimensional feedback (a ball moving in 2D) in order for the subject to more easily perceive the NF training as one regulation task instead of two.

Mots clés: Neurofeedback; EEG; fMRI; bimodal; simultaneous

Domaines: Neurosciences

Lorraine Perronnet, Anatole Lécuyer, Marsel Mano, Elise Bannier, Fabien Lotte, et al.. EEG-fMRI neurofeedback of a motor imagery task. Organization for Human Brain Mapping, Jun 2016, Genève, Switzerland. ⟨hal-01426182⟩