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Section: New Results
EEG and MR Imaging
Feasibility and specificity of simultaneous EEG and ASL MRI at 3T
Participants : Elise Bannier, Marsel Mano, Isabelle Corouge, Lorraine Perronnet, Christian Barillot.
Brain functional imaging can be performed using several approaches, including EEG, BOLD and ASL MRI. The Neurinfo platform has acquired an EEG MR compatible 64ch device over the summer to perform joint EEG and BOLD or ASL fMRI. To date, only a few studies have addressed the issue of connecting EEG signal to ASL perfusion. The aim of this study was to assess ASL-EEG at 3T in terms of safety as well as EEG and MR signal quality. The temperature measurements, specific absorption rate, and signal to noise ratio experiments have shown that ASL EEG can be safely performed using the parameters presented above. However, residual gradient artifacts in the PASL-EEG data have to be considered. Further research is needed to understand the artifact variability and to develop an appropriate correction strategy. This study is performed as part of the HEMISFER project in close collaboration with the involved teams.
Neurofeedback using Virtual Reality and Hybrid EEG-MRI for Brain Rehabilitation
Participants : Lorraine Perronnet, Marsel Mano, Christian Barillot.
We have conducted a thorough state-of-the-art of Neurofeedback (NF) and restorative Brain Computer Interfaces (BCI) under EEG and fMRI modality as well as of EEG-fMRI integration, with a particular focus on applications in depression and motor rehabilitation. This enabled us to build a theoretical comparison of EEG- and fMRI-NF methodology that will be helpful in designing NF protocols combining both modalities. In this perspective, we are currently designing a NF protocol based on motor imagery that will be compatible with EEG and fMRI, and running preliminary recordings of motor execution and motor imagery. Besides, we are writing a book chapter about NF and BCI that is intended to disambiguate the existing definitions and to present basic knowledge about NF principles and applications to naive readers. This is a joint work with Anatole Lécuyer team (Hybrid), in the frame of the Hemisfer project.
Symmetrical EEG and fMRI Imaging by Sparse Regularization
Participants : Thomas Oberlin, Pierre Maurel, Christian Barillot.
This work considers the problem of brain imaging using simultaneously recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). To this end, we introduce a linear coupling model that links the electrical EEG signal to the hemodynamic response from the blood-oxygen level dependent (BOLD) signal. Both modalities are then symmetrically integrated, to achieve a high resolution in time and space while allowing some robustness against potential decoupling of the BOLD effect. The novelty of the approach consists in expressing the joint imaging problem as a linear inverse problem, which is addressed using sparse regularization. The sparsity prior naturally reflects the fact that only few areas of the brain are activated at a certain time, and it is easily implemented through efficient so-called proximal algorithms. The significance of the method and the effectiveness of the algorithms are demonstrated through numerical investigations on a simplified head model and simulated data on a realistic brain model. This is a joint work with Remi Gribonval team (Panama), in the frame of the Hemisfer project.