MEG

This Student Award is based on my accepted 2020 abstract submission. I will give a presentation during the next Virtual BCI meeting, scheduled next June ! For more information regarding this work, our study is available [here](https://hal.archives-ouvertes.fr/hal-02438794/).

Glad to present our last piece of work in which we combined MEG and EEG data to track brain networks reorganization during BCI training ! Preprint available [here](http://arxiv.org/abs/2010.13459)

Functional connectivity and brain network reorganization underlying longitudinal processes, mainly BCI training

Development of methods to enhance subjets' mental state classification. They can be divided in two main approaches: the integration of multimodal information and the search for alternative features

Development of cryogenic-free sensors for magnetocardiography and magnetoencephalography

Brain-computer interfaces (BCIs) have been largely developed to allow communication, control, and neurofeedback in human beings. Despite their great potential, BCIs perform inconsistently across individuals and the neural processes that enable humans …

We adopted a fusion approach that combines features from simultaneously recorded electroencephalogram (EEG) and magnetoencephalogram (MEG) signals to improve classification performances in motor imagery-based brain-computer interfaces (BCIs). We …