Our last piece deals with the combination of MEG with EEG to track brain networks reorganization during BCI training. The accepted manuscript is now published in the Journal of Neural Engineering [here](http://iopscience.iop.org/article/10.1088/1741-2552/abef39), and available in open access [here](https://hal.archives-ouvertes.fr/hal-03171591v1)
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/).
In the last decade, functional connectivity (FC) has been increasingly adopted based on its ability to capture statistical dependencies between multivariate brain signals. However, the role of FC in the context of brain-computer interface …
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)
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
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 …
Discriminating mental states from brain signals is crucial for many applications in cognitive and clinical neuroscience. Most of the studies relied on the feature extraction from the activity of single brain areas, thus neglecting the potential …