EEG

Just up on ArXiv, our latest work on functional connectivity ensemble method to enhance BCI performance!

Thrilled to present our last piece of work in which we combined functional connectivity estimators with Riemannian geometry via an ensemble methods to improve the classification accuracy on a large number of publicly available datasets! Preprint available [here](http://arxiv.org/abs/2111.03122) and code used available [here](https://github.com/mccorsi/FUCONE).

OpenViBE, an open-source software platform for Brain-Computer Interfaces

On October 6th, with Arthur Desbois, we had the pleasure to organize a workshop on OpenViBE and Brain-Computer Interfaces research during the CuttingEEG conference in the beautiful city of Aix-en-Provence! If you could not make it, all the resources are available on Github! You will have access to our slides, the OpenViBE scenarios and many more resources helping you to learn more about the BCI research by browsing the dedicated [github page](https://github.com/BCI-NET/BCI-OpenViBE-CuttingEEG2021)

Hands-on tutorial on OpenViBE during the next CuttingEEG symposium !

Thrilled to announce that we will organize a workshop during 5th Symposium on cutting-edge methods for EEG research [CuttingEEG](https://cuttingeeg2021.org). We will propose a hands-on tutorial on [OpenViBE](http://openvibe.inria.fr), a software plaform dedicated to BCI research. All the resources available in the dedicated [github page](https://github.com/BCI-NET/BCI-OpenViBE-CuttingEEG2021)

Glad to be awarded a BCI Society Best Oral presentation Award on our work on markers of BCI training based on functional connectivity !

Truly honoured to have received the #vBCI2021 best oral presentation award ! Thank you very much to the BCI Society for this award and for having put together this incredible conference ! Slides are available in the Talks section.

Talk on M/EEG data analysis during the next Cortico days !

Glad to announce that I will give a talk during the day dedicated to early-career researchers (JJC-ICON’2021) of the [Cortico days 2021](https://www.cortico.fr/journees-cortico-2021/). I will present an overview of the M/EEG signals and the associated data analysis. The video and the materials of my talk are available [here](https://www.cortico.fr/videos-jjcicon-2021/) !

A machine learning approach to screen for preclinical Alzheimer's disease

Combining multimodal biomarkers could help in the early diagnosis of Alzheimer's disease (AD). We included 304 cognitively normal individuals from the INSIGHT-preAD cohort. Amyloid and neurodegeneration were assessed on 18F-florbetapir and …

Abstract accepted for oral presentation in Networks 2021 conference !

Pleased to announce that I will give a presentation during the [Networks 2021](https://networks2021.net) conference. I will present my last piece of work on the use of multilayer appproaches to elicit patterns of BCI learning. More info to come !

Paper on core-periphery reorganization in M/EEG multiplex brain networks during BCI training accepted in the Journal of Neural Engineering !

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)

Glad to be awarded a BCI Society Student Award on our work on markers of BCI training based on functional connectivity !

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/).

Phase/Amplitude Synchronization of Brain Signals During Motor Imagery BCI Tasks

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 …