Brain–Computer Interface (BCI) systems allow to perform actions by translating brain activity into commands. Such systems require training a classification algorithm to discriminate between mental states, using specific features from the brain …
Large-scale interactions among multiple brain regions manifest as bursts of activations called neuronal avalanches, which reconfigure according to the task at hand and, hence, might constitute natural candidates to design brain-computer interfaces …
Truely happy to have taken part of the organization of the [CuttingGardens](https://cuttinggardens2023.org), a multi-hub meeting on EEG and MEG methods! I have notably animated a session dedicated to the use of BCI with 3 insightful talks given by R. Kobler, M. Tangermann, and T. Vaughan. All the materials (and many other features!) are available in the dedicated [github page](https://github.com/mccorsi/CuttingGarden2023-RealTimeEEG_BCI)
Truely happy to take part of the organization of the [PracticalMEEG](https://practicalmeeg2022.org/) workshop! I will notably co-animate a [hands-on tutorial on OpenViBE](https://github.com/Inria-NERV/BCI-OpenViBE-PracticalMEEG2022) with my colleague Arthur Desbois and I will be a tutor during the [Fieldtrip sessions](https://www.fieldtriptoolbox.org/workshop/practicalmeeg2022/) with Robert Oostenveld and Laure Spieser!
Glad to present our last piece of work in collaboration with P. Sorrentino in which we used neuronal avalanches to propose alternative and robust markers to differenciate mental states! Preprint available [here](https://www.biorxiv.org/content/10.1101/2022.06.14.495887v1)
Glad to present the chapter I wrote for the Book entitled *Machine learning for brain diseases*. This chapter aims at providing an overview of the electroencephalography and the magnetoencephalography domains. A preliminary version is available [here](https://hal.inria.fr/hal-03604421), and the code used to plot the figures and to propose some insights on M/EEG processing is available [here](https://github.com/mccorsi/ML-for-Brain-Disorders_MEEG).
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! OA version available [here](http://arxiv.org/abs/2111.03122), code paper available [here](https://www.softwareimpacts.com/article/S2665-9638(22)00019-7/fulltext) and code used available [here](https://github.com/mccorsi/FUCONE).
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).
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)
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)