Talks

Using models for classification, real-life applications

Talk given during the symposium entitled "Alternative functional connectivity estimators and their real-life application", I co-organized with Pierpaolo Sorrentino. Our symposium proposed an overview over the crosstalk between brain models and brain data analysis. My slides are available on [HAL](https://hal.science/hal-04701100v1)."

A theory-driven approach to data analysis, practical applications

Talk given during the workshop entitled "Virtual Brains, From data to modeling and back", I co-organized with Damien Depannemaecker, Leonardo L. Gollo, Spase Petkoski & Pierpaolo Sorrentino. Whole-brain network models have recently emerged as a powerful method for studying brain function and dysfunction at the system level. In this context, we primarily access human brain signals through imaging techniques such as magnetoencephalography, electroencephalography and functional MRI. When combined with advanced artificial intelligence and machine learning tools for parameter inference, these models enable us to describe how the brain operates within the constraints of its underlying structure, such as white-matter connectivity but also other biophysical features such as neuromodulation. During this workshop, we explored the various aspects of constructing these models and how data can be integrated. My slides are available on [HAL](https://hal.science/hal-04701039v1)."

Using critical dynamics to capture processes underlying brain-computer interface performance

Talk given during the NeuroFrance conference (Theoretical and computational approaches in neuroscience - network neuroscience beyond connectivity session). I presented the [work](https://www.biorxiv.org/content/10.1101/2022.06.14.495887v3) done in collaboration with P. Sorrentino.

Ensemble of Riemannian classifiers for multimodal data - FUCONE approach for M/EEG data

Talk given during the 2023 IEEE ISBI conference. I presented my last piece of work in collaboration with F. Yger and S. Chevallier on the application of the FUCONE approach for bimodal M/EEG fusion. This talk has been given during the special session entitled 'Bimodal functional neuroimaging data fusion - methods and applications', organized by C. Cury and J. Coloigner.

Exploiting neuronal avalanches to inform BCI performance

Talk given during the CSN*2022 conference (Memory and learning, machine learning session). I presented the [work](https://www.biorxiv.org/content/10.1101/2022.06.14.495887v1) done in collaboration with P. Sorrentino.

Core-periphery markers of longitudinal BCI from multiplex brain networks

Talk given during the Networks 2021 conference (Biomarkers and Networks session).

Functional connectivity predicts MI-based BCI learning

Talk awarded during the Virtual BCI meeting 2021.

M/EEG data analysis, where it all begins !

Short master class on M/EEG data analysis.