Fiche de KUBLER Samuel

Titre : Statistical methods for the robust extraction of objects’ spatio-temporal relations in bioimaging - Application to the functional analysis of neuronal networks in vivo
Date : 24 novembre 2023
Heure: 14:00
Résumé : Recent advances in fluorescent calcium imaging, genetical engineering and single-particle tracking have allowed to monitor the activity of individual neurons in freely behaving animals. This groundbreaking research helps neuroscientists to understand how groups of neurons work together to encode animal behavior through synchronized activation patterns. To achieve this, we use powerful statistical tools to analyze in vivo neural network data obtained from fluorescent calcium microscopy. However, working with this data is challenging due to noise and the inherent randomness of neural activity. In this thesis, spatial statistics and Bayesian inference are explored to identify specific neurons within synchronized neural groups during various stimuli and behaviors. By providing interpretable biological estimates and free software, this research aims to shed light on how collective properties emerge from extremely varying individual neural signals, that make the neural code still elusive.
Lieu : Institut Pasteur - Amphithéâtre AGNES ULLMANN - Bâtiment Monod 25 rue du docteur Roux 75015 PARIS