Profile


Field of study: 

computational modeling in epilepsy,

neuronal population models, EEG signals,

parameter identification, bayesian filtering,

optimization methods.

Degrees: 

Ph.D. in telecommunication and signal processing from University of Rennes1

 
Main research interests

My current research deals with the physiopathological interpretation of SEEG signals recorded during pre-chirurgical of epileptic patients. The interpretation of these complex data is currently mostly qualitative and efforts are still to be produced in order to quantitatively assess physiological information conveyed by signals. In my thesis, a neuronal population model whose free parameters represent excitation and inhibition levels in recorded neuronal tissue is analyzed. A Maximum likelihood based  estimator is proposed by computing the likelihood with non linear filters (Extended Kalman Filter, Unscented Kalman Filter...). This Likelihood is then maximize via a Particle swarm optimization algorithm (PSO). Several C++ tools has been developed for bayesian filtering (BFilt) and swarm optimzation (PSOL).

 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
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