Resultados : Analisis

Investigador principal : Bruno CESSAC.

El trabajo en curso : Analizar, a nivel de red local, el propiedades estadísticas de la producción pico de las células ganglionares los trenes, incluidos los mecanismos de adaptación.

• Biológica de orden análisis de las estadísticas
• Algoritmo de mejora del rendimiento
• Red de modelo de estimación paramétrica.

Publicaciones y resultados:

Cessac, B. (2011) Statistics of spike trains in conductance-based neural networks: Rigorous results, The Journal of Mathematical Neuroscience 2011, 1:8 (25 August 2011).

Cessac, B. and Palacios, A. (2012) «Spike train statistics from empirical facts to theory: the case of the retina», In Mathematical Problems in Computational Biology and Biomedicine, F. Cazals and P. Kornprobst, Springer, to appear.

Vasquez, J.C., Palacios, A., Marre, O., Berry II, M. and Cessac, B. Gibbs distribution analysis of temporal correlation structure on multicell spike trains from retina ganglion cells, J. Physiol. Paris (in press)

Cofre, R. and Cessac, B:  Dynamics and spike trains statistics in

conductance-based Integrate-and-Fire neural networks with chemical and electric synapses, submitted to «Chaos, Solitons and Fractals», 2012.

Hassan Nasser, Olivier Marre, and Bruno Cessac. Spike trains analysis using gibbs distributions and monte-carlo method. submitted to «Journal of Statistical Mechanics», 2012.

Event Neural Assembly Simulation (Enas) C++ open-source middleware (interoperationable with Matlab, Java, Python, with Gtk GUI) providing :

– Statistical methods and numerical tools to analyse and simulate the statistics of spike trains obtained from retina MEA recordings.

– Variational methods and estimation tools to estimate and optimize the parameters of a neural assembly.

http://enas.gforge.inria.fr