Students will initially learn that the computational mechanisms of the human brain are one of the greatest challenges of this century and that a great effort has been provided thanks to large-scale simulations and the development of theoretical models at different scales of observation. Students will then be introduced to the usage of computational techniques to model biological neural networks and will understand the brain and its function through a variety of theoretical constructs and computer science analogies. Students will be provided with insights about how the developing of in silico models, as well as of neuromorphic computational engines – based on the brain's circuitry – can contribute a better understanding of the coding strategies used by the “biological” brain to process incoming stimuli, and produce cognitive and/or motor outputs.
The emphasis is on neural information processing at “network level”, in developing quantitative models, as well as in formalizing new paradigms of computation and data representation.
Lectures and practicals
Materiale disponibile su aulaweb o distribuito a lezione (copia dei lucidi e note).
Ulteriori riferimenti:
Methods in Neuronal Modeling, Koch and Segev, MIT press, 1999.
Spiking Neuron Models, Gerstner and Kistler, Cambridge press, 2002.
Dynamical systems in neuroscience. Izhikevich, MIT press, 2007.
P. Dayan and L.F. Abbott. Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. The MIT Press, 200
Ricevimento: Previo appuntamento via e-mail.
Ricevimento: Lunedì 11:00-13:00 Giovedì 16:00-17:00 Ufficio: pad. E, Via Opera Pia 13 (III piano) Lab: “Bioengineering - SyNaPSI”, pad. E, Via Opera Pia 13, (I piano)
PAOLO MASSOBRIO (Presidente)
SILVIO PAOLO SABATINI (Presidente)
Esame orale e discussione progetto