Brain modelling for biomedicine and ict

Aim of the course are: a) to understand how neuroscientific knowledge and methods can inspire AI methods, and vice versa (physiologically-informed AI models); b) to learn computational techniques for modeling biological neural networks and understanding the brain and its function (in healthy or disease states) through a variety of theoretical constructs and computer science analogies; c) to explore neural information processing at "network level", in developing quantitative models, as well as in formalizing new paradigms of computation and data representation

Students will learn the principles to build neural models of brain structures, able to embed multi-scale information, from single neuron functional mechanisms to microcircuits, till the generation of high-level functional behaviors. The students are expected to learn how to use large-scale neurocomputational models and brain-inspired neural networks and AI to simulate specific physio-pathological perceptual and motor circuits (e.g. Brain Digital Twin). The students will see also possible ICT applications of these physiologically-informed AI models.