Neurophysiology and Biophysics for Ai

This foundational course provides the theoretical basis of neurophysiology needed to address neurocomputation, AI algorithms and their applications to ICT and biomedicine and to provide a perspective for the comparison between natural and artificial intelligence. This includes understanding how neurons and synapses operate inside local microcircuits, how their activity propagates through large-scale networks, and how synaptic and non-synaptic plasticity is generated based on network activity patterns.  Moreover, the anatomical organization of large-scale systems will be considered along-with large-scale dynamics and their control of cognitive and emotional states and consciousness. Special attention will be given to biophysical and computational aspects of brain activity at all scales, providing insight on algorithmic properties. Basics of experimental measurements of brain structure and function and of brain biological properties will be provided.

Students will learn the foundations of central nervous system physiology, at multiple levels: how complex neuronal functions arise from cellular biophysical properties, the rules governing neuronal network activity and plasticity, and how these features combine to generate higher cognitive functions at the macroscale level. The students are expected to learn how brain investigations are performed, from the experimental and computational point of view, and the relevant applications to AI.