Neurophysiology and biophysics for ai

The program is divided into three main sections:
1) Cellular Neurophysiology: a brief introduction of neuroscience and its history; basics of cytology and classification of neurons and glia; the excitable membrane, the generation of the membrane potential; action potentials generation and propagation; introduction to the application of biophysics to represent neuronal membrane physiology. Applications to computational modelling and AI: extended biophysics for neuron modelling; Hodgkin-Huxley theory; Markov chain theory; single neuron models (reconstruction, simulation, validation, optimization).
2) Microcircuit functions: synaptic transmission; excitation and inhibition in neuronal networks (temporal and spatial organization of the E/I balance), synaptic plasticity (short- and long-term plasticity, plasticity rules, Hebbian and non-Hebbian plasticity, heterosynaptic plasticity, spike-timing-dependent plasticity). Applications to computational modelling and AI: extended biophysics for microcircuit modelling; learning rules in network models; artificial neural network theory (simple perceptron, self-organizing networks, hidden layer networks, autoassociative networks, Elman networks); principles of efficient computing with networks; principles of machine learning in engineering and neuroscience.
3) System neurophysiology: gross anatomy of the nervous system; sensory system (e.g., vision, auditory and vestibular system, somatic sensory system); motor system (spinal cord, reflexes, central control of voluntary movement; motor cortex, basal ganglia, cerebellum); hypothalamus, autonomic nervous system and neuromodulators; motivation; emotion; language; sleep; the resting brain and the attention system; consciousness; memory. Applications to computational modelling and AI: extended biophysics for brain modelling; multiscale brain models (bottom-up and top-down principles); virtual brain modelling (TVB); dynamics causal modelling (DCM); neurorobotic controllers; AI and brain functioning for cognitive and sensorimotor control.
For each section, Prof. Mapelli will teach the pure biological part, while Prof. D'Angelo will develop the computational and AI-related applications of the biological concepts.