Know and understand the neural basis of cognitive processes. Understand the basis of computational modeling at different scales of complexity from single neurons, to microcircuits and neural networks, also demonstrating the ability to analyze their differences and similarities
Course Prerequisites
Neuroanatomy and neurophysiology basis
Teaching Methods
Face-to-face lectures. Possible educational seminars to expand the student knowledge.
Assessment Methods
No “in itinere” tests are scheduled. The final exam is scheduled as an oral, structured as follow: open questions assessing critical thinking skills and spot questions assessing knowledge of structures, processes and terminology. The aim is to ascertain the achievement of the educational objectives of the course. The subject of the exam covers the entire content of the lectures and educational seminars.
Texts
Digital material will be provided through the kiro platform
Contents
The course is divided in two modules: the first tackles with physiology of cognitive processes and bottom-up modelling, while the second deals with brain function recording and modelling at large-scale. 1. Brain functional architecture - Structure, function, dynamics and control - Computation, coding, information - Interaction between sensorimotor and cognitive sub-systems - Closed-loop computation: forward and inverse controllers, and error detection - Circuit mechanisms of learning, memory, computation and information transfer 2. Multiscale organization of the nervous system - Microscale: molecular and cellular aspects, neurons and microcircuits - Mesoscale: multineuronal assemblies and basis of Artificial Intelligence - Macroscale: large scale networks 3. Brain function recording - Techniques for the measurement of ensemble neuronal functions - Analysis of distributed signals and the inverse problem - PET, TMS, EEG, MEG - Structural and functional MRI - Brain architecture and Connectomics 4. Multiscale modelling of nervous functions - Principles of realistic brain modelling: Single neuron models (Hodgkin-Huxley style) and Microcircuit models - Spiking Neural Networks theory - Model simplification and mean field models - Artificial Intelligence and Brain modelling: The Virtual Brain and Dynamics causal modelling During the course are presented some practical applications: - Neurophysiology and neuropathology - Neuroinformatics - Neurobotics - Neuromorphic computing
Course Language
English
More information
For students with disabilities or DSA, student workers, students involved in caring for their family members, student parents, students at risk of dropping out, student athletes, the teacher will be available "ON DEMAND" through in-person meetings or through online platforms to understand the student's problems and to find the most appropriate solutions.
