Know and understand the relation between brain features and neural network architecture, and understand the basis of computation modeling of large-scale networks.
Course Prerequisites
Basic anatomy of the brain
Teaching Methods
Face-to-face lectures and hands-on sessions. Possible 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, educational seminars and hands-on.
Texts
Digital material will be provided through the kiro platform.
Contents
Introduction to neural networks whose rules are inspired by brain physiology. Structural architectures and topologies to model the brain and its functional activity at multiple scales of complexity. Particular interest will be given to the large-scale characterization of the brain towards Digital Brain Twins. Topics: - Brain-inspired ANNs and brain analogies: from the simple perceptron to the Elman network. - Theory for physiologically based mean field models. - Brain structure-function relation: the whole-brain network. - Functional Brain Networks and large-scale connectivity. - Brain modeling to predict brain activity and functional hierarchy. - Digital Brain Twins. - AI applications to NeuroImaging.
