Catalogo dei Corsi di studio

* General objectives
The course aims to introduce the principles, methodologies, and applications of the main engineering techniques used to study and interact with neural systems.

* Specific objectives

- Knowledge and understanding
Students will learn the basics of the human brain functioning and organization at different scales, and to the main applications of engineering and information technologies to neuroscience

- Applying knowledge and understanding
Students will familiarize with basic tools to utilize to acquire, process and decode neurophysiological and muscular signals and to interface them with artificial devices

- Critical and judgment skills
Students will learn how to choose the most suitable control methodology for a specific problem and to evaluate the complexity of the proposed solution.

- Communication skills
Students will learn to communicate in a multidisciplinary context the main issues of interfacing neurophysiological signals with artificial systems, and to convey possible design choices for this purpose.

- Learning ability
Students will develop a mindset oriented to independent learning of advanced concepts not covered in the course.

Programme

Module A

Anatomy and physiology of the neural cell
Generation of neural electrical and metabolic correlates
Neural encoding and decoding
Principles of the brain organization, natural neural networks, different levels of organization
Network neuroscience - basic definitions (synchronicity, causality, influence)
Model­-free (data-driven) vs model­-based (biologically inspired) models of the brain as a complex system
Analysis of brain networks at different scales (cellular and synaptic, cognitive neuroscience, behavioral neuroscience, multi-subject systems)
Examples of application to clinical and physiological problems

Seminars

Experts in the field of neuroengineering will be invited to give seminars on methodological or applicative topics. The program is still to be defined.

Possible topics:

Study of the neural basis of social behavior and its pathological alterations
...

Adopted texts

Hari R, Puce A, MEG-EEG primer, Oxford Press, 2017, ISBN: 9780190497774

L.F. Dayan and D. Abbott, Theoretical Neuroscience. Computational and Mathematical Modeling of Neural Systems, the MIT Press, 2005. ISBN: 9780262041997 / 9780262541855

M.X. Cohen, Analyzing Neural Time Series Data: Theory and Practice. The MIT Press, 2014

Wolpaw J and Wolpaw E (eds.), Brain-Computer Interfaces, Oxford University Press, 2012. ISBN 9780195388855 / 9780199921485

Course notes and scientific articles will be distributed by the teachers during the semester.

Prerequisites

The course is self-contained and does not need special prerequisites beyond those already required to access the curricula in which it is offered.

Study modes

Teaching classes with exercises..

Frequency modes

In presence.

Exam modes

Written exams for the evaluation of knowledge and understanding, applying knowledge and understanding, and making judgments

Exam reservation date start	Exam reservation date end	Exam date
18/12/2023	03/01/2024	08/01/2024
15/01/2024	27/01/2024	01/02/2024
09/03/2024	23/03/2024	28/03/2024
16/05/2024	30/05/2024	04/06/2024
14/06/2024	28/06/2024	03/07/2024