Control Engineering

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 ...

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

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.

In presence.

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

Teaching classes with exercises.

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 Module B ----------- - Non-invasive measurement of bioelectrical signals: electroencephalography (EEG), electromyography (EMG) - Overview of electrophysiological signals - Instrumentation for biosignals acquisition - Fundamentals of biosignal analysis and interpretation - Analysis of spontaneous, evoked and induced activity - Basics of biosignal processing - Analog to digital conversion - Characterization of digital signals - Spectral analysis - Digital filters - Brain-Computer Interfaces 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 ... - On the use of Brain-Computer Interfaces in rehabilitation after brain stroke

No 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. Basic programming skills in any language (Python, Matlab, ...) will be needed to follow class demonstrations and complete homework.

Books - 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 (available through the Sapienza Library System SBS) - Wolpaw J and Wolpaw E (eds.), Brain-Computer Interfaces, Oxford University Press, 2012. ISBN 9780195388855 / 9780199921485 Handouts - Course notes, class slides and scientific articles will be distributed by the teachers during the semester. Students are warmly invited to join the course's Piazza class, to learn how to access the teaching material: https://piazza.com/uniroma1.it/spring2026/10592834/home

See the course website: https://sites.google.com/uniroma1.it/neuroengineering

Attending lessons is not mandatory. Students are warmly invited to join the course's Piazza class, to receive announcements and participate in discussions: https://piazza.com/uniroma1.it/spring2026/10592834/home

Written exams for the evaluation of knowledge and understanding, applying knowledge and understanding, and making judgments. To pass the exam students are expected to pass two written tests, both taken in the same session: - Test 1 (closed-ended answers), aimed at assessing Knowledge and understanding - Test 2 (open-ended answers), aimed at assessing Knowledge and understanding, Critical and judgment skills, Communication skills

TBD