NEUROENGINEERING

Obiettivi formativi

* Obiettivi generali Il corso introduce i principi base, le metodologie e le applicazioni delle tecniche ingegneristiche utilizzate per lo studio sistemi neurali e dell’interazione con essi. * Obiettivi specifici - Conoscenza e comprensione Lo studente apprenderà le nozioni di base sul funzionamento e l’organizzazione a diverse scale del cervello umano, nonché le principali applicazioni dell’ingegneria e della tecnologia dell’informazione alle neuroscienze. - Applicare conoscenza e comprensione Lo studente apprenderà l’uso degli strumenti essenziali per acquisire, elaborare e decodificare i segnali neurofisiologici e neuromuscolari, e per il loro interfacciamento con dispositivi artificiali. - Capacità critiche e di giudizio Lo studente imparerà a scegliere la metodologia di controllo più appropriata per indirizzare uno specifico problema, e per valutare la complessità della soluzione proposta. - Capacità comunicative Lo studente imparerà a comunicare in un contesto multidisciplinare i principali problemi dell’interfacciamento di segnali neurofisiologici con un sistema artificiale, e ad argomentare le possibili scelte progettuali per lo scopo. - Capacità di apprendimento Le modalità di svolgimento del corso mirano a creare una forma mentis dello studente orientata all’autoapprendimento di concetti avanzati che non sono stati affrontati nel corso.

Canale 1
LAURA ASTOLFI Scheda docente

Programmi - Frequenza - Esami

Programma
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 ...
Prerequisiti
Il corso fornisce le conoscenze necessarie al raggiungimento degli obiettivi formativi, e non richiede prerequisiti specifici, oltre a quelli già previsti per i curricula per i quali è erogato.
Testi di riferimento
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 Dispense distribuite dai docenti
Frequenza
In presenza.
Modalità di esame
Prove scritte per la valutazione delle conoscenze e delle competenze
Modalità di erogazione
Il corso è erogato mediante lezioni ex-catedra ed esercitazioni.
FEBO CINCOTTI Scheda docente

Programmi - Frequenza - Esami

Programma
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
Prerequisiti
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.
Testi di riferimento
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
Modalità insegnamento
Vedi sito web del corso: https://sites.google.com/uniroma1.it/neuroengineering
Frequenza
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
Modalità di esame
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
Modalità di erogazione
TBD
  • Codice insegnamento10592834
  • Anno accademico2025/2026
  • CorsoControl Engineering - Ingegneria Automatica
  • CurriculumCurriculum unico
  • Anno1º anno
  • Semestre2º semestre
  • SSDING-INF/06
  • CFU6