Duration
26h Th, 26h Labo., 15h Proj.
Number of credits
Master of Science (MSc) in Biomedical Engineering | 5 crédits | |||
Master of Science (MSc) in Electrical Engineering | 5 crédits |
Lecturer
Guillaume Drion, Alessio Franci, Christophe Phillips, Pierre Sacré
Language(s) of instruction
English language
Organisation and examination
Teaching in the first semester, review in January
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
The course provides an introduction to the main computational modeling tools for understanding the brain (principles, building blocks, functions) and the main technologies for measuring and controlling brain activity.
The following topics are addressed:
Microscopic level
- Biophysics-based models
- Spike-based models
- Intracellular and extracellular recordings
Mesoscopic level
- Rate-based models
Macroscopic level
- BOLD signal model and measurement
- Principles of functional MRI
- Dynamic causal modeling of fMRI
Learning outcomes of the learning unit
At the end of the course, the student will master the basic modeling concepts of computational neuroscience and will be able to use the corresponding tools to model simple neural circuits.
Prerequisite knowledge and skills
The course relies on knowledge of basic concepts in signals and systems.
Planned learning activities and teaching methods
The course includes both ex-cathedra lectures, tutorial sessions, laboratories, and projects.
Mode of delivery (face to face, distance learning, hybrid learning)
Face-to-face course
Recommended or required readings
The course material will be made available as the semester progresses.
Exam(s) in session
Any session
- In-person
written exam
Written work / report
Additional information:
To be defined.
Work placement(s)
Organisational remarks and main changes to the course
Contacts
Lecturers: Guillaume Drion, Alessio Franci, Christophe Phillips, Pierre Sacré.
Webpage: https://people.montefiore.uliege.be/sacre/GNEU0001/.