NX-421 / 6 credits

Teacher(s): Van De Ville Dimitri Nestor Alice, Micera Silvestro

Language: English


Summary

Understanding, processing, and analysis of signals and images obtained from the central and peripheral nervous system

Content

Keywords

Electrophysiology, nervous system, neuroimaging, brain mapping, systems-level neuroscience, MRI

Learning Prerequisites

Required courses

Mathematics at the engineering level (i.e., matrix algebra, probability theory)

Basic signal processing, statistics, and machine-learning concepts

Basic knowledge of programming

Learning Outcomes

By the end of the course, the student must be able to:

  • Analyze processing steps of neural signals and imaging data
  • Assemble a neural data processing pipeline
  • Critique suitability of analysis methods
  • Interpret results of neural signals analysis
  • Explain choice of methodology

Transversal skills

  • Use a work methodology appropriate to the task.
  • Make an oral presentation.
  • Give feedback (critique) in an appropriate fashion.

Teaching methods

Weekly lectures (4h) and weekly exercise session (2h)

Mini-projects during the semester with presentations

Expected student activities

Attendance at lectures and exercises

Assessment methods

Attendance and completion of mini-projects with presentations

Written exam

Supervision

Office hours Yes
Assistants Yes
Forum Yes

Resources

Virtual desktop infrastructure (VDI)

No

Bibliography

  • H. Op de Beeck, C. Nakatani, "Introduction to Human Neuroimaging", Cambridge University Press, 2019.
  • N. V. Thakor, "Handbook of Neuroengineering", Springer, 2020.

Ressources en bibliothèque

In the programs

  • Semester: Fall
  • Exam form: Written (winter session)
  • Subject examined: Neural signals and signal processing
  • Lecture: 4 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Fall
  • Exam form: Written (winter session)
  • Subject examined: Neural signals and signal processing
  • Lecture: 4 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Fall
  • Exam form: Written (winter session)
  • Subject examined: Neural signals and signal processing
  • Lecture: 4 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Fall
  • Exam form: Written (winter session)
  • Subject examined: Neural signals and signal processing
  • Lecture: 4 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Fall
  • Exam form: Written (winter session)
  • Subject examined: Neural signals and signal processing
  • Lecture: 4 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Fall
  • Exam form: Written (winter session)
  • Subject examined: Neural signals and signal processing
  • Lecture: 4 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Fall
  • Exam form: Written (winter session)
  • Subject examined: Neural signals and signal processing
  • Lecture: 4 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Fall
  • Exam form: Written (winter session)
  • Subject examined: Neural signals and signal processing
  • Lecture: 4 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Fall
  • Exam form: Written (winter session)
  • Subject examined: Neural signals and signal processing
  • Lecture: 4 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks

Reference week

 MoTuWeThFr
8-9     
9-10 CM3   
10-11    
11-12    
12-13    
13-14     
14-15     
15-16     
16-17   INR219 
17-18    
18-19     
19-20     
20-21     
21-22     

Tuesday, 9h - 13h: Lecture CM3

Thursday, 16h - 18h: Exercise, TP INR219