MICRO-513: Signal Processing for Functional Brain Imaging

General information

Instructors: Dimitri Van De Ville and Melissa Saenz
Time/Location: Thursday 14h-17h, CM1.105
Lab exercises: Computer room CO.023
Contact: Dimitri Van De Ville and Melissa Saenz


The aim of this course is to demonstrate how advanced signal processing techniques contribute to study brain function using modern medical imaging modalities. Over the past decade, seeing the brain at work has had a tremendous impact on neurosciences and medicine. The essentials of signal and image processing methods that lead to successful interpretation of functional brain imaging data are described, with a particular emphasis on multivariate and exploratory techniques. The proposed methodologies are widely applicable; particular examples include functional brain imaging using fMRI, EEG, and optical modalities.


  • All materials, including slides of the lectures and papers for the journal club (JC), are available for download (inside the EPFL/UniGE/UNIL domains)


Week 1 (February 23): Introduction to course and JC

Week 2 (March 1): General linear model: basics (no JC)

Week 3 (March 8): Topographic mapping + JC example

Week 4 (March 15): General linear model: revisited + lab exercise

Week 5 (March 22): Independent component analysis 1 + JC

Week 6 (March 29): Independent component analysis 2 + JC

Week 7 (April 5): Multimodal imaging + lab exercise

Week 8 (April 12): Easter holidays

Week 9 (April 19): Pattern recognition I: essentials + JC

Week 10 (April 26): Pattern recognition II: applications + lab exercise

Week 11 (May 3): Real-time FMRI + JC

Week 12 (May 10): Graph models + JC

Week 13 (May 17): Ascension holiday

Week 14 (May 24): Test-run exam + JC

Week 15 (May 31): Summary