MICRO-513: Signal Processing for Functional Brain Imaging

General information

Instructors: Dimitri Van De Ville and Melissa Saenz
Time/Location: Thursday 14h15-17h, AAC.137
Lab exercises: Computer room CO.6
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 20): Introduction to course and primer on brain anatomy and statistics

Week 2 (February 27): General linear model: basics

Week 3 (March 6): General linear model: continued

Week 4 (March 13): Topographic mapping

Week 5 (March 20): Lab exercise (CO6)

Week 6 (March 27): Independent component analysis + JC (GLM)

Week 7 (April 3): Multimodal + JC (Topographic)

Week 8 (April 10): Lab exercise (CO6)

Week 9 (April 17): Pattern recognition + JC (ICA)

Week 10 (April 24): Easter holidays

Week 11 (May 1): Real-time FMRI + JC (PR/Multimodal)

Week 12 (May 8): Graph models + JC (PR)

Week 13 (May 15): Hyperscanning + JC (Graph Models/rt-fMRI)

Week 14 (May 22): Summary

Week 15 (May 29): Ascension holiday