MICRO-513: Signal Processing for Functional Brain Imaging

General information

Instructors: Dimitri Van De Ville and Melissa Saenz
Time/Location: Thursday 14h-17h, CM1.104
Contact: Dimitri Van De Ville and Melissa Saenz

Description

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.

Notes

  • All papers and material, including for the journal club, are available for download (inside the EPFL/UniGE/UNIL domains)

Syllabus

Week 1 (February 24): Introduction and Journal Club Guidelines

Week 2 (March 3): General linear model (revisited)

Week 3 (March 10): Effective connectivity and dynamic causal modeling

Week 4 (March 17): Independent component analysis

Week 5 (March 24): Independent component analysis: applications

Week 6 (March 31): Pattern recognition I: essentials

Week 7 (April 7): Pattern recognition II: advanced

Week 8 (April 14): Topographic mapping

Week 9 (April 21): Graph models for the brain

Week 10 (April 28): Easter holidays

Week 11 (May 5): Multimodal imaging

Week 12 (May 12): Real-time FMRI

Week 13 (May 19): Questionnaire

Week 14 (May 26): Summary and Lab Exercise