MICRO-513

Signal Processing for Functional Brain Imaging

General information

Instructor:
Dimitri Van De Ville
Time/Location:
Thursday 14h15-17h, AAC.137
Lab exercises:
Computer room ELD.020
Contact:
Lorena Freitas
Nawal Kinany
Anjali Tarun
Thomas Bolton

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.

Reference books

  1. F. Gregory Ashby, Statistical Analysis of fMRI Data, The MIT Press, 2011.
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  2. Russell A. Poldrack et al., Handbook of Functional MRI Data Analysis, Cambridge, 2011.
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  3. Gordon E Sarty, Computing Brain Activity Maps from fMRI Time-Series Images, Cambridge, 2006.
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  4. Strang. Best basis from the SVD. Ch 1.8 from Computational Science and Engineering, Wellesley, 2007.
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  5. James V Stone, Independent Component Analysis, The MIT Press, 2005.
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  6. Olaf Sporns, Networks of the Brain, The MIT Press, 2010.
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