Bravi seminar: Ill-posed problems in brain imaging: from MEG source estimation to resting state networks and decoding with fMRI.

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October 14th, 2011

Monday – August 8, 2011 – 4:00pm

Dr. Alexandre Gramfort PhD
Ill-posed problems in brain imaging: from MEG source estimation to resting state networks and decoding with fMRI.

Martinos Center for Biomedical Imaging,
Harvard – Massachusetts General Hospital,
Boston, MA

44 Cummington St. Room 705

Abstract:
If the number of parameters to estimate exceeds the number of measurements, an estimation problem is said to be ill-posed. Due to limited acquisition times, physics of the problems and complexity of the brain, the field of brain imaging needs to address many ill-posed problems. Among such problems are: the localization in space and time of active brain regions with MEG and EEG, the estimation of functional networks from fMRI resting state data and what was is commonly called “decoding”. Decoding consists in predicting from fMRI data a behavorial variable or classifying brain states using supervised learning methods like SVM. In this talk I will describe some recent contributions to all three problems. The concepts shared by the different methods presented are: estimation and statistical learning in high dimension, convex optimization, sparse and structured priors.