Assisted Dictionary Learning for fMRI Data Analysis

ABSTRACT Extracting information from functional magnetic resonance (fMRI) images has been a major area of research for more than two decades. The goal of this work is to present a new method for the analysis of fMRI data sets, that is capable to incorporate a priori available information, via an efficient optimization framework. Tests on synthetic data sets demonstrate significant performance gains over existing methods of this kind. Index Terms -- fMRI Data Analysis, Dictionary Learning, Blind Source Separation 1. INTRODUCTION Functional magnetic resonance imaging (fMRI) is a powerful noninvasive technique suitable to providing important information concerning the brain activity. Studying the different areas in the brain that correspond to important tasks such as vision, perception, recognition, etc., constitutes a major open area of research, demanding robust and high precision techniques for the analysis of fMRI data analysis [1], [2], [3], [4].