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Proceedings Paper

Paradigm-free mapping with morphological component analysis: getting most out of fMRI data
Author(s): César Caballero Gaudes; Dimitri Van De Ville; Natalia Petridou; François Lazeyras; Penny Gowland
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Paper Abstract

Functional magnetic resonance imaging (fMRI) is a non-invasive imaging technique that maps the brain's response to neuronal activity based on the blood oxygenation level dependent (BOLD) effect. This work proposes a novel method for fMRI data analysis that enables the decomposition of the fMRI signal in its sources based on morphological descriptors. Beyond traditional fMRI hypothesis-based or blind data-driven exploratory approaches, this method allows the detection of BOLD responses without prior timing information. It is based on the deconvolution of the neuronal-related haemodynamic component of the fMRI signal with paradigm free mapping and also furnishes estimates of the movement-related effects, instrumental drifts and physiological fluctuations. Our algorithm is based on an overcomplete representation of the fMRI voxel time series with an additive linear model that is recovered by means of a L1-norm regularized least-squares estimators and an adapted block coordinate relaxation procedure. The performance of the technique is evaluated with simulated data and real experimental data acquired at 3T.

Paper Details

Date Published: 27 September 2011
PDF: 11 pages
Proc. SPIE 8138, Wavelets and Sparsity XIV, 81381K (27 September 2011); doi: 10.1117/12.893920
Show Author Affiliations
César Caballero Gaudes, Univ. of Geneva (Switzerland)
Univ. Hospital of Geneva (Switzerland)
Dimitri Van De Ville, Univ. of Geneva (Switzerland)
Univ. Hospital of Geneva (Switzerland)
Ecole Polytechnique Fédérale de Lausanne (Switzerland)
Natalia Petridou, Univ. of Nottingham (United Kingdom)
Univ. Medical Ctr. Utrecht (Netherlands)
François Lazeyras, Univ. of Geneva (Switzerland)
Univ. Hospital of Geneva (Switzerland)
Penny Gowland, The Univ. of Nottingham (United Kingdom)


Published in SPIE Proceedings Vol. 8138:
Wavelets and Sparsity XIV
Manos Papadakis; Dimitri Van De Ville; Vivek K. Goyal, Editor(s)

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