Blind Source Separation Approaches to Remove Imaging Artefacts in EEG Signals Recorded Simultaneously with fMRI

Bertrand Rivet (1) , Guillaume Flandin (2) , Antoine Souloumiac (3) , Jean-Baptiste Poline (2)

1 GIPSA-MPACIF - GIPSA - Machines Parlantes, Agents Communicants & Interaction Face-à-face
2 NEUROSPIN - Service NEUROSPIN
3 LOAD (CEA, LIST) - Laboratoire Outils d'Analyse des Données (CEA, LIST)

Using jointly functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) is a growing field in human brain mapping. However, EEG signals are contaminated during acquisition by imaging artefacts which are stronger by several orders of magnitude than the brain activity. In this paper, we propose three methods to remove the imaging artefacts based on the temporal and/or the spatial structures of these specific artefacts. Moreover, we propose a new objective criterion to measure the performance of the proposed algorithm on real data. Finally, we show the efficiency of the proposed methods applied to a real dataset.

Keywords: signal processing; algorithm performance; method efficiency; image processing; spectrum analysis; EEG; electroencephalography; MRI; magnetic resonance imaging; imaging artefact; medical imaging; Denoising; blind source separation; statistical analysis

Domains: Signal and Image Processing; Neurons and Cognition [q-bio.NC]

Bertrand Rivet, Guillaume Flandin, Antoine Souloumiac, Jean-Baptiste Poline. Blind Source Separation Approaches to Remove Imaging Artefacts in EEG Signals Recorded Simultaneously with fMRI. EUSIPCO 2008 - 16th European Signal Processing Conference, Aug 2008, Lausanne, Switzerland. ⟨hal-00315814⟩