Ballistocardiogram artifact correction taking into account physiological signal preservation in simultaneous EEG-fMRI

被引:28
作者
Abreu, Rodolfo [1 ,2 ]
Leite, Marco [1 ,2 ,3 ,4 ]
Jorge, Joao [1 ,2 ,5 ]
Grouiller, Frederic [6 ]
van der Zwaag, Wietske [7 ]
Leal, Alberto [8 ,9 ]
Figueiredo, Patricia [1 ,2 ]
机构
[1] Univ Lisbon, Inst Syst & Robot, P-1699 Lisbon, Portugal
[2] Univ Lisbon, Dept Bioengn, Inst Super Tecn, P-1699 Lisbon, Portugal
[3] UCL, Inst Neurol, Dept Clin & Expt Epilepsy, Queen Sq, London WC1N 3BG, England
[4] UCL, Inst Neurol, Wellcome Trust Ctr Neuroimaging, Queen Sq, London WC1N 3BG, England
[5] Ecole Polytech Fed Lausanne, Lab Funct & Metab Imaging, Lausanne, Switzerland
[6] Univ Geneva, Univ Hosp Geneva, Dept Radiol & Med Informat, Biomed Imaging Res Ctr CIBM, Geneva, Switzerland
[7] Ecole Polytech Fed Lausanne, Biomed Imaging Res Ctr CIBM, Lausanne, Switzerland
[8] Ctr Hosp Psiquiatr Lisboa, Ctr Invest & Intervencao Social, Lisbon, Portugal
[9] Ctr Hosp Psiquiatr Lisboa, Dept Neurophysiol, Lisbon, Portugal
关键词
Ballistocardiogram; Electroencephalography; fMRI; Independent Component Analysis; INDEPENDENT COMPONENT ANALYSIS; INTERICTAL EPILEPTIFORM DISCHARGES; PULSE ARTIFACT; MR SCANNER; 7; T; IMAGING-ARTIFACT; MAGNETIC-FIELDS; FUNCTIONAL MRI; RECORDINGS; REMOVAL;
D O I
10.1016/j.neuroimage.2016.03.034
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
The ballistocardiogram (BCG) artifact is currently one of the most challenging in the EEG acquired concurrently with fMRI, with correction invariably yielding residual artifacts and/or deterioration of the physiological signals of interest. In this paper, we propose a family of methods whereby the EEG is decomposed using Independent Component Analysis (ICA) and a novel approach for the selection of BCG-related independent components (ICs) is used (PROJection onto Independent Components, PROJIC). Three ICA-based strategies for BCG artifact correction are then explored: 1) BCG-related ICs are removed from the back-reconstruction of the EEG (PROJIC); and 2-3) BCG-related ICs are corrected for the artifact occurrences using an Optimal Basis Set (OBS) or Average Artifact Subtraction (AAS) framework, before back-projecting all ICs onto EEG space (PROJIC-OBS and PROJIC-AAS, respectively). A novel evaluation pipeline is also proposed to assess the methods performance, which takes into account not only artifact but also physiological signal removal, allowing for a flexible weighting of the importance given to physiological signal preservation. This evaluation is used for the group-level parameter optimization of each algorithm on simultaneous EEG-fMRI data acquired using two different setups at 3 T and 7 T. Comparison with state-of-the-art BCG correction methods showed that PROJIC-OBS and PROJIC-AAS outperformed the others when priority was given to artifact removal or physiological signal preservation, respectively, while both PROJIC-AAS and AAS were in general the best choices for intermediate trade-offs. The impact of the BCG correction on the quality of event-related potentials (ERPs) of interest was assessed in terms of the relative reduction of the standard error (SE) across trials: 26/66%, 32/62% and 18/61% were achieved by, respectively, PROJIC, PROJIC-OBS and PROJIC-AAS, for data collected at 3 T/7 T. Although more significant improvements were achieved at 7 T, the results were qualitatively comparable for both setups, which indicate the wide applicability of the proposed methodologies and recommendations. (C) 2016 Elsevier Inc. All rights reserved.
引用
收藏
页码:45 / 63
页数:19
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