Rejection of pulse related artefact (PRA) from continuous electroencephalographic (EEG) time series recorded during functional magnetic resonance imaging (fMRI) using constraint independent component analysis (cICA)

Rejection of the pulse related artefact (PRA) from electroencephalographic (EEG) time series recorded simultaneously with fMRI data is difficult, particularly during NREM sleep because of the similarities between sleep slow waves and PRA, in both temporal and frequency domains and the need to work with non-averaged data. Here we introduce an algorithm based on constrained independent component analysis (cICA) for PRA removal. This method has several advantages: (1) automatic detection of the components corresponding to the PRA; (2) stability of the solution and (3) computational treatability. Using multichannel EEG recordings obtained in a 3 T MR scanner, with and without concomitant fMRI acquisition, we provide evidence for the sensitivity and specificity of the method in rejecting PRA in various sleep and waking conditions.

[1]  Robert Turner,et al.  A Method for Removing Imaging Artifact from Continuous EEG Recorded during Functional MRI , 2000, NeuroImage.

[2]  G Buzsáki,et al.  The hippocampo-neocortical dialogue. , 1996, Cerebral cortex.

[3]  Graeme D. Jackson,et al.  Measurement and reduction of motion and ballistocardiogram artefacts from simultaneous EEG and fMRI recordings , 2007, NeuroImage.

[4]  Gian Luca Romani,et al.  Complete artifact removal for EEG recorded during continuous fMRI using independent component analysis , 2007, NeuroImage.

[5]  Abraham Z. Snyder,et al.  Moving GLM ballistocardiogram artifact reduction for EEG acquired simultaneously with fMRI , 2007, Clinical Neurophysiology.

[6]  J. MacQueen.  Some methods for classification and analysis of multivariate observations , 1967 .

[7]  Mark S. Cohen,et al.  Acquiring simultaneous EEG and functional MRI , 2000, Clinical Neurophysiology.

[8]  Manuel Abbafati,et al.  An independent component analysis-based approach on ballistocardiogram artifact removing. , 2006, Magnetic resonance imaging.

[9]  H. L. Le Roy,et al.  Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability; Vol. IV , 1969 .

[10]  M. Verhoye,et al.  Reduction of ECG and gradient related artifacts in simultaneously recorded human EEG/MRI data. , 2000, Magnetic resonance imaging.

[11]  C M Michel,et al.  EEG mapping and functional MRI in presurgical epilepsy evaluation. , 2001, Revue neurologique.

[12]  N. Thakor,et al.  Removal of ECG interference from the EEG recordings in small animals using independent component analysis , 2001, Journal of Neuroscience Methods.

[13]  Ivaylo I Christov,et al.  Real time electrocardiogram QRS detection using combined adaptive threshold , 2004, Biomedical engineering online.

[14]  Wei Lu,et al.  Constrained Independent Component Analysis , 2000, NIPS.

[15]  J. Riera,et al.  Artifact reduction for EEG / fMRI recording part 1 : nonlinear reduction of ballistocardiogram artifact , 2005 .

[16]  Rami K. Niazy,et al.  Removal of FMRI environment artifacts from EEG data using optimal basis sets , 2005, NeuroImage.

[17]  G. Srivastava,et al.  ICA-based procedures for removing ballistocardiogram artifacts from EEG data acquired in the MRI scanner , 2005, NeuroImage.

[18]  C A Czeisler,et al.  Variation of electroencephalographic activity during non‐rapid eye movement and rapid eye movement sleep with phase of circadian melatonin rhythm in humans , 1997, The Journal of physiology.

[19]  Erkki Oja,et al.  Independent component analysis: algorithms and applications , 2000, Neural Networks.

[20]  Aapo Hyvärinen,et al.  Fast and robust fixed-point algorithms for independent component analysis , 1999, IEEE Trans. Neural Networks.

[21]  O. Witte,et al.  Functional Mapping of the Human Brain , 2000 .

[22]  G. Tononi,et al.  Local sleep and learning , 2004, Nature.

[23]  Kazuki Iwata,et al.  Artifact reduction for EEG/fMRI recording: Nonlinear reductionof ballistocardiogram artifacts , 2006, Clinical Neurophysiology.

[24]  Terrence J. Sejnowski,et al.  An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.

[25]  S. Mukhopadhyay,et al.  A new interpretation of nonlinear energy operator and its efficacy in spike detection , 1998, IEEE Transactions on Biomedical Engineering.

[26]  E. Wolpert.  A Manual of Standardized Terminology, Techniques and Scoring System for Sleep Stages of Human Subjects. , 1969 .

[27]  Emery N. Brown,et al.  Motion and Ballistocardiogram Artifact Removal for Interleaved Recording of EEG and EPs during MRI , 2002, NeuroImage.

[28]  Jeffrey R. Binder,et al.  Simultaneous ERP and fMRI of the auditory cortex in a passive oddball paradigm , 2003, NeuroImage.

[29]  Frédéric Grouiller,et al.  A comparative study of different artefact removal algorithms for EEG signals acquired during functional MRI , 2007, NeuroImage.

[30]  Hyun Wook Park,et al.  Improved ballistocardiac artifact removal from the electroencephalogram recorded in fMRI , 2004, Journal of Neuroscience Methods.

[31]  S. Debener,et al.  Properties of the ballistocardiogram artefact as revealed by EEG recordings at 1.5, 3 and 7 T static magnetic field strength. , 2008, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[32]  J. Gotman,et al.  Quality of EEG in simultaneous EEG-fMRI for epilepsy , 2003, Clinical Neurophysiology.

[33]  Manuel Schabus,et al.  Hemodynamic cerebral correlates of sleep spindles during human non-rapid eye movement sleep , 2007, Proceedings of the National Academy of Sciences.

[34]  Andrzej Cichocki,et al.  Removal of ballistocardiogram artifacts from simultaneously recorded EEG and fMRI data using independent component analysis , 2006, IEEE Transactions on Biomedical Engineering.

[35]  Andreas Kleinschmidt,et al.  EEG-correlated fMRI of human alpha activity , 2003, NeuroImage.

[36]  Hellmuth Obrig,et al.  Correlates of alpha rhythm in functional magnetic resonance imaging and near infrared spectroscopy , 2003, NeuroImage.

[37]  Bettina Sorger,et al.  Improved quality of auditory event-related potentials recorded simultaneously with 3-T fMRI: Removal of the ballistocardiogram artefact , 2007, NeuroImage.

[38]  A. Rechtschaffen,et al.  A manual of standardized terminology, technique and scoring system for sleep stages of human subjects , 1968 .

[39]  Christian Kaufmann,et al.  Altered Processing of Acoustic Stimuli during Sleep: Reduced Auditory Activation and Visual Deactivation Detected by a Combined fMRI/EEG Study , 2002, NeuroImage.

[40]  Louis Lemieux,et al.  Identification of EEG Events in the MR Scanner: The Problem of Pulse Artifact and a Method for Its Subtraction , 1998, NeuroImage.