Top

Published in:

01-11-2016 | Original Paper

Removing Cardiac Artefacts in Magnetoencephalography with Resampled Moving Average Subtraction

Authors: Limin Sun, Seppo P. Ahlfors, Hermann Hinrichs

Published in: Brain Topography | Issue 6/2016

Abstract

Magnetoencephalography (MEG) signals are commonly contaminated by cardiac artefacts (CAs). Principle component analysis and independent component analysis have been widely used for removing CAs, but they typically require a complex procedure for the identification of CA-related components. We propose a simple and efficient method, resampled moving average subtraction (RMAS), to remove CAs from MEG data. Based on an electrocardiogram (ECG) channel, a template for each cardiac cycle was estimated by a weighted average of epochs of MEG data over consecutive cardiac cycles, combined with a resampling technique for accurate alignment of the time waveforms. The template was subtracted from the corresponding epoch of the MEG data. The resampling reduced distortions due to asynchrony between the cardiac cycle and the MEG sampling times. The RMAS method successfully suppressed CAs while preserving both event-related responses and high-frequency (>45 Hz) components in the MEG data.

Allen PJ, Polizzi G, Krakow K, Fish DR, Lemieux L (1998) Identification of EEG events in the MR scanner: the problem of pulse artifact and a method for its subtraction. Neuroimage 8:229–239CrossRefPubMed

Allen PJ, Josephs O, Turner R (2000) A method for removing imaging artifact from continuous EEG recorded during functional MRI. Neuroimage 12:230–239CrossRefPubMed

Becker R, Ritter P, Moosmann M, Villringer A (2005) Visual evoked potentials recovered from fMRI scan periods. Hum Brain Mapp 26:221–230CrossRefPubMed

Breuer L, Dammers J, Roberts TP, Shah NJ (2014a) A constrained ICA approach for real-time cardiac artifact rejection in magnetoencephalography. IEEE Trans Biomed Eng 61:405–414CrossRefPubMed

Breuer L, Dammers J, Roberts TP, Shah NJ (2014b) Ocular and cardiac artifact rejection for real-time analysis in MEG. J Neurosci Methods 233:105–114CrossRefPubMed

Cohen D (1972) Magnetoencephalography: detection of the brain’s electrical activity with a superconducting magnetometer. Science 175:664–666CrossRefPubMed

Dammers J, Schiek M, Boers F, Silex C, Zvyagintsev M, Pietrzyk U, Mathiak K (2008) Integration of amplitude and phase statistics for complete artifact removal in independent components of neuromagnetic recordings. IEEE Trans Biomed Eng 55:2353–2362CrossRefPubMed

de Munck JC, van Houdt PJ, Goncalves SI, van Wegen E, Ossenblok PP (2013) Novel artefact removal algorithms for co-registered EEG/fMRI based on selective averaging and subtraction. Neuroimage 64:407–415CrossRefPubMed

Ellingson ML, Liebenthal E, Spanaki MV, Prieto TE, Binder JR, Ropella KM (2004) Ballistocardiogram artifact reduction in the simultaneous acquisition of auditory ERPS and fMRI. Neuroimage 22:1534–1542CrossRefPubMed

Escudero J, Hornero R, Abasolo D, Fernandez A, Lopez-Coronado M (2007) Artifact removal in magnetoencephalogram background activity with independent component analysis. IEEE Trans Biomed Eng 54:1965–1973CrossRefPubMed

Escudero J, Hornero R, Abasolo D, Fernandez A (2011) Quantitative evaluation of artifact removal in real magnetoencephalogram signals with blind source separation. Ann Biomed Eng 39:2274–2286CrossRefPubMed

Feuerstein D, Parker KH, Boutelle MG (2009) Practical methods for noise removal: applications to spikes, nonstationary quasi-periodic noise, and baseline drift. Anal Chem 81:4987–4994CrossRefPubMed

Florin E, Bock E, Baillet S (2013) Targeted reinforcement of neural oscillatory activity with real-time neuroimaging feedback. Neuroimage 88C:54–60

Fonteneau E, Bozic M, Marslen-Wilson WD (2015) Brain network connectivity during language comprehension: interacting linguistic and perceptual subsystems. Cereb Cortex 25:3962–3976CrossRefPubMed

Garreffa G, Bianciardi M, Hagberg GE, Macaluso E, Marciani MG, Maraviglia B, Abbafati M, Carni M, Bruni I, Bianchi L (2004) Simultaneous EEG-fMRI acquisition: how far is it from being a standardized technique? Magn Reson Imaging 22:1445–1455CrossRefPubMed

Goldman RI, Stern JM, Engel J Jr, Cohen MS (2000) Acquiring simultaneous EEG and functional MRI. Clin Neurophysiol 111:1974–1980CrossRefPubMed

Hari R (2005) In: Niedermeyer E, da Lopes Silva F (eds) “Magnetoencephalography in clinical neurophysiological assessment of human cortical functions,” in Electroencephalography: basic principles, clinical applications, and related fields, 5th edn. Lippincott Williams & Wilkins, Philadelphia, pp 1165–1197

Hashimoto T, Elder CM, Vitek JL (2002) A template subtraction method for stimulus artifact removal in high-frequency deep brain stimulation. J Neurosci Methods 113:181–186CrossRefPubMed

Hyvärinen A (1999) Fast and robust fixed-point algorithms for independent component analysis. IEEE Trans Neural Netw 10:626–634CrossRefPubMed

Hyvärinen A, Oja E (1997) A fast fixed point algorithm for independent component analysis. Neural Comput 9(7):283–292CrossRef

Hämäläinen M, Hari R, Ilmoniemi RJ, Knuutila J, Lounasmaa OV (1993) Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain. Rev Mod Phys 65:413–497CrossRef

Jousmäki V, Hari R (1996) Cardiac artifacts in magnetoencephalogram. J Clin Neurophysiol 13:172–176CrossRefPubMed

LeVan P, Maclaren J, Herbst M, Sostheim R, Zaitsev M, Hennig J (2013) Ballistocardiographic artifact removal from simultaneous EEG-fMRI using an optical motion-tracking system. Neuroimage 75:1–11CrossRefPubMed

Mantini D, Franciotti R, Romani GL, Pizzella V (2008) Improving MEG source localizations: an automated method for complete artifact removal based on independent component analysis. Neuroimage 40:160–173CrossRefPubMed

Mellinger J, Schalk G, Braun C, Preissl H, Rosenstiel W, Birbaumer N, Kubler A (2007) An MEG-based brain-computer interface (BCI). Neuroimage 36:581–593CrossRefPubMedPubMedCentral

Ramirez RR, Kopell BH, Butson CR, Hiner BC, Baillet S (2011) Spectral signal space projection algorithm for frequency domain MEG and EEG denoising, whitening, and source imaging. Neuroimage 56:78–92CrossRefPubMed

Rodin E, Funke M, Haueisen J (2005) Cardio-respiratory contributions to the magnetoencephalogram. Brain Topogr 18:37–46CrossRefPubMed

Sander TH, Wubbeler G, Lueschow A, Curio G, Trahms L (2002) Cardiac artifact subspace identification and elimination in cognitive MEG data using time-delayed decorrelation. IEEE Trans Biomed Eng 49:345–354CrossRefPubMed

Shams N, Alain C, Strother S (2015) Comparison of BCG artifact removal methods for evoked responses in simultaneous EEG-fMRI. J Neurosci Methods 245:137–146CrossRefPubMed

Shao SY, Shen KQ, Ong CJ, Wilder-Smith EP, Li XP (2009) Automatic EEG artifact removal: a weighted support vector machine approach with error correction. IEEE Trans Biomed Eng 56:336–344CrossRefPubMed

Sun L, Hinrichs H (2009) Simultaneously recorded EEG-fMRI: removal of gradient artifacts by subtraction of head movement related average artifact waveforms. Hum Brain Mapp 30:3361–3377CrossRefPubMed

Sun L, Grutzner C, Bolte S, Wibral M, Tozman T, Schlitt S, Poustka F, Singer W, Freitag CM, Uhlhaas PJ (2012) Impaired gamma-band activity during perceptual organization in adults with autism spectrum disorders: evidence for dysfunctional network activity in frontal-posterior cortices. J Neurosci 32:9563–9573CrossRefPubMed

Tal I, Abeles M (2013) Cleaning MEG artifacts using external cues. J Neurosci Methods 217:31–38CrossRefPubMed

Taulu S, Kajola M, Simola J (2004) Suppression of interference and artifacts by the signal space separation method. Brain Topogr 16:269–275CrossRefPubMed

Uusitalo MA, Ilmoniemi RJ (1997) Signal-space projection method for separating MEG or EEG into components. Med Biol Eng Comput 35:135–140CrossRefPubMed

Welch PD (1967) The use of fast Fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms. IEEE Trans. Audio Electroacoust 15(2):17–20CrossRef

Title: Removing Cardiac Artefacts in Magnetoencephalography with Resampled Moving Average Subtraction
Authors: Limin Sun
Seppo P. Ahlfors
Hermann Hinrichs
Publication date: 01-11-2016
Publisher: Springer US
Published in: Brain Topography / Issue 6/2016
Print ISSN: 0896-0267
Electronic ISSN: 1573-6792
DOI: https://doi.org/10.1007/s10548-016-0513-3

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Removing Cardiac Artefacts in Magnetoencephalography with Resampled Moving Average Subtraction

Abstract

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Please log in to get access to this content

Other articles of this Issue 6/2016

Cortical Thinning at Midlife: The PATH Through Life Study

Articulation Artifacts During Overt Language Production in Event-Related Brain Potentials: Description and Correction

Commonalities in EEG Spectral Power Abnormalities Between Women With ADHD and Women With Bipolar Disorder During Rest and Cognitive Performance

Combined DTI–fMRI Analysis for a Quantitative Assessment of Connections Between WM Bundles and Their Peripheral Cortical Fields in Verbal Fluency

Developmental Trajectory of Beta Cortical Oscillatory Activity During a Knee Motor Task

Change in Excitability of Corticospinal Pathway and GABA-Mediated Inhibitory Circuits of Primary Motor Cortex Induced by Contraction of Adjacent Hand Muscle