Literature DB >> 17582785

Measurement and reduction of motion and ballistocardiogram artefacts from simultaneous EEG and fMRI recordings.

Richard A J Masterton1, David F Abbott, Steven W Fleming, Graeme D Jackson.   

Abstract

Recording the electroencephalogram (EEG) during functional magnetic resonance imaging (fMRI) permits the identification of haemodynamic changes associated with EEG events. However, subject motion within the MR scanner can cause unpredictable and frustrating artefacts on the EEG that may appear focally, bilaterally or unilaterally and can sometimes be confused for epileptiform activity. Motion may arise from a number of sources: small involuntary cardiac-related body movements (ballistocardiogram); acoustic vibrations due to the scanner machinery; and voluntary subject movements. Here we describe a new real-time technique for removing ballistocardiogram (BCG) and movement artefact from EEG recordings in the MR scanner using a novel method for recording subject motion. We record the current induced in a number of wire loops, attached to a cap worn by the subject, due to motion in the static magnetic field of the scanner (Faraday's Law). This is the same process that leads to the motion artefacts on the EEG, and hence these signals are ideally suited to filtering these artefacts from the EEG. Our filter uses a linear adaptive technique based upon the Recursive Least Squares (RLS) algorithm. We demonstrate in both simulations and real EEG recordings from epilepsy patients that our filter significantly reduces the artefact power whilst preserving the underlying EEG signal.

Entities:  

Mesh:

Year:  2007        PMID: 17582785     DOI: 10.1016/j.neuroimage.2007.02.060

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  33 in total

1.  Adaptive removal of gradients-induced artefacts on ECG in MRI: a performance analysis of RLS filtering.

Authors:  Mario Sansone; Luciano Mirarchi; Marcello Bracale
Journal:  Med Biol Eng Comput       Date:  2010-03-18       Impact factor: 2.602

2.  Networks underlying paroxysmal fast activity and slow spike and wave in Lennox-Gastaut syndrome.

Authors:  Neelan Pillay; John S Archer; Radwa A B Badawy; Danny F Flanagan; Samuel F Berkovic; Graeme Jackson
Journal:  Neurology       Date:  2013-07-17       Impact factor: 9.910

3.  SSVEP signatures of binocular rivalry during simultaneous EEG and fMRI.

Authors:  Keith W Jamison; Abhrajeet V Roy; Sheng He; Stephen A Engel; Bin He
Journal:  J Neurosci Methods       Date:  2015-01-30       Impact factor: 2.390

4.  Physical modeling of pulse artefact sources in simultaneous EEG/fMRI.

Authors:  Winston X Yan; Karen J Mullinger; Gerda B Geirsdottir; Richard Bowtell
Journal:  Hum Brain Mapp       Date:  2010-04       Impact factor: 5.038

5.  Dynamic coupling between fMRI local connectivity and interictal EEG in focal epilepsy: A wavelet analysis approach.

Authors:  Amir Omidvarnia; Mangor Pedersen; David N Vaughan; Jennifer M Walz; David F Abbott; Andrew Zalesky; Graeme D Jackson
Journal:  Hum Brain Mapp       Date:  2017-07-24       Impact factor: 5.038

6.  An empirical investigation of motion effects in eMRI of interictal epileptiform spikes.

Authors:  Padmavathi Sundaram; Robert V Mulkern; William M Wells; Christina Triantafyllou; Tobias Loddenkemper; Ellen J Bubrick; Darren B Orbach
Journal:  Magn Reson Imaging       Date:  2011-05-08       Impact factor: 2.546

7.  Unified Retrospective EEG Motion Educated Artefact Suppression for EEG-fMRI to Suppress Magnetic Field Gradient Artefacts During Motion.

Authors:  Danilo Maziero; Victor A Stenger; David W Carmichael
Journal:  Brain Topogr       Date:  2021-09-23       Impact factor: 3.020

8.  Ballistocardiogram artifact removal with a reference layer and standard EEG cap.

Authors:  Qingfei Luo; Xiaoshan Huang; Gary H Glover
Journal:  J Neurosci Methods       Date:  2014-06-22       Impact factor: 2.390

9.  Presurgical brain mapping in epilepsy using simultaneous EEG and functional MRI at ultra-high field: feasibility and first results.

Authors:  Frédéric Grouiller; João Jorge; Francesca Pittau; Wietske van der Zwaag; Giannina Rita Iannotti; Christoph Martin Michel; Serge Vulliémoz; Maria Isabel Vargas; François Lazeyras
Journal:  MAGMA       Date:  2016-03-05       Impact factor: 2.310

10.  Geometric classification of brain network dynamics via conic derivative discriminants.

Authors:  Matthew F Singh; Todd S Braver; ShiNung Ching
Journal:  J Neurosci Methods       Date:  2018-06-30       Impact factor: 2.390

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