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

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 focal...

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Bibliographic Details
Published in:NeuroImage (Orlando, Fla.) Fla.), 2007-08, Vol.37 (1), p.202-211
Main Authors: Masterton, Richard A.J., Abbott, David F., Fleming, Steven W., Jackson, Graeme D.
Format: Article
Language:English
Subjects:
Action Potentials - physiology
Adult
Ballistocardiography
Cerebral Cortex - physiopathology
Computer Simulation
Decomposition
Electrodes
Electroencephalography - methods
Epilepsy
Epilepsy - diagnosis
Epilepsy - physiopathology
Female
Fourier Analysis
Humans
Image Processing, Computer-Assisted - methods
Least-Squares Analysis
Magnetic fields
Magnetic Resonance Imaging - methods
Male
Methods
Middle Aged
Reference Values
Reproducibility of Results
Scanners
Signal Processing, Computer-Assisted
Software
Studies
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Description
Summary: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.
ISSN:1053-8119
1095-9572
DOI:10.1016/j.neuroimage.2007.02.060