A method for removing imaging artifact from continuous EEG recorded during functional MRI.

By P. Allen, Oliver Josephs, Robert Turner. NeuroImage, 2000

1,344 citations recorded by the source corpus.

Subfields: Atomic and Molecular Physics, and Optics, Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/73a721075db9fbd85aab765207a387398b7b5984

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In Atomic and Molecular Physics, and Optics

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Citations in the corpus

EEG-correlated fMRI of human alpha activity (2003, methodology): “Two types of MRI artifact reduction techniques have been described: first, the subtraction of an average image artifact from the EEG (Allen et al., 2000) and, second, band-stop filtering in the frequency domain (Hoffmann et al.”
Spontaneous brain activity and EEG microstates. A novel EEG/fMRI analysis approach to explore resting-state networks (2010, methodology): “Gradient artifact correction was performed using modified versions of the algorithms proposed by Allen et al. (2000), where a gradient artifact template is subtracted from the EEG using a baseline corrected sliding average of 20 MR-volumes.”
BOLD correlates of EEG alpha phase-locking and the fMRI default mode network (2009, methodology): “An average pulse artifact was computed spanning the period between two Scan-Start-Markers (1980 ms=1TR) and subtracted from the individual pulse artifacts following the procedure developed by Allen et al. (2000, 1998).”
Spatiotemporal dynamics of the brain at rest - Exploring EEG microstates as electrophysiological signatures of BOLD resting state networks (2012, methodology): “The EEG data acquired simultaneously with the fMRI data were corrected for artifacts related to the gradient switching and cardiac ballistic effect using the template subtraction method (Allen et al., 1998; Allen et al., 2000) implemented in BrainVision Analyzer software (Brain Products GmbH, Munich”
Don't fear ‘fear conditioning’: Methodological considerations for the design and analysis of studies on human fear acquisition, extinction, and return of fear (2017, positive): “For EEG/EMG/startle data (e.g. Lindner et al., 2015), imaging rtefact removal is indispensable and can be achieved through umerous methods and software (Allen et al., 1998, 2000; Garreffa t al., 2003; Mantini et al., 2007; Niazy et al., 2005; Ritter et al., 007; Ullsperger and Debener, 2010).”
Trial-by-trial coupling between EEG and BOLD identifies networks related to alpha and theta EEG power increases during working memory maintenance (2009, methodology): “The EEG data recorded inside the MR scanner were corrected for gradient and pulse artifacts along the lines described by Allen et al. (1998,2000) using Vision Analyzer (Brainproducts).”
The feedback-related negativity (FRN) revisited: New insights into the localization, meaning and network organization (2014, methodology): “MR-artifact correction was computed using implemented sliding average subtraction (Allen et al., 2000).”
EEG correlates of time-varying BOLD functional connectivity (2013, neutral): “Gradient and ballistocardiogram artifacts in the EEG data were treated using EGI's NetStation software, which implements methods based on template subtraction (Allen et al., 2000) and principal component analysis (Niazy et al., 2005), respectively.”
Correlates of alpha rhythm in functional magnetic resonance imaging and near infrared spectroscopy (2003, methodology): “Continuous EEG evaluation during fMRI scans only recently became an option with the advent of adapted EEG amplifiers and adaptive artifact filter algorithms (Sijbers et al., 1999; Allen et al., 2000; Hoffmann et al., 2000).”
Removal of FMRI environment artifacts from EEG data using optimal basis sets (2005, methodology): “This validation, however, was not intended to assess the general performance of IAR, but rather to compare it to FASTR given a generic, limited setup.”
Trial-by-Trial Coupling of Concurrent Electroencephalogram and Functional Magnetic Resonance Imaging Identifies the Dynamics of Performance Monitoring (2005, methodology): “EEG data were corrected for MR gradient and ballistocardiac artifacts by applying modified versions of the algorithms proposed by Allen and colleagues (Allen et al., 1998, 2000 pass-filtered data, using a baseline-corrected sliding average of 20 consecutive volumes.”
Brain activity relating to the contingent negative variation: an fMRI investigation (2004, methodology): “Imaging and pulse artifacts were processed using an established in-house EEG analysis system (Allen et al., 1998, 2000).”
Non-white noise in fMRI: Does modelling have an impact? (2006, positive): “If filtering techniques known from simultaneous EEG-fMRI (Allen et al., 2000) were applied it should be possible to increase the precision of the phase estimated from the ECG time-courses.”