Literature DB >> 17462844

Evaluating gradient artifact correction of EEG data acquired simultaneously with fMRI.

Petra Ritter1, Robert Becker, Christine Graefe, Arno Villringer.   

Abstract

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) has become a widely used application in spite of EEG perturbations due to electromagnetic interference in the MR environment. The most prominent and disturbing artifacts in the EEG are caused by the alternating magnetic fields (gradients) of the MR scanner. Different methods for gradient artifact correction have been developed. Here we propose an approach for the systematic evaluation and comparison of these gradient artifact correction methods. Exemplarily, we evaluate different algorithms all based on artifact template subtraction--the currently most established means of gradient artifact removal. We introduce indices for the degree of gradient artifact reduction and physiological signal preservation. The combination of both indices was used as a measure for the overall performance of gradient artifact removal and was shown to be useful in identifying problems during artifact removal. We demonstrate that the evaluation as proposed here allows to reveal frequency-band specific performance differences among the algorithms. This emphasizes the importance of carefully selecting the artifact correction method appropriate for the respective case.

Mesh:

Year:  2007        PMID: 17462844     DOI: 10.1016/j.mri.2007.03.005

Source DB:  PubMed          Journal:  Magn Reson Imaging        ISSN: 0730-725X            Impact factor:   2.546


  17 in total

1.  Rolandic alpha and beta EEG rhythms' strengths are inversely related to fMRI-BOLD signal in primary somatosensory and motor cortex.

Authors:  Petra Ritter; Matthias Moosmann; Arno Villringer
Journal:  Hum Brain Mapp       Date:  2009-04       Impact factor: 5.038

2.  The virtual brain integrates computational modeling and multimodal neuroimaging.

Authors:  Petra Ritter; Michael Schirner; Anthony R McIntosh; Viktor K Jirsa
Journal:  Brain Connect       Date:  2013

3.  Data quality in fMRI and simultaneous EEG-fMRI.

Authors:  Toni Ihalainen; Linda Kuusela; Sampsa Turunen; Sami Heikkinen; Sauli Savolainen; Outi Sipilä
Journal:  MAGMA       Date:  2014-04-26       Impact factor: 2.310

4.  Statistical feature extraction for artifact removal from concurrent fMRI-EEG recordings.

Authors:  Zhongming Liu; Jacco A de Zwart; Peter van Gelderen; Li-Wei Kuo; Jeff H Duyn
Journal:  Neuroimage       Date:  2011-10-20       Impact factor: 6.556

5.  Inferring multi-scale neural mechanisms with brain network modelling.

Authors:  Michael Schirner; Anthony Randal McIntosh; Viktor Jirsa; Gustavo Deco; Petra Ritter
Journal:  Elife       Date:  2018-01-08       Impact factor: 8.140

6.  Exploring the advantages of multiband fMRI with simultaneous EEG to investigate coupling between gamma frequency neural activity and the BOLD response in humans.

Authors:  Makoto Uji; Ross Wilson; Susan T Francis; Karen J Mullinger; Stephen D Mayhew
Journal:  Hum Brain Mapp       Date:  2018-01-13       Impact factor: 5.038

7.  Development, validation, and comparison of ICA-based gradient artifact reduction algorithms for simultaneous EEG-spiral in/out and echo-planar fMRI recordings.

Authors:  S Ryali; G H Glover; C Chang; V Menon
Journal:  Neuroimage       Date:  2009-07-04       Impact factor: 6.556

Review 8.  Functional MRI using robotic MRI compatible devices for monitoring rehabilitation from chronic stroke in the molecular medicine era (Review).

Authors:  Loukas G Astrakas; Syed Hassan Naqvi; Babak Kateb; A Aria Tzika
Journal:  Int J Mol Med       Date:  2012-03-15       Impact factor: 4.101

Review 9.  Physiological recordings: basic concepts and implementation during functional magnetic resonance imaging.

Authors:  Marcus A Gray; Ludovico Minati; Neil A Harrison; Peter J Gianaros; Vitaly Napadow; Hugo D Critchley
Journal:  Neuroimage       Date:  2009-05-19       Impact factor: 6.556

Review 10.  State-dependencies of learning across brain scales.

Authors:  Petra Ritter; Jan Born; Michael Brecht; Hubert R Dinse; Uwe Heinemann; Burkhard Pleger; Dietmar Schmitz; Susanne Schreiber; Arno Villringer; Richard Kempter
Journal:  Front Comput Neurosci       Date:  2015-02-26       Impact factor: 2.380

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