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Source localisation in concurrent EEG/fMRI: applications at 7T.

Matthew J Brookes1, Jiri Vrba, Karen J Mullinger

  • 1Sir Peter Mansfield Magnetic Resonance Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK. matthew.brookes@nottingham.ac.uk

Neuroimage
|December 4, 2008
PubMed
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This summary is machine-generated.

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Source reconstruction methods accurately locate EEG sources and reduce MR scanner interference. Beamformers with higher channel density (64 EEG channels) offer superior interference reduction for simultaneous EEG/fMRI at 7T.

Area of Science:

  • Neuroimaging
  • Biomedical Engineering
  • Signal Processing

Background:

  • Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) at 7 Tesla (7T) offers high spatiotemporal resolution.
  • However, MR scanner-induced interference significantly contaminates EEG signals, complicating analysis.
  • Source reconstruction techniques are crucial for mitigating this interference and improving EEG data quality.

Purpose of the Study:

  • To evaluate the accuracy and efficacy of EEG source reconstruction methods for concurrent 7T EEG/fMRI.
  • To compare the performance of dipole fitting and beamformer algorithms in localizing simulated and phantom EEG sources.
  • To assess the impact of EEG channel density on interference reduction and signal quality.

Main Methods:

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  • EEG phantom experiments with a controlled dipolar current source were conducted.
  • Dipole fitting and beamformer algorithms were applied for source localization.
  • Simulations and theoretical analyses were used to demonstrate interference reduction properties.
  • In-vivo 7T EEG/fMRI experiments were performed using a 64-channel EEG system.

    • Main Results:

    • Both dipole fitting and beamformer methods accurately localized the dipole source in the EEG phantom.
    • Source reconstruction significantly reduced MR scanner interference in recorded EEG data.
    • Beamformers demonstrated superior interference suppression compared to dipole fitting due to adaptive weighting.
    • Increasing EEG channel density from 32 to 64 channels improved the signal-to-interference ratio by approximately 1.6 using the beamformer.
    • Gamma band effects were successfully recorded in vivo using the beamformer on 64-channel EEG data.

    Conclusions:

    • Source reconstruction methodologies are effective for accurate EEG source localization in 7T concurrent EEG/fMRI.
    • Beamformer approaches, particularly with higher channel density, provide enhanced interference reduction.
    • These advancements enable the reliable recording of neural activity, such as gamma band effects, during simultaneous 7T EEG/fMRI acquisition.