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Best Current Practice for Obtaining High Quality EEG Data During Simultaneous fMRI
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Real-time EEG artifact correction during fMRI using ICA.

Ahmad Mayeli1, Vadim Zotev2, Hazem Refai3

  • 1Laureate Institute for Brain Research, Tulsa, OK, USA; Department of Electrical and Computer Engineering, University of Oklahoma, Tulsa, OK, USA.

Journal of Neuroscience Methods
|October 5, 2016
PubMed
Summary
This summary is machine-generated.

A new real-time artifact correction method, rtICA, improves electroencephalogram (EEG) signal quality during simultaneous EEG and functional magnetic resonance imaging (fMRI). This method effectively reduces artifacts without impacting neural signals, offering a significant advancement for neurofeedback applications.

Keywords:
EEGEEG-fMRIReal-time ICAReal-time artifact correctionfMRI

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Simultaneous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) acquisition is challenged by artifact contamination from imaging (MR) and ballistocardiogram (BCG).
  • Real-time artifact correction is crucial for applications like neurofeedback, yet current software-only methods are limited.
  • Average artifact subtraction (AAS) is the most common real-time technique but only partially removes artifacts and requires no extra hardware.

Purpose of the Study:

  • To introduce and validate a novel, improved real-time approach for correcting EEG artifacts during fMRI acquisition.
  • To enhance EEG signal quality for real-time applications by reducing MR and BCG artifacts.
  • To provide an alternative to existing real-time artifact correction methods.

Main Methods:

  • Development and implementation of a real-time Independent Component Analysis (ICA) method, termed rtICA.
  • rtICA is applied following the Average Artifact Subtraction (AAS) method for enhanced artifact removal.
  • Validation through simultaneous EEG and fMRI experiments on healthy subjects.

Main Results:

  • The rtICA method achieved 98.4% success in detecting eye blinks.
  • Demonstrated a 4.4 times greater reduction in Ballistocardiogram (BCG) artifacts compared to RecView-corrected data.
  • Effectively reduced motion, imaging, and muscle artifacts in real-time, validated across six healthy subjects.

Conclusions:

  • A novel real-time ICA method (rtICA) significantly improves EEG signal quality during fMRI.
  • The rtICA method effectively reduces various artifacts, including MR, BCG, motion, and muscle artifacts.
  • Importantly, rtICA preserves neural signals within relevant EEG frequency bands, such as the alpha band.