Artifact Reduction in Simultaneous EEG-fMRI: A Systematic Review of Methods and Contemporary Usage.

Madeleine Bullock,David F Abbott,Graeme D Jackson

doi:10.3389/fneur.2021.622719

Abstract

Simultaneous electroencephalography-functional MRI (EEG-fMRI) is a technique that combines temporal (largely from EEG) and spatial (largely from fMRI) indicators of brain dynamics. It is useful for understanding neuronal activity during many different event types, including spontaneous epileptic discharges, the activity of sleep stages, and activity evoked by external stimuli and decision-making tasks. However, EEG recorded during fMRI is subject to imaging, pulse, environment and motion artifact, causing noise many times greater than the neuronal signals of interest. Therefore, artifact removal methods are essential to ensure that artifacts are accurately removed, and EEG of interest is retained. This paper presents a systematic review of methods for artifact reduction in simultaneous EEG-fMRI from literature published since 1998, and an additional systematic review of EEG-fMRI studies published since 2016. The aim of the first review is to distill the literature into clear guidelines for use of simultaneous EEG-fMRI artifact reduction methods, and the aim of the second review is to determine the prevalence of artifact reduction method use in contemporary studies. We find that there are many published artifact reduction techniques available, including hardware, model based, and data-driven methods, but there are few studies published that adequately compare these methods. In contrast, recent EEG-fMRI studies show overwhelming use of just one or two artifact reduction methods based on literature published 15–20 years ago, with newer methods rarely gaining use outside the group that developed them. Surprisingly, almost 15% of EEG-fMRI studies published since 2016 fail to adequately describe the methods of artifact reduction utilized. We recommend minimum standards for reporting artifact reduction techniques in simultaneous EEG-fMRI studies and suggest that more needs to be done to make new artifact reduction techniques more accessible for the researchers and clinicians using simultaneous EEG-fMRI.

Highlights

Simultaneous electroencephalography (EEG) and functional MRI is a non-invasive imaging method first described over 25 years ago, and early on was mostly used for characterizing seizure location in epilepsy patients [1, 2]
A technical challenge with recording simultaneous EEG-functional MRI (fMRI) is that EEG recorded inside the MR environment is subject to large sources of noise, which can obscure neuronal activity, or induce artificial artifacts in the EEG recording [11]
Our review provides a comprehensive overview of all artifact reduction methods available since 1998, and there is an opportunity for future studies to compare these different methods in one comprehensive data set to independently validate the best pipeline for artifact reduction in EEG-fMRI

Summary

Introduction

Simultaneous electroencephalography (EEG) and functional MRI (fMRI) is a non-invasive imaging method first described over 25 years ago, and early on was mostly used for characterizing seizure location in epilepsy patients [1, 2]. Given the many artifacts and their impact, methods to reduce all artifacts are crucial to ensuring that the EEG recorded during EEG-fMRI is an accurate representation of brain activity. The earliest algorithm for artifact removal in EEG-fMRI was the average artifact subtraction (AAS) method, which was adapted to remove either BCG [19] or GA [15], and permitted the first fully simultaneous EEG-fMRI. In the years since the publication of the AAS method, many novel methods have been proposed to improve accuracy of EEG-fMRI, and research in this area is ongoing [20]. An aim of this review is to distill the literature from these 21 years and provide updated recommendations about artifact reduction to those interested in practicing EEG-fMRI

Methods

Results

Conclusion