EEG-Informed fMRI: A Review of Data Analysis Methods

Abstract

The simultaneous acquisition of electroencephalography (EEG) with functional magnetic resonance imaging (fMRI) is a very promising non-invasive technique for the study of human brain function. Despite continuous improvements, it remains a challenging technique, and a standard methodology for data analysis is yet to be established. Here we review the methodologies that are currently available to address the challenges at each step of the data analysis pipeline. We start by surveying methods for pre-processing both EEG and fMRI data. On the EEG side, we focus on the correction for several MR-induced artifacts, particularly the gradient and pulse artifacts, as well as other sources of EEG artifacts. On the fMRI side, we consider image artifacts induced by the presence of EEG hardware inside the MR scanner, and the contamination of the fMRI signal by physiological noise of non-neuronal origin, including a review of several approaches to model and remove it. We then provide an overview of the approaches specifically employed for the integration of EEG and fMRI when using EEG to predict the blood oxygenation level dependent (BOLD) fMRI signal, the so-called EEG-informed fMRI integration strategy, the most commonly used strategy in EEG-fMRI research. Finally, we systematically review methods used for the extraction of EEG features reflecting neuronal phenomena of interest.

EPI distortion correction for simultaneous human brain stimulation and imaging at 3T

“…Nevertheless, in the event that the TMS system does introduce problematic spatial artifacts and signal loss, PSF-EPI may be helpful particularly when specialized hardware solutions for treating susceptibility effects are unavailable. PSF-EPI may also be a general solution for multimodal stimulation and imaging studies (e.g., EEG-fMRI (Liu et al, 2006;Abreu et al, 2018), tDCS-fMRI (Callan et al, 2016), and focused ultrasound-fMRI (Legon et al, 2014) that require the introduction of metallic hardware into the scanner environment. Moreover, PSF-EPI may hold great promise for measuring functional connectivity from the combination of simultaneous TMS-fMRI and resting state fMRI (Fox et al, 2012).…”

A sparse EEG-informed fMRI model for hybrid EEG-fMRI neurofeedback prediction

“…During the past few years, the use of simultaneous EEG-fMRI recording has been used to understand the links between EEG and fMRI in different states of the brain activity and received recognition as a promising multi-modal measurement of the brain activity (Perronnet et al, 2018;Abreu et al, 2018).…”

“…However this bi-modal acquisition is not comfortable for subjects or patients, due to the use of the fMRI scanner. The methodology to extract information from fMRI with EEG have been also intensively investigated (some methods involved in the process are reviewed here (Abreu et al, 2018)). Indeed, both modalities are sensitive to different aspect of brain activity, with different speeds.…”

“…In the literature, the term EEG-informed fMRI refers to methods extracting features from EEG signals in order to derive a predictor of the associated BOLD signal in the region of interest under study. A recent review (Abreu et al, 2018) gives a good overview of the principal EEG-informed fMRI methods and their limitations. Different strategies have been investigated, depending on the type of activity under study (epilepsy, resting state, open/closed eyes, relaxation): either by selecting one channel on interest, either by using multiple channels, before extracting features of interest.…”

Linking visual gamma to task‐related brain networks—a simultaneous EEG‐fMRI study

“…According to Bastos and colleagues, these influences extend to network operations that are also beyond the visual cortex. Thus, the inclusion of this electrophysiological measure in functional connectivity analysis appears to be a promising avenue (Abreu, Leal, & Figueiredo, ).…”