Two is better? combining EEG and fMRI for BCI and neurofeedback: a systematic review

Abstract

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are two commonly used non-invasive techniques for measuring brain activity in neuroscience and brain- computer interfaces (BCI). While EEG has high temporal resolution and low spatial resolution, fMRI has high spatial resolution and low temporal resolution. In this review, we focus on the use of EEG and fMRI in neurofeedback (NF) and discuss the challenges of combining the two modalities in order to improve understanding of brain activity and achieve more effective clinical outcomes. Advanced technologies have been developed to simultaneously record EEG and fMRI signals in order to provide a better understanding of the relationship between the two modalities. However, the complexity of brain processes and the heterogeneous nature of EEG and fMRI present challenges in extracting useful information from the combined data. We will survey existing EEG-fMRI combinations and recent studies that exploit EEG-fMRI in NF, highlighting the experimental and technical challenges. We will also identify some of the remaining challenges in this field.

Consistency of resting-state correlations between fMRI networks and EEG band-power

“…Simultaneous EEG-fMRI studies have sought to identify electrophysiological correlates of fMRI RSNs, by leveraging the complementary characteristics of the two modalities. However, integrating EEG and fMRI data remains a challenge, and multiple multimodal data integration methods have been employed in the literature (Jorge et al, 2014; Abreu et al, 2018; Chang and Chen, 2021; Wirsich et al, 2023; Fleury et al, 2023).…”