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Review

Concurrent fNIRS and EEG for Brain Function Investigation: A Systematic, Methodology-Focused Review

1
Center for Interdisciplinary Brain Sciences Research, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
2
Department of Biomedical Engineering, University of Houston, Houston, TX 77004, USA
3
School of Mechanical Engineering, Pusan National University, Pusan 43241, Korea
4
Mallinckrodt Institute of Radiology, Washington University School of Medicine in St. Louis, 4515 McKinley Avenue, St. Louis, MO 63110, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Sung-Phil Kim
Sensors 2022, 22(15), 5865; https://doi.org/10.3390/s22155865 (registering DOI)
Received: 20 June 2022 / Revised: 27 July 2022 / Accepted: 30 July 2022 / Published: 5 August 2022
(This article belongs to the Special Issue Signal Processing for Brain–Computer Interfaces)
Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) stand as state-of-the-art techniques for non-invasive functional neuroimaging. On a unimodal basis, EEG has poor spatial resolution while presenting high temporal resolution. In contrast, fNIRS offers better spatial resolution, though it is constrained by its poor temporal resolution. One important merit shared by the EEG and fNIRS is that both modalities have favorable portability and could be integrated into a compatible experimental setup, providing a compelling ground for the development of a multimodal fNIRS–EEG integration analysis approach. Despite a growing number of studies using concurrent fNIRS-EEG designs reported in recent years, the methodological reference of past studies remains unclear. To fill this knowledge gap, this review critically summarizes the status of analysis methods currently used in concurrent fNIRS–EEG studies, providing an up-to-date overview and guideline for future projects to conduct concurrent fNIRS–EEG studies. A literature search was conducted using PubMed and Web of Science through 31 August 2021. After screening and qualification assessment, 92 studies involving concurrent fNIRS–EEG data recordings and analyses were included in the final methodological review. Specifically, three methodological categories of concurrent fNIRS–EEG data analyses, including EEG-informed fNIRS analyses, fNIRS-informed EEG analyses, and parallel fNIRS–EEG analyses, were identified and explained with detailed description. Finally, we highlighted current challenges and potential directions in concurrent fNIRS–EEG data analyses in future research. View Full-Text
Keywords: EEG; functional NIRS; multimodal neuroimaging; concurrent recording; integrated analysis EEG; functional NIRS; multimodal neuroimaging; concurrent recording; integrated analysis
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MDPI and ACS Style

Li, R.; Yang, D.; Fang, F.; Hong, K.-S.; Reiss, A.L.; Zhang, Y. Concurrent fNIRS and EEG for Brain Function Investigation: A Systematic, Methodology-Focused Review. Sensors 2022, 22, 5865. https://doi.org/10.3390/s22155865

AMA Style

Li R, Yang D, Fang F, Hong K-S, Reiss AL, Zhang Y. Concurrent fNIRS and EEG for Brain Function Investigation: A Systematic, Methodology-Focused Review. Sensors. 2022; 22(15):5865. https://doi.org/10.3390/s22155865

Chicago/Turabian Style

Li, Rihui, Dalin Yang, Feng Fang, Keum-Shik Hong, Allan L. Reiss, and Yingchun Zhang. 2022. "Concurrent fNIRS and EEG for Brain Function Investigation: A Systematic, Methodology-Focused Review" Sensors 22, no. 15: 5865. https://doi.org/10.3390/s22155865

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