Neurovascular coupling in simultaneous EEG-fNIRS studies: A scoping review of analytical frameworks and clinical applications
5 affiliations
- 1Department of Sports Science, College of Education, Zhejiang University, Hangzhou, China; Science of Learning in Education Centre, National Institute of Education, Nanyang Technological University, Singapore
- 2Science of Learning in Education Centre, National Institute of Education, Nanyang Technological University, Singapore
- 3EuroMov Digital Health in Motion, University of Montpellier, IMT Mines Alès, France; Institut Universitaire de France (IUF), 1 rue Descartes CEDEX 05, Paris, 75231, France
- 4School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, 19104, USA; Department of Psychological and Brain Sciences, College of Arts and Sciences, Drexel University, Philadelphia, PA, 19104, USA; Drexel Solutions Institute, Drexel University, Philadelphia, PA, 19104, USA; A.J. Drexel Autism Institute, Drexel University, Philadelphia, PA, 19104, USA
- 5Science of Learning in Education Centre, National Institute of Education, Nanyang Technological University, Singapore; Physical Education and Sports Science Academic Department, National Institute of Education, Nanyang Technological University, Singapore; Corresponding author at: Science of Learning in Education Centre, National Institute of Education, Nanyang Technological University, Singapore.
Abstract
Simultaneous electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) have been used across cognitive and physiological states and in diverse clinical populations. However, the interpretation of cross-modal coupling remains difficult because findings from different analytical frameworks, populations, and experimental conditions have not been systematically mapped. This scoping review followed the Arksey and O’Malley framework and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). PubMed, Scopus, Web of Science, EBSCO, and IEEE Xplore were searched through February 10, 2026, for studies that quantitatively related simultaneously recorded EEG and fNIRS signals. Two reviewers independently screened the records. Findings were synthesized narratively, and analytical pipelines were mapped across the signal domain, feature extraction, coupling metric, and temporal lag handling. Fifty-seven studies were included. Amplitude-based studies related event-related potentials and oscillatory EEG features to focal hemodynamic responses, with associations varying across electrophysiological features, cortical regions, and task conditions. Frequency- and scale-specific analyses identified band-dependent relationships, while coupling at ultra-slow scales showed sensitivity to vascular and systemic physiological influences. Studies that explicitly modeled timing identified several-second offsets in some paradigms, while directional estimates varied across tasks and recording states. Network analyses showed partial and context-dependent correspondence between EEG- and fNIRS-derived measures, while model-based approaches characterized multivariate and predictive cross-modal relationships. Across frameworks, observed coupling differed with recording state, frequency band, cortical region, and temporal lag handling rather than representing a single quantity. Clinical findings were heterogeneous, and most condition-specific patterns were supported by small and methodologically diverse evidence bases. These findings support framework-matched analysis and pipeline-explicit reporting when interpreting EEG-fNIRS coupling.
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BibTeX
@article{wu2026neurovascular,
title = {{Neurovascular coupling in simultaneous EEG-fNIRS studies: A scoping review of analytical frameworks and clinical applications}},
author = {Yu Wu and Rajamanickam Yuvaraj and Stéphane Perrey and Hasan Ayaz and Wei-Peng Teo},
journal = {NeuroImage},
year = {2026},
month = oct,
doi = {10.1016/j.neuroimage.2026.122298},
url = {https://doi.org/10.1016/j.neuroimage.2026.122298},
note = {CC BY},
}
RIS
TY - JOUR
TI - Neurovascular coupling in simultaneous EEG-fNIRS studies: A scoping review of analytical frameworks and clinical applications
AU - Yu Wu
AU - Rajamanickam Yuvaraj
AU - Stéphane Perrey
AU - Hasan Ayaz
AU - Wei-Peng Teo
PY - 2026
DA - 2026/10/30
JO - NeuroImage
DO - 10.1016/j.neuroimage.2026.122298
UR - https://doi.org/10.1016/j.neuroimage.2026.122298
AB - Simultaneous electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) have been used across cognitive and physiological states and in diverse clinical populations. However, the interpretation of cross-modal coupling remains difficult because findings from different analytical frameworks, populations, and experimental conditions have not been systematically mapped. This scoping review followed the Arksey and O’Malley framework and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). PubMed, Scopus, Web of Science, EBSCO, and IEEE Xplore were searched through February 10, 2026, for studies that quantitatively related simultaneously recorded EEG and fNIRS signals. Two reviewers independently screened the records. Findings were synthesized narratively, and analytical pipelines were mapped across the signal domain, feature extraction, coupling metric, and temporal lag handling. Fifty-seven studies were included. Amplitude-based studies related event-related potentials and oscillatory EEG features to focal hemodynamic responses, with associations varying across electrophysiological features, cortical regions, and task conditions. Frequency- and scale-specific analyses identified band-dependent relationships, while coupling at ultra-slow scales showed sensitivity to vascular and systemic physiological influences. Studies that explicitly modeled timing identified several-second offsets in some paradigms, while directional estimates varied across tasks and recording states. Network analyses showed partial and context-dependent correspondence between EEG- and fNIRS-derived measures, while model-based approaches characterized multivariate and predictive cross-modal relationships. Across frameworks, observed coupling differed with recording state, frequency band, cortical region, and temporal lag handling rather than representing a single quantity. Clinical findings were heterogeneous, and most condition-specific patterns were supported by small and methodologically diverse evidence bases. These findings support framework-matched analysis and pipeline-explicit reporting when interpreting EEG-fNIRS coupling.
SN - 1095-9572
SN - 1053-8119
ER -