The following table highlights some key scientific studies supporting the technologies behind Mendi; including functional near-infrared spectroscopy (fNIRS) and neurofeedback training.
These works cover foundational discoveries, safety validation, and findings on attention, emotional regulation, and neuroplasticity.
fNIRS & Neurofeedback Research Summary
| Title of Research | Key Findings | Source |
|---|---|---|
| Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters | First demonstration that near-infrared light can safely pass through living tissue to measure oxygenation; foundation of fNIRS. | Jöbsis, F. F. (1977). Science, 198(4323), 1264–1267. https://pubmed.ncbi.nlm.nih.gov/929199/ |
| A brief review on the history of human functional near-infrared spectroscopy (fNIRS) development and fields of application | Overview of fNIRS history, physics, and applications; confirms strong agreement with fMRI signals and long-term safety. | Ferrari, M., & Quaresima, V. (2012). NeuroImage, 63(2), 921–935. https://doi.org/10.1016/j.neuroimage.2012.03.049 |
| Interdisciplinary views of fNIRS: Current advancements, equity challenges, and an agenda for future needs of a diverse fNIRS research community | Reviews modern fNIRS techniques, wearable systems, and accessibility across neuroscience fields. | Doherty, E. J., et al. (2023). Frontiers in Integrative Neuroscience, 17, 1059679. https://pubmed.ncbi.nlm.nih.gov/36922983/ |
| Optical brain imaging and its application to neurofeedback | Describes how optical methods like fNIRS enable real-time brain feedback; validates safety and signal reliability. | Soekadar, S. R., et al. (2021). NeuroImage: Clinical, 30, 102577. https://doi.org/10.1016/j.nicl.2021.102577 |
| Closed-loop brain training: The science of neurofeedback | Defines neurofeedback as a self-regulation learning system; summarizes mechanisms of brain plasticity across EEG, fMRI, and fNIRS. | Sitaram, R., et al. (2017). Nature Reviews Neuroscience, 18(2), 86–100. https://doi.org/10.1038/nrn.2016.164 |
| The potential of functional near-infrared spectroscopy-based neurofeedback—A systematic review and recommendations for best practice | Comprehensive review of fNIRS neurofeedback studies (22 total); concludes participants can learn to regulate brain activity with fNIRS. | Kohl, S. H., et al. (2020). Frontiers in Neuroscience, 14, 594. https://doi.org/10.3389/fnins.2020.00594 |
| Improving attention through individualized fNIRS neurofeedback training: A pilot study | fNIRS-based training improved sustained attention; demonstrated individualized neurofeedback protocols. | Gu, Y., et al. (2022). Brain Sciences, 12(7), 862. https://doi.org/10.3390/brainsci12070862 |
| fNIRS-based neurofeedback for prefrontal cortex modulation: A proof-of-concept study | Demonstrated voluntary up-regulation of prefrontal activity using fNIRS feedback in healthy adults. | Yakovlev, L., et al. (2025). bioRxiv. https://doi.org/10.1101/2025.10.02.679948 |
| Neurofeedback Treatment on Depressive Symptoms and Functional Recovery in Treatment-Resistant Patients with Major Depressive Disorder: an Open-Label Pilot Study | Despite the small sample size, these results suggest that neurofeedback treatment may be effective as an augmentation treatment, not only for depressive symptoms, but also for functional recovery, in patients with TRD. |
Lee, H., et al. (2019). Frontiers in Psychiatry, 10, 542. https://jkms.org/DOIx.php?id=10.3346/jkms.2019.34.e287 |
| Sustained effects of neurofeedback in ADHD: A systematic review and meta-analysis | Evidence of lasting attention improvements after structured neurofeedback training in ADHD populations. | Van Doren, J., et al. (2019). European Child & Adolescent Psychiatry, 28(3), 293–305. https://doi.org/10.1007/s00787-018-1121-4 |
| The potential of real-time fMRI neurofeedback for stroke rehabilitation: A systematic review | Shows how feedback-based self-regulation can aid recovery of motor and cognitive function post-stroke. | Wang, T., et al. (2019). Frontiers in Human Neuroscience, 13, 528. https://doi.org/10.3389/fnhum.2019.00528 |
| Consumer-Grade Electroencephalogram and Functional Near-Infrared Spectroscopy Neurofeedback Technologies for Mental Health and Wellbeing | Reviews consumer neurotechnology; concludes modern EEG/fNIRS wearables are safe and potentially beneficial for wellbeing. | Flanagan, K., & Saikia, M. J. (2023). Sensors, 23(20), 8482. https://doi.org/10.3390/s23208482 |
|
Validation of a consumer-grade functional Near-Infrared Spectroscopy device for measurement of frontal pole brain oxygenation – an interim report |
A Mendi specific study which found strong correlation (r = 0.81) between consumer and lab-grade fNIRS signals; supports at-home research use. | Högman, L., & Dravniknes, H. (2020). Stockholm University Interim Report. https://mendi-webpage.s3.eu-north-1.amazonaws.com/Mendi_signal_validation_interim_report_final.pdf |
| Wearable functional near-infrared spectroscopy for measuring dissociable activation dynamics of prefrontal cortex subregions during working memory | Demonstrated dissociable activation patterns in prefrontal subregions during cognitive tasks; confirms measurement precision. | Shin, J. H., Kang, M. J., & Lee, S. A. (2024). Human Brain Mapping, 45(2), e26619. https://doi.org/10.1002/hbm.26619 |
In Summary
fNIRS is a validated, non-invasive imaging technology used worldwide in research and medicine.
Neurofeedback using fNIRS and EEG has been shown to improve attention, emotional regulation, and cognitive control.
Decades of research confirm fNIRS is safe, reliable, and correlates closely with fMRI in measuring brain activity.
Modern wearables now allow these benefits to be practiced outside the lab — bringing neuroscience into everyday life.