byIngrid Fadelli, Phys.org

How the researchers collected their experimental data. Credit: Yucel et al.

Functional near-infrared spectroscopy (fNIRS) is a promising non-invasive neuroimaging technique that works by detecting changes in blood oxygenation linked to neural activity using near-infrared light. Compared to fMRI and various other methods commonly used to study the brain, fNIRS is easier to apply outside of laboratory settings.

This technique requires study participants to wear a special cap fitted with optodes, which consist of light sources that emit near-infrared light into the scalp and detectors that measure the light that is reflected back. These measurements can be used to estimate blood oxygenation in the brain's outer layers. Despite its potential for conducting research in everyday settings, the quality of signals collected using fNIRS is known to be influenced by biophysical factors.

A team of researchers at Boston University recently set out to better delineate the extent to which people'shairand skin color, age and sex impact the quality of fNIRS signals picked up from their scalp.

Their paper,publishedinNature Human Behavior, offers valuable insight that could inform future research practices, potentially allowing neuroscientists to run more inclusive fNIRS-based experiments.

"Our study was inspired by a simple but important observation: while fNIRS is increasingly used to study thehuman brain, not everyone's data is captured equally well," Meryem A. Yücel, first author of the study, told Medical Xpress

"Hair and skin characteristics can strongly affect the quality of the signals we record, yet the field lacked a systematic, quantitative evaluation of this issue. Our main objective was to rigorously measure these effects, so we could provide evidence-based guidance to researchers and ensure that fNIRS can become a more inclusive neuroimaging method."

Yücel and her colleagues predict that fNIRS will be increasingly used over the next decade or so, both for research and medical purposes. They have thus been trying to make this technology more inclusive, firstly by trying to pin-point factors that affect the quality of collected signals.

As part of their recent study, they used fNIRS to collect data from over 100 participants, while also documenting multiple hair characteristics—such as hair density, color, and type—as well asskin pigmentation.

"We then compared these characteristics to the quality of the brain signals recorded with fNIRS," explained Yücel. "Using statistical models, we could then directly measure how much each factor influenced signal quality. This allowed us to move beyond anecdotal reports and provide solid quantitative evidence."

The researchers found that specific hair and skin characteristics had definite and measurable effects on the quality of collected fNIRS signals. Specifically, they found that darker and denser hair, as well as higher levels of skin pigmentation (i.e., darker skin tones) reduced the quality of these signals.

"This is important because it means that some groups are at higher risk of being excluded from neuroimaging research if we don't account for these factors," said Yücel.

"Our paper not only documents this inequity but also offers practical steps for researchers to improve inclusivity—for example, adapting study designs, improving hardware, and reporting participants' characteristics more transparently."

The recent study by Yücel and her colleagues provides clear evidence that hair and skin color influence the quality of fNIRS data. The researchers are now trying to develop strategies and experimental procedures that could result in the collection of high-quality data from all individuals.

"We are testing new hardware designs, signal processing methods and devising best-practice guidelines that could reduce these disparities," added Yücel.

"Our long-term goal is to make fNIRS truly inclusive, so that its benefits—whether in neuroscience research,clinical studies, everyday brain health monitoring, or neurofeedback—are accessible to everyone, allowing all populations to participate and benefit."

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More information: Meryem A. Yücel et al, Quantifying the impact of hair and skin characteristics on fNIRS signal quality for enhanced inclusivity, Nature Human Behaviour (2025). DOI: 10.1038/s41562-025-02274-7 . Journal information: Nature Human Behaviour