The appeal of fNIRS lies in its simplicity and its tolerance of real-world behavior. Unlike functional magnetic resonance imaging, which requires participants to lie motionless inside a loud, cramped scanner, fNIRS relies on nothing more intimidating than a cap fitted with light emitters and detectors pressed gently against the scalp. Near-infrared light at wavelengths around 700 to 900 nanometers penetrates the skull and skull-adjacent tissues by a few centimeters, and because oxygenated and deoxygenated hemoglobin absorb those wavelengths differently, the device can calculate changes in cortical blood oxygenation from the fraction of light that scatters back to the detectors. When a brain region becomes more active, local blood flow increases and delivers a surplus of oxygenated hemoglobin—a signal fNIRS can track with a temporal resolution of fractions of a second. That makes the technique well suited to swallowing, a behavior that unfolds in under two seconds and that cannot be cleanly performed inside an MRI bore, particularly by frail or elderly patients.

To chart how researchers have exploited this window onto the swallowing brain, the Korean team followed the Joanna Briggs Institute methodology for scoping reviews and adhered to the PRISMA-ScR reporting guidelines. They searched four major databases—MEDLINE, Embase, Scopus and Web of Science—from their inception through September 2025, casting a wide net across experimental and clinical literatures. After screening, 21 studies met the inclusion criteria: investigations involving adult participants in whom fNIRS was used to measure swallowing-related cortical activity, whether during natural swallowing tasks, deliberately designed swallowing exercises, sensory stimulation paradigms or neuromodulation interventions. The studies spanned healthy volunteers as well as clinical populations, most notably stroke survivors with dysphagia.

The central finding to emerge from the synthesis is strikingly consistent: swallowing recruits a distributed fronto-sensorimotor cortical network rather than a single “swallowing center.” Across studies, hemodynamic responses clustered over the primary motor and sensory cortices—particularly the regions representing the tongue, pharynx and larynx—along with the inferior frontal gyrus, the supplementary motor area and adjacent prefrontal territory. This pattern aligns with the classical model of swallowing control, in which the brainstem central pattern generator executes the reflexive sequence of muscle contractions while cortical areas handle the volitional initiation, sensory gating and fine tuning of the swallow. The reviews’ authors note that the degree and spatial distribution of this activation are not fixed: they shift depending on what the swallow entails, what sensations accompany it and what the brain is being asked to do differently.

One of the most clinically provocative threads in the reviewed literature concerns sensory modulation. Several studies examined how manipulating the oral environment changes cortical responses to swallowing. Acidic solutions, for example, produced stronger and sometimes more bilateral cortical activation than plain water, suggesting that sour taste stimuli heighten the salience of the swallow and amplify sensory feedback to the cortex. Other experiments delivered tactile vibration over the larynx or applied pharyngeal electrical stimulation and observed increases in both swallowing frequency and activation of the sensorimotor cortex. In patients with brainstem stroke—a group whose dysphagia is traditionally attributed to damage of the reflex machinery itself—visual and gustatory stimuli were still able to reshape cortical hemodynamic patterns, hinting that even “brainstem” dysphagia retains a cortical dimension that might be therapeutically targeted. For rehabilitation specialists, these findings support a long-standing hypothesis that intensifying sensory input during swallowing can drive use-dependent plasticity in the cortical networks that support recovery.

Motor demand tells a complementary story. Studies that compared simple water swallows with effortful or resistance-based swallowing exercises—such as the chin-tuck-against-resistance maneuver, in which patients swallow while flexing the neck against opposing force—found distinct cortical signatures associated with increasing motor challenge. This resonates with the “challenge point” framework from motor learning research, which holds that practice conditions must be sufficiently demanding to induce adaptation without overwhelming the learner. In practical terms, the reviewed evidence suggests that fNIRS could serve as a physiological dosimeter, allowing clinicians to verify that a given swallowing exercise is actually engaging the intended cortical circuitry in a given patient, rather than relying on surface muscle activity alone.

Perhaps the most forward-looking section of the review concerns neuromodulation. Several included studies paired fNIRS with non-invasive brain stimulation techniques. Repetitive transcranial magnetic stimulation, delivered over the swallowing motor cortex, was shown in randomized studies of stroke patients to alter hemodynamic signals in parallel with measurable swallowing improvements. Transcranial direct current stimulation experiments compared stimulation amplitudes over the sensorimotor cortex and documented dose-dependent cortical responses. Modified pharyngeal electrical stimulation changed swallowing-related functional connectivity, and even electroacupuncture at traditional acupuncture points produced stronger activation of the swallowing cortex than single-point stimulation. Together, these studies sketch a future in which fNIRS is not merely an observational tool but a real-time feedback instrument—confirming within a single session whether a neuromodulatory intervention is shifting cortical excitability in the desired direction, and potentially enabling closed-loop rehabilitation protocols in which stimulation parameters are titrated against the patient’s own cortical response.

Yet the review is equally emphatic about what stands in the way of that future. Methodological heterogeneity pervades nearly every aspect of the field. Studies differ in task paradigms—dry swallows versus water swallows versus flavored liquids; single swallows versus repeated blocks; volitional versus spontaneous swallows—each of which is known to elicit somewhat different hemodynamic signatures. Optode placement varies widely, with some groups densely sampling the sensorimotor strip and others covering broader prefrontal territories, which complicates any direct comparison of activation maps. Analytical pipelines are similarly divergent, encompassing different filtering choices, baseline corrections, channel-averaging schemes and statistical thresholds. The reviewers also flag a more fundamental imbalance: of the 21 studies, the majority enrolled healthy adults, and the number of investigations involving actual dysphagia patients—particularly longitudinal studies tracking recovery—remains small. Without larger clinical cohorts and standardized measurement protocols, the field cannot yet determine whether cortical activation patterns measured by fNIRS predict which patients will recover swallowing function or respond to particular therapies.

The implications for rehabilitation are nonetheless considerable. Dysphagia affects a substantial proportion of stroke survivors and is a leading contributor to post-stroke aspiration pneumonia, yet bedside and instrumental assessments—videofluoroscopy and fiberoptic endoscopic evaluation—capture the mechanical act of swallowing rather than the neural drive behind it. fNIRS, by contrast, is inexpensive, portable, silent and compatible with bedside use, making it conceivable that future dysphagia assessments could incorporate a cortical activation profile alongside structural and functional measures. Such profiles could reveal, for example, whether a patient’s swallowing network has shifted activation toward the undamaged hemisphere after a stroke—a pattern of reorganization that neuroimaging research in limb motor recovery has linked to better outcomes. The reviewers point to earlier fMRI work demonstrating time-dependent hemispheric shifts in swallowing control as a conceptual template that fNIRS could now pursue at the bedside and at much lower cost.

The path from scoping review to clinical standard is, of course, long. The authors call for the development of standardized fNIRS protocols for swallowing research—harmonized optode montages, task paradigms, data processing pipelines and clinically relevant outcome measures—so that findings from different laboratories and hospitals can be pooled and translated into practice. They also emphasize that fNIRS has inherent limitations: light penetrates only the outer cortex, leaving brainstem and subcortical swallowing centers invisible to the technique, and signals can be contaminated by scalp blood flow, head motion and the very jaw and neck movements that swallowing entails. Sophisticated signal processing and careful experimental design will be needed to disentangle genuine cortical hemodynamics from these artifacts.

Still, the overall message of the review is one of cautious optimism. Twenty-one studies have collectively demonstrated that fNIRS is feasible and sensitive enough to detect swallowing-related cortical activation in both experimental and clinical settings, and that the measured signals respond meaningfully to sensory stimulation, motor demands and neuromodulation. What the field lacks is not proof of principle but coordination. If researchers can converge on shared protocols and expand their focus to the clinical populations who stand to benefit most, the humble near-infrared cap—already a fixture in stroke rehabilitation research and brain-computer interface laboratories—could become a routine instrument in the dysphagia clinic, transforming swallowing rehabilitation from an empirical craft into a neuroscientifically guided therapy. For the millions of patients who struggle to swallow safely each day, bringing the swallowing brain into view may be the first step toward rewiring it.

In an investigation involving 115 participants, a research team has sought to systematically quantify the influence of hair properties, skin pigmentation, head size, sex, and age on the quality of fNIRS signals. The findings reveal critical insights into how these physiological traits interact with the optical properties of near-infrared light, impacting the absorption and scattering patterns fundamental to fNIRS measurements. As the use of fNIRS expands into broader and more diverse populations, understanding these influences is paramount to ensuring the accuracy and reliability of research outcomes.

One of the key challenges faced by researchers using fNIRS is the variability introduced by the different hair types found across individuals. The texture, thickness, and color of hair can substantially alter how near-infrared light penetrates the scalp, potentially leading to inconsistent signal quality. While it is widely acknowledged that dark and thick hair tends to absorb more near-infrared light, lighter and finer hair may allow more light to penetrate, affecting the robustness of the signals collected. This variability can introduce bias, especially in studies aiming to include underrepresented groups with distinct hair characteristics.

Skin pigmentation further complicates the landscape of fNIRS data collection. Darker skin tones naturally absorb more infrared light, which may inadvertently dampen the fNIRS signal. This issue raises essential questions about inclusivity in neuroimaging research and serves as a reminder that standardization in methodology must account for physiological diversity. The implications are profound; as the scientific community seeks to advance our understanding of human cognition and behavior, it must simultaneously ensure that all voices and experiences are represented in its findings.

The research also underscores the importance of considering head size as a biophysical variable that can influence fNIRS signal quality. Larger heads may present unique challenges due to the distances that light must travel through various tissue types before being detected by fNIRS sensors. Consequently, researchers must be diligent in calibrating their instruments to account for these differences, as failing to do so may compromise the integrity and reproducibility of their work.

Sex and age appear to be additional variables of concern in the context of fNIRS research. Variations in biological and physiological characteristics associated with these two factors may contribute to differential absorption and scattering of near-infrared light. For instance, hormonal changes related to age can impact hair and skin quality, while sex-based differences in physiology may further complicate interpretations of fNIRS data. Researchers are encouraged to include these factors in their experimental designs and consider them when analyzing data.

To address these challenges, the research team proposed a series of recommendations aimed at enhancing the reliability of fNIRS studies. Chief among these is the creation of a comprehensive metadata table that encourages researchers to document participant characteristics meticulously. By detailing factors such as hair color, type, and texture, along with skin tone and age, future studies can become more transparent, allowing for rigorous analyses and comparisons across different groups.

Another recommendation includes providing specific guidance on cap and optode configurations. This involves optimizing sensor placement relative to individual hair and skin characteristics, which could enhance signal acquisition and minimize variability. Techniques for managing hair, such as using specialized caps designed to accommodate varying hair types, can further mitigate biases in signal quality. Furthermore, the incorporation of user-friendly optical devices that help standardize fNIRS data collection across diverse populations is crucial as we move towards more inclusive neuroimaging practices.

By adopting these recommendations, fNIRS researchers can aspire to maintain high standards of quality in their investigations while pushing the boundaries of inclusivity. As the field of neuroimaging continues to grow, it is essential to ensure that diverse populations are included in the research narrative, enabling findings to reflect a broader spectrum of human experiences.

Inclusivity in fNIRS research not only benefits the quality of studies but also enhances the credibility of findings, making them more applicable to real-world scenarios. As researchers continue to unravel the complexities of the human brain, it is vital that they do so through lenses that acknowledge our individual differences, thereby paving the way for more comprehensive understandings of human cognition and behavior.

In conclusion, the research team’s contributions to the field of fNIRS not only shine a light on critical variables affecting signal quality but also furnish the scaffolding for future studies aimed at inclusivity. By engaging with the findings and recommendations outlined in this research, the scientific community can actively work towards overcoming barriers and fostering a more equitable landscape in neuroimaging research. As we aim for greater accuracy and applicability, let us not overlook the nuances that accompany the diverse tapestry of human physiology.

The future of fNIRS studies depends significantly on our commitment to addressing these challenges head-on. Through collaborative efforts, ongoing research, and rigorous methodological refinements, we can cultivate a field of inquiry that does justice to the complexity and diversity of the human experience, ultimately enriching our understanding of how the brain functions across different contexts.

Subject of Research: fNIRS signal quality influenced by hair and skin characteristics.

Article Title: Quantifying the impact of hair and skin characteristics on fNIRS signal quality for enhanced inclusivity.

Article References:

Yücel, M.A., Anderson, J.E., Rogers, D. et al. Quantifying the impact of hair and skin characteristics on fNIRS signal quality for enhanced inclusivity. Nat Hum Behav (2025). https://doi.org/10.1038/s41562-025-02274-7

Image Credits: AI Generated

DOI:

Keywords: fNIRS, inclusivity, neuroimaging, signal quality, hair characteristics, skin pigmentation, demographics.