Simulation-based dosimetry of transcranial and intranasalphotobiomodulation of the human brain: the roles of wavelength, powerdensity, and skin tone
Bibliographic record
Abstract
Photobiomodulation (PBM) using near-infrared (NIR) light is a novel neuromodulation technique. However, despite the many in vivo studies, the stimulation protocols for PBM vary across studies, and the current understanding of the physiological effects of PBM, as well as the dose dependence, is limited. Specifically, although NIR light can be absorbed by melanin in the skin, the understanding of how skin tones compare and how their influence interacts with other dose parameters remains limited. This study investigates the effect of melanin, optical power density, and wavelength on light penetration and energy accumulation via forehead and intranasal PBM. We use Monte Carlo simulations of a single laser source for transcranial (tPBM, forehead position) and intranasal (iPBM, nostril position) irradiation on a healthy human brain model. We investigate wavelengths of 670, 810, and 1064 nm at various power densities in combination with light ("Caucasian"), medium ("Asian"), and dark ("African") skin tone categories as defined in the literature. Our simulations show that a maximum of 15% of the incidental energy for tPBM and 1% for iPBM reaches the cortex from the light source. The rostral dorsal prefrontal cortex and the ventromedial prefrontal cortex accumulate the highest light energy in tPBM and iPBM, respectively, for both wavelengths. Notably, we show that nominally "Caucasian" skin allows the highest energy accumulation of all three skin tones. Moreover, the 810 nm wavelength for tPBM and the 1064 nm wavelength for iPBM produced the highest cortical energy accumulation, which was linearly correlated with optical power density, but these variations could be overridden by a difference in skin tone in the tPBM case.The simulations serve as a starting point for enabling hypothesis generation for in vivo PBM investigations. This study is the first to account for skin tone as a tPBM dosing consideration. For the future of PBM research, it is important to evaluate combinations of stimulation parameters (wavelength, optical power density, pulsation frequency, duration, light source) when working to determine an optimal dosage for PBM-based therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".