Near-infrared light increases functional connectivity with a non-thermal mechanism
Bibliographic record
Abstract
Abstract Although techniques for non-invasive brain stimulation are under intense investigation, an approach that has received limited attention is transcranial photobiomodulation (tPBM), the delivery of near-infrared light to the brain with a laser directed at the scalp. Here we employed functional magnetic resonance imaging (fMRI) to measure the Blood-Oxygenation-Level Dependent (BOLD) signal in n = 20 healthy humans while concurrently stimulating their right frontal pole with a near-infrared laser. We failed to detect an evoked BOLD response at illumination. However, functional connectivity with the illuminated region increased by an average of 10% during stimulation, with some connections strengthening by as much as 40%. 23% of connections with the illuminated region experienced a significant acute increase, with the time course of connectivity exhibiting a sharp rise at illumination onset. Brain-wide connectivity increases were also observed, with connections in the stimulated hemisphere showing a significantly larger increase than those in the non-stimulated hemisphere. We subsequently employed MR Thermometry to measure brain temperature during tPBM (separate cohort, n = 20), and found no significant temperature differences between active and sham stimulation. Our findings suggest that near-infrared light synchronizes brain activity with a non-thermal mechanism, underscoring the promise of tPBM as a new technique for stimulating brain function.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".