Blue Light Stimulates Cognitive Brain Activity in Visually Blind Individuals
Bibliographic record
Abstract
Light regulates multiple non-image-forming (or nonvisual) circadian, neuroendocrine, and neurobehavioral functions, via outputs from intrinsically photosensitive retinal ganglion cells (ipRGCs). Exposure to light directly enhances alertness and performance, so light is an important regulator of wakefulness and cognition. The roles of rods, cones, and ipRGCs in the impact of light on cognitive brain functions remain unclear, however. A small percentage of blind individuals retain non-image-forming photoreception and offer a unique opportunity to investigate light impacts in the absence of conscious vision, presumably through ipRGCs. Here, we show that three such patients were able to choose nonrandomly about the presence of light despite their complete lack of sight. Furthermore, 2 sec of blue light modified EEG activity when administered simultaneously to auditory stimulations. fMRI further showed that, during an auditory working memory task, less than a minute of blue light triggered the recruitment of supplemental prefrontal and thalamic brain regions involved in alertness and cognition regulation as well as key areas of the default mode network. These results, which have to be considered as a proof of concept, show that non-image-forming photoreception triggers some awareness for light and can have a more rapid impact on human cognition than previously understood, if brain processing is actively engaged. Furthermore, light stimulates higher cognitive brain activity, independently of vision, and engages supplemental brain areas to perform an ongoing cognitive process. To our knowledge, our results constitute the first indication that ipRGC signaling may rapidly affect fundamental cerebral organization, so that it could potentially participate to the regulation of numerous aspects of human 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) | 0.001 | 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".