Blue flicker modifies the subfoveal choroidal blood flow in the human eye
Bibliographic record
Abstract
The objective of the present study was to reveal an interaction between choroidal blood flow (ChBF) and light-induced photoreceptor activity, a physiological coupling that has been already demonstrated for retinal blood flow but rejected for ChBF. Ten healthy adults volunteered for this study. A real-time recording near-infrared laser-Doppler flowmeter was used to quantify the subfoveal ChBF while the luminance of blue flicker between 1 and 64 Hz was first increased and then decreased by 4.0 log units in 1.0-log unit steps between 0.0375 and 375 cd/m2. In separate testing, flash electroretinograms (ERGs) provided electrophysiological indexes of the relative response of short-wave cones (s-cones) and rods to blue light stimulation. Group-averaged, normalized ChBF measurements revealed that it was modulated by approximately 9% by flicker frequency. Increasing the blue flicker luminance from low to high attenuated the subfoveal ChBF, volume, and velocity by approximately 32%, approximately 30%, and approximately 5%, respectively. Decreasing the luminance from high to low over the same range had no effect on the subfoveal choroidal hemodynamics. The markedly different effects of reversed directions of change in blue flicker luminance on the subfoveal ChBF were linked to transitions between rod-dominated and s-cone-dominated retinal responses. Collectively, these findings indicate that the blue light-induced photoreceptor response is associated with a differential distribution of the ChBF across the ocular fundus according to the degree and type of retinal photoreceptor stimulated.
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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".