Abstract
The optical density of visual pigment can be measured by imaging the dark-adapted eye while bleaching with visible light. This measurement can be made for individual photoreceptor cells using adaptive optics; however, activation of the phototransduction cascade imparts rapid changes in phase that modulate the signal via optical interference. This limits utility because data must be averaged over many experimental runs. Here we used a "flood" illuminated adaptive optics system at 4000 fps, bright light to achieve rapid bleaching, and broad illumination bandwidth to mitigate interference effects. Data were super-resolved using the natural motion of the eye to overcome the reduced pixel resolution of the ultrafast camera. This approach was applied to classify the trichromatic cone photoreceptor mosaic at a single fixation locus within the foveal region of 3 healthy subjects. Subjects were dark adapted for 6 minutes to replenish cone photopigment. This was followed either directly by imaging at 555 ± 50 nm, or by first pre-adapting the retina to 700 nm light to preferentially deplete "L" cone pigment. A total of 3,252 cones were classified as either "S", "M", or "L" type based on clustering of the intensity data observed under these two conditions. Mean classification probability ranged from 99.3 to 99.8%, with individual cell probabilities exceeding 95% in 97.0 to 99.2% of cones. Accuracy of cone classification peaked when using the first 10-30 ms of data, with significant reductions in accuracy noted with the inclusion of data from later times. Our results show that rapid bleaching and data acquisition significantly improve the robustness of cell-resolved densitometry.