The Optimal Retinal Locus for High-Resolution Vision in Space and Time
Gautier, J.; Bowers, N. R.; Banks, M. S.; Roorda, A.
Show abstract
Humans exhibit machine-like eye-movement behavior in space and time while performing challenging visual resolution tasks. Fewer microsaccades occur as stimulus presentation is imminent. Drifts and microsaccades combine to confine the landing location of an anticipated visual stimulus to a tiny retinal region: the preferred retinal locus (PRL). We find that this location confers the best visual acuity despite it being offset from the anatomical fovea (the location of maximum cone density). We also find that acuity is best when the last microsaccade occurs 400msec or longer before stimulus presentation. The machine-like eye movements are involuntary and not perceived. Our findings thus reveal a highly evolved oculomotor system such that gaze direction during fixation is rarely far enough from the PRL to cause a decline in visual resolution. TeaserHumans exhibit machine-like eye-movement behavior during fine visual tasks that rarely deviates from an optimal retinal location.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Continuous psychophysics shows millisecond-scale visual processing delays are faithfully preserved in movement dynamics 96%
- Local variations in L/M ratio influence the detection and color naming of small spots 94%
- Microsaccadic suppression of peripheral perceptual detection performance as a function of foveated visual image appearance 94%
Similar papers in this journal
- Perisaccadic perceptual mislocalization strength depends on the visual appearance of saccade targets 97%
- Visual feature tuning properties of stimulus-driven saccadic inhibition in macaque monkeys 97%
- Where we perceive before we look: The distribution of presaccadic attention assessed with dynamic 1/f noise 96%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.