A Neural Computation for Visual Acuity in the Presence of Eye Movements
Figure 5
Model Performance on the Horizontal versus Vertical Discrimination Task Shown in Figure 2
Performance is measured by simulating retinal responses, calculating decisions based on those responses, and computing the fraction of correct decisions (see Materials and Methods). When fixational eye movements jitter the stimulus, the Markov decoder is able to perform well on the task by accounting for the eye movement statistics (black curves). Two naive decoders are also applied to this task, one that assumes the stimulus is fixed (red) and one that assumes maximum uncertainty about those movements (blue). Performance is shown as a function of stimulus duration (A), peak stimulated firing rate (B), and stimulus size (C). Where not otherwise specified, the parameters for these simulations are background firing rate of 10 Hz, a peak stimulated rate of 100 Hz, a stimulus of 1 × 2 arcmin2, a duration of 500 ms, and a diffusion constant of 100 arcmin2/s.