Exploitation of image statistics with sparse coding in the case of stereo vision.

The sparse coding algorithm has served as a model for early processing in mammalian vision. It has been assumed that the brain uses sparse coding to exploit statistical properties of the sensory stream. We hypothesize that sparse coding discovers patterns from the data set, which can be used to estimate a set of stimulus parameters by simple readout. In this study, we chose a model of stereo vision to test our hypothesis. We used the Locally Competitive Algorithm (LCA), followed by a naïve Bayes classifier, to infer stereo disparity. From the results we report three observations. First, disparity inference was successful with this naturalistic processing pipeline. Second, an expanded, highly redundant representation is required to robustly identify the input patterns. Third, the inference error can be predicted from the number of active coefficients in the LCA representation. We conclude that sparse coding can generate a suitable general representation for subsequent inference tasks.

Characterizing visual performance in mice: an objective and automated system based on the optokinetic reflex.

Testing optokinetic head or eye movements is an established method to determine visual performance of laboratory animals, including chickens, guinea pigs, mice, or fish. It is based on the optokinetic reflex which causes the animals to track a drifting stripe pattern with eye and head movements. We have developed an improved version of the optomotor test with better control over the stimulus parameters, as well as a high degree of automation. The stripe pattern is presented on computer monitors surrounding the animal. By tracking the head position of freely moving animals in real time, the visual angle under which the stripes of the pattern appeared was kept constant even for changing head positions. Furthermore, an algorithm was developed for automated evaluation of the tracking performance of the animal. Comparing the automatically determined behavioral score with manual assessment of the animals' tracking behavior confirmed the reliability of our methodology. As an example, we reproduced the known contrast sensitivity function of wild type mice. Furthermore, the progressive decline in visual performance of a mouse model of retinal degeneration, rd10, was demonstrated.