Visual adaptations to natural statistics

Biological vision is unlike a camera; rather than transmitting light information faithfully, early visual circuits process the visual scene to convey only the relevant information in an efficient manner. Consequentially, the nature of this visual processing then depends on what is the relevant information in a scene and on the notion of efficiency. In this work, I study how visual processing is modulated by two different variations in the visual scene. First, I discovered that in the mouse (Mus musculus) retina, Retinal Ganglion Cells in the upper and lower visual field have differences in the center surround structure of their receptive fields. Comparison with models of efficient coding show that this adaptation likely evolved to cope with the brightness gradient from the sky to the ground that is pervasive in natural scenes. In the second project, I study how the downstream neurons in the Superior Colliculus dynamically change their temporal selectivity depending on the ambient luminance and behavioral state. As the scene gets darker or when the animal is is less aroused, the neuronal responses get laggier, while still maintaining their relative timing with respect to the population. Overall, this work emphasises the need to understand visual processing in the context of specific demands of the animal in its the environment. The adaptive changes in the visual system, from the retinal ganglion cells to the superior colliculus, highlight the intricate ways in which biological vision optimizes the processing of visual information.