Understanding the Diversity of Retinal Cell Types and Mosaic Organizations through Efficient Coding Theory

Abstract

Efficient coding theory provides a powerful framework for understanding the organization of the early visual system. Prior research has demonstrated that efficient coding theory can help account for a range of retinal ganglion cell (RGC) organizational features, including the center-surround spatial receptive fields and ON and OFF parallel pathways. Here, we use a machine learning-based computational framework for efficient coding and show that more functional architecture of visual processing can be explained on the basis of this principle. First, how should receptive fields (RFs) be arranged to best encode natural images? When the spatial RFs and contrast response functions are optimized in order to maximally encode natural stimuli given noise and firing rate constraints, the RFs form a pair of mosaics, one with ON RFs and one with OFF RFs, similar to those of mammalian retina, as an existing finding from previous research. Interestingly, the relative arrangement of the two mosaics transitions between alignment under high signal-to-noise conditions and anti-alignment under low signal-to-noise conditions. The next question we tackled is: how are the ON and OFF RF mosaics arranged in the mammalian retina? We examined the retina of rats and primates and confirmed that the ON and OFF mosaic pairs encoding the same visual feature are anti-aligned, indicating that the retina is optimized to handle dim or low-contrast stimuli. Finally, we dove into the question: how many cell types can be predicted by efficient coding theory? We examined encoding of natural videos, and found that, as the available channel capacity – the number of simulated RGCs available for encoding – increases, new cell types emerge that focus on higher temporal frequencies and larger spatial areas. Together, these studies advance our understanding of the relationships between efficient coding, retinal organization, and diversity of retinal cell types.