Retinal processing of natural scenes: challenges ahead

While substantial knowledge exists about the way the retina processes simple stimuli, our understanding of how the retina processes natural stimuli remains limited. Here we highlight key challenges that remain to be addressed to understand retinal processing of natural stimuli and describe emerging research avenues to overcome them. A key issue is model complexity. When complexifying the probing stimuli towards natural stimuli, the number of parameters required in models of retinal computations increases, raising issues of overfitting, generalization, and interpretability. This increase in complexity also poses a challenge for normative approaches, as it makes it difficult to derive non-linear retinal computations from simple principles. We describe two approaches that may help circumvent this issue. First, we propose that a new form of reductionism is emerging: instead of breaking down natural stimuli into sums of simpler stimuli, it becomes possible to "divide and conquer" natural scenes into different visual inputs corresponding to different visual tasks, allowing to study retinal computations separately for each of these tasks. Moreover, the abstract computations performed by some cell types may be understood as the result of being constrained by multiple tasks. Second, several studies suggest that it will soon be possible to mitigate the issue of complexity, by "embodying" models with more biological constraints, in particular those derived from connectomic studies. Together, these approaches offer a powerful strategy to tackle current limitations and advance our understanding of how the retina processes natural visual environments, and suggest methods that could be used in other sensory areas.