Behavior-Specific Computations in the Vertebrate Retina

Abstract

Since Lettvin and colleagues’ seminal discovery of bug detector neurons in the frog retina, understanding how retinal circuits support behavioral demands has been a central goal of visual neuroscience. Recent advances in machine learning, genetic tools, and neural recording have transformed our understanding of these circuits, particularly in the mouse retina. With a focus on mice, we examine how species-specific visual sampling strategies determine the behavioral relevance of retinal computations and review recent insights into circuits underlying reflexive behaviors, threat detection, prey capture, color vision, and night vision. We also highlight how the behavioral state itself influences retinal processing through direct neuromodulation and pupillary changes, challenging the traditional view of purely feedforward retinal processing in mammals. These findings confirm the retina as a sophisticated computational engine whose circuits have evolved to meet species-specific behavioral demands. While Lettvin’s discovery of dedicated retinal circuits for innate behaviors launched the field, new tools now promise to expand our understanding of retinal contributions to naturalistic and flexible behaviors across species.