Distinct inhibitory connectivity motifs trigger distinct forms of anticipation in the retinal network

Motion is an important feature of visual scenes and retinal neuronal circuits selectively signal different motion features. It has been shown that the retina can extrapolate the position of a moving object, thereby compensating sensory transmission delays and enabling signal processing in real-time. Amacrine cells, the inhibitory interneurons of the retina, play essential roles in such computations although their precise function remain unclear. Here, we computationally explore the effect of two different inhibitory connectivity motifs on the retina’s response to moving objects: feed-forward and recurrent feed-back inhibition. We show that both can account for motion anticipation with two different mechanisms. Feed-forward inhibition truncates motion responses and shifts peak responses forward via subtractive inhibition, whereas recurrent feedback coupling evokes, via divisive inhibition, excitatory and inhibitory waves with different phases that add up and shift the response peak. A key difference between the two mechanisms is how the peak response scales with the speed of a moving object. Motion prediction with feedforward circuits monotonically decreases with increasing speeds, while recurrent feedback coupling induces tuning curves that exhibit a preferred speed for which motion prediction is maximal.