A robust receptive field code for optic flow detection and decomposition during self-motion

Abstract

The perception of optic flow is essential for any visually guided behavior of a moving animal. To mechanistically predict behavior and understand the emergence of self-motion perception in vertebrate brains, it is essential to systematically characterize the motion receptive fields (RFs) of optic-flow-processing neurons. Here, we present the fine-scale RFs of thousands of motion-sensitive neurons studied in the diencephalon and the midbrain of zebrafish. We found neurons that serve as linear filters and robustly encode directional and speed information of translation-induced optic flow. These neurons are topographically arranged in pretectum according to translation direction. The unambiguous encoding of translation enables the decomposition of translational and rotational self-motion information from mixed optic flow. In behavioral experiments, we successfully demonstrated the predicted decomposition in the optokinetic and optomotor responses. Together, our study reveals the algorithm and the neural implementation for self-motion estimation in a vertebrate visual system.

Keywords: diencephalon; matched-filter algorithm; optic flow decomposition; optokinetic response; optomotor response; receptive field; self-motion; visually guided behavior; zebrafish.