Algorithmic dissection of optic flow memory in larval zebrafish

The visual stabilization behavior in the larval zebrafish reflects the history of optic flow experienced in the recent past. This integrative process has gained traction in recent years as a simplified, tractable model of working memory and decision-making. Yet its algorithmic bases are poorly understood. In this study, we first demonstrate that only externally generated, but not self-generated, optic flow contributes to future history-dependent stabilization behaviors. This observation suggests that the hysteresis in the stabilization behavior reflects a sensory low-pass filtering process rather than the self-location memory achieved through path integration. Second, through reverse correlation and delay-based paradigms, we reveal multiple timescales involved in the integration of optic flow. With the help of quantitative modeling, we show that the fish becomes more forgetful about the past optic flow in a more dynamic visual environment. Next, with whole-brain, light-sheet calcium imaging, we find optic-flow-selective neurons that exhibit signatures of motor efference copies in various brain regions, mirroring the behavioral findings. Lastly, with two-photon calcium imaging, we show that inferior olive neurons integrate forward and backward flow separately, giving clues about how the multiple timescales of optic flow integration are implemented. Overall, the results here refine our algorithmic and functional understanding of the history dependence of the visual stabilization behaviors in the larval zebrafish, paving the way for deciphering its circuit implementations.