ObjectiveThis study aims to improve the management efficiency of zebrafish strains and zebrafish facilities and to transform the traditional management model that relies on manual labor. The goal is to promote a comprehensive transition from traditional manual operation to standardized, digitalized, automated, and refined management, thereby significantly improving management quality and work efficiency. MethodsThe research group independently developed the "Zebrafish Facility and Zebrafish Strain Automation Management System V1.0" (Software Copyright Registration No. 2021SR0236837), which comprehensively recorded all operational data of the zebrafish facilities and completed data on zebrafish strains. By combining in-depth mining of these data with management experience, management regulations were transformed into executable system instruction sets, and a full-process automated closed-loop management framework of "Monitoring–Analysis–Early Warning–Task Assignment–Execution–Recording" was established. ResultsThis management system has been operating stably for 5 years and has been successfully applied in 3 zebrafish facilities, cumulatively supporting 78 researchers and efficiently managing 1 108 plasmids and 1 123 zebrafish strains, among which 291 strains has been incorporated into zebrafish sperm bank management. A Likert scale survey of 28 core users covering 14 evaluation dimensions across 4 major categories showed average scores of 4.46–4.89, all far above the midpoint (3 points) of the scale, indicating that users gave high evaluations to all dimensions of the system. Meanwhile, the standard deviations of most dimensions were low (s ≤ 0.44), reflecting good consistency in user evaluations. ConclusionThis study integrates information technology, big data analysis, and modern management concepts to achieve a virtuous cycle of "data collection–analysis and execution–system optimization" in zebrafish facility management. It significantly improves management efficiency and refinement and promotes the development of management models toward automation.

Detection of moving objects is an essential skill for animals to hunt prey, recognize conspecifics and avoid predators. The zebrafish, as a vertebrate model, primarily uses its elaborate visual system to distinguish moving objects against background scenes. The optic tectum (OT) receives and integrates inputs from various types of retinal ganglion cells (RGCs), including direction-selective (DS) RGCs and size-selective RGCs, and is required for both prey capture and predator avoidance. However, it remains largely unknown how motion information is processed within the OT. Here we performed in vivo whole-cell recording and calcium imaging to investigate the role of superficial interneurons (SINs), a specific type of optic tectal neurons, in motion detection of larval zebrafish. SINs mainly receive excitatory synaptic inputs, exhibit transient ON- or OFF-type of responses evoked by light flashes, and possess a large receptive field (RF). One fifth of SINs are DS and classified into two subsets with separate preferred directions. Furthermore, SINs show size-dependent responses to moving dots. They are efficiently activated by moving objects but not static ones, capable of showing sustained responses to moving objects and having less visual adaptation than periventricular neurons (PVNs), the principal tectal cells. Behaviorally, ablation of SINs impairs prey capture, which requires local motion detection, but not global looming-evoked escape. Finally, starvation enhances the gain of SINs' motion responses while maintaining their size tuning and DS. These results indicate that SINs serve as a motion detector for sensing and localizing sized moving objects in the visual field.