DataSheet1_PyZebrascope: An Open-Source Platform for Brain-Wide Neural Activity Imaging in Zebrafish.pdf

Understanding how neurons interact across the brain to control animal behaviors is one of the central goals in neuroscience. Recent developments in fluorescent microscopy and genetically-encoded calcium indicators led to the establishment of whole-brain imaging methods in zebrafish, which record neural activity across a brain-wide volume with single-cell resolution. Pioneering studies of whole-brain imaging used custom light-sheet microscopes, and their operation relied on commercially developed and maintained software not available globally. Hence it has been challenging to disseminate and develop the technology in the research community. Here, we present PyZebrascope, an open-source Python platform designed for neural activity imaging in zebrafish using light-sheet microscopy. PyZebrascope has intuitive user interfaces and supports essential features for whole-brain imaging, such as two orthogonal excitation beams and eye damage prevention. Its camera module can handle image data throughput of up to 800 MB/s from camera acquisition to file writing while maintaining stable CPU and memory usage. Its modular architecture allows the inclusion of advanced algorithms for microscope control and image processing. As a proof of concept, we implemented a novel automatic algorithm for maximizing the image resolution in the brain by precisely aligning the excitation beams to the image focal plane. PyZebrascope enables whole-brain neural activity imaging in fish behaving in a virtual reality environment. Thus, PyZebrascope will help disseminate and develop light-sheet microscopy techniques in the neuroscience community and advance our understanding of whole-brain neural dynamics during animal behaviors.

解析神经元在全脑范围内的相互作用以调控动物行为，是神经科学领域的核心研究目标之一。近年来，荧光显微镜（fluorescent microscopy）与基因编码钙指示剂（genetically-encoded calcium indicators）的技术进步，推动了斑马鱼全脑成像方法的建立，该方法可在全脑体积范围内以单细胞分辨率记录神经活动。早期全脑成像研究采用定制化光片显微镜（light-sheet microscope），但其运行依赖商业化开发与维护的软件，这类软件并非全球范围内均可获取。因此，在科研社群中推广与开发该技术一直颇具挑战。为此，我们推出PyZebrascope——一款面向斑马鱼光片显微镜神经活动成像的开源Python平台。PyZebrascope拥有直观的用户界面，并支持全脑成像所需的核心功能，例如双正交激发光束与眼部损伤防护机制。其相机模块可实现从相机采集到文件写入的最高800 MB/s的图像数据吞吐速率，同时保持稳定的CPU与内存占用。该平台的模块化架构支持集成用于显微镜控制与图像处理的高级算法。作为概念验证，我们实现了一种新型自动算法，通过将激发光束精确对准图像焦平面，以最大化脑部图像的分辨率。PyZebrascope可支持在虚拟现实环境中行为的斑马鱼的全脑神经活动成像。因此，PyZebrascope将助力神经科学社群推广与开发光片显微镜技术，并推动我们对动物行为过程中全脑神经动力学的认知。