DataJoint Pipelines for Neurophysiology

神经科学领域，尤其是BRAIN计划，正在为管理、分析和共享数据积累丰富的信息学资源。然而，每个实验室都必须解决类似的问题集，将这些工具集成到他们的实验的特定工作流程中：数据输入、获取、处理、分析和可视化。我们创建了DataJoint：一个用于实验数据管道和协作自动化工作流的开源通用框架。无论是独立还是在我们公司的支持下，数十个研究小组已经采用DataJoint进行多种数据模式，如多电极电生理学，钙成像，光学和电子显微镜，行为跟踪，感觉刺激，转录组学和光学。在这些复杂的数据生态系统中，DataJoint使科学家团队能够通过清晰的工作流程进行协作，同时持续共享数据并保持数据完整性。

The field of neuroscience and the BRAIN Initiative in particular are amassing a wealth of informatics resources for managing, analyzing, and sharing data. Yet every lab must solve similar sets of problems to integrate these tools into the particular workflows of their experiments: data entry, acquisition, processing, analysis, and vi­sualization. We created DataJoint: an open-source general framework for experiment data pipelines and col­laborative automated workflows . Either independently or with support from our company, dozens of research groups have adopted DataJoint for diverse data modalities such as multielectrode electrophysiology, calcium imaging, light and electron microscopy, behavior tracking, sensory stimulation, transcriptomics, and optoge­netics. In these complex data ecosystems, DataJoint enables groups of scientists to collaborate with clear work­ flows while sharing data continuously and conserving data integrity. To disseminate and integrate shared data pipelines into neuroscience practice, we propose to compile and dis­seminate a library of DataJoint Pipelines for Neurophysiology. We will extract essential motifs from DataJoint­ based open projects and organize them by data modality into a collection of curated, mutually-compatible modules stringing together data collection and computation. Documented and ready for de novo deployment, the modules will feature ancillary tools for data entry (electronic lab books), interactive graphical user inter­ faces adapted from existing projects (e.g. customizable data processing steps integrating popular algorithms for image segmentation and spike sorting), and integration of existing brain atlases, coordinate frameworks, ontologies for cell classification , and nomenclatures for viruses and transgenic lines. To foster uniform ontolo­gies, we will harmonize these pipelines with emerging neurodata standards. The results of this work will be administered as an online resource showcasing the pipelines along with sample data, executable demos, and guidelines for deployment. Visitors will be able to customize, extend, and combine the modules into complete pipelines suitable for their particular experiments and learn the techniques for building new solutions. The modules will support diverse computing architectures, including specialized hardware and cloud services. We will also conduct web-based trainings and in-person hackathons to help accelerate the adoption of these tools in working neuroscience labs. Vathes LLC is uniquely positioned to perform this work as we co-develop data pipelines for collaborative projects such as IARPA's MICrONS, International Brain Lab, and BRAIN Initiative Ul9 pro jects. The output of this project will enable many new research groups to adopt DataJoint and to effectively integrate informatics tools into neuroscience practice.