Scaling Volumetric Imaging, Analysis and Science Communication Using Immersive Virtual Reality: Administrative Supplement

最初的第二阶段提案涉及分析、访问和 在神经科学中传播越来越大的3D和4D图像集。本副刊 请求的动机是自提交和审查以来的两个意外发展 原始申请。所要求的活动对于保持以下方面的高总体影响是必要的 这个项目。首先，由于教育工作者的积极反应超出预期， 为了测试这项技术，我们需要为教师改进主动学习功能 和学生测试人员，并推进性能监控，以严格捕获数据。第二, 基础性人工智能模型(FM)有了非常迅速的改进，但还没有 合并到我们的原始应用程序中的适当开发阶段。我们建议 通过将性能监控无缝地结合到 软件，通过研究适当的FM并将其集成到用户体验中。

The original Phase IIb proposal addressed problems in analyzing, accessing and communicating increasingly large 3D and 4D image sets in neuroscience. This supplement request is motivated by two unforeseen developments since submission and review of the original application. The requested activities are necessary to maintain the high overall impact of the project. First, due to larger than expected positive response from educators who are interested in testing the technology, we need to refine the active learning features for instructors and student testers and advance performance monitoring to capture data rigorously. Second, there has been a very rapid improvement in Foundational AI Models (FM) but which were not at the appropriate stage of development to incorporate into our original application. We propose to address these developments by seamless incorporation of performance monitoring into the software, and by researching and integrating appropriate FMs into the user experience.