Advancing Bio-Realistic Modeling via the Brain Modeling ToolKit and SONATA Data Format

通过大脑建模工具包和 SONATA 数据格式推进生物真实建模

• 批准号: 10306896
• 负责人: ANTON ARKHIPOV
• 金额: $ 66.24万
• 依托单位: ALLEN INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2027-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10306896
• 关键词: Address; Area; BRAIN initiative; Behavior; Biological; Biophysics; Brain; Brain region; Cells; Code; Communities; Complex; Computer Workstations; Computer software; Data; Data Analyses; Databases; Documentation; Educational workshop; European; FAIR principles; Feedback; Goals; Graph; Human; Illinois; Institutes; Intuition; Language; Literature; Manuscripts; Modality; Modeling; Molecular; Neurons; Neurosciences; Output; Personal Computers; Persons; Population Dynamics; Population Statistics; Property; Publications; Reproducibility; Resolution; Resources; Running; Software Tools; Structural Models; Training; Universities; Vision; Visual; Visualization; Visualization software; Work; Zaleplon; base; data exchange; data format; data integration; digital; diverse data; experimental study; file format; flexibility; graphical user interface; interest; model building; models and simulation; movie; multimodal data; network architecture; network models; response; scripting interface; simulation; theories; tool; user-friendly

Advancing Bio-Realistic Modeling via the Brain Modeling ToolKit and SONATA Data Format One of the major goals of the BRAIN Initiative is to distill complex, multi-modal data into predictive frameworks via theory/modeling. As the planning document "BRAIN 2025: A Scientific Vision" urges, “theory and modeling should be woven into successive stages of ongoing experiments, enabling bridges to be built from single cells to connectivity, population dynamics, and behavior.” However, data-driven, bio-realistic modeling is not widely practiced, in part because the field needs software supporting such complex modeling and standards for model sharing and reproducibility. The Allen Institute has developed two powerful tools addressing these needs. One is the Brain Modeling ToolKit (BMTK) – a software suite for model building and simulation at multiple levels of resolution, from networks of biophysically detailed neuronal models, to point-neuron networks, to population-statistics approaches. The other one is the SONATA (Scalable Open Network Architecture TemplAte) data format, which provides computationally efficient solutions for storing and exchanging data describing all stages of the modeling workflow (e.g., structure of model networks, configuration of simulations, simulation outputs). These tools were developed in coordination with many initiatives, such as NEURON, NEST, Neurodata Without Borders, NeuroML, PyNN, NetPyNE, and the Human Brain Project. As a result, BMTK and SONATA enable many applications and have generated substantial interest, with many users already employing these tools. Most recently, BMTK and SONATA were instrumental in integrating diverse data from the Allen Institute and from the literature into some of the most sophisticated and bio-realistic models of a brain region to date. We propose to build a comprehensive user support and dissemination platform for BMTK and SONATA and help integrate these tools into model building and simulation practices in the community. In addition, the Allen Institute team joins forces with a University of Illinois team that developed a widely used molecular visualization software VMD. By integrating this software with SONATA, we will leverage its powerful existing capabilities to offer a free, highly efficient visualization tool for neuroscience modeling. Together, these tools will facilitate free exchange and reproducibility of models and support sophisticated modeling work – especially in cases of large-scale biologically realistic models relying on systematic integration of experimental data – for novice and expert users alike. These contributions will advance the BRAIN Initiative’s priority areas of Theory and Data Analysis and Integrated Approaches and will strongly facilitate FAIRness (Findability, Accessibility, Interoperability, and Reuse of digital assets) in neuroscience modeling.

通过大脑建模工具包和 SONATA 数据格式推进生物真实建模 BRAIN Initiative 的主要目标之一是将复杂的多模式数据提炼成预测框架 正如规划文件“BRAIN 2025：科学愿景”所敦促的那样，“理论和建模。 应该融入正在进行的实验的连续阶段，从而能够从单细胞构建桥梁 然而，数据驱动的生物现实建模并未得到广泛使用。 实践中，部分原因是该领域需要支持如此复杂的建模和模型标准的软件 共享性和可重复性。 艾伦研究所开发了两种强大的工具来满足这些需求，其中之一是大脑建模。 ToolKit (BMTK) – 用于在多个分辨率级别上进行模型构建和仿真的软件套件，从 生物物理详细神经模型网络、点神经元网络、群体统计 另一种方法是SONATA（可扩展开放网络架构TemplAte）数据格式， 它为存储和交换描述所有阶段的数据提供了计算有效的解决方案 建模工作流程（例如模型网络的结构、模拟的配置、模拟输出）。 工具是与许多计划协调开发的，例如 NEURON、NEST、Neurodata Without Borders、NeuroML、PyNN、NetPyNE 和人脑项目因此，BMTK 和 SONATA 得以实现。 许多应用程序并引起了极大的兴趣，许多用户已经在使用这些工具。 最近，BMTK 和 SONATA 在整合来自艾伦研究所和 从文献中转化为迄今为止最复杂、最符合生物现实的大脑区域模型。 我们建议为BMTK和SONATA建立一个全面的用户支持和传播平台 此外，Allen 还帮助将这些工具集成到社区的模型构建和模拟实践中。 研究所团队与伊利诺伊大学团队联手开发了广泛使用的分子可视化 通过将该软件与 SONATA 集成，我们将利用其强大的现有功能来 为神经科学建模提供免费、高效的可视化工具，这些工具将共同促进免费。 模型的交换和再现性，并支持复杂的建模工作——尤其是在以下情况下 依赖于实验数据的系统整合的大规模生物现实模型 - 适合新手和 这些贡献将推动 BRAIN Initiative 的理论和数据优先领域的发展。 分析和综合方法将大力促进公平性（可查找性、可访问性、 神经科学建模中的互操作性和数字资产的重用。