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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

基本信息

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
项目类别：
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

项目摘要

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数据格式推进生物逼真建模