Integration of information across heterogeneous sources creates added scientific value. Interoperability of data, tools and models is, however, difficult to accomplish across spatial and temporal scales. Here we introduce the toolbox Parallel Co-Simulation, which enables the interoperation of simulators operating at different scales. We provide a software science co-design pattern and illustrate its functioning along a neuroscience example, in which individual regions of interest are simulated on the cellular level allowing us to study detailed mechanisms, while the remaining network is efficiently simulated on the population level. A workflow is illustrated for the use case of The Virtual Brain and NEST, in which the CA1 region of the cellular-level hippocampus of the mouse is embedded into a full brain network involving micro and macro electrode recordings. This new tool allows integrating knowledge across scales in the same simulation framework and validating them against multiscale experiments, thereby largely widening the explanatory power of computational models.

中文翻译：

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神经科学应用的多尺度联合仿真设计模式

跨异构来源的信息整合创造了附加的科学价值。然而，数据、工具和模型的互操作性很难跨空间和时间尺度实现。在这里，我们介绍并行联合仿真工具箱，它可以实现不同规模的模拟器的互操作。我们提供了一种软件科学协同设计模式，并通过神经科学示例说明了其功能，其中在细胞水平上模拟各个感兴趣的区域，使我们能够研究详细的机制，而其余网络则在群体水平上进行有效模拟。图中展示了虚拟大脑和 NEST 用例的工作流程，其中小鼠细胞级海马体的 CA1 区域被嵌入到涉及微观和宏观电极记录的完整大脑网络中。这种新工具允许将跨尺度的知识整合到同一模拟框架中，并根据多尺度实验对其进行验证，从而极大地扩大了计算模型的解释能力。