Background

The Allen Institute recently built a set of high-throughput experimental pipelines to collect comprehensive in vivo surveys of physiological activity in the visual cortex of awake, head-fixed mice. Developing these large-scale, industrial-like pipelines posed many scientific, operational, and engineering challenges.

New method

Our strategies for creating a cross-platform reference space to which all pipeline datasets were mapped required development of 1) a robust headframe, 2) a reproducible clamping system, and 3) data-collection systems that are built, and maintained, around precise alignment with a reference artifact.

Results

When paired with our pipeline clamping system, our headframe exceeded deflection and reproducibility requirements. By leveraging our headframe and clamping system we were able to create a cross-platform reference space to which multi-modal imaging datasets could be mapped.

Comparison with existing methods

Together, the Allen Brain Observatory headframe, surgical tooling, clamping system, and system registration strategy create a unique system for collecting large amounts of standardized in vivo datasets over long periods of time. Moreover, the integrated approach to cross-platform registration allows for multi-modal datasets to be collected within a shared reference space.

Conclusions

Here we report the engineering strategies that we implemented when creating the Allen Brain Observatory physiology pipelines. All of the documentation related to headframe, surgical tooling, and clamp design has been made freely available and can be readily manufactured or procured. The engineering strategy, or components of the strategy, described in this report can be tailored and applied by external researchers to improve data standardization and stability.

中文翻译：

---

用于在小鼠中进行大规模体内生理记录的标准化头部固定系统。

背景

艾伦研究所最近建立了一组高通量实验管线，以收集清醒的，头部固定的小鼠视觉皮层中生理活性的全面体内调查。开发这些大型的，类似工业的管道带来了许多科学，运营和工程方面的挑战。

新方法

我们创建跨平台参考空间（所有管道数据集都映射到该参考空间）的策略需要以下方面的开发：1）坚固的机架，2）可再现的夹紧系统和3）围绕精确对齐构建和维护的数据收集系统带有参考工件。

结果

与我们的管道夹紧系统配合使用时，我们的头架超出了挠度和可重复性的要求。通过利用我们的机架和夹紧系统，我们可以创建一个跨平台参考空间，可以将多模式成像数据集映射到该参考空间。

与现有方法的比较

艾伦大脑天文台的头架，手术工具，夹持系统和系统配准策略共同创建了一个独特的系统，可长期收集大量标准化的体内数据集。此外，跨平台注册的集成方法允许在共享的参考空间内收集多模式数据集。

结论

在这里，我们报告创建Allen Brain Observatory生理管线时实施的工程策略。与头架，手术工具和夹具设计有关的所有文档均可免费获得，并且可以轻松制造或采购。本报告中描述的工程策略或策略的组成部分可以由外部研究人员定制和应用，以提高数据的标准化和稳定性。