Comparative neuroscience is entering the era of big data. New high-throughput methods and data-sharing initiatives have resulted in the availability of large, digital data sets containing many types of data from ever more species. Here, we present a framework for exploiting the new possibilities offered. The multimodality of the data allows vertical translations, which are comparisons of different aspects of brain organization within a single species and across scales. Horizontal translations compare particular aspects of brain organization across species, often by building abstract feature spaces. Combining vertical and horizontal translations allows for more sophisticated comparisons, including relating principles of brain organization across species by contrasting horizontal translations, and for making formal predictions of unobtainable data based on observed results in a model species. Expected final online publication date for the Annual Review of Neuroscience, Volume 44 is July 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

中文翻译：

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比较神经科学的通用空间方法。

比较神经科学正在进入大数据时代。新的高通量方法和数据共享计划已导致提供了大型数字数据集，其中包含来自越来越多物种的许多类型的数据。在这里，我们提出了一个框架，以利用所提供的新可能性。数据的多模态性允许垂直翻译，这是单个物种内和跨尺度的大脑组织不同方面的比较。水平翻译通常通过建立抽象特征空间来比较跨物种的大脑组织的特定方面。将垂直和水平翻译结合起来可以进行更复杂的比较，包括通过对比水平翻译来比较跨物种的大脑组织原理，并根据模型物种的观察结果对无法获得的数据进行正式预测。《神经科学年度评论》（第44卷）的最终最终在线发布日期为2021年7月。有关修订的估算，请参见http://www.annualreviews.org/page/journal/pubdates。