Simultaneous recordings from hundreds or thousands of neurons are becoming routine because of innovations in instrumentation, molecular tools, and data processing software. Such recordings can be analyzed with data science methods, but it is not immediately clear what methods to use or how to adapt them for neuroscience applications. We review, categorize, and illustrate diverse analysis methods for neural population recordings and describe how these methods have been used to make progress on longstanding questions in neuroscience. We review a variety of approaches, ranging from the mathematically simple to the complex, from exploratory to hypothesis-driven, and from recently developed to more established methods. We also illustrate some of the common statistical pitfalls in analyzing large-scale neural data.

中文翻译：

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大规模神经元记录的分析方法


由于仪器、分子工具和数据处理软件的创新，来自数百或数千个神经元的同时记录正在成为常规。可以使用数据科学方法分析此类记录，但目前尚不清楚使用哪些方法或如何使它们适应神经科学应用。我们回顾、分类和说明了神经群体记录的不同分析方法，并描述了如何使用这些方法在神经科学中长期存在的问题上取得进展。我们回顾了各种方法，从数学上简单的到复杂的，从探索性到假设驱动的，从最近开发的方法到更成熟的方法。我们还说明了分析大规模神经数据时的一些常见统计陷阱。