Howard Hughes Medical Institute (HHMI) Janelia Research Campus, Ashburn, VA, USA.
Science. 2024 Nov 8;386(6722):eadp7429. doi: 10.1126/science.adp7429.
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.
由于仪器设备、分子工具和数据处理软件的创新，同时记录数百或数千个神经元已经成为常规操作。这些记录可以使用数据科学方法进行分析，但目前尚不清楚应该使用哪些方法以及如何将其应用于神经科学。我们综述了神经群体记录的各种分析方法，并进行了分类和说明，同时描述了这些方法如何被用于解决神经科学中长期存在的问题。我们综述了从数学上简单到复杂、从探索性到假设驱动、从最近开发到更成熟的各种方法。我们还举例说明了分析大规模神经数据时常见的一些统计陷阱。
