NeuroDecodeR: a package for neural decoding in R

被引:1
作者
Meyers, Ethan M. [1 ,2 ,3 ]
机构
[1] Yale Univ, Dept Stat & Data Sci, New Haven, CT 06511 USA
[2] Hampshire Coll, Sch Cognit Sci, Amherst, MA 01002 USA
[3] MIT, Ctr Brains Minds & Machines, Cambridge, MA 02139 USA
基金
美国国家科学基金会;
关键词
neural decoding; readout; multivariate pattern analysis; R; data analysis; statistics; machine learning; data science; INFORMATION; OBJECT; PATTERNS; CLASSIFICATION; PREDICTION; DYNAMICS; IDENTITY; NEURONS;
D O I
10.3389/fninf.2023.1275903
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Neural decoding is a powerful method to analyze neural activity. However, the code needed to run a decoding analysis can be complex, which can present a barrier to using the method. In this paper we introduce a package that makes it easy to perform decoding analyses in the R programing language. We describe how the package is designed in a modular fashion which allows researchers to easily implement a range of different analyses. We also discuss how to format data to be able to use the package, and we give two examples of how to use the package to analyze real data. We believe that this package, combined with the rich data analysis ecosystem in R, will make it significantly easier for researchers to create reproducible decoding analyses, which should help increase the pace of neuroscience discoveries.
引用
收藏
页数:13
相关论文
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