NeuroDecodeR: Decode Information from Neural Activity

Neural decoding is method of analyzing neural data that uses a pattern classifiers to predict experimental conditions based on neural activity. 'NeuroDecodeR' is a system of objects that makes it easy to run neural decoding analyses. For more information on neural decoding see Meyers & Kreiman (2004) <doi:10.7551/mitpress/8404.003.0024>.

Version: 0.1.0
Depends: R (≥ 4.1.0)
Imports: dplyr, doSNOW, e1071, forcats, foreach, ggplot2, gridExtra, magrittr, methods, purrr, R.matlab, scales, stats, stringr, tibble, tictoc, tidyr, utils
Suggests: knitr, rmarkdown, testthat
Published: 2022-09-29
Author: Ethan Meyers [aut, cre]
Maintainer: Ethan Meyers <ethan.meyers at gmail.com>
BugReports: https://github.com/emeyers/NeuroDecodeR/issues
License: GPL-3
URL: https://github.com/emeyers/NeuroDecodeR
NeedsCompilation: no
Materials: README
CRAN checks: NeuroDecodeR results

Documentation:

Reference manual: NeuroDecodeR.pdf
Vignettes: NeuroDecodeR object specification
Data formats
Datasets
Generalization analysis tutorial
Introductory tutorial

Downloads:

Package source: NeuroDecodeR_0.1.0.tar.gz
Windows binaries: r-devel: NeuroDecodeR_0.1.0.zip, r-release: NeuroDecodeR_0.1.0.zip, r-oldrel: NeuroDecodeR_0.1.0.zip
macOS binaries: r-release (arm64): NeuroDecodeR_0.1.0.tgz, r-oldrel (arm64): NeuroDecodeR_0.1.0.tgz, r-release (x86_64): NeuroDecodeR_0.1.0.tgz

Linking:

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