title: The neural decoding toolbox.
abstract: Population decoding is a powerful way to analyze neural data, however, currently only a small percentage of systems neuroscience researchers use this method. In order to increase the use of population decoding, we have created the Neural Decoding Toolbox (NDT) which is a Matlab package that makes it easy to apply population decoding analyses to neural activity. The design of the toolbox revolves around four abstract object classes which enables users to interchange particular modules in order to try different analyses while keeping the rest of the processing stream intact. The toolbox is capable of analyzing data from many different types of recording modalities, and we give examples of how it can be used to decode basic visual information from neural spiking activity and how it can be used to examine how invariant the activity of a neural population is to stimulus transformations. Overall this toolbox will make it much easier for neuroscientists to apply population decoding analyses to their data, which should help increase the pace of discovery in neuroscience.
authors.affiliation: Department of Brain and Cognitive Sciences, McGovern Institute, Massachusetts Institute of Technology Cambridge, MA, USA.
authors.forename: Ethan M
authors.initials: EM
authors.lastname: Meyers
keywords: Matlab; data analysis; machine learning; multivariate pattern analysis; neural decoding; readout