The Neural Decoding Toolbox

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...

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Published in:Frontiers in Neuroinformatics
Main Author: Ethan eMeyers
Format: Article
Language:English
Published: Frontiers Media S.A. 2013-05-01
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fninf.2013.00008/full
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author Ethan eMeyers
author_facet Ethan eMeyers
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container_title Frontiers in Neuroinformatics
description 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.
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spelling doaj-art-7060cd2e2efd4e66968a35fce37a46272025-08-19T20:23:00ZengFrontiers Media S.A.Frontiers in Neuroinformatics1662-51962013-05-01710.3389/fninf.2013.0000847170The Neural Decoding ToolboxEthan eMeyers0Massachusetts Institute of TechnologyPopulation 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.http://journal.frontiersin.org/Journal/10.3389/fninf.2013.00008/fullmachine learningMATLABdata analysismultivariate pattern analysisneural decodingreadout
spellingShingle Ethan eMeyers
The Neural Decoding Toolbox
machine learning
MATLAB
data analysis
multivariate pattern analysis
neural decoding
readout
title The Neural Decoding Toolbox
title_full The Neural Decoding Toolbox
title_fullStr The Neural Decoding Toolbox
title_full_unstemmed The Neural Decoding Toolbox
title_short The Neural Decoding Toolbox
title_sort neural decoding toolbox
topic machine learning
MATLAB
data analysis
multivariate pattern analysis
neural decoding
readout
url http://journal.frontiersin.org/Journal/10.3389/fninf.2013.00008/full
work_keys_str_mv AT ethanemeyers theneuraldecodingtoolbox
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