Department of Brain and Cognitive Sciences, McGovern Institute, Massachusetts Institute of Technology Cambridge, MA, USA.
Front Neuroinform. 2013 May 22;7:8. doi: 10.3389/fninf.2013.00008. eCollection 2013.
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.
群体解码是一种强大的分析神经数据的方法,然而,目前只有一小部分系统神经科学研究人员使用这种方法。为了增加群体解码的使用,我们创建了神经解码工具箱(NDT),这是一个 Matlab 软件包,使得应用群体解码分析神经活动变得容易。该工具箱的设计围绕着四个抽象对象类,使用户能够交换特定的模块,以便在保持处理流程其余部分完整的情况下尝试不同的分析。该工具箱能够分析来自多种不同类型记录方式的数据,我们给出了一些示例,说明如何使用它从神经尖峰活动中解码基本视觉信息,以及如何使用它来检查神经群体的活动对刺激变换的不变性。总的来说,这个工具箱将使神经科学家更容易地将群体解码分析应用于他们的数据,这应该有助于加快神经科学的发现速度。