An integrative analysis platform for multiple neural spike train data.

作者:Huang Yu; Li Xiangning; Li Yanling; Xu Qingwei; Lu Qiang; Liu Qian*
来源:J Neurosci Methods, 2008, 172(2): 303-311.
DOI:10.1016/j.jneumeth.2008.04.026

摘要

In neuroscience research, multiple electrodes are used to record simultaneous spiking activity of many neurons lossless in real time. Accordingly, to analyze the data from multiple electrodes, many algorithms and computer programs have been developed. Since these programs are developed by commercial companies or academic institutes independently, the lack of common standard makes the talks between them difficult. In one integrative analysis, when several of them are needed, neuroscience researchers are usually exhausted by the program switching and data transformation. In this paper, we developed an integrative workflow-based platform for multiple neural spike train data analysis, namely MEA-Platform. MEA-Platform is a Java-based software platform, which provides (1) a general application development interface to integrate or bridge other programs and (2) a workflow mechanism to operate them and make them talk easily. At the moment, many algorithms and tools abstracted from MEA-Tools, Spike manager and DATA-MEAns are integrated. They together provide comprehensive functionalities of data normalization, statistics and result reporting, which are indispensable for a complete analysis of multiple neural spike train data. Because the interface developed is very general and flexible, new analysis tools can be integrated effectively as required. MEA-Platform implies an ideal environment for integrative neuroscience research.