Günay Cengiz, Edgerton Jeremy R, Li Su, Sangrey Thomas, Prinz Astrid A, Jaeger Dieter
Dept. of Biology, Emory University, Atlanta, GA 30322, USA.
Neuroinformatics. 2009 Jun;7(2):93-111. doi: 10.1007/s12021-009-9048-z. Epub 2009 May 28.
Neuronal recordings and computer simulations produce ever growing amounts of data, impeding conventional analysis methods from keeping pace. Such large datasets can be automatically analyzed by taking advantage of the well-established relational database paradigm. Raw electrophysiology data can be entered into a database by extracting its interesting characteristics (e.g., firing rate). Compared to storing the raw data directly, this database representation is several orders of magnitude higher efficient in storage space and processing time. Using two large electrophysiology recording and simulation datasets, we demonstrate that the database can be queried, transformed and analyzed. This process is relatively simple and easy to learn because it takes place entirely in Matlab, using our database analysis toolbox, PANDORA. It is capable of acquiring data from common recording and simulation platforms and exchanging data with external database engines and other analysis toolboxes, which make analysis simpler and highly interoperable. PANDORA is available to be freely used and modified because it is open-source (http://software.incf.org/software/pandora/home).
神经元记录和计算机模拟产生的数据量不断增加，使得传统分析方法难以跟上步伐。利用成熟的关系数据库范式可以自动分析如此庞大的数据集。通过提取原始电生理数据的有趣特征（例如放电率），可以将其输入数据库。与直接存储原始数据相比，这种数据库表示在存储空间和处理时间方面的效率要高出几个数量级。使用两个大型电生理记录和模拟数据集，我们证明了可以对数据库进行查询、转换和分析。这个过程相对简单且易于学习，因为它完全在Matlab中进行，使用我们的数据库分析工具箱PANDORA。它能够从常见的记录和模拟平台获取数据，并与外部数据库引擎和其他分析工具箱交换数据，这使得分析更简单且具有高度的互操作性。PANDORA是开源的（http://software.incf.org/software/pandora/home），可供免费使用和修改。
