Gehring Tiago V, Vasilaki Eleni, Giugliano Michele
Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:4178-81. doi: 10.1109/EMBC.2015.7319315.
Technological advances of Multielectrode Arrays (MEAs) used for multisite, parallel electrophysiological recordings, lead to an ever increasing amount of raw data being generated. Arrays with hundreds up to a few thousands of electrodes are slowly seeing widespread use and the expectation is that more sophisticated arrays will become available in the near future. In order to process the large data volumes resulting from MEA recordings there is a pressing need for new software tools able to process many data channels in parallel. Here we present a new tool for processing MEA data recordings that makes use of new programming paradigms and recent technology developments to unleash the power of modern highly parallel hardware, such as multi-core CPUs with vector instruction sets or GPGPUs. Our tool builds on and complements existing MEA data analysis packages. It shows high scalability and can be used to speed up some performance critical pre-processing steps such as data filtering and spike detection, helping to make the analysis of larger data sets tractable.
用于多部位并行电生理记录的多电极阵列(MEA)技术进步,导致产生的原始数据量不断增加。具有数百到数千个电极的阵列正逐渐得到广泛应用,并且预计在不久的将来会有更复杂的阵列出现。为了处理MEA记录产生的大量数据,迫切需要能够并行处理多个数据通道的新软件工具。在此,我们展示了一种用于处理MEA数据记录的新工具,该工具利用新的编程范式和最新技术发展来释放现代高度并行硬件(如具有向量指令集的多核CPU或通用图形处理器)的能力。我们的工具基于现有MEA数据分析软件包构建并对其进行补充。它具有高可扩展性,可用于加速一些对性能要求较高的预处理步骤,如数据滤波和尖峰检测,有助于使更大数据集的分析变得可行。