Mönke Gregor, Schäfer Tim, Parto-Dezfouli Mohsen, Kajal Diljit Singh, Fürtinger Stefan, Schmiedt Joscha Tapani, Fries Pascal
Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt, Germany.
Brain Research Institute, Universität Bremen, Bremen, Germany.
Front Neuroinform. 2024 Nov 20;18:1448161. doi: 10.3389/fninf.2024.1448161. eCollection 2024.
We introduce an open-source Python package for the analysis of large-scale electrophysiological data, named SyNCoPy, which stands for Systems Neuroscience Computing in Python. The package includes signal processing analyses across time (e.g., time-lock analysis), frequency (e.g., power spectrum), and connectivity (e.g., coherence) domains. It enables user-friendly data analysis on both laptop-based and high-performance computing systems. SyNCoPy is designed to facilitate trial-parallel workflows (parallel processing of trials), making it an ideal tool for large-scale analysis of electrophysiological data. Based on parallel processing of trials, the software can support very large-scale datasets via innovative out-of-core computation techniques. It also provides seamless interoperability with other standard software packages through a range of file format importers and exporters and open file formats. The naming of the user functions closely follows the well-established FieldTrip framework, which is an open-source MATLAB toolbox for advanced analysis of electrophysiological data.
我们推出了一个用于分析大规模电生理数据的开源Python包，名为SyNCoPy，即Python中的系统神经科学计算。该包包括跨时间（如锁时分析）、频率（如功率谱）和连通性（如相干性）域的信号处理分析。它能在基于笔记本电脑的系统和高性能计算系统上实现用户友好型的数据分析。SyNCoPy旨在促进试验并行工作流程（试验的并行处理），使其成为大规模电生理数据分析的理想工具。基于试验的并行处理，该软件可通过创新的核外计算技术支持超大规模数据集。它还通过一系列文件格式导入器和导出器以及开放文件格式，与其他标准软件包实现无缝互操作性。用户函数的命名紧密遵循成熟的FieldTrip框架，FieldTrip是一个用于电生理数据高级分析的开源MATLAB工具箱。
