Systems Neuroscience Computing in Python (SyNCoPy): a python package for large-scale analysis of electrophysiological data - Mönke, Gregor; Schäfer, Tim; Parto-Dezfouli, Mohsen; Kajal, Diljit Singh; Fürtinger, Stefan; Schmiedt, Joscha Tapani; Fries, Pascal (Frontiers in neuroinformatics, 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.