Systems Neuroscience Computing in Python (SyNCoPy): A Python Package for Large-scale Analysis of Electrophysiological Data

Abstract

We introduce an open-source Python package for the analysis of large-scale electrophysiological data called SyNCoPy, 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.