Systems Neuroscience Computing in Python (SyNCoPy): a python package for large-scale analysis of electrophysiological data

• Published in: Frontiers in neuroinformatics Vol. 18; p. 1448161
• Main Authors: Mönke, Gregor, Schäfer, Tim, Parto-Dezfouli, Mohsen, Kajal, Diljit Singh, Fürtinger, Stefan, Schmiedt, Joscha Tapani, Fries, Pascal
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Research Foundation 20.11.2024; Frontiers Media S.A
• Subjects: Algorithms; Application programming interface; Brain; coherence spectra; Data processing; Datasets; Distributed processing; Electroencephalography; electroencephalography (EEG); High performance computing; local field potential (LFP); Localization; magnetoencephalography (MEG); Memory; Metadata; Neural networks; Neuroscience; Neurosciences; Portable computers; power spectra; Signal processing; Software packages; spike train; electroencephalography (EEG); Granger causality spectra; coherence spectra; magnetoencephalography (MEG); power spectra; local field potential (LFP); spike train; big data
• ISSN: 1662-5196; 1662-5196
• DOI: 10.3389/fninf.2024.1448161

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.