Systems Neuroscience Computing in Python (SyNCoPy): a python package for large-scale analysis of electrophysiological data
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.
Authors
- Diljit Singh Kajal (ORCID: https://orcid.org/0000-0002-0176-5342)
- Joscha T. Schmiedt (ORCID: https://orcid.org/0000-0001-6233-1866)
- Mohsen Parto-Dezfouli (ORCID: https://orcid.org/0000-0002-9064-2212)
- Gregor Mönke (ORCID: https://orcid.org/0000-0002-3521-715X)
- Pascal H. Fries (ORCID: https://orcid.org/0000-0002-7137-9439)
- Stefan Fürtinger
- Tim Schäfer
Institutions
- Radboud University Nijmegen (NL)
- University of Bremen (DE)
- Ernst Strüngmann Institute for Neuroscience (DE)
- Max Planck Institute for Biological Cybernetics (DE)
- Brain (Germany) (DE)
Publication Details
- Journal
- Frontiers in Neuroinformatics
- Published
- 2024-11-20
- DOI
- https://doi.org/10.3389/fninf.2024.1448161
- Citations
- 3
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 1.03
Funders
- Deutsche Forschungsgemeinschaft