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.

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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

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article

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

Diljit Singh Kajal, Joscha T. Schmiedt, Mohsen Parto-Dezfouli, Gregor Mönke et al.
3 citations
Frontiers in Neuroinformatics
EEG and Brain-Computer Interfaces
1.03
article

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

Diljit Singh Kajal, Joscha T. Schmiedt, Mohsen Parto-Dezfouli, Gregor Mönke, Pascal H. Fries, Stefan Fürtinger, Tim Schäfer
article en
3 citations

Abstract

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.

Frontiers in NeuroinformaticsVol. 18
Radboud University Nijmegen (NL), University of Bremen (DE), Ernst Strüngmann Institute for Neuroscience (DE), Max Planck Institute for Biological Cybernetics (DE), Brain (Germany) (DE)
Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 23%
EEG and Brain-Computer Interfaces
1.03
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