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

Authors :
Mönke, Gregor
Schäfer, Tim
Parto-Dezfouli, Mohsen
Kajal, Diljit Singh
Fürtinger, Stefan
Schmiedt, Joscha Tapani
Fries, Pascal
Source :
Frontiers in Neuroinformatics; 2024, p1-8, 8p
Publication Year :
2024

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16625196
Database :
Complementary Index
Journal :
Frontiers in Neuroinformatics
Publication Type :
Academic Journal
Accession number :
181412110
Full Text :
https://doi.org/10.3389/fninf.2024.1448161