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

Moenke, G., Schaefer, T., Parto-Dezfouli, M., Kajal, D., Fuertinger, S., Schmiedt, J., et al. (submitted). Systems Neuroscience Computing in Python (SyNCoPy): A Python Package for Large-scale Analysis of Electrophysiological Data.

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 Creators:
Moenke, G, Author
Schaefer, T, Author
Parto-Dezfouli, M, Author
Kajal, DS, Author
Fuertinger, S, Author
Schmiedt, JT, Author
Fries, P1, Author                 
Affiliations:
1Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_3017468              

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 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.

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 Dates: 2024-04
 Publication Status: Submitted
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.1101/2024.04.15.589590
 Degree: -

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