系统神经科学计算在Python (SyNCoPy):一个Python包的电生理数据的大规模分析。

IF 2.5 4区 医学 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Frontiers in Neuroinformatics Pub Date : 2024-11-20 eCollection Date: 2024-01-01 DOI:10.3389/fninf.2024.1448161
Gregor Mönke, Tim Schäfer, Mohsen Parto-Dezfouli, Diljit Singh Kajal, Stefan Fürtinger, Joscha Tapani Schmiedt, Pascal Fries
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引用次数: 0

摘要

我们介绍了一个用于分析大规模电生理数据的开源Python包,名为SyNCoPy,它代表Python中的系统神经科学计算。该软件包包括跨时间(例如,时间锁分析)、频率(例如,功率谱)和连接(例如,相干)域的信号处理分析。它支持在基于笔记本电脑和高性能计算系统上进行用户友好的数据分析。SyNCoPy旨在促进试验并行工作流程(并行处理试验),使其成为电生理数据大规模分析的理想工具。基于试验的并行处理,该软件可以通过创新的核外计算技术支持非常大规模的数据集。它还通过一系列文件格式导入和导出以及打开文件格式,提供了与其他标准软件包的无缝互操作性。用户函数的命名密切遵循完善的FieldTrip框架,这是一个开源的MATLAB工具箱,用于电生理数据的高级分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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来源期刊
Frontiers in Neuroinformatics
Frontiers in Neuroinformatics MATHEMATICAL & COMPUTATIONAL BIOLOGY-NEUROSCIENCES
CiteScore
4.80
自引率
5.70%
发文量
132
审稿时长
14 weeks
期刊介绍: Frontiers in Neuroinformatics publishes rigorously peer-reviewed research on the development and implementation of numerical/computational models and analytical tools used to share, integrate and analyze experimental data and advance theories of the nervous system functions. Specialty Chief Editors Jan G. Bjaalie at the University of Oslo and Sean L. Hill at the École Polytechnique Fédérale de Lausanne are supported by an outstanding Editorial Board of international experts. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics and the public worldwide. Neuroscience is being propelled into the information age as the volume of information explodes, demanding organization and synthesis. Novel synthesis approaches are opening up a new dimension for the exploration of the components of brain elements and systems and the vast number of variables that underlie their functions. Neural data is highly heterogeneous with complex inter-relations across multiple levels, driving the need for innovative organizing and synthesizing approaches from genes to cognition, and covering a range of species and disease states. Frontiers in Neuroinformatics therefore welcomes submissions on existing neuroscience databases, development of data and knowledge bases for all levels of neuroscience, applications and technologies that can facilitate data sharing (interoperability, formats, terminologies, and ontologies), and novel tools for data acquisition, analyses, visualization, and dissemination of nervous system data. Our journal welcomes submissions on new tools (software and hardware) that support brain modeling, and the merging of neuroscience databases with brain models used for simulation and visualization.
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