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PyDapsys:一个用于访问由DAPSYS记录的电生理数据的开源库。

PyDapsys: an open-source library for accessing electrophysiology data recorded with DAPSYS.

作者信息

Konradi Peter, Troglio Alina, Pérez Garriga Ariadna, Pérez Martín Aarón, Röhrig Rainer, Namer Barbara, Kutafina Ekaterina

机构信息

Institute of Medical Informatics, Medical Faculty, RWTH Aachen University, Aachen, Germany.

Research Group Neuroscience, IZKF, RWTH Aachen, Aachen, Germany.

出版信息

Front Neuroinform. 2023 Sep 14;17:1250260. doi: 10.3389/fninf.2023.1250260. eCollection 2023.

Abstract

In the field of neuroscience, a considerable number of commercial data acquisition and processing solutions rely on proprietary formats for data storage. This often leads to data being locked up in formats that are only accessible by using the original software, which may lead to interoperability problems. In fact, even the loss of data access is possible if the software becomes unsupported, changed, or otherwise unavailable. To ensure FAIR data management, strategies should be established to enable long-term, independent, and unified access to data in proprietary formats. In this work, we demonstrate PyDapsys, a solution to gain open access to data that was acquired using the proprietary recording system DAPSYS. PyDapsys enables us to open the recorded files directly in Python and saves them as NIX files, commonly used for open research in the electrophysiology domain. Thus, PyDapsys secures efficient and open access to existing and prospective data. The manuscript demonstrates the complete process of reverse engineering a proprietary electrophysiological format on the example of microneurography data collected for studies on pain and itch signaling in peripheral neural fibers.

摘要

在神经科学领域,相当多的商业数据采集和处理解决方案依赖专有格式来存储数据。这常常导致数据被锁定在只有使用原始软件才能访问的格式中,这可能会引发互操作性问题。事实上,如果软件不再受支持、发生更改或以其他方式无法使用,甚至可能导致数据访问丢失。为确保实现公平的数据管理,应制定策略,以便能够长期、独立且统一地访问专有格式的数据。在这项工作中,我们展示了PyDapsys,这是一种用于开放访问使用专有记录系统DAPSYS采集的数据的解决方案。PyDapsys使我们能够直接在Python中打开记录的文件,并将它们保存为NIX文件,NIX文件常用于电生理学领域的开放研究。因此,PyDapsys确保了对现有和未来数据的高效且开放的访问。本文以收集用于研究外周神经纤维疼痛和瘙痒信号的微神经图数据为例,展示了对专有电生理格式进行逆向工程的完整过程。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/038e/10539619/6467fb17e238/fninf-17-1250260-g001.jpg

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