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

Frontiers in Neuroinformatics, vol. 17, pp. 1250260

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.

Authors 6

1. Peter Konradi corresponding Aachen Institute of Medical Informatics Medical Faculty

   RWTH Aachen University

   Affiliation as printed

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

2. Alina Troglio Aachen Research group Neuroscience

   RWTH Aachen University

   Affiliation as printed

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

3. Ariadna Pérez Garriga Aachen Institute of Medical Informatics Medical Faculty

   RWTH Aachen University

   Affiliation as printed

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

4. Aarón Pérez Martín

   Forschungszentrum Jülich · Jülich Aachen Research Alliance · Jülich Supercomputing Centre

   Affiliation as printed

   Simulation and Data Lab Neuroscience, Jülich Supercomputing Centre (JSC), Institute for Advanced Simulation, JARA, Forschungszentrum Jülich GmbH, Jülich, Germany

5. Barbara Namer Aachen Department for Neurophysiology Research group Neuroscience

   Friedrich-Alexander-Universität Erlangen-Nürnberg · Universitätsklinikum Aachen · RWTH Aachen University

   Affiliation as printed

   Department for Neurophysiology, University Hospital RWTH Aachen, Aachen, Germany

   Institute of Physiology and Pathophysiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany

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

6. Ekaterina Kutafina Aachen Institute of Medical Informatics Medical Faculty

   RWTH Aachen University

   Affiliation as printed

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