odML-Tables as a Metadata Standard in Microneurography.

Metadata standards are well-established for many types of electrophysiological methods but are still lacking for microneurographic recordings of peripheral sensory nerve fibers in humans. Finding a solution for daily work in the laboratory is a complex process. We have designed templates based on odML and odML-tables to structure and capture metadata and provided an extension to the existing GUI to enable database searching.

odML-Tables as a Metadata Standard in Microneurography.

Metadata is essential for handling medical data according to FAIR principles. Standards are well-established for many types of electrophysiological methods but are still lacking for microneurographic recordings of peripheral sensory nerve fibers in humans. Developing a new concept to enhance laboratory workflows is a complex process. We propose a standard for structuring and storing microneurography metadata based on odML and odML-tables. Further, we present an extension to the odML-tables GUI that enables user-friendly search functionality of the database. With our open-source repository, we encourage other microneurography labs to incorporate odML-based metadata into their experimental routines.

openMNGlab: Data Analysis Framework for Microneurography - A Technical Report.

openMNGlab is an open-source software framework for data analysis, tailored for the specific needs of microneurography - a type of electrophysiological technique particularly important for research on peripheral neural fibers coding. Currently, openMNGlab loads data from Spike2 and Dapsys, which are two major data acquisition solutions. By building on top of the Neo software, openMNGlab can be easily extended to handle the most common electrophysiological data formats. Furthermore, it provides methods for data visualization, fiber tracking, and a modular feature database to extract features for data analysis and machine learning.