Abstract
Analyses of brain function and anatomy using shared neuroimaging data is an important development, and have acquired the potential to be scaled up with the specification of a new Brain Imaging Data Structure (BIDS) standard. To date, a variety of software tools help researchers in converting their source data to BIDS but often require programming skills or are tailored to specific institutes, data sets, or data formats. In this paper, we introduce BIDScoin, a cross-platform, flexible, and user-friendly converter that provides a graphical user interface (GUI) to help users finding their way in BIDS standard. BIDScoin does not require programming skills to be set up and used and supports plugins to extend their functionality. In this paper, we show its design and demonstrate how it can be applied to a downloadable tutorial data set. BIDScoin is distributed as free and open-source software to foster the community-driven effort to promote and facilitate the use of BIDS standard.
Highlights
In the last few decades, neuroimaging data have become an increasingly rich source of information for studying the working of the brain in health and disease
The latest BIDScoin version 3.7 as described in this paper is written in Python 3.6 and dependent on the freely available PyQt5 (Riverbank Computing Limited, Dorchester, England) software library for the graphical user interface (GUI)
BIDScoin has been developed in the Donders Institute for Cognitive Neuroimaging at the Radboud University
Summary
In the last few decades, neuroimaging data have become an increasingly rich source of information for studying the working of the brain in health and disease. Contemporary neuroscientific and clinical research questions are based on ever advancing analysis methods that require the availability of data sets that are very large ( known as “big data”) or of superior quality, or both. The initial lack of data-structure standardization, data-sharing tools, and data-sharing mindset (Poline et al, 2012; Nichols et al, 2017; White et al, 2020) have led to the use of a large variety of file formats and data management methods, and to the lack of metadata descriptions, leaving researchers with the daunting task of adapting all the collected data in a custom format to run their analysis pipelines. The Brain Imaging Data Structure (BIDS; Gorgolewski et al, 2016) was introduced to alleviate this task to increase data sharing and usage and to facilitate reproducibility studies
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