The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments

By Krzysztof J. Gorgolewski, Tibor Auer, Vince D. Calhoun, R. Craddock, Samir Das, Samir Das, Eugene P. Duff, Guillaume Flandin, Satrajit S. Ghosh, T. Glatard and 19 more. Scientific Data, 2016

1,663 citations recorded by the source corpus.

The development of magnetic resonance imaging (MRI) techniques has defined modern neuroimaging. Since its inception, tens of thousands of studies using techniques such as functional MRI and diffusion weighted imaging have allowed for the non-invasive study of the brain. Despite the fact that MRI is routinely used to obtain data for neuroscience research, there has been no widely adopted standard for organizing and describing the data collected in an imaging experiment. This renders sharing and reusing data (within or between labs) difficult if not impossible and unnecessarily complicates the application of automatic pipelines and quality assurance protocols. To solve this problem, we have developed the Brain Imaging Data Structure (BIDS), a standard for organizing and describing MRI datasets. The BIDS standard uses file formats compatible with existing software, unifies the majority of practices already common in the field, and captures the metadata necessary for most common data processing operations.

Subfields: Cognitive Neuroscience, Information Systems and Management, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/b3b5993819f5dddeeff1a99c43545d1133296881

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Citations in the corpus

Data-Efficient Mutual Information Neural Estimator (2019, methodology): “All fMRI data were formatted according to the Brain Imaging Data Structure (BIDS) standard [22] and preprocessed using fMRIPrep [10]10.”
Convolutional Neural Networks for Classification of Alzheimer's Disease: Overview and Reproducible Evaluation (2019, methodology): “The framework comprises: i) tools to automatically convert three publicly available datasets into the Brain Imaging Data Structure (BIDS) format (Gorgolewski et al., 2016) and ii) a modular set of preprocessing pipelines, feature extraction and classification methods, together with an evaluation fr”
Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank (2017, methodology): “This ﬁle organisation can be converted to BIDS format (Gorgolewski et al., 2016) with a conversion script included in the pipeline.”
The OpenNeuro resource for sharing of neuroscience data (2021, neutral): “We engaged a large group of researchers from the neuroimaging community to establish a standard that ultimately became the BIDS ( Gorgolewski et al., 2016 ), which is now a highly successful community standard for a broad and growing range of neuroimaging data types.”
EEG-BIDS, an extension to the brain imaging data structure for electroencephalography (2019, background): “The right side of the figure shows the contents of the eeg modality directory, including the raw EEG data (1) and associated metadata (2).”
MRIQC: Advancing the automatic prediction of image quality in MRI from unseen sites (2016, methodology): “3) Interoperability and standards: MRIQC is compatible with input data formatted according to the the Brain Imaging Data Structure (BIDS, [27]) standard, and the”