Home: What this tutorial is about
Tutorial: How to create a BIDS dataset
This tutorial is inspired by and reuses content from the Princeton Handbook for Reproducible Neuroimaging by Wagner et al. (2021). The handbook is licensed under a a CC BY-SA 4.0 license.
Tutorial: Create a BIDS dataset using heudiconv
In this tutorial, we will create a BIDS dataset using heudiconv.
HeuDiConv is a flexible DICOM converter that helps organize brain imaging data into structured directory layouts. It converts DICOM files to NIfTI format using customizable heuristics (rules) to determine how files should be named and organized. HeuDiConv is particularly useful for converting raw scanner data to BIDS format, making your data more standardized and analysis-ready.
What is BIDS (Brain Imaging Data Structure)?
Many of the best practices we encourage in this handbook revolve around the Brain Imaging Data Structure (BIDS) (Gorgolewski et al., 2016). Neuroimaging research relies on complex multimodal data and different software packages have historically used different naming and organization conventions. Different labs and different researchers use idiosyncratic conventions—even the same researcher may use different conventions from experiment to experiment. The goal of BIDS is to create an easy-to-adopt community standard for organizing neuroimaging data. BIDS facilitates:
Data validation: Data often has “bugs”—just like software. The BIDS-Validator can be used to check the integrity of your BIDS dataset, allowing you to identify potential errors or inconsistencies in the data structure.
Collaboration: By using a standard format, working on data collaboratively within and across labs becomes much easier (no more re-organizing someone else’s data). It also makes it much easier to return to the same dataset years later (your future self will thank you).
Data analysis: The machine-readable format and rich metadata of BIDS allows software packages—such as fMRIPrep and MRIQC—to process BIDS data in an automated fashion. There is a growing number of software packages—called BIDS Apps—that capitalize on BIDS (Gorgolewski et al., 2017).
Sharing data: Data sharing is an important element of reproducible science and is encouraged (often enforced!) by many major federal funding agencies (e.g., NIH, NSF, ERC). BIDS allows others to more easily use your data and is the standard used by the OpenNeuro data sharing platform (Poldrack & Gorgolewski, 2017). The workflow in this handbook encourages converting your data to BIDS format as early in the workflow as possible to facilitate reproducibility and save you the energy of retroactively organizing your data at the time of sharing.
Consult the BIDS Specification for detailed documentation on formatting. If you want to setup a new study using BIDS, check out documentation and scripts for converting raw data to BIDS format. You can also practice using BIDS with sample datasets.
Resources
- BIDS Specification
- BIDS Validator
- BIDS Validator on GitHub
- BIDS Apps
- OpenNeuro
- fMRIPrep
- MRIQC
- National Institutes of Health (NIH) Data Sharing Policy
- National Science Foundation (NSF) Dissemination and Sharing of Research Results
- European Research Council (ERC) Open Science
- DFG: Handling of Research Data