# A community-driven development of the brain imaging data standard (BIDS) to describe macroscopic brain connections

> **NIH NIH R01** · UNIVERSITY OF TEXAS AT AUSTIN · 2022 · $328,574

## Abstract

Project Summary/Abstract
 The Brain Imaging Data Structure (BIDS) is a BRAIN initiative (R24 MH114705)
community-driven standard meant to maximize neuroimaging data sharing, and facilitate analysis tool
development. We propose to extend the standard to encompass derivatives resulting from experiments
related to both functional as well as structural magnetic resonance imaging data that describe
macroscopic brain connectivity estimates. The focus of this proposal is to advance BIDS to describe the
entire experimental workflow—from minimally processed anatomical, functional and diffusion MRI data
through connectivity matrices and tractometry features—in service of supporting BRAIN initiative
studies of large-scale connectivity of human and nonhuman brains. BIDS was initially scoped to MRI
data of the brain, but the standard has set up a solid infrastructure to steer the community and has
been extended to cover a range of other modalities (PET, EEG, MEG, ECoG). Since its first
announcement, BIDS has evolved to become an organized community with shared governance and a
strong impact well beyond the U.S. BRAIN initiative. To date, 131 individuals among faculty, students,
and postdocs contributed to the development of the standard and the article describing BIDS has been
cited 277 times.
 Current gaps exist in developing BIDS to effectively support the process of scientific results
generation. This is because the standard does not yet describe brain features that can be extracted
from MRI data and that are routinely used to perform statistical tests and complete scientific studies.
These features comprise connectivity maps, structural and functional connections, major white matter
tracts, diffusion signal models as well as white matter tractograms and tractometry. Sharing processed
data and features in addition to raw and minimally-processed data is critical to accelerating scientific
discovery. This is because substantial effort, software, and hardware instrumentation, and know-how
are required to bring raw data to a usable state. One previous project (R24 MH114705) laid the
foundations for the BIDS derivatives standard, ultimately leading to the existing Common Derivatives
standard. However, the current BIDS derivative standard does not cover advanced data derivatives that
describe brain connectivity experiments. The current proposal is to advance the BIDS standard beyond
preprocessed data to describe data products generated from experiments and models fit after
preprocessing. The project will deliver a community-developed standard describing brain connectivity
experiments. The standard will be accompanied by software to validate the datasets.

## Key facts

- **NIH application ID:** 10460628
- **Project number:** 5R01MH126699-02
- **Recipient organization:** UNIVERSITY OF TEXAS AT AUSTIN
- **Principal Investigator:** Franco Pestilli
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $328,574
- **Award type:** 5
- **Project period:** 2021-08-06 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10460628

## Citation

> US National Institutes of Health, RePORTER application 10460628, A community-driven development of the brain imaging data standard (BIDS) to describe macroscopic brain connections (5R01MH126699-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10460628. Licensed CC0.

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