/bids

name: bids
description: >
  Use this skill when working with Brain Imaging Data Structure (BIDS) datasets:
  organizing neuroscience and biomedical data (MRI, EEG, MEG, iEEG, PET, microscopy,
  NIRS, motion capture, EMG, MR spectroscopy, behavioral), querying BIDS layouts,
  validating compliance, converting DICOM to BIDS, writing metadata sidecars, or
  creating BIDS derivatives.
license: https://creativecommons.org/licenses/by/4.0/
metadata:
  version: "1.1"
  skill-author: Yaroslav Halchenko

Brain Imaging Data Structure (BIDS)

Overview

The Brain Imaging Data Structure (BIDS) is a community standard for organizing and describing neuroscience and biomedical research datasets. It defines a consistent file naming convention, directory hierarchy, and metadata schema so that datasets are immediately understandable by humans and software tools alike. BIDS is governed by the BIDS Specification (currently v1.11.x) and is maintained by the community via the BIDS-Standard GitHub organization.

While BIDS originated for MRI, it has grown well beyond neuroimaging. The specification now covers 11 modalities spanning imaging, electrophysiology, and behavioral data:

• **Imaging**: MRI (structural, functional, diffusion, fieldmaps, perfusion/ASL), PET, microscopy
• **Electrophysiology**: EEG, MEG, iEEG (intracranial EEG), EMG
• **Other**: NIRS (near-infrared spectroscopy), motion capture, behavioral data (without imaging), MR spectroscopy

Active BEPs are extending BIDS further — notably BEP032 (microelectrode electrophysiology) will add support for extracellular recordings including Neuropixels probes, bringing BIDS to a prevalent methodology in animal neuroscience research (see also the neuropixels-analysis skill).

Adoption is required or strongly encouraged by major data repositories (OpenNeuro, DANDI), leading journals (NeuroImage, Human Brain Mapping, Scientific Data), and funding agencies (NIH, ERC).

The Python ecosystem for BIDS centers on **PyBIDS** (`pybids`) for querying and indexing BIDS datasets, and the **bids-validator** (Deno-based, available as PyPI package `bids-validator-deno` or via Deno directly) for compliance checking. Conversion from DICOM is typically done with **HeuDiConv**, **dcm2bids**, or **BIDScoin**.

When to Use This Skill

Apply this skill when:

• Organizing raw neuroscience data (imaging, electrophysiology, behavioral) into BIDS-compliant directory structures
• Querying an existing BIDS dataset to find specific files by subject, session, task, run, or modality
• Validating a dataset against the BIDS specification before sharing or submission
• Converting DICOM data from scanners into BIDS format
• Writing or editing JSON sidecar metadata files
• Creating BIDS-compliant derivatives (preprocessed data, analysis outputs)
• Setting up a `dataset_description.json` for a new dataset
• Working with BIDS entities (subject, session, task, acquisition, run, etc.)
• Configuring `.bidsignore` to exclude files from validation
• Preparing data for upload to OpenNeuro, DANDI, or other BIDS-aware repositories

Installation

# Core BIDS querying library
uv pip install pybids

# BIDS validator (Deno-based, installed via PyPI wrapper)
uv pip install bids-validator-deno
# Alternative: install directly via Deno
# deno install -g -A npm:bids-validator

# DICOM-to-BIDS converters (install as needed)
uv pip install heudiconv       # HeuDiConv - heuristic-based DICOM conversion
uv pip install dcm2bids        # dcm2bids - config-file-based conversion
# BIDScoin: uv pip install bidscoin

# Useful companions
uv pip install nibabel          # NIfTI/other neuroimaging file I/O
uv pip install pydicom          # DICOM file reading (used by converters)

Core Workflows

Twelve workflow areas, each with worked code, are documented in [references/core_workflows.md](references/core_workflows.md):

1. **BIDS directory structure** — the required layout and where each modality belongs. 2. **`dataset_description.json`** — the required fields and how to generate it. 3. **Querying with PyBIDS** — `BIDSLayout`, entity filters, sidecar metadata with automatic inheritance, and building paths from entities. 4. **Validation** — `bids-validator` via the PyPI wrapper (recommended), via Deno directly, the legacy Node validator, and using `.bidsignore` to exclude files. 5. **Entities and file naming** — the entity order and naming grammar. 6. **DICOM to BIDS conversion** — HeuDiConv (including the turnkey ReproIn path and the reconnaissance → heuristic → convert sequence) and dcm2bids (config-file based). 7. **Metadata sidecars** — required and recommended JSON fields per modality. 8. **Events files** — task fMRI event timing and column conventions. 9. **Participants file** — `participants.tsv` and its data dictionary. 10. **Derivatives** — the derivatives layout and its `dataset_description.json`. 11. **Advanced PyBIDS** — index caching, including derivatives, confound regressors, and DataFrame output. 12. **BIDS-Apps** — the standard invocation pattern, and fMRIPrep, MRIQC, and QSIPrep.

Validate early and often: PyBIDS validates structure when it indexes a dataset, so an indexing failure usually means a naming or metadata problem rather than a code bug.

Reference Materials

This skill includes detailed reference documentation:

• **bids_schema.json**: Machine-readable BIDS schema (from https://bids-specification.readthedocs.io/en/stable/schema.json). This is the authoritative source for entity definitions, ordering rules, filename templates, allowed suffixes per datatype, and metadata field requirements. BEP-specific schemas are at https://github.com/bids-standard/bids-schema/tree/main/BEPs.
• **beps.yml**: Current list of all BIDS Extension Proposals with titles, leads, status, and links (from [bids-website](https://github.com/bids-standard/bids-website/blob/main/data/beps/beps.yml))
• **bids_specification.md**: Human-readable summary of the entity table, data