bids

The MATLAB toolbox for MEG, EEG and iEEG analysis

fMRIPrep is a robust and easy-to-use pipeline for preprocessing of diverse fMRI data. The transparent workflow dispenses of manual intervention, thereby ensuring the reproducibility of the results.

Brain Imaging Data Structure (BIDS) Specification

The Starter-kit has moved to the new BIDS website.

Python tools for querying and manipulating BIDS datasets.

A set of BIDS compatible datasets with empty raw data files that can be used for writing lightweight software tests.

Reorganising NIfTI files from dcm2niix into the Brain Imaging Data Structure

Validator for the Brain Imaging Data Structure

Preprocessing of diffusion MRI

MNE-BIDS is a Python package that allows you to read and write BIDS-compatible datasets with the help of MNE-Python.

Automatically process entire electrophysiological datasets using MNE-Python.

BIDScoin converts your source-level neuroimaging data to BIDS

A free and open platform for analyzing and sharing neuroimaging data

micapipe from the Multimodal imaging and connectome analysis lab (http://mica-mni.github.io) at the Montreal Neurological Institute. Read The Docs documentation below

ENIGMA HALFpipe is a user-friendly software that facilitates reproducible analysis of fMRI data

A Visual Studio extension that enhances development functionality in Business Intelligence Development Studio (BIDS) and SQL Server Data Tools (SSDT).

Temporal Network Tools

Connectome Mapper 3 is a BIDS App that implements full anatomical, diffusion, resting/state functional MRI, and recently EEG processing pipelines, from raw T1 / DWI / BOLD , and preprocessed EEG data to multi-resolution brain parcellation with corresponding connection matrices.

dMRIPrep is a robust and easy-to-use pipeline for preprocessing of diverse dMRI data. The transparent workflow dispenses of manual intervention, thereby ensuring the reproducibility of the results.

fmriflows is a consortium of many (dependent) fMRI analysis pipelines, including anatomical and functional pre-processing, univariate 1st and 2nd-level analysis, as well as multivariate pattern analysis.