This repository is the Github sibling of the corresponding DataLad dataset, i.e. it does not contain the data itself. The GitHub sibling, nevertheless, provides insights into the general data structure (directory tree, filenames) and serves as a starting point to download, share and discuss the dataset. Data is in BIDS format and may include behavioral, questionnaire and derivative data, too. Data is stored in a special S3 remote provided by Coscine and can't be downloaded without the dataset specific secret token. Token is available at project Z03 for members of TRR289 and collaborators upon reasonable request.
See dataset_description.json
for project related meta-data.
This does not download the actual data, only the gin-annex "skeleton".
datalad install -s [email protected]:pni-data/<dataset_name>.git <dataset_name>
datalad siblings configure -s origin --publish-depends coscine-rds-s3
Token is available at project Z03 for members of TRR289 and collaborators upon reasonable request.
export AWS_ACCESS_KEY_ID="XXXXX-XXXX-XXXX-XXXX-XXXX"
export AWS_SECRET_ACCESS_KEY="XXXXXXXX"
You can selectively download what you need (e.g. derivatives only).
cd <dataset_name>
datalad get <path/to/file*>
ToDo:
description of the dataset,including link to the openly available SFB proposal/some publication eg: This dataset was acquired by the team of the SFB289 XX project. It includes YY subjects and the common sequences within the SFB289 project, namely a high resolution T1w, resting state fMRI, 133 direction multi shell DWI, and 2 fieldmaps for the functional data (one reversed phase encoding direction, one Siemens deafult fieldmap sequnce) and one fieldmap for the DWI (reversed field encoding direction). An additional reference image of the resting state fMRI is included without multiband factor.
Questionnaires data are also acquired and can be found in the ... fodler.
The proposal can be found here: link
The BIDS conversion was done with heudiconv by the XX project coordinators and/or supported by the Z03 project coordinators.
Defacing was done by the Z03 cooridnator. Pydeface was used on all anatomical images to ensure deindentification of subjects. The code can be found at https://github.com/poldracklab/pydeface
N/A ToDo
�[32mThis dataset appears to be BIDS compatible.�[39m
�[34m�[4mSummary:�[24m�[39m �[34m�[4mAvailable Tasks:�[24m�[39m �[34m�[4mAvailable Modalities:�[39m�[24m
1960 Files, 21.44GB rest MRI
93 - Subjects TODO: full task name for rest
1 - Session
�[36m If you have any questions, please post on https://neurostars.org/tags/bids.�[39m