ds003216

Project description: Whole Brain Layer-fMRI Connectome: An Open Dataset

This is a fork of openneuro ds003216 to showcase how to make VASO data more BIDS compatible

• source data: https://openneuro.org/datasets/ds003216/versions/2.1.5

Log of changes:

• update README and pacify bids validator
• add events.tsv
• add AcquisitionDuration to comply with https://bids-specification.readthedocs.io/en/latest/04-modality-specific-files/01-magnetic-resonance-imaging-data.html#timing-parameters_1
• fix volume timing
• add volume timing metadata
• add context.tsv
• rename derivatives
• reformat json
• remove now unrelated source data
• remove derivatives of now non-existent raw files
• keep one run of movie task and one T1w
• remove subject 1 and 3

TODO

• Add REQUIRED metadata of derivatives (TaskName and RepetitionTime for each .nii file)

Content

.
├── CHANGES
├── code             # some matlab scripts that were used to 'consolidate the dataset'
│   ├── add_context.m
│   ├── add_volume_timing.m
│   └── create_events_tsv.m
├── dataset_description.json
├── derivatives
│   └── sub-02
│       ├── atlas
│       ├── BOLD_func
│       │   └── sub-02_ses-04_task-movie_run-01_bold.nii
│       ├── layerification
│       │   └── sub-02_layers.nii
│       ├── moco_result
│       │   ├── sub-02_ses-04_task-movie_run-01_notnulled.nii # non-null volumes
│       │   └── sub-02_ses-04_task-movie_run-01_nulled.nii    # nulled volumes
│       └── VASO_func
│           └── sub-02_ses-04_task-movie_run-01_desc-boco_vaso.nii # volumes with the bold correction applied
├── participants.tsv
├── README.md
├── sub-02
│   ├── ses-01
│   │   └── anat
│   │       ├── sub-02_ses-01_run-01_T1w.json
│   │       └── sub-02_ses-01_run-01_T1w.nii.gz
│   └── ses-04
│       └── func
│           ├── sub-02_ses-04_task-movie_run-01_context.tsv  # contains the volume type for each volume
│           ├── sub-02_ses-04_task-movie_run-01_vaso.json    # contains the volume timing and acquisition time for each volume
│           └── sub-02_ses-04_task-movie_run-01_vaso.nii.gz  # mixture of nulled and non-null volumes
└── task-movie_events.tsv

Overview

Here, we provide a whole-brain layer-dependent connectome dataset with cerebral blood volume and BOLD contrast. It is coming along with a quality assessment comprising metrics of skew, kurtosis, tSNR and sharpness. The purpose of this dataset is 1.) to characterize the prospects and challenges of whole brain layer-fMRI acquisition sequences in a test-retest setting 2.) and to provide a test bed for developing and benchmarking new layer-dependent analysis tools that may be able to address novel neuroscientific research questions. Note that these data have been acquired with a CBV-sensitive VASO sequence, thus the datatype is rather unconventional compared to standard fMRI datasets. TRs as well as resolution is variable across time and contrasts within one run. Please notice, this is an initial release of an ongoing study. We are happy to share the data via SIEMENS C2P.

Data Acquisition

Scanning was performed at Scannexus as part of the Maastricht Brain Imaging Centre (MBIC) embedded in theMaastricht University, Maastricht, The Netherlands. VASO and BOLD contrasts of the whole brain were obtained from one participant at a SIEMENS MAGNETOM 7T scanner at 6 days during watching the Human Connectome Project (HCP) audio movie. The link to the psychopy stimulation script is: Link to the movie: https://github.com/layerfMRI/Phychopy_git/tree/master/movie). The link to the movie file is here: https://youtu.be/qndD3ErUaEE For information about detailed scanning parameters see: https://github.com/layerfMRI/Sequence_Github/blob/master/Whole_brain_layers/Ann_WB_VASO_fMRI.pdf. There is no data available for day 3 due to technical issues at scanning (PCI_RX receiver error). At day 6, respiration and pulse were recorded to provide the required physiological measures for further analysis. Link to physiological recording on Github: https://github.com/layerfMRI/Phychopy_git/tree/master/movie/physio_log/physio_ses-06

Data processing

Defacing was performed with freeSurfer. Motion correction (MOCO), BOLD correction (BOCO), and segmentation of grey + white matter were performed. The additional folder "derivatives" contains the processed data in steps: MOCO, BOCO, and segmentation of grey + white matter. For detailed information see: https://github.com/layerfMRI/repository/tree/master/stand_alone_VASO_NEURODEBIAN (MOCO), https://doi.org/10.1002/mrm.24916 (BOCO), and https://github.com/kenshukoiso/Whole_Brain_Project (preprocessing pipeline and script)

Presenting on ISMRM 2022

You can find our abstract draft here: https://layerfmri.page.link/ISMRM2022_WB. The main participant of this abstract is subject 02 on this open dataset.