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

Remi Gau 76b50fd855 update README and silence some validator warnings 2 years ago
.datalad 5c0c750d8a [DATALAD] new dataset 4 years ago
derivatives 76b50fd855 update README and silence some validator warnings 2 years ago
sourcedata 4a3460fbfa [OpenNeuro] Files removed 2 years ago
sub-01 9cc6beecb5 remove Mac ._ files and make sure they will not come back 2 years ago
sub-02 b2795021be [OpenNeuro] Files removed 2 years ago
sub-03 7b073a7a2d [OpenNeuro] Files removed 2 years ago
.bids-validator-config.json 76b50fd855 update README and silence some validator warnings 2 years ago
.bidsignore 76b50fd855 update README and silence some validator warnings 2 years ago
.gitattributes 94a992724a [DATALAD] exclude paths from annex'ing 4 years ago
.gitignore 9cc6beecb5 remove Mac ._ files and make sure they will not come back 2 years ago
CHANGES 097f2543ec [OpenNeuro] Recorded changes 2 years ago
README.md 76b50fd855 update README and silence some validator warnings 2 years ago
dataset_description.json a5370dc419 [OpenNeuro] Recorded changes 2 years ago
participants.tsv a222e0a294 [DATALAD] Recorded changes 4 years ago

README.md

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

Content

    Summary:                 Available Tasks:        Available Modalities: 
    217 Files                test                    MRI                   
    3 - Subjects             movie                                         
    13 - Sessions            tapping  

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.