Access to Data

Digital Alliance

Ethics

Downloading the dataset

All data are made available as a DataLad collection on github in public repositories. DataLad is a tool for versioning a large data structure in a git repository. The dataset can be explored without downloading the data, and it is easy to only download the subset of the data you need for your project. See the DataLad handbook for further information.

We recommend creating an SSH key (if not already present) on the machine on which the dataset will be installed and adding it to github. See the official github instructions on how to create and add a key to your account.

To obtain the data, you need to install a recent version of the DataLad software, available for Linux, OSX and Windows. Note that you need to have valid login credentials to access any dataset through git using your Digital Alliance account. Once you have obtained these credentials, you can proceed as follows in a terminal:

# Install recursively the dataset and subdataset of the current project.
# If using ssh git clone as follow, you can set your public SSH key in the present git to ease future updates.
datalad install -r git@github.com:conrodlab/neuroventure.git
# If errors show up relative to .heudiconv subdataset/submodule, this is OK, they are not published (will be cleaned up in the future).
cd neuroventure

Versioning

TBD

Preprocessed data

For analysis of fMRI data, it is preferable to directly get the preprocessed data (smriprep and fmriprep for now).

datalad install git@github.com:conrodlab/neuroventure.processed.git
cd neuroventure.processed

You can install the sub-datasets you are interested in (instead of installing all of them) using for instance:

datalad get -n smriprep fmriprep/movie10

and then get only the files you need (for instance MNI space output):

datalad get smriprep/sub-*/anat/*space-MNI152NLin2009cAsym_* # get all anatomical output in MNI space
datalad get fmriprep/movie10/sub-*/ses-*/func/*space-MNI152NLin2009cAsym_* # get all functional output in MNI space

You can add the flag -J n to download files in parallel with n being the number of threads to use.

The source data used for preprocessing (including raw data) are referenced as sources in the preprocessed dataset following Yoda, so as to track provenance. You can also track the version of the neuroventure dataset you are using by installing it in a datalad dataset created for your project.

Stimuli and event files

You will likely need the events files and stimuli for your analysis which can be obtained from the sourcedata reference sub-datasets, for example:

datalad get -r fmriprep/movie10/sourcedata/movie10/stimuli fmriprep/movie10/sourcedata/movie10/*_events.tsv

or to get subject specific event files for tasks collecting behavioral responses:

datalad get -r fmriprep/movie10/sourcedata/hcptrt/sub-*/ses-*/func/*_events.tsv

Updates

The dataset will be updated with new releases so you might want to get these changes (unless you are currently running analyses, or trying to reproduce results). The main branches of all datasets will always track the latest stable release.

# update the dataset recursively
datalad update -r --merge --reobtain-data

Once your local dataset clone is updated, you might need to pull new data, as some files could have been added or modified. The --reobtain-data flag should automatically pull files that you had already downloaded in case these were modified.