The goal of this tool is to offer a simple interface for downloading, storing, and getting access to neuroimaging datasets. We want to:

• Decrease the amount of time spent by data scientists in accessing new datasets
• Decrease the difficulty of scientists in sharing their data with the world
• Increase the visibility of available data

The types of data we wish to expose include:

• MRI / tMRI / rsMRI / dMRI

Not all data sources have been implemented. Our list of known data sources can be found here: https://github.com/nidata/nidata/wiki/Data-sources

Current data sources will be available via the website, when implemented: http://nidata.github.io/

nidata is tested in Python 2.7, and 3.5. The only package-level dependencies are pip, numpy, and nibabel .

Individual datasets may have package dependencies for downloads or examples. If so, nidata attempts to install them via pip. These packages include:

• nilearn - Machine learning for neuroimaging, contains generic download tools and logic for accessing fMRI datasets

sudo pip install git+https://github.com/nidata/nidata

To run an example, python nidata/multimodal/hcp/example1.py

To download data,

from nidata.multimodal import HcpDataset
HcpDataset(username=#####, passwd=######).fetch(n_subjects=1, data_types=['anat'])