This dataset is from a collaborative study for Parkinson’s Research to improve PD therapeutics. We consider the DTI acquisition of 754 subjects, with 596 Parkinson’s disease patients and 158 healthy controls. The raw data are first aligned to correct for head motion and eddy current distortions. Then the non-brain tissue is removed and the skull-stripped images are linearly aligned and registered. 84 ROIs are parcellated from T1-weighted structural MRI and the brain network is reconstructed using the deterministic 2nd-order Runge-Kutta (RK2) whole-brain tractography algorithm.
This rs-fMRI dataset is from the Brain Behavior Laboratory at the University of Pennsylvania and the Children’s Hospital of Philadelphia. 289 (57.46%) of the 503 included subjects are female, indicating this dataset is balanced across genders. The regions are parcellated based on the 264-node atlas defined by Power et al. The preprocessing includes slice timing correction, motion correction, registration, normalization, removal of linear trends, bandpass filtering, and spatial smoothing. In the resulting data, each sample contains 264 nodes with time-series data collected through 120 time steps. We focus on the 232 nodes in the Power’s atlas associated with major resting-state functional modules.
This study recruits children aged 9-10 years across 21 sites in the U.S. Each child is followed into early adulthood, with repeated imaging scans, as well as extensive psychological and cognitive testing. After selection, 7,901 children are included in the analysis, and 3,961 (50.1%) among them are female. We use rs-fMRI scans for the baseline visit processed with the standard and open-source ABCD-HCP BIDS fMRI Pipeline17. After processing, each sample contains a connectivity matrix whose size is 360 ×360 and BOLD time-series for each node. The region definition is based on the HCP 360 ROI atlas.
You can read more about fMRI and DTI here.