This project archives the scripts necessary to replicate the analyses as uploaded to OpenNeuro project "ANT: Healthy aging and Parkinson's disease," ver. 2.0.3.
Link: https://openneuro.org/datasets/ds001907/versions/2.0.3
DOI: 10.18112/openneuro.ds001907.v2.0.3
The processing is very simple:
bin/subject-processing/00-invokeall.sh (a) converts scanner format to Nifti;
(b) skullstrips and defaces anatomical images; and (c) runs afni_proc.py
to preprocess data.
bin/subject-processsing/01-organizeBIDS.sh converts from our in-house
organization to the Brain Imaging Data Structure format for upload to
OpenNeuro.
bin/demo-final.R shows how demographic information was converted from
supplied spreadsheets (not included) to CSV for sharing.
See Data Note: Day TKM, Madhyastha TM, Askren MK et al. Attention Network Test fMRI data for participants with Parkinson’s disease and healthy elderly [version 1; peer review: 2 approved]. F1000Research 2019, 8:780 (https://doi.org/10.12688/f1000research.19288.1)
These scripts have also been archived on Zenodo: Day TKM: 'ANT: Healthy aging and Parkinson's disease' processing script (Version 1.0.0). Zenodo. 2019. http://www.doi.org/10.5281/zenodo.2847832
See papers using this data:
Boord, P., Madhyastha, T. M., Askren, M. K., & Grabowski, T. J. (2017). Executive attention networks show altered relationship with default mode network in PD. NeuroImage: Clinical, 13, 1–8. https://doi.org/10.1016/j.nicl.2016.11.004
Madhyastha, T. M., Askren, M. K., Boord, P., & Grabowski, T. J. (2015). Dynamic Connectivity at Rest Predicts Attention Task Performance. Brain Connectivity, 5(1), 45–59. https://doi.org/10.1089/brain.2014.0248