- Kong R, Yang Q, Gordon E, et al. Individual-Specific Areal-Level Parcellations Improve Functional Connectivity Prediction of Behavior. Cerebral Cortex. In press.
In this study we utillized HCP S1200 dataset. We will release parcellations and FC matrices of 1024 HCP subjects passed our postrocessing pipeline. The parcellations and FC matrices include 100, 200, ..., 1000 reslutions.
The subject list can be found here: HCP_subject_list_txt
Note: we will move parcellations and FC to BALSA once the BALSA link is made public. The BALSA link will be: https://balsa.wustl.edu/study/show/Pr8jD
Please visit this link to check the code of Kong2022 individual areal-level parcellations: https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Kong2022_ArealMSHBM
For each resolution, the relevant parcellations for all HCP subjects were saved as two 32492 x 1029 matrix, where each column corresponds to the parcellation of a single subject. The color table is also attached together. The subject order list can be found in Parcellations folder.
For resolution K, the individual areal-level parcellations can be found here:
Parcellations/<resolution K>
For resolution K, the relevant FC for all HCP subjects were saved as a K x K x 1029 matrix, where the 3rd dimension corresponds to subject orderring. The subject order list can be found in FC folder. Due to the file size limit in Github, we separate the data into a few sub-grups. The subject lists of the sub-groups can be found in FC/HCP_sub_group_list.
For resolution K, FC matrices generated by individual areal-level parcellations can be found here:
FC/<resolution K>
Please contact Ru(by) Kong at [email protected].