Thalamocortical triple-network dysconnectivities in psychosis (Kim, M., Kim, T. et al. 2022, Schizophr Bull).
- Identification of network modules of cortex and thalamus using an InfoMap algorithm (https://www.mapequation.org/infomap/) for community detection.
ref to Hwang, K. et al. 2017, J Neurosci: Modularity-based thalamic parcellation.
- ./cortMod_parc_6mods/cortNet_mods.nii.gz: cortical modular networks
- ./thalMod_parc_6mods/thalNet_mods.nii.gz: thalamic modular networks
- data from 273 individuals with (high risk for) psychosis or without any psychiatric disorder (healthy volunteers).
- data acquisition from Dept of Psychiatry at Seoul National University Hospital (PI: Prof. Jun Soo Kwon).
- used the Godon atals (333 regions).
- 01_thr_conn.m: iteratively thresholded the connectivity map of each subject, ranging from 15% to 1% in steps of 0.1% connectivity density.
- returns ./linkArray/Subj##/clink_thr###.net.
- 02_prepCortmod.sh: used the InfoMap algorithm.
- returns ./linkArray/Subj##/modOut/clink_thr###.clu.
- sample data: Subj01
- cortmod_01_update.ipynb: updating a consensus matrix across the ranges (descending order).
- returns ./linkArray/consMats/consMat_Subj##.csv.
- cortmod_02_group.ipynb: avaraging subject-level modularity matrices, returning ./linkArray/consMatDM_low.csv.
- 03_cortmod_thrConn.m: thresholding group-level cortico-cortical connectivity matrix, returing ./linkArray/links_group/clink_thr###.net.
- 04_runCortmod_grp.sh: identifying group-level cortical network modules, returing ./linkArray/links_group/modOut/clink_thr###.clu.
- cortmod_02_group.ipynb: updating a group-level consensus matrix across the ranges, returning ./linkArray/links_group/modOut/cortmod_grp.csv.
- 05_cortMod_parc_6mods.sh: merging nodes to creat modular networks.
- used the Morel thalamus atlas
- partial correlation between thalamic voxels and mean timeseries of each cortical module.
- controlling for signals from rest of the cortical modules.
- a winnter-take-all parcellation approach: assigning network labels where having the largest corr coeff.