Project Description

This directory contains code to create cortical brainmaps showing genetic and environmental cotribution to functional inter-subject variability. The corresponding paper "Disentangling cortical functional connectivity strength and topography reveals divergent roles of genes and environment" is available here (biorXiv).

Data

We used data from the 1200 subjects release of the Human Connectome Project. In particular we used the ICA-FIX denoised dataset, which includes only grayordinates and already went through initial preprocessing. More information on the release can be found here. To access some of the subject-related information (f.e. zygosity) Restricted Access Data Use Terms have to be accepted (See Quick Reference: Open Access vs Restricted Data). Data can be downloaded from ConnectomeDB after creating a user account.

Assumptions

• It is assumed that the downloaded data is already mapped to freesurfer's fsavarage4 surface in mgh-format and stored in two folders corresponding to data download:

  • HCProot/HCP_3T_RESTA_fmri
  • HCProot/HCP_3T_RESTB_fmri.

  We also applied bandpass filtering and global signal regression, which is also indicated in the file name (f.e. lh.rfMRI_REST1_LR_Atlas_hp2000_clean_bpss_gsr_fs4.mgh).

• Additionally, the relative mean motion for each subject is stored in txt-files in similar folders

  • HCProot/HCP_3T_RESTA_Motion/motion_mean/
  • HCProot/HCP_3T_RESTA_Motion/motion_mean/

  named for example REST1_LR_Movement_RelativeRMS_mean.txt

• inflated surface and sphere (VTK-format !) surface of fsaverage4 have to be copied in Deliveries/fsaverage4-folder.

To map from HCP-space to fsaverage4 you can follow this manual. It requires Connectome Workbench and Freesurfer, which can be installed for free. The freesurfer command mris_convert is useful to convert between image file formats.

You will also need to install the R-package OpenMX. An MSM binary is also required in Code/Embedding. We provide the one for centos, if you require a different binary, you can find them here.

Pipeline

Here is the order in which the scripts in the Code-folder need to be run:

• settigs.py and settings.Renviron: set paths of projectfolder and data

• LargeCorrelation_ParcelSelection/calcCors.py, referenceCors.py and select_parcels.py: calculate fMRI correlation matrices, chose representative parcels of Yeo networks

• PrepareTables/SelectedROICorrs_vertex.py:calculate tables for twin model input (entagled fucntional connectivity and disentagled connectivity strength)

• Embedding/

  • cosine.py
  • MSM_alignment.py
  • MSMcorrespondance_vertex.py

• PrepareTables/

  • SelectedROICorrs_vertex.py: change input and output directory for disentagled connectivity strength
  • SelectedROICorrs_position.py: create tables for twin model input (topography/spatial layout)

• Remove_GenderMotion/

  • getSubjectID.py
  • getMeanMotion.py
  • getGender.R
  • RemoveGender_Motion.R (set directories according to entagled or disentagled setting) and RemoveGender_Motion_position.R

• Models/

  • estimate_factors.R (set directories according to entagled or disentagled setting) and estimate_factors_position.R: twin models vor each vertex
  • create_matrices_vertex.py: create brain surface maps based on estimates obtained by twin model

Deliveries

In the deliveries folder we provide files, which are needed by the scripts. Most of those file will be regenerated, when running the scripts. Exceptions are

• the parcellation files Schaefer2018_Parcels_7Networks_oder.annot for left and right hemisphere: The parcellation for fsaverage5 was taken from here and mapped through freesurfer's mri_surf2surf command to fsaverage4
• Subjects.csv: It contains the ID of subjects used in our paper. When running the scripts, it will be regenerated containing additional subject-related information

Output

• 7NETS_vertex:contains subfolders with script outputs
• long_corr_matricesLR and long_corr_matricesRL: subject_vise vertex-by-vertex correlation matrices for LR and RL runs

Maps for genetic (A), common environmental (C) and random environmental (E) contribution

The Deliveries-folder also contains *.mat- files with ACE-brain maps compatible with Freesurfer's fsaverage4 for entangled and disentangled function and position, which can also be seen in the image above (and also in Figure 2 and Supplementary Figure 6 of our paper). The files are:

• ACE_matrices_anat.mat: entangled function and position
• ACE_matrices_func.mat: disentangled function
• ACE_matrices_pos.mat: disentangled position

Note: Negative values have been assigned to the medial wall, since no fMRI signal was available for this area. They are basically meaningless.