Code used in Glerean et al. 2015 "Reorganization of functionally connected brain subnetworks in high-functioning autism" (in press: https://onlinelibrary.wiley.com/doi/10.1002/hbm.23084/abstract)

DOI for the code:

This is part of the code used for the article mentioned above.

The BraMiLa Matlab tools were used for further preprocessing and head motion quality control https://git.becs.aalto.fi/bml/bramila/ specifically

• bramila_clean_signal.m (to further clean the fMRI data as described in Power et al. 2014 https://www.sciencedirect.com/science/article/pii/S1053811913009117)
• bramila_diagnostics.m (for quality control)

Tools for graph-theoretical analysis in Python 2.7 are available at: https://git.becs.aalto.fi/rmkujala/brainnets

The scripts are using the extensive library developed by the Complex Networks group at the Neuroscience and Biomedical Engineering department of Aalto University https://git.becs.aalto.fi/complex-networks/verkko/tree/master https://becs.aalto.fi/en/research/complex_networks/

Please refere to the readme of the subfolder ABIDE

The following MATLAB functions and toolboxes were used for permutation based statistics:

• bramila_ttest_np.m from https://git.becs.aalto.fi/bml/bramila/ ..* Used to efficiently compute difference of the means using permutations. It uses Matlab parallel computing toolbox.
• bramila_mantel.m from https://git.becs.aalto.fi/bml/bramila/ (a copy available also in the ABIDE subfolder) ..* Used to perform Mantel test (correlation between two distance/similarity matrices).
• Micro-level statistics were computed with https://bia.korea.ac.kr/people/~cheolhan/software/