**CONTACT FOR ASSISTANCE AND QUERIES** Oren Civier (orenciv@gmail.com) https://www.swinburne.edu.au/research/our-research/access-our-research/find-a-researcher-or-supervisor/researcher-profile/?id=ocivier ---------- This repository accompanies the following paper: > Civier O, Sourty M, Calamante F (2023) MFCSC: Novel method to calculate mismatch between functional and structural brain connectomes, and its application for detecting hemispheric functional specialisations. Scientific Reports https://doi.org/10.1038/s41598-022-17213-z --------- **USING MFCSC 1.1 IN NEURODESK - NO INSTALLATION REQUIRED! (any platform)** MFCSC comes pre-installed as part of the free open-source Neurodesk platform. It is provided as a compiled Matlab code, hence, Matlab license is not required! Run Neurodesktop, the desktop environment of Neurodek, by choosing your OS under "Quick Start" in https://neurodesk.github.io/ and following the instructions with a slight change: When executing the command starting in 'docker run', replace the two appearances of the date string "20221216" with "20230324". After running Neurodesktop, mfcsc can be launched from either "Neurodesk"-->"Diffusion Imaging --> mfsc --> mfcsc 1.1" or "Neurodesk"-->"Functional Imaging --> mfcsc --> mfcsc 1.1" in the start menu. A terminal will open, where the following syntax should be used: mfcsc FC_SC_LIST FC_INPUT_DIR SC_INPUT_DIR OUTPUT_DIR not_in_mask_value is_contra is_keep_neg_fc is_symmetrical is_figures The input, output and arguments are identical to the source code version of mfcsc, as described in: https://github.com/civier/mfcsc **Known bugs:** - Specifying true in the is_symmetrical option will cause mfcsc 1.1 to exit with an error. Please use the Matlab version of mfcsc 1.1 if symmetrical output matrices are desired. This bug will be fixed in the next version of the compiled mfcsc. ---------- **USING MFCSC 1.1 IN MATLAB (any platform, require Matlab license)** To obtain the code for MFCSC 1.1, browse here: https://github.com/civier/mfcsc/releases/tag/1.1. The code can be executed from within Matlab IDE or through the command line. Detailed usage instructions are here: https://github.com/civier/mfcsc ---------- **RUNNING THE PROOF-OF-CONCEPT EXAMPLE APPLICATION (testlat)** **testlat** (test laterality) is a matlab function that compares the mismatch between FC and SC in the left hemisphere to the mismatch in the right hemisphere. It is a proof-of-concept application that shows how MFCSC can be used to study brain organisation, in this case -- learning more on hemispheric functional specialisations. In Civier, Sourty and Calamante (2023), we used MFCSC and testlat on the functional and structural connectomes of 50 participants from the Human Connectome Project (HCP) database. Follow these steps to reproduce our results: 1. Follow the instructions in the TESTING MFCSC INSTALLATION section below in order to generate MFCSC matrices for the 50 participants. The matrices will be generated in **outputdir**. 2. Within the Matlab IDE, go to the folder where mfcsc.m is located, and change to the 'test' subfolder. The 'test' subfolder includes the Matlab code file testlat.m 3. Run the following command in Matlab: Mac/Linux testlat('../outputdir','testlast_outputdir') Windows testlat('..\outputdir','testlast_outputdir') 4. The output of testlat will be generated in testlat_ootputdir. Detailed explanation of the outputs is available at https://github.com/civier/mfcsc/blob/main/test/testlat.m 5. Examine the outputs to make sure they agree with our results. Specifically, the sig_*_labels.txt files should include the same label pairs listed in table S1 of the Supplementary material of Civier, Sourty and Calamante (2023) (https://doi.org/10.1038/s41598-022-17213-z). **Important notice:** sig_neg_L_st_R.txt will include one extra label pair compared with table S1(d): ctx-lh-medialorbitofrontal - Left-Amygdala The difference is due a slight difference in the implementation between the code provided here and that used for the paper. Here the linear regression inside each individual includes all connections where direct SC is the shortest structural path, even if that is the case in *only one of the hemispheres*. In contrast, in the paper, the linear regression only includes the connections where direct SC is the shortest structural path in *both hemispheres*. ---------- **TESTING MFCSC INSTALLATION** To test MFCSC, download the "Input" folder from this repository, open Matlab, change to the folder where the MFCSC code is, and run the following commands (with **input** being the directory where the input data was downloaded to, and **outputdir** being the directory where the output should be written to): Mac/Linux mfcsc('input/FC_SC_list.txt', 'input/FC', 'input/SC', 'outputdir'); Windows mfcsc('input\FC_SC_list.txt', 'input\FC', 'input\SC', 'outputdir'); After MFCSC finishes running, the content of **outputdir** should be identical to the "output" folder in this repository ---------- **CITATIONS** When using MFCSC and/or the example application (testlat), authors should cite: > Civier O, Sourty M, Calamante F (2023) MFCSC: Novel method to calculate mismatch between functional and structural brain connectomes, and its application for detecting hemispheric functional specialisations. Scientific Reports https://doi.org/10.1038/s41598-022-17213-z > Rubinov M, Sporns O (2010) Complex network measures of brain connectivity: Uses and interpretations. NeuroImage 52:1059-69. When using the structural connectivity matrices, authors should cite: > Civier O, Smith RE, Yeh CH, Connelly A, Calamante F (2019) Is removal of weak connections necessary for graph-theoretical analysis of dense weighted structural connectomes from diffusion MRI? NeuroImage http://doi.org/10.1016/j.neuroimage.2019.02.039 ... and include the following acknowledgment: > Data were provided by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University, St. Louis, MO. When using the functional connectivity matrices, authors should cite: > Civier O, Sourty M, Calamante F (2023) MFCSC: Novel method to calculate mismatch between functional and structural brain connectomes, and its application for detecting hemispheric functional specialisations. Scientific Reports https://doi.org/10.1038/s41598-022-17213-z ... and include the following acknowledgment: > Data were provided by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University, St. Louis, MO. ----------------- **ACKNOWLEDGMENTS** National Health and Medical Research Council of Australia (grant numbers APP1091593 andAPP1117724) Australian Research Council (grant number DP170101815) National Imaging Facility (NIF), a National Collaborative Research Infrastructure Strategy (NCRIS) capability at Swinburne Neuroimaging, Swinburne University of Technology. Victorian Government’s Operational Infrastructure Support Melbourne Bioinformatics at the University of Melbourne (grant number UOM0048) Sydney Informatics Hub and the University of Sydney’s high performance computing cluster Artemis