============================= Extra features configurations ============================= The Connectome Analyzer also provides extra features for :ref:`relax_label` and compute :ref:`single_subj_label` .. _relax_label: P-value matrix relaxation -------------------------------- .. image:: snapshots/matrix_relaxation.jpg **Matrix file** Select the file containing the matrix of p-values to relax. The file can be in csv format or matlab ".mat" format. In the case of a ".mat" file, make sure that the matrix variable is named "matrix". The p-values can come from any test (Student t-test, Wilcoxon test, multivariate Hotelling test, etc...). **Data separator** If the matrix file is in csv format, select the character that separates columns in the file. For matlab ".mat" files, this setting is ignored **Decomposition method** * Automatic: decomposes the network subnetworks using the algorithm of your choice (walktrap, leading eigenvector or spinglass). * File: provide a file containing the decomposition of the nodes into sub-regions. The file should have 2 columns and as much rows as nodes. The first column should contain the node label, ranging from 1 to the maximum number of nodes. The second column should contain the sub-region label to which the corresponding node belongs. Sub-regions labels should range from 1 to the number of sub-regions without skipping numbers **Correction** Select the method used for the correction for multiple testing **Alpha1** Threshold to detect significantly different sub-networks **Alpha2** Threshold bellow which the null hypothesis Group1 == Group2 can be rejected in favor of the H1 used to compute the original p-values **Strong** Factor by which the p-values of non-significatively different sub-networks should be multiplied in the RMIO procedure .. _single_subj_label: Single subject measures ----------------------- .. image:: snapshots/single_subject.jpg **Connectivity matrix** Select the file containing the connectivity matrix. The file can be in csv format or matlab ".mat" format. In the case of a ".mat" file, make sure that the matrix variable is named "matrix". **Data separator** If the connectivity matrix file is in csv format, select the character that separates columns in the file. For matlab ".mat" files, this setting is ignored **Network measures** You can choose to compute the network measures on: * Non-Weighted graphs: the edge values represent the number of connections between the vertices * Weighted graphs: the edge values represent some measure of the connection strength between the vertices * Binarized graphs: the edges that have non-zero values are set to one before computing the network measures Select the set of measures you want to test: * Degree: computes the mean degree of the network. If the matrix is weighted, the mean strength is computed * Betweenness: computes the network mean node betweenness * Closeness: computes the network mean closeness * Diameter: computes the network mean diameter * Efficiency: compute the network mean efficiency