Null network models. Network randomization: These functions randomize the network, while preserving the degree distribution (the indegree and outdegree distributions in directed networks). randomizer_bin_und.m (BU networks): This function directly searches for rewirable edge pairs (rather than trying to rewire edge pairs at random), and hence avoids long loops and works . · Brain Connectivity Toolbox. version ( KB) by Mika. A toolbox for complex-network analysis of structural and functional brain-connectivity data. MATLAB Release Compatibility. Created with Rb Compatible with any release Platform Compatibility Reviews: 2. Brain Connectivity Toolbox. A NEW AND UPDATED VERSION OF THE TOOLBOX IS NOW AVAILABLE AT: www.doorway.ru
www.doorway.ru This toolbox provides a cohesive platform for analyzing brain network connectivity in electroencephalography (EEG). Gaussian drop-off of connectivity: This function generates a directed network with a Gaussian drop-off in edge density with increasing distance from the main diagonal. There are no toroidal boundary counditions (i.e. no ring-like "wrapping around"). Brain Connectivity Toolbox. A NEW AND UPDATED VERSION OF THE TOOLBOX IS NOW AVAILABLE AT: www.doorway.ru
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