Using this algorithm, one can extract the main brain modular structures ), which fluctuate over time during rest and task. . The proposed framework simply takes as input a set of connectivity matrices, without making any constraint on how these matrices are computed.
Using this algorithm, one can extract the main brain modular structures ), which fluctuate over time during rest and task. . The proposed framework simply takes as input a set of connectivity matrices, without making any constraint on how these matrices are computed.
The function "Categorical_modularity_NN" detects the categorical modular structures while the "Sequential_modularity_NN" extracts the sequential modular structures. One should run either Categorical_modularity_NN.m or sequential_modlarity_NN.m depending on his application.
Remark: genlouvain-2.1 should be added to the matlab path while running the code.
Reference: Kabbara et al. 2019, Detecting modular brain states in rest and task, Network Neuroscience