Randomizing brain network partitioning
This protocol is extracted from research article:
Cognitive chimera states in human brain networks
Sci Adv, Apr 3, 2019; DOI: 10.1126/sciadv.aau8535

To assess the importance of a cognitively informed framework, we obtained the patterns of synchronization when the brain was randomly partitioned into nine different groups (systems). To obtain a random partition of the brain, we fixed the number of regions in each group to match their sizes with the original cognitively informed partitioning (systems 1 to 9 were 4, 4, 12, 10, 8, 6, 14, 10, and 8 regions per system, respectively) and then randomly assigned brain regions to each of these groups. We then used the previously simulated brain activity for each subject to calculate the system-level Kuramoto parameter, system-level synchronization matrices, and the patterns of synchrony (as described above) based on the new random partitioning of the brain. In the first randomization experiment, a single random partition was created and applied across all 30 subjects to extract the prevalent patterns (those that occur with a frequency of ≥3%) for each group. In the second randomization experiment, 10 different random partitions were created, and each partition was applied across all 30 subjects to extract the prevalent patterns from this larger ensemble.

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