Over the past two decades, human neuroscience has shown how cognitive behaviour relies on a large-scale neural system that exhibits intrinsic, spontaneous patterns of dynamic activity. Although this computation emerges from excitatory and inhibitory interactions at the synaptic level, how the large-scale brain architecture constrains system’s entire dynamics, is still unclear. Network controllability is a mathematical framework to explore structure-function relationships in complex systems, and may be suited to study how the underlying network topology influences brain dynamics. Here I will discuss brain network controllability as an organising principle of the human brain: linking micro-scale neurochemical excitation with system’s dynamics, through network topology.
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