  Network control theory has recently emerged as a promising approach for
understanding brain function and dynamics. By operationalizing notions of
control theory for brain networks, it offers a fundamental explanation for how
brain dynamics may be regulated by structural connectivity. While powerful, the
approach does not currently consider other non-structural explanations of brain
dynamics. Here we extend the analysis of network controllability by formalizing
the evolution of neural signals as a function of effective inter-regional
coupling and pairwise signal covariance. We find that functional
controllability characterizes a region's impact on the capacity for the whole
system to shift between states, and significantly predicts individual
difference in performance on cognitively demanding tasks including those task
working memory, language, and emotional intelligence. When comparing
measurements from functional and structural controllability, we observed
consistent relations between average and modal controllability, supporting
prior work. In the same comparison, we also observed distinct relations between
controllability and synchronizability, reflecting the additional information
obtained from functional signals. Our work suggests that network control theory
can serve as a systematic analysis tool to understand the energetics of brain
state transitions, associated cognitive processes, and subsequent behaviors.
