The developing human brain contains a cacophony of electrical and chemical signals from which emerge the powerful adult capacities for decision-making, strategizing, and critical thinking. These signals support the trafficking of information across brain regions, in patterns that share many similarities with traffic patterns in railway and airline transportation systems. Yet while air traffic is guided by airport control towers, and railway routes are guided by signal control rooms, it remains a mystery how the information traffic in the brain is guided and how that guidance changes as kids grow.
In part, this mystery has been complicated by the fact that, unlike transportation systems, the brain is not hooked up to external controllers. Control must happen internally. The problem becomes even more complicated when we think about the sheer number of routes that must exist in the brain to support the full range of human cognitive capabilities. Thus, the controllers would need to produce a large set of control signals or use different control strategies. Where internal controllers might be, how they produce large variations in routing, and whether those controllers and their function change with age are important open questions.
A recent paper published in Nature Communications – a product of collaboration among the Departments of Bioengineering and Electrical & Systems Engineering at the University of Pennsylvania and the Department of Psychiatry of Penn’s Perelman School of Medicine – offers some interesting answers. In their article, Danielle Bassett, Ph.D., Eduardo D. Glandt Faculty Fellow and Associate Professor in the Penn BE Department, Theodore D. Satterthwaite, M.D., Assistant Professor in the Penn Psychiatry Department, postdoctoral fellow Evelyn Tang, and their colleagues suggest that control in the human brain works in a similar way to control in man-made robotic and other mechanical systems. Specifically, controllers exist inside each human brain, each region of the brain can perform multiple types of control, and this control grows as children grow.
As part of this study, the authors applied network control theory — an emerging area of systems engineering – to explain how the pattern of connections (or network) between brain areas directly informs the brain’s control functions. For example, hubs of the brain’s information trafficking system (like Grand Central Station in New York City) show quite different capacities for and sensitivities to control than non-hubs (like Newton Station, Kansas). Applying these ideas to a large set of brain imaging data from 882 youths in the Philadelphia area between the ages of 8 and 22 years old, the authors found that the brain’s predicted capacity for control increases over development. Older youths have a greater predicted capacity to push their brains into nearby mental states, as well as into distant mental states, indicating a greater potential for diversity of mental operations than in younger youths.
The investigators then asked whether the principles of network control could explain the specific manner in which connections in the brain change as youths age. They used tools from evolutionary game theory – traditionally used to study Darwinian competition and evolving populations in biology – to ‘evolve’ brain networks in silico from their 8-year old state to their 22-year-old state. The results demonstrated that the optimization of network control is a principle that explains the observed changes in brain connectivity as youths develop over childhood and adolescence. “One of the observations that I think is particularly striking about this study,” Bassett says, “is that the principles of network controllability are sufficient to explain the observed evolution in development, suggesting that we have identified a quintessential rule of developmental rewiring.”
This research informs many possible future directions in scientific research. “Showing that network control properties evolve during adolescence also suggests that abnormalities of this developmental process could be related to cognitive deficits that are present in many neuropsychiatric disorders,” says Satterthwaite. The discovery that the brain optimizes certain network control functions over time could have important implications for better understanding of neuroplasticity, skill acquisition, and developmental psychopathology.
Jason Burdick, Ph.D., who is a professor in the University of Pennsylvania’s Department of Bioengineering, has been named one of the three chairs of the 2019 annual meeting of the 
