Description
Center of Complex Networks Research, Northeastern University and Division
of Network Medicine, Harvard University.
The ultimate proof of our understanding of biological or technological
systems is reflected in our ability to control them. While control theory
offers mathematical tools to steer engineered and natural systems towards a
desired state, we lack a framework to control complex self-organized
systems. Here I will explore the controllability of an arbitrary complex
network, identifying the set of driver nodes whose time-dependent control
can guide the systems entire dynamics. Virtually all technological and
biological networks must be able to control their internal processes. Given
that, issues related to control deeply shape the topology and the
vulnerability of real systems. Consequently, unveiling the control
principles of real networks, the goal of our research, forces us to address
series of fundamental questions pertaining to our understanding of complex
systems. Finally, I will discuss how control principles inform our ability
to predict neurons involved in specific processes in the brain, offering an
avenue to experimentally falsify and test the predictions of network
control.