As part of the Centre for Mathematics of Precision Healthcare Lecture Series we are delighted to welcome Professor Danielle Bassett, Eduardo D. Glandt Faculty Fellow and Associate Professor, Bioengineering, University of Pennsylvania to talk about her outstanding work.

Perturbation and Control of Human Brain Network Dynamics

The human brain is a complex organ characterized by heterogeneous patterns of interconnections. New non-invasive imaging techniques now allow for these patterns to be carefully and comprehensively mapped in individual humans, paving the way for a better understanding of how wiring supports our thought processes. While a large body of work now focuses on descriptive statistics to characterize these wiring patterns, a critical open question lies in how the organization of these networks constrains the potential repertoire of brain dynamics. In this talk, I will describe an approach for understanding how perturbations to brain dynamics propagate through complex writing patterns, driving the brain into new states of activity. Drawing on a range of disciplinary tools – from graph theory to network control theory and optimization – I will identify controlpoints in brain networks, characterize trajectories of brain activity states following perturbation to those points, and propose a mechanism for how network control evolves in our brains as we grow from children into adults. Finally, I will describe how these computational tools and approaches can be used to better understand how the brain controls its own dynamics (and we in turn control our own behavior), but also how we can inform stimulation devices to control abnormal brain dynamics, for example in patients with severe epilepsy.

Professor Danielle Bassett

Danielle Bassett is a physicist and systems neuroscientist who was the youngest individual to be awarded a 2014 MacArthur fellowship. She was also awarded a 2014 Sloan fellowship. Bassett is the Skirkanich Associate Professor of Innovation at the University of Pennsylvania, where she applies network science to the study of learning in the human brain in addition to the study of other complex physical and biological systems. She received a B.S. in physics from Pennsylvania State University in 2004, and her Ph.D in physics from the University of Cambridge in 2009.