Neural systems in general - and the human brain in particular - are organised as networks of interconnected components. Across a range of spatial scales from single cells to macroscopic areas, biological neural networks are neither perfectly ordered nor perfectly random. Their heterogeneous organisation supports - and simultaneously constrains - complex patterns of activity. 

How does the network constraint affect the cost of a specific brain's pattern? In this talk, Dani will use the formalism of network control theory to define a notion of network economy and will demonstrate how the principle of network economy can inform our study of neural system function in health and disease and provide a useful lens on neural computation.

Dani Bassett is the J. Peter Skirkanich Professor at the University of Pennsylvania. In 2016, Dani was named one of the ten most brilliant scientists of the year by Popular Science magazine and in 2018 received the Erdős–Rényi Prize for fundamental contributions to our understanding of the network architecture of the human brain.

Please email @email to register to attend in person.

The lecture will be broadcast on the Oxford Mathematics YouTube Channel on Wednesday 11 February at 5-6 pm and any time after (no need to register for the online version).

The Oxford Mathematics Public Lectures are generously supported by XTX Markets.