5th USIAS Fellows Seminar

Tackling the complexity of neuronal connectivity: from lab experiments to mathematical modelling

Stephen Eglen, Fellow 2013, Computational Biology, University of Cambridge

We may understand the processes by which single neurons connect to each other, but how to understand how millions of neurons connect into complex networks? Lab experiments alone can never unravel the complexity of neuronal network formation, but with the help of computational modeling the insights in neuronal connectivity can be improved in crucial ways. Applying mathematics can lead to a breakthrough in developmental neuroscience. 

On the cross-section of disciplines and methods, Stephen Eglen combines theoretical mathematical modelling with experimental work in unique ways to arrive at a better understanding of these processes. This can lead to more general insights in how the brain is wired and rewired over time, and may in the future help to develop important applications for restoring connectivity and “repairing” the brain after injury or disease.