CCSS Masterclass on Numerical and Analytical Methods for Spatially-Extended Neurobiological Networks: Part III

The CCSS MasterClass is a series of lectures on a specific topic of Complexity Science given by a leading expert in the field, which is generously supported by one of our UU alumni Laurens Gaarenstroom.

Masterclass Overview

General Title: Numerical and Analytical Methods for Spatially-Extended Neurobiological Networks.

Part I on Monday May 13 (10:00-15:00 with lunch): Models, analytical and semi-analytical methods
Part II on Tuesday May 14 (10:00-15:00 with lunch): Numerical methods for brain dynamics
Part III on Thursday May 16 (10:00-15:00 with lunch): Models with random data and stochastic forcing 

Speaker Overview

Dr. Daniele Avitabile is a mathematician in the Amsterdam Center for Dynamics and Computation at Vrije Universiteit Amsterdam, and a member of Inria's MathNeuro Team. He works on spatio-temporal patterns in biological and physical models, which he studies using numerical and analytical methods. Daniele's research interests include: numerical bifurcation analysis, mathematical neuroscience, multi-scale dynamics, numerical methods, localised states, coherent structures, nonlinear media, reaction-diffusion systems, and nonlocal models. He is also an editor-in-chief of the SIAM series on Mathematical Neuroscience.

Models with random data and stochastic forcing

As any model in the physical and life sciences, neurobiological networks return a stochastic outcome when subject to stochastic forcing, or when their input data is random. We will discuss recent progress by PhD candidates Francesca Cavallini (VU Amsterdam) and Khadija Meddouni (Radboud University) on uncertainty quantification techniques for brain dynamics. They develop provably-accurate numerical schemes to estimate quantities of interests for neural field with random data, or time step stochastic differential equations for large-scale dynamics. If time permits, I will give you a sneak peek into inverse problems, in which parameters or states are estimated from data.

Meeting Details (location: MIN 4.16)

10:00-12:00 Lecture on "Models with random data and stochastic forcing"
12:00-13:00 FREE lunch for all participants (signup below)
13:00–15:00 Hands-on tutorials

To attend the lecture (physically), please signup below before 15:00 on Thursday May 9.