Neurodynamics with delays

Recent advances in applied mathematics have brought us closer to using neural-like dynamics for computing, particularly through the concept of heteroclinic networks for winner-takes-all computations. These networks create transitions between different dynamic structures, enabling computations within a network of states, such as

phase-locked clusters of oscillators. By constructing real-world networks of interacting oscillators, scientists can mimic the properties of biological neural networks to create useful heteroclinic computers. This project aims to develop the mathematics for these computers, leveraging the rich space-time connectome of the human brain and

its white matter plasticity.