Topic: mathematical tools

Tom Crawford explores how mathematical models turn questions about the world into equations that can be investigated. Examples range from relativity and infectious-disease modelling to his research on the spread of pollution in the ocean. The lecture also applies modelling to video games, sport and partner selection, illustrating how the same mathematical tools can clarify problems across very different settings.

The shapes of neuronal morphologies are essential for the dynamical properties of the brain, as their branching patterns govern different functional properties of cell types. However, disagreements on the definition of neuronal classes due to the subjective views of the experts have spawned several efforts to find an objective way of deriving a morphology classification. We combine machine learning with a variety of mathematical tools to group neuronal morphologies into stable classes. We show that different methods perform optimally on different use-cases. Thus, we propose a combination of tr