Courses: All

Computational Neurodynamics

Lecturer : Murray Shanahan

Overview

Computational neurodynamics is the use of computer models to study the dynamics of large networks of interacting neurons. The rationale behind the field, which lies at the theoretical end of computational neuroscience, is that the language of dynamical systems is the right one to express the underlying principles of nervous system operation. The course has two parts. In Part One, the student will learn how to model single neurons mathematically, how to simulate them computationally, and how to construct models of large networks of such neurons with a variety of topologies. In Part Two, the student will learn how to characterise the resulting behaviour using various measures, and will acquire an understanding of the phenomena that are revealed as a result.