My research aims to understand the principles by which neuronal circuits perform flexible cognitive and perceptual computations. I employ a combination of approaches, including: 1) analysis and simulation of biological neural networks; 2) development of data analysis methods to extract meaningful structure from large-scale neural recordings; and 3) top-down modelling of the computations and algorithms through which a circuit might solve a given cognitive task, using insights from machine learning and artificial intelligence. I have previously developed models of the neural circuit computations underlying navigation and spatial memory in the hippocampus, and of the impact of learning on network dynamics in visual cortex and their role in sensory processing. Future projects will develop models of the computations performed through hierarchically interacting brain areas during cognitive tasks, such as in visual and spatial circuits during navigation.

PhD Computational Neuroscience, University of Edinburgh 2015.

Angus Chadwick is a lecturer in Computational Neuroscience and Artificial Intelligence at the Institute for Adaptive and Neural Computation within the School of Informatics. Dr Chadwick worked previously as a Research Associate at University College London where he investigated the role of cortical dynamics for sensory processing. His PhD at the University of Edinburgh focused on the representation of space in the rodent hippocampus. He holds a Masters degree in Mathematical Physics, and worked briefly in research and development for the renewable energy sector before moving into Computational Neuroscience.