Computational Neuroscience and Neuroinformatics
In computational neuroscience and neuroinformatics we study how the brain processes information. A major goal is to understand how, in contrast to most computer systems, the brain is so robust and adaptive. These insights will be important to build better future hardware and software. At the same time, tools from informatics such as image analysis, computer simulation, and machine learning are essential to accelerate neuroscientific discovery.
- David Willshaw: Computational models of development of the nervous system
- James A. Bednar: Simulations of the development of the visual cortex
- Peggy Seriès: Bayesian approaches to cognition and perception
- Mark van Rossum: Synaptic plasticity, coding in the visual system, noise in the nervous system
- Douglas Armstrong: Molecular neuroinformatics, network models, behavioural models
- Matthias Hennig: Models of neural networks, homeostasis and development; visual and auditory neuroscience; analysis of large-scale electrophysiological recordings
- Ian Simpson: Regulatory genomics, bioinformatics and computational biology. Neural development and function especially in cortical structures and in relation to cognition, learning and memory using genomic, meta-genomic, transcriptomic and proteomic data
- Barbara Webb: Perceptual systems for the control of behaviour, robot models of animals, simulation of neural circuits
Undergraduates: As an undergraduate in the School of Informatics, you can do projects in our institute.
MSc students: You should apply directly to the School for information. Once you are a student you can follow the courses and do projects in our institute.
PhD students: If you're interested in knowing more about PhD Programmes being offered by ANC, then please check our information at http://www.anc.ed.ac.uk/prospective-postgraduates
- DTC Workshop Series
- The Neural Coding and Bayesian Methods Journal Club
- Neurons & Systems Journal Club
We teach a number of MSc courses in these subjects: