The brain uses information gathered from the body and the surrounding world to build internal representations and to control behaviour. Sensory signals are processed as they flow from peripheral sensory receptors through networks of neurons, and computations are performed at the synaptic, neuronal and network level. Computational neuroscience seeks to construct theories and quantitative models of how these computations take place.
Computational neuroscientists use analyses and
models of the nervous system at these different structural scales in
order to understand how such computations might be performed. This
enables them to provide new interpretations of experimental data, make
predictions that can be tested experimentally and suggest entirely new
avenues for investigating how the brain works.
At UCL, there is a large
and vibrant community of researchers involved in computational
neuroscience. Their research ranges from computational models of
individual synapses and single neurons to entire networks.
A particular focus of interdisciplinary computational neuroscience research at UCL is the internationally renowned Gatsby Computational Neuroscience Unit. Work at the Gatsby studies neural computational theories of perception and action in neural and machine systems, with an emphasis on learning. The Unit has an active role in teaching the next generation of computational neuroscience researchers, centered on an innovative four-year PhD program in Computational Neuroscience and Machine Learning.