Modelling of neural plasticity for enhanced performance of brain-machine interfaces
Plasticity of the brain is one of the great scientific challenges of neuroscience. The aim of this project is to model the synaptic changes that occur with reward-modulated spike-timing-dependent plasticity and apply the model to developing plasticity targeted brain-machine interfaces. The significance of this approach is that such plasticity targeted techniques provide the prospect of taking advantage of the underlying neural plasticity to optimise the form of the neural recording and electrical stimulation. The outcomes will be to greatly improve the performance of brain-machine interface in terms of measures such as the number and sensitivity of channels, as well as robustness and reliability.
Leader: Anthony Burkitt
Staff: Catherine Davey, David Grayden
Convergence of engineering and IT with the life sciences
biomedical engineering; computational neuroscience; medical bionics; neural models; neuroengineering