Modelling of neural plasticity for enhanced performance of brain-machine interfaces

大脑的可塑性是神经科学的重大科学挑战之一。本项目的目的是模拟与奖励调节的spike- time -dependent可塑性相关的突触变化，并将该模型应用于开发针对可塑性的脑机接口。这种方法的意义在于，这种针对可塑性的技术为利用潜在的神经可塑性来优化神经记录和电刺激的形式提供了前景。结果将大大提高脑机接口的性能，如通道的数量和灵敏度，以及鲁棒性和可靠性。

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.