Motor cortical adaptation induced by closed-loop BCI

Brain-computer interface (BCI) could help disabled patients with a broken neural pathway from brain to limbs restore movements by directly exploiting brain signals. Current laboratory BCIs on nonhuman primates (NHPs) were usually started from open-loop hand control (HC) setup for calibration and training, and then progressed to closed-loop brain control (BC) setup without using natural limbs. Successful transition from HC to BC necessitated motor leaning and neural plasticity which might involve the cortical adaptation induced by learning BCI. One useful strategy is to design neural feedback procedure to assist such adaptation and learning. We present an intracortical BCI on NHP with our designed feedback training procedure. In particular, we showed the motor cortical adaptation in terms of single neuron spiking activity in vivo during the closed-loop motor learning induced by our designed feedback training procedure. This experimental work can complement the existing theoretical modeling works on such closed-loop learning process.