A Brain-Machine Interface Operating with a Real-Time Spiking Neural Network Control Algorithm

@article{Dethier2011ABI,
  title={A Brain-Machine Interface Operating with a Real-Time Spiking Neural Network Control Algorithm},
  author={Julie Dethier and Paul Nuyujukian and Chris Eliasmith and Terrence C. Stewart and Shauki A. Elasaad and Krishna V. Shenoy and Kwabena Boahen},
  journal={Advances in neural information processing systems},
  year={2011},
  volume={2011},
  pages={2213-2221}
}
Motor prostheses aim to restore function to disabled patients. Despite compelling proof of concept systems, barriers to clinical translation remain. One challenge is to develop a low-power, fully-implantable system that dissipates only minimal power so as not to damage tissue. To this end, we implemented a Kalman-filter based decoder via a spiking neural network (SNN) and tested it in brain-machine interface (BMI) experiments with a rhesus monkey. The Kalman filter was trained to predict the… CONTINUE READING