Neural Control Algorithms
The cerebellum plays a critical role for sensorimotor control and learning. However, dysmetria or delays in movements' onsets consequent to damages in cerebellum cannot be cured completely at the moment. Neuroprosthesis is an emerging technology that can potentially substitute such motor control module in the brain. A pre-requisite for this to become practical is the capability to simulate the cerebellum model in real-time, with low timing distortion for proper interfacing with the biological system. In this work, we present a frame-based network-on-chip (NoC) hardware architecture for implementing a bio-realistic cerebellum model with ~ 100 000 neurons, which has been used for studying timing control or passage-of-time (POT) encoding mediated by the cerebellum. Here we show a hardware electronic setup and illustrate how the silicon cerebellum can be adapted as a potential neuroprosthetic platform for future biological or clinical application.