Balancing Specialized Versus Flexible Computation in Brain–Computer Interfaces

Abstract

We are building HALO, a flexible ultralow-power processing architecture for implantable brain– computer interfaces (BCIs) that directly communicate with biological neurons in real time. This article discusses the rigid power, performance, and flexibility tradeoffs that BCI designers must balance, and how we overcome them via HALO’s palette of domain-specific hardware accelerators, general-purpose microcontroller, and configurable interconnect. Our evaluations using neuronal data collected in vivo from a nonhuman primate, along with full-stack algorithm to chip codesign, show that HALO achieves flexibility and superior performance per watt versus existing implantable BCIs.