Low-power analog and mixed-signal circuit techniques for next-generation miniature implantable neural interface systems.

Abstract

Miniature implantable neural interface devices are increasingly critical for both neuroscience research and clinical neuromodulation applications. However, device miniaturization imposes stringent constraints on power, area, and performance, creating challenges for implementing energy-efficient neuromodulation, high-fidelity neural recording, and wireless data telemetry. This review provides a comprehensive overview of low-power circuit designs enabling next-generation neural interfaces. We discuss energy-efficient stimulation drivers for optogenetic neuromodulation, highlighting advanced switched-capacitor-based techniques that reduce supply voltage requirements while maintaining high-current LED pulses. Low-noise neural recording frontends, including preamplifier-fronted structures, as well as ΔΣ ADC-based and NS-SAR-based direct-digitizing architectures, are reviewed with emphasis on techniques for dynamic range extension, linearity improvement, and artifact tolerance. Finally, state-of-the-art backscatter-based wireless telemetry methods are presented, covering load-shift keying (LSK), frequency-splitting, and push-pull quadrature modulation approaches that decouple power and data transfer to achieve high data rates with minimal energy consumption. This review highlights the critical role of circuit-level innovations in overcoming the power and performance limitations of miniature implants and provides insights for the design of next-generation neural interface systems.