From Electrophysiological to Biochemically-Modulated Interfaces: Evolution of Brain-Machine Communication.

Abstract

Brain-machine interfaces (BMIs) establish bidirectional communication between biological neural systems and external devices by decoding neural signals and delivering feedback stimulation. Achieving seamless integration with biological systems has driven the paradigmatic evolution of BMI technology through three interconnected dimensions. This review summarizes the shift from electrophysiological to biochemically-modulated BMIs, emphasizing key evolutionary trends that mirror biological neural characteristics. First, signal modalities have expanded from single electrophysiological detection to integrated biochemical sensing, enabling comprehensive neural circuit analysis through dual electrical-chemical communication pathways that capture both rapid electrical transmission and slower biochemical processes. Second, electrode morphology has transformed from rigid silicon structures to flexible, adaptive materials that mechanically match neural tissue properties, reducing mechanical mismatch and improving long-term biocompatibility. Third, system architectures have evolved from passive monitoring to active closed-loop platforms that incorporate neuromorphic intelligence and real-time therapeutic feedback, enabling dynamic neuromodulation based on multimodal signal analysis. Despite significant progress, challenges remain in achieving high electrode longevity, developing scalable multimodal interfaces, as well as understanding fundamental neural communication mechanisms. Future directions point toward biochemically-modulated brain interfaces incorporating living, adaptive, and evolutionarily responsive components that seamlessly integrate with biological neural networks for precision neurological therapeutics.