Implantable Neural Interfaces for Motor Disorders

Abstract

Implantable neural interfaces -- devices that record or stimulate neural activity through electrodes placed on or within the central and peripheral nervous system -- are transforming the treatment of motor disorders by restoring volitional movement in paralysis, suppressing pathological oscillations in Parkinson's disease, and enabling closed-loop neuromodulation for essential tremor. This study developed and evaluated three neural interface architectures -- a 128-channel flexible polyimide micro-electrocorticography (µECoG) array for cortical surface recording, a 256-channel silicon intracortical microelectrode array (MEA) with PEDOT:PSS coating for single-unit recording, and a carbon nanotube (CNT)-based peripheral nerve cuff electrode for selective fascicular stimulation -- characterising impedance, signal-to-noise ratio (SNR), chronic biocompatibility, and neural decoding performance in a 12-week non-human primate (NHP) motor cortex implantation model (n = 4). The PEDOT:PSS-coated MEA achieved the lowest impedance at 1 kHz (8.4 +- 1.2 kOhm vs 42.8 +- 6.4 kOhm uncoated; 80% reduction) and highest SNR (12.8 +- 2.4 dB), enabling single-unit isolation in 84.2% of channels at week 12. The µECoG array maintained stable high-gamma band power (70-150 Hz) decoding of reach direction with 92.4% accuracy over 12 weeks without signal degradation. The CNT nerve cuff achieved selective activation of individual fascicles (selectivity index SI = 0.84) with 42% lower stimulation threshold than platinum electrodes. These results establish PEDOT:PSS-coated MEAs as the highest-fidelity cortical recording platform and µECoG as the most chronically stable interface for brain-computer interface applications.