Neuromodulation of a peripheral nerve using fully polymeric cuff electrodes: understanding predictability of selective stimulation

<i>Objective.</i>Peripheral nerve stimulation (PNS) offers therapeutic benefits across numerous clinical applications but remains limited by poor spatial selectivity in mixed nerves. This study aimed to evaluate whether a fully polymeric, transverse, multipolar nerve cuff can achieve selective fascicular activation and to assess the predictability of such selectivity using imaging-informed computational models.<i>Approach.</i>A flexible, fully polymeric nerve cuff fabricated from a conductive elastomer (CE) was developed and evaluated<i>ex vivo</i>on rat sciatic nerves. Compound nerve action potentials were recorded from individual fascicles to quantify selectivity across a wide range of stimulation parameters. The non-metallic electrodes enabled microCT-based three-dimensional reconstruction of nerve-electrode geometries without imaging artifacts, which were incorporated into anatomically accurate simulations using the ASCENT modeling pipeline.<i>Main results. Ex vivo</i>experiments demonstrated reliable neural recordings and high levels of fascicular selectivity (selectivity index > 0.65 in each fascicle). Imaging-informed simulations reproduced selective activation patterns in some cases but showed systematic discrepancies in both selectivity magnitude and electrode-fascicle correspondence, particularly for sural and tibial fascicles. Simulated outcomes were more sensitive to neuroanatomical variability than experimental results, highlighting limitations in current modeling assumptions.<i>Significance.</i>These findings validate fully polymeric CE cuffs as effective alternatives to metallic nerve interfaces for selective PNS. The study also demonstrates the value of combining microCT imaging with computational modeling to interrogate and refine predictive frameworks, underscoring the need for improved tissue and electrode modeling to advance spatially selective PNS technologies.