MODELING HUMAN PERIPHERAL SENSORY AXON BUNDLES ON HIGH-DENSITY MEAS FOR HIGH-RESOLUTION ELECTROPHYSIOLOGICAL ANALYSIS

The development of wireless power transfer and next-generation wireless technologies requires a quantitative understanding of the effects of electromagnetic fields (EMFs) on human neural tissue. From an engineering perspective, the establishment of biologically relevant safety guidelines demands experimental platforms that enable precise and reproducible functional evaluation. Pain perception is often considered a critical endpoint; however, the peripheral nervous system responsible for pain and tactile sensation consists of heterogeneous axons organized into axon bundles, complicating threshold evaluation in vivo. Here, we present an in vitro human peripheral sensory axon bundle model integrated with a high-density microelectrode array (HD-MEA) to enable high spatio-temporal resolution electrophysiological measurements. Polydimethylsiloxane (PDMS)-based microfluidic channels were fabricated and bonded onto an HD-MEA to guide axonal growth and form bundled architectures. Human sensory neurons were co-cultured with rat Schwann cells to generate three-dimensional spheroids, which were subsequently cultured within the microfluidic device. Morphological observations confirmed robust axon bundle formation inside the microchannels. Immunocytochemistry and transmission electron microscopy demonstrated the presence of multiple myelinated axons within the bundles. Extracellular recordings using the HD-MEA successfully captured propagating action potentials along the axons. Conduction velocity analysis revealed a tendency toward increased propagation speed under myelination-promoting conditions compared with control cultures. This platform enables detailed functional assessment of signal conduction in human peripheral sensory axon bundles with high spatial and temporal resolution. The proposed model provides a technological foundation for evaluating neural responses in complex peripheral nerve architectures and may contribute to the engineering-based assessment of EMF exposure and neural interface safety.