Reproducible Human Neural Circuits Printed with Single-Cell Precision Reveals the Functional Roles of Ephaptic Coupling

Although in vitro neuronal models are accessible and versatile systems for functional electrophysiological studies, the spontaneous and random formation of neural circuits often compromises the structural control and reproducibility. Here, we introduce a robust method for engineering human neuronal networks in vitro with single-cell precision and reproducibility. Our integrated platform combines direct laser-written microstructure templates and soft lithography-based fabrication of microscaffolds with functional multielectrode array recordings. This system enables high-throughput production of diverse circuit designs and allows for the exact placement of neurons within confined microenvironments. The system enables precise recording of spontaneous neuronal activity, as well as electrical and optogenetic stimulations. Using this approach, we constructed reproducible, bottom-up neuronal circuits composed of a defined number of human neurons. As a proof of principle, we employed these circuits to investigate ephaptic coupling, which refers to the modulation of neuronal activity by endogenous electric fields. Although it is believed to play a role in neural computations and cardiac conduction and is associated with epilepsy and arrhythmia, its mechanisms are unclear due to limitations in experimental models, both in vivo and in vitro. By controlling axonal proximity within microchannels and the number of neurons in the engineered circuits, we can quantify ephaptic coupling at different strengths, which validates theoretical predictions, including reduced action potential velocity, increased activity synchronization, and lower stimulation thresholds. Furthermore, the platform has broad potential for studying synaptic and nonsynaptic interactions, myelination processes, advancing disease modeling, and fundamental neuroscience research.

direct laser writing; ephaptic coupling; in vitro stem cell-derived neuronal networks; microelectrode array; microscaffolds; reproducible neuronal network formation; single-cell resolution.