Optimal solid state neurons

Bioelectronic medicine is driving the need for neuromorphic microcircuits that integrate raw nervous stimuli and respond identically to biological neurons. However, designing such circuits remains a challenge. Here we estimate the parameters of highly nonlinear conductance models and derive the ab-initio equations of intracellular currents and membrane voltages embodied in analog solidstate electronics. By conguring individual ion channels of solid-state neurons with parameters estimated from large-scale assimilation of electrophysiological recordings, we successfully transfer the complete dynamics of hippocampal and respiratory neurons in-silico. The solid-state neurons are found to respond nearly identically to biological neurons under stimulation by a wide range of current injection protocols. The optimisation of nonlinear models demonstrates a powerful method for programming analog electronic circuits. This approach oers a route for repairing diseased biocircuits and emulating their function with biomedical implants that can adapt to biofeedback.