2019/12/03 by Kamal Abuhassan, Joseph D. Taylor, Paul G. Morris +5 · 1 voice
Engineering · Neuroscience · #Advanced Memory and Neural Computing #Neural dynamics and brain function #Neuroscience and Neural Engineering
paper · pdf · doi:10.1038/s41467-019-13177-3
openalex publication_date 2019/12/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30
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 solid-state electronics. By configuring 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 optimization of nonlinear models demonstrates a powerful method for programming analog electronic circuits. This approach offers a route for repairing diseased biocircuits and emulating their function with biomedical implants that can adapt to biofeedback.