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- W2978923360 abstract "Abstract 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." @default.
- W2978923360 created "2019-10-10" @default.
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- W2978923360 date "2019-12-03" @default.
- W2978923360 modified "2023-10-01" @default.
- W2978923360 title "Optimal solid state neurons" @default.
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- W2978923360 doi "https://doi.org/10.1038/s41467-019-13177-3" @default.
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