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Optimal solid state neurons.

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.

SUBMITTER: Abu-Hassan K

PROVIDER: S-EPMC6890780 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Optimal solid state neurons.

Abu-Hassan Kamal K Taylor Joseph D JD Morris Paul G PG Donati Elisa E Bortolotto Zuner A ZA Indiveri Giacomo G Paton Julian F R JFR Nogaret Alain A

Nature communications 20191203 1

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 ...[more]

PMID: 31796727

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Optimal solid state neurons.

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Optimal solid state neurons.

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