Optimal solid state neurons

Kamal Abu-Hassan, Joseph D. Taylor, Paul G. Morris, Elisa Donati, Zuner A. Bortolotto, Giacomo Indiveri, Julian F. R. Paton and Alain Nogaret ()
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Kamal Abu-Hassan: University of Bath
Joseph D. Taylor: University of Bath
Paul G. Morris: University of Bath
Elisa Donati: University of Zürich and ETH Zürich
Zuner A. Bortolotto: University of Bristol
Giacomo Indiveri: University of Zürich and ETH Zürich
Julian F. R. Paton: University of Bristol
Alain Nogaret: University of Bath

Nature Communications, 2019, vol. 10, issue 1, 1-13

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.

Date: 2019
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DOI: 10.1038/s41467-019-13177-3

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