Optimal solid state neurons.

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ID: 69684
2019
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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.
Reference Key
abuhassan2019optimalnature Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Abu-Hassan, Kamal;Taylor, Joseph D;Morris, Paul G;Donati, Elisa;Bortolotto, Zuner A;Indiveri, Giacomo;Paton, Julian F R;Nogaret, Alain;
Journal Nature communications
Year 2019
DOI
10.1038/s41467-019-13177-3
URL
Keywords
gaba disinhibition computational modeling brain connectivity tms-eeg disorders of consciousness (doc) feedforward inhibition

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