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Publication - Professor Julian Paton

    Optimal solid state neurons

    Citation

    Bortolotto, ZA, Paton, JFR & Morris, PG, 2019, ‘Optimal solid state neurons’. Nature Communications.

    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 solidstate electronics. By conguring 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 optimisation of nonlinear models demonstrates a powerful method for programming analog electronic circuits. This approach oers a route for repairing diseased biocircuits and emulating their function with biomedical implants that can adapt to biofeedback.

    Full details in the University publications repository