Optimal solid-state neurons

Kamal Abu Hassan, Joseph Taylor, Paul G Morris, Elisa Donati, Zuner A Bortolotto, Giacomo Indiveri, Julian Paton, Alain Nogaret

Research output: Contribution to journalArticle

1 Citation (Scopus)

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.

Original languageEnglish
Article number5309
Pages (from-to)5309
Number of pages13
JournalNature Communications
Volume10
Issue number1
Early online date3 Dec 2019
DOIs
Publication statusPublished - 3 Dec 2019

ASJC Scopus subject areas

  • Chemistry(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Physics and Astronomy(all)

Cite this

Abu Hassan, K., Taylor, J., Morris, P. G., Donati, E., Bortolotto, Z. A., Indiveri, G., Paton, J., & Nogaret, A. (2019). Optimal solid-state neurons. Nature Communications, 10(1), 5309. [5309]. https://doi.org/10.1038/s41467-019-13177-3