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 language | English |
---|---|
Article number | 5309 |
Pages (from-to) | 5309 |
Number of pages | 13 |
Journal | Nature Communications |
Volume | 10 |
Issue number | 1 |
Early online date | 3 Dec 2019 |
DOIs | |
Publication status | Published - 3 Dec 2019 |
ASJC Scopus subject areas
- General Chemistry
- General Biochemistry,Genetics and Molecular Biology
- General Physics and Astronomy
Fingerprint
Dive into the research topics of 'Optimal solid-state neurons'. Together they form a unique fingerprint.Profiles
-
Alain Nogaret
- Department of Physics - Professor
- Centre for Networks and Collective Behaviour
- Centre for Nanoscience and Nanotechnology
- Condensed Matter Physics CDT
- Institute for Mathematical Innovation (IMI)
- Centre for Therapeutic Innovation
- Centre for Mathematical Biology
- Bath Institute for the Augmented Human
- NanoBioEletronics - Head of Group
Person: Research & Teaching, Core staff, Affiliate staff