Silicon central pattern generator model of cardiac contraction behaviour

Kamal Abu Hassan, Joseph Taylor, Joanne van Bavel, Marc Vos, Alain Nogaret

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Synchronization of brain cells underlies the generation of key motor functions including breathing, cardiac activity and locomotion. The circuitry mechanisms underpinning this phase-locked rhythmic patterns have been studied in local circuitry networks known as Central Pattern Generators (CPGs). Biological CPGs (bCPGs) in healthy nervous systems demonstrate robustness and adaptation in response to variations in sensory feedback. This study aims at constructing biologically-plausible network models of analog hardware CPGs (hCPGs), and assimilating the membrane voltages of all constituting neurons in the network with large-scale constrained nonlinear optimization. The hCPG model exhibits a tetra-phasic behavior where the spike timings of the four neurons corresponds to the activation of the heart chambers: sino-atrial node, left atrium, left ventricle and right ventricle. We show the results of modelling electrocardiogram (ECG) recordings from anesthetized dogs. This research will facilitate designing bioelectronic implants to recover cardiac function in heart diseases.
Original languageEnglish
Title of host publicationSilicon Central Pattern Generator Model of Cardiac Contraction Behavior
PublisherIEEE
Publication statusPublished - Jul 2020

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