Title :
Memristor macromodel and its application to neuronal spike generation
Author :
Sangho Shin ; Kyungmin Kim ; Kang, Sung-Mo Steve
Author_Institution :
Jack Baskin Sch. of Eng., Univ. of California, Santa Cruz, Santa Cruz, CA, USA
Abstract :
This paper introduces a memristor-based neuronal spike event generator, in which the memristor models the nonlinear behavior of opening and closing of sodium and potassium ion channels. The neuronal action potential describing both the integrate-and-fire spiking events and the refractory period of nerve membrane cells is enabled by utilizing dual time-constants offered by the bistable resistance state of practical memristive devices. A memristor macromodel which is capable of representing both the threshold effects and boundary assurance is also presented.
Keywords :
memristors; neural nets; bistable resistance state; boundary assurance; dual time-constants; integrate-and-fire spiking events; ion channels; memristive devices; memristor macromodel; memristor models; memristor-based neuronal spike event generator; nerve membrane cells; neuronal action potential; neuronal spike generation; nonlinear behavior; refractory period; threshold effects; Biomembranes; Electric potential; Generators; Integrated circuit modeling; Memristors; Neurons; Threshold voltage;
Conference_Titel :
Circuit Theory and Design (ECCTD), 2013 European Conference on
Conference_Location :
Dresden
DOI :
10.1109/ECCTD.2013.6662306