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A Memristor SPICE Model Accounting for Synaptic Activity Dependence

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TLDR
This work proposes a new memristor SPICE model that accounts for the typical synaptic characteristics that have been previously demonstrated with practical memristive devices and shows that this model could account for both volatile and non-volatile memristance changes under distinct stimuli.
Abstract
In this work, we propose a new memristor SPICE model that accounts for the typical synaptic characteristics that have been previously demonstrated with practical memristive devices. We show that this model could account for both volatile and non-volatile memristance changes under distinct stimuli. We then demonstrate that our model is capable of supporting typical STDP with simple non-overlapping digital pulse pairs. Finally, we investigate the capability of our model to simulate the activity dependence dynamics of synaptic modification and present simulated results that are in excellent agreement with biological results.

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References
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Journal ArticleDOI

The missing memristor found

TL;DR: It is shown, using a simple analytical example, that memristance arises naturally in nanoscale systems in which solid-state electronic and ionic transport are coupled under an external bias voltage.
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Memristor-The missing circuit element

TL;DR: In this article, the memristor is introduced as the fourth basic circuit element and an electromagnetic field interpretation of this relationship in terms of a quasi-static expansion of Maxwell's equations is presented.
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Synaptic Modifications in Cultured Hippocampal Neurons: Dependence on Spike Timing, Synaptic Strength, and Postsynaptic Cell Type

TL;DR: The results underscore the importance of precise spike timing, synaptic strength, and postsynaptic cell type in the activity-induced modification of central synapses and suggest that Hebb’s rule may need to incorporate a quantitative consideration of spike timing that reflects the narrow and asymmetric window for the induction of synaptic modification.
Journal ArticleDOI

Nanoscale Memristor Device as Synapse in Neuromorphic Systems

TL;DR: A nanoscale silicon-based memristor device is experimentally demonstrated and it is shown that a hybrid system composed of complementary metal-oxide semiconductor neurons and Memristor synapses can support important synaptic functions such as spike timing dependent plasticity.
Journal Article

SPICE Model of Memristor with Nonlinear Dopant Drift

TL;DR: It is shown that the hitherto published approaches to the modeling of boundary conditions need not conform with the requirements for the behavior of a practical circuit element, and the described SPICE model of the memristor is constructed as an open model, enabling additional modifications of non-linear boundary conditions.
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