Experimental demonstration of a second-order memristor and its ability to biorealistically implement synaptic plasticity.

Nano Lett

Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan 48109, United States.

Published: March 2015

Memristors have been extensively studied for data storage and low-power computation applications. In this study, we show that memristors offer more than simple resistance change. Specifically, the dynamic evolutions of internal state variables allow an oxide-based memristor to exhibit Ca(2+)-like dynamics that natively encode timing information and regulate synaptic weights. Such a device can be modeled as a second-order memristor and allow the implementation of critical synaptic functions realistically using simple spike forms based solely on spike activity.

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Source
http://dx.doi.org/10.1021/acs.nanolett.5b00697DOI Listing

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