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Experimental demonstration of a second-order memristor and its ability to biorealistically implement synaptic plasticity.
Kim, Sungho; Du, Chao; Sheridan, Patrick; Ma, Wen; Choi, ShinHyun; Lu, Wei D.
Affiliation
  • Kim S; Department of Electrical Engineering and Computer Science, University of Michigan , Ann Arbor, Michigan 48109, United States.
Nano Lett ; 15(3): 2203-11, 2015 Mar 11.
Article in En | MEDLINE | ID: mdl-25710872
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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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Computer Storage Devices / Neural Networks, Computer / Synaptic Transmission / Biomimetic Materials / Memory / Neuronal Plasticity Type of study: Prognostic_studies Limits: Animals / Humans Language: En Journal: Nano Lett Year: 2015 Type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Computer Storage Devices / Neural Networks, Computer / Synaptic Transmission / Biomimetic Materials / Memory / Neuronal Plasticity Type of study: Prognostic_studies Limits: Animals / Humans Language: En Journal: Nano Lett Year: 2015 Type: Article Affiliation country: United States