Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/103537
Title: Synaptic long-term potentiation realized in Pavlov's dog model based on a NiOx-based memristor
Authors: Hu, S. G.
Liu, Y.
Liu, Z.
Yu, Q.
Deng, L. J.
Yin, Y.
Chen, T. P.
Hosako, Sumio
Keywords: DRNTU::Science::Physics
Issue Date: 2014
Source: Hu, S. G., Liu, Y., Liu, Z., Chen, T. P., Yu, Q., Deng, L. J., et al. (2014). Synaptic long-term potentiation realized in Pavlov's dog model based on a NiOx-based memristor. Journal of applied physics, 116(21), 214502-.
Series/Report no.: Journal of applied physics
Abstract: Synaptic Long-Term Potentiation (LTP), which is a long-lasting enhancement in signal transmission between neurons, is widely considered as the major cellular mechanism during learning and memorization. In this work, a NiOx-based memristor is found to be able to emulate the synaptic LTP. Electrical conductance of the memristor is increased by electrical pulse stimulation and then spontaneously decays towards its initial state, which resembles the synaptic LTP. The lasting time of the LTP in the memristor can be estimated with the relaxation equation, which well describes the conductance decay behavior. The LTP effect of the memristor has a dependence on the stimulation parameters, including pulse height, width, interval, and number of pulses. An artificial network consisting of three neurons and two synapses is constructed to demonstrate the associative learning and LTP behavior in extinction of association in Pavlov's dog experiment.
URI: https://hdl.handle.net/10356/103537
http://hdl.handle.net/10220/24532
DOI: 10.1063/1.4902515
Rights: © 2014 AIP Publishing LLC. This paper was published in Journal of Applied Physics and is made available as an electronic reprint (preprint) with permission of AIP Publishing LLC. The paper can be found at the following official DOI: [http://dx.doi.org/10.1063/1.4902515].  One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.
Fulltext Permission: open
Fulltext Availability: With Fulltext
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