Cited by 471Advanced Memory and Neural ComputingNeural Networks and ApplicationsNeural dynamics and brain function

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Memristor-based neural networks

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Thomas, Andy·2013·Journal of Physics D: Applied Physics

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Abstract

The synapse is a crucial element in biological neural networks, but a simple electronic equivalent has been absent. This complicates the development of hardware that imitates biological architectures in the nervous system. Now, the recent progress in the experimental realization of memristive devices has renewed interest in artificial neural networks. The resistance of a memristive system depends on its past states and exactly this functionality can be used to mimic the synaptic connections in a (human) brain. After a short introduction to memristors, we present and explain the relevant mechanisms in a biological neural network, such as long-term potentiation and spike time-dependent plasticity, and determine the minimal requirements for an artificial neural network. We review the implementations of these processes using basic electric circuits and more complex mechanisms that either imitate biological systems or could act as a model system for them.

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A quantitative description of membrane current and its application to conduction and excitation in nerve
Hodgkin, A. L., & Huxley, A. F. (1952) · The Journal of Physiology · doi:10.1113/jphysiol.1952.sp004764 · Cited by 23,191
The missing memristor found
Strukov, D. B., Snider, G. S., Stewart, D. R., & Williams, R. S. (2008) · Nature · doi:10.1038/nature06932 · Cited by 11,828
A synaptic model of memory: long-term potentiation in the hippocampus
Bliss, T. V. P., & Collingridge, G. L. (1993) · Nature · doi:10.1038/361031a0 · Cited by 11,566
Memristor—The Missing Circuit Element
Chua, L. (1971) · IEEE Transactions on Circuit Theory · doi:10.1109/tct.1971.1083337 · Cited by 10,268 · cited 2×
“If we follow Chua’s original line of argumentation in his seminal paper in which he introduced the memristor, we ﬁnd the following concept [1].”
BackgroundInfluential
The Organization of Behavior
Hebb, D. O. (2005) · doi:10.4324/9781410612403 · Cited by 9,825
Long‐lasting potentiation of synaptic transmission in the dentate area of the unanaesthetized rabbit following stimulation of the perforant path
Bliss, T. V. P., & Gardner-Medwin, A. R. (1973) · The Journal of Physiology · doi:10.1113/jphysiol.1973.sp010274 · Cited by 7,424
The organization of behavior.
indicated, N. A. (1950) · Journal of Consulting Psychology · doi:10.1037/h0049612 · Cited by 6,984
The Organization of Behavior; A Neuropsychological Theory.
Attneave, F., B., M., & Hebb, D. O. (1950) · The American Journal of Psychology · doi:10.2307/1418888 · Cited by 5,146
Nanoionics-based resistive switching memories
Waser, R., & Aono, M. (2007) · Nature Materials · doi:10.1038/nmat2023 · Cited by 4,923
Synaptic Modifications in Cultured Hippocampal Neurons: Dependence on Spike Timing, Synaptic Strength, and Postsynaptic Cell Type
Bi, G.-Q., & Poo, M.-M. (1998) · The Journal of Neuroscience · doi:10.1523/jneurosci.18-24-10464.1998 · Cited by 4,744

Show all 141 references

Research works printed but not linked: 9

Snider G S, 2007, Nanotechnology, 18
Yang J J, 2009, Nanotechnology, 20
Biolek Z, 2009, Radioengineering, 18, 210
Bliss T V P, 1973, J. Physiol., 232, 331, 10.1113/jphysiol.1973.sp010273 · DOI · Paper page
Lapicque L, 1907, J. Physiol. Pathol. Gen., 9, 620
Lapicque L, 1926, L'excitabilit en fonction du temps
Erokhin V, 2010, Int. J. Unconv. Comput., 6, 15
Steels L Babloyantz Sepulchre J A, 1991, Proc. Int. Conf. on Artificial Neural Networks
Lindsten J, 1998, Nobel Lectures in Physiology or Medicine 1971–80

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Authors: Thomas, A.
Affiliations: Universität Hamburg (DE)
Corresponding author: Thomas, Andy
ORCID: Thomas, Andy
Venue: Journal of Physics D: Applied Physics
Publisher: IOP Publishing
Published: 2013-02-05
Volume: 46
Issue: 9
Pages: 093001
ISSN: 0022-3727 (ISSN-L)
1361-6463
DOI: 10.1088/0022-3727/46/9/093001
OpenAlex: W2159543793
Cited by: 471
References: 141
Citations by year: 2026: 10 · 2025: 41 · 2024: 50 · 2023: 51 · 2022: 40 · 2021: 43 · 2020: 32 · 2019: 37 · 2018: 42 · 2017: 31 · 2016: 31 · 2015: 26 · 2014: 22 · 2013: 13
FWCI: 18.40
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: iopscience.iop.org/info/page/text-and-data-mining (tdm)
iopscience.iop.org/page/copyright (vor)
Locations: Journal of Physics D Applied Physics (publishedVersion)
PUB – Publications at Bielefeld University (Bielefeld University) (submittedVersion)
Publikationen an der Universität Bielefeld (Universität Bielefeld) (submittedVersion)
Topics: Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Memory and Neural Computing
Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Applications
Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
Keywords: memristors, artificial neural networks, synaptic plasticity, long-term potentiation, spike-timing-dependent plasticity, neuromorphic hardware, electronic synapses, biological neural networks, electric circuit model

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