The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Activity-Dependent Synaptic Plasticity of a Chalcogenide Electronic Synapse for Neuromorphic Systems
Open accessAbstract
Nanoscale inorganic electronic synapses or synaptic devices, which are capable of emulating the functions of biological synapses of brain neuronal systems, are regarded as the basic building blocks for beyond-Von Neumann computing architecture, combining information storage and processing. Here, we demonstrate a Ag/AgInSbTe/Ag structure for chalcogenide memristor-based electronic synapses. The memristive characteristics with reproducible gradual resistance tuning are utilised to mimic the activity-dependent synaptic plasticity that serves as the basis of memory and learning. Bidirectional long-term Hebbian plasticity modulation is implemented by the coactivity of pre- and postsynaptic spikes, and the sign and degree are affected by assorted factors including the temporal difference, spike rate and voltage. Moreover, synaptic saturation is observed to be an adjustment of Hebbian rules to stabilise the growth of synaptic weights. Our results may contribute to the development of highly functional plastic electronic synapses and the further construction of next-generation parallel neuromorphic computing architecture.
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Cites
Nanoscale Memristor Device as Synapse in Neuromorphic Systems
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Memristive devices for computing
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Synaptic Plasticity and Memory: An Evaluation of the Hypothesis
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Synaptic plasticity: taming the beast
Abbott, L. F., & Nelson, S. B. (2000) · Nature Neuroscience · doi:10.1038/81453 · Cited by 2,263
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Spike Timing–Dependent Plasticity: A Hebbian Learning Rule
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‘Memristive’ switches enable ‘stateful’ logic operations via material implication
Borghetti, J., Snider, G. S., Kuekes, P. J., Yang, J. J., Stewart, D. R., & Williams, R. S. (2010) · Nature · doi:10.1038/nature08940 · Cited by 1,929
Short-term plasticity and long-term potentiation mimicked in single inorganic synapses
Ohno, T., Hasegawa, T., Tsuruoka, T., Terabe, K., Gimzewski, J. K., & Aono, M. (2011) · Nature Materials · doi:10.1038/nmat3054 · Cited by 1,793
Nanoelectronic programmable synapses based on phase change materials for brain-inspired computing
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Short-Term Memory to Long-Term Memory Transition in a Nanoscale Memristor
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Pattern classification by memristive crossbar circuits using ex situ and in situ training
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Ultrafast Synaptic Events in a Chalcogenide Memristor
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Self-citationFour-dimensional address topology for circuits with stacked multilayer crossbar arrays
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Cited by
A comprehensive review on emerging artificial neuromorphic devices
Zhu, J., Zhang, T., Yang, Y., & Huang, R. (2020) · Applied Physics Reviews · doi:10.1063/1.5118217 · Cited by 758
Short-Term Plasticity and Long-Term Potentiation in Artificial Biosynapses with Diffusive Dynamics
Kim, M.-K., & Lee, J.-S. (2018) · ACS Nano · doi:10.1021/acsnano.7b08331 · Cited by 294
Hardware Implementation of Neuromorphic Computing Using Large‐Scale Memristor Crossbar Arrays
Li, Y., & Ang, K.-W. (2021) · Advanced Intelligent Systems · doi:10.1002/aisy.202000137 · Cited by 220
Self-citationKim, G. S., Song, H., Lee, Y. K., Kim, J. H., Kim, W., Park, T. H., Kim, H. J., Min Kim, K., & Hwang, C. S. (2019) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.9b16499 · Cited by 64
Metadata
- Authors
- Li, Y., Zhong, Y., Zhang, J., Xu, L., Wang, Q., Sun, H., Tong, H., Cheng, X., & Miao, X.
- Venue
- Scientific Reports
- Published
- 2014-05-09
- Volume
- 4
- Issue
- 1
- Pages
- 4906-4906
- ISSN
- 2045-2322 (ISSN-L)
- OpenAlex
- W1996388323
- Cited by
- 344
- References
- 13
- FWCI
- 9.55
- Type
- journal article
- Language
- en
- Open access
- gold
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
