Skip to main content

Neuromorphic Technologies, Memristors

  • Living reference work entry
  • First Online:
Encyclopedia of Computational Neuroscience
  • 334 Accesses

Synonyms

Memristive hardware artificial neural networks

Definition

Like biological networks, hardware neuromorphic networks are built up of neurons and synapses. The emergence of memristors, innovative electronic components with plasticity properties similar to those of synapses, offers a new technological solution for building neuromorphic VLSI.

Detailed Description

The design of analog silicon neurons has now been mastered (Indiveri et al. 2011), lowering computational cost down to a picojoule per action potential. However, considering a ratio of 1,000 synapses to 1 neuron, as observed in biological networks, the bottleneck in designing large- to very large-scale networks is likely to be integrating synapses and related connectivity. Artificial synapses with synaptic plasticity require three computational elements: generation of synaptic current, storage of synaptic weight, and plasticity calculation. Memristors present the advantage of combining these three elements in a single...

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

References

  • Chua L (1971) Memristor: the missing circuit element. IEEE Trans Circuit Theor 18(5):507–519

    Article  Google Scholar 

  • Indiveri G, Linares-Barranco B, Hamilton TJ, van Schaik A, Etienne-Cummings R, Delbruck T, Liu S-C, Dudek P, Häfliger P, Renaud S, Schemmel J, Cauwenberghs G, Arthur J, Hynna K, Folowosele F, Saïghi S, Serrano-Gotarredona T, Wijekoon J, Wang Y, Boahen K (2011) Neuromorphic silicon neuron circuits. Front Neurosci 5:73

    PubMed Central  PubMed  Google Scholar 

  • Linares-Barranco B, Serrano-Gotarredona T, Camuñas-Mesa LA, Perez-Carrasco JA, Zamarreño-Ramos C, Masquelier T (2011) On spike-timing-dependent-plasticity, memristive devices, and building a self-learning visual xortex. Front Neurosci 5:26

    PubMed Central  PubMed  Google Scholar 

  • Strukov G, Snider D, Stewart D, Williams R (2008) The missing memristor found. Nature 453(7191):80–83

    Article  CAS  PubMed  Google Scholar 

Further Reading

  • Chang T, Yang Y, Lu W (2013) Building neuromorphic circuits with memristive devices. IEEE Circuits Syst Mag 13(2):56–73

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sylvain Saïghi .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Science+Business Media New York

About this entry

Cite this entry

Saïghi, S. (2014). Neuromorphic Technologies, Memristors. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_116-1

Download citation

  • DOI: https://doi.org/10.1007/978-1-4614-7320-6_116-1

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, New York, NY

  • Online ISBN: 978-1-4614-7320-6

  • eBook Packages: Living Reference Biomedicine and Life SciencesReference Module Biomedical and Life Sciences

Publish with us

Policies and ethics