Skip to main content
SpringerLink
Log in

Anti-Hebbian Learning

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

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

Access this chapter

Log in via an institution

Institutional subscriptions

References

  • Bliss TVP, Collingridge GL (1993) A synaptic model of memory: long-term potentiation in the hippocampus. Nature 361:31–39

    Article  PubMed  CAS  Google Scholar 

  • Caporale N, Dan Y (2008) Spike timing-dependent plasticity: a Hebbian learning rule. Ann Rev Neurosci 31:25–46

    Article  PubMed  CAS  Google Scholar 

  • Carlson A (1990) Anti-Hebbian learning in a non-linear neural network. Biol Cybern 64:171–176

    Article  PubMed  CAS  Google Scholar 

  • Dudek SM, Bear MF (1992) Homosynaptic long-term depression in area CA1 of hippocampus and effects of N-Methyl-d-Aspartate receptor blockade. Proce Natl Acad Sci USA 89:4363–4367

    Article  CAS  Google Scholar 

  • Földiák P (1990) Forming sparse representations by local anti-Hebbian learning. Biol Cybern 64:165–170

    Article  PubMed  Google Scholar 

  • Frégnac Y (2003) Hebbian synaptic plasticity. In: Arbib MA (ed) The handbook of brain theory and neural networks, vol 2. MIT Press, Cambridge, MA, pp 515–522

    Google Scholar 

  • Girolami M, Fyfe C (1996) A temporal model of linear anti-Hebbian learning. Neural Process Lett 4:139–148

    Article  Google Scholar 

  • Hebb DO (1949) The organization of behavior: a neuropsychological theory. Wiley, New York

    Google Scholar 

  • Kullmann DM, Lamsa KP (2007) Long-term synaptic plasticity in hippocampal interneurons. Nat Rev Neurosci 8:687–699

    Article  PubMed  CAS  Google Scholar 

  • Nelson SB (2004) Hebb and anti-Hebb meet in the brainstem. Nat Neurosci 7:687–688

    Article  PubMed  CAS  Google Scholar 

  • Oja E (1982) A simplified neuron model as a principal component analyzer. J Math Biol 15:267–273

    Article  PubMed  CAS  Google Scholar 

  • Palmieri F, Zhu J, Chang C (1993) Anti-Hebbian learning in topologically constrained linear networks: A tutorial. IEEE Trans Neural Netw 4:748–761

    Article  PubMed  CAS  Google Scholar 

  • Schraudolph NN, Sejnowski TJ (1992) Competitive anti-Hebbian learning of invariants. In: Moody JE, Hanson SJ, Lippmann RP (eds) Advances in neural information processing systems. Morgan Kaufmann, San Mateo, pp 1017–1024

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA

    Yoonsuck Choe

Authors
  1. Yoonsuck Choe
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yoonsuck Choe .

Editor information

Editors and Affiliations

  1. Atlanta, Georgia, USA

    Dieter Jaeger

  2. Department of Biomedical Engineering, Florida International University, Miami, Florida, USA

    Ranu Jung

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Science+Business Media New York

About this entry

Cite this entry

Choe, Y. (2014). Anti-Hebbian Learning. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_675-1

Download citation

  • DOI: https://doi.org/10.1007/978-1-4614-7320-6_675-1

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, New York, NY

  • Online ISBN: 978-1-4614-7320-6

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

Publish with us

Policies and ethics

Search

Navigation