Skip to main content
Download PDF

Volume 16 Supplement 1

24th Annual Computational Neuroscience Meeting: CNS*2015

Computational modeling of heterosynaptic plasticity in the hippocampus

BMC Neuroscience volume 16, Article number: P1 (2015) Cite this article

Hippocampal long-term potentiation (LTP) and long-term depression (LTD) are central synaptic mechanisms of learning and memory. Here we use compartmental models of hippocampal granule cells to better understand LTP and heterosynaptic LTD which have been reported in the dentate gyrus of awake rats [1]. Our simulations indicate that LTP and heterosynaptic LTD can be explained by a spike-timing-dependent plasticity (STDP) rule combined with a fast Bienenstock-Cooper-Munro (BCM)-like metaplasticity rule [2–5]. We study the interaction between these plasticity rules and ongoing pre- and postsynaptic activity. Our models are able to account for the experimentally observed degree of LTP and heterosynaptic LTD induced by various plasticity-inducing protocols.

References

  1. Bowden JB, Abraham WC, Harris KM: Differential effects of strain, circadian cycle, and stimulation pattern on LTP and concurrent LTD in the dentate gyrus of freely moving rats. Hippocampus. 2012, 22 (6): 1363-1370.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Abraham WC: Metaplasticity: tuning synapses and networks for plasticity. Nat Rev Neurosci. 2008, 9 (5): 387-

    Article  PubMed  CAS  Google Scholar 

  3. Benuskova L, Abraham WC: STDP rule endowed with the BCM sliding threshold accounts for hippocampal heterosynaptic plasticity. J Comp Neurosci. 2007, 22 (2): 129-133.

    Article  Google Scholar 

  4. Abraham WC, Logan B, Wolff A, Benuskova L: "Heterosynaptic" LTD in the dentate gyrus of anesthetized rat requires homosynaptic activity. J Neurophysiol. 2007, 98 (2): 1048-1051.

    Article  PubMed  Google Scholar 

  5. Benuskova L, Jedlicka P: Computational modeling of long-term depression of synaptic weights: insights from STDP, metaplasticity and spontaneous activity. Neural Network World. 2012, 22 (2): 161-180.

    Article  Google Scholar 

Download references

Acknowledgements

The work was supported by a Young Investigators Grant (from the faculty of medicine Goethe-University to P.J.) and by a BMBF grant (Germany-USA Collaboration in Computational Neuroscience to P.J., No. 01GQ1203A).

Author information

Authors and Affiliations

  1. Institute of Clinical Neuroanatomy, Neuroscience Center, Goethe University Frankfurt, Frankfurt am Main, Germany

    Peter Jedlicka

  2. Department of Computer Science, University of Otago, Dunedin, New Zealand

    Lubica Benuskova

  3. Department of Psychology, University of Otago, Dunedin, New Zealand

    Wickliffe C Abraham

  4. Brain Health Research Centre, University of Otago, Dunedin, New Zealand

    Lubica Benuskova & Wickliffe C Abraham

Authors
  1. Peter Jedlicka
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lubica Benuskova
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wickliffe C Abraham
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Peter Jedlicka.

Rights and permissions

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Jedlicka, P., Benuskova, L. & Abraham, W.C. Computational modeling of heterosynaptic plasticity in the hippocampus. BMC Neurosci 16 (Suppl 1), P1 (2015). https://doi.org/10.1186/1471-2202-16-S1-P1

Download citation

  • Published:

  • DOI: https://doi.org/10.1186/1471-2202-16-S1-P1

Keywords

  • Animal Model
  • Computational Modeling
  • Granule Cell
  • Dentate Gyrus
  • Compartmental Model

BMC Neuroscience

ISSN: 1471-2202

Contact us