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Computational modeling of heterosynaptic plasticity in the hippocampus

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 [25]. 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.

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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

Correspondence to Peter Jedlicka.

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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.

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Keywords

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