Journal of Computational Neuroscience

, Volume 22, Issue 2, pp 129–133 | Cite as

STDP rule endowed with the BCM sliding threshold accounts for hippocampal heterosynaptic plasticity

BRIEF COMMUNICATION

Abstract

We have combined the nearest neighbour additive spike-timing-dependent plasticity (STDP) rule with the Bienenstock, Cooper and Munro (BCM) sliding modification threshold in a computational model of heterosynaptic plasticity in the hippocampal dentate gyrus. As a result we can reproduce (1) homosynaptic long-term potentiation of the tetanized input, and (2) heterosynaptic long-term depression of the untetanized input, as observed in real experiments.

Keywords

Heterosynaptic plasticity Metaplasticity STDP Sliding BCM threshold 

References

  1. Abarbanel HDI, Huerta R, Rabinovich MI (2002) Dynamical model of long-term synaptic plasticity. Proc. Natl. Acad. Sci. USA 99(15): 10132–10137.PubMedCrossRefGoogle Scholar
  2. Abraham WC, Bear MF (1996) Metaplasticity: The plasticity of synaptic plasticity. Trends Neurosci. 19(4): 126–130.PubMedCrossRefGoogle Scholar
  3. Abraham WC, Mason-Parker SE, Bear MF, Webb S, Tate WP (2001) Heterosynaptic metaplasticity in the hippocampus in vivo: A BCM-like modifiable threshold for LTP. Proc. Natl. Acad. Sci. USA 98(19): 10924–10929.PubMedCrossRefGoogle Scholar
  4. Benuskova L, Rema V, Armstrong-James M, Ebner FF (2001) Theory for normal and impaired experience-dependent plasticity in neocortex of adult rats. Proc. Natl. Acad. Sci. USA 98(5): 2797–2802.PubMedCrossRefGoogle Scholar
  5. Bi G-q, Poo M-m (2001) Synaptic modification by correlated activity: Hebb's postulate revisited. Annu. Rev. Neurosci. 24: 139–166.PubMedCrossRefGoogle Scholar
  6. Castellani GC, Quinlan EM, Cooper LN, Shouval HZ (2001) A biophysical model of bidirectional synaptic plasticity: dependence on AMPA and NMDA receptors. Proc. Natl. Acad. Sci. USA 98(22): 12772–12777.PubMedCrossRefGoogle Scholar
  7. Delorme A, Perrinet L, Thorpe SJ (2001) Network of integrate-and-fire neurons using rank order coding B: Spike timing dependent plasticity and emergence of orientation selectivity. Neurocomputing 38(40): 539–545.CrossRefGoogle Scholar
  8. Frank LM, Brown EN, Wilson MA (2001) A comparison of the firing properties of putative excitatory and inhibitory neurons from CA1 and the entorhinal cortex. J. Neurophysiol. 86(4): 2029–2049.PubMedGoogle Scholar
  9. Froemke RC, Poo M-m, Dang Y (2005) Spike-timing-dependent synaptic plasticity depends on dendritic location. Nature 434: 221–225.PubMedCrossRefGoogle Scholar
  10. Gloveli T, Schmitz D, Empson RM, Heineman U (1997) Frequency-dependent information flow from the entorhinal cortex to the hippocampus. J. Neurophysiol. 78: 3444–3449.PubMedGoogle Scholar
  11. Izhikevich EM (2003) Simple model of spiking neurons. IEEE Trans. Neural Netw. 14(6): 1569–1572.CrossRefGoogle Scholar
  12. Izhikevich EM, Desai NS (2003) Relating STDP to BCM. Neural Comput. 15: 1511–1523.PubMedCrossRefGoogle Scholar
  13. Karmarkar UR, Buonomano DV (2002) A model of spike-timing dependent plasticity: One or two coincidence detectors. J. Neurophysiol. 88: 507–513.PubMedGoogle Scholar
  14. Kimura A, Pavlides C (2000) Long-term potentiation/depotentiation are accompanied by complex changes in spontaneous unit activity in the hippocampus. J. Neurophysiol. 84: 1894–1906.PubMedGoogle Scholar
  15. McNaughton BL, Barnes CA, Andersen P (1981) Synaptic efficacy and EPSP summation in granule cells of rat fascia dentata studied in vitro. J. Neurophysiol. 46(5): 952–966.PubMedGoogle Scholar
  16. Shouval HZ, Bear MF, Cooper LN (2002a) A unified model of NMDA receptor-dependent bidirectional synaptic plasticity. Proc. Natl. Acad. Sci. USA 99(16): 10831–10836.PubMedCrossRefGoogle Scholar
  17. Shouval HZ, Castellani GC, Blais BS, Yeung LC, Cooper LN (2002b) Converging evidence for a simplified biophysical model of synaptic plasticity. Biol. Cybern. 87: 383–391.PubMedCrossRefGoogle Scholar
  18. Tamura H, Tsumoto T, Hata Y (1992) Activity-dependent potentiation and depression of visual cortical responses to optic nerve stimulation in kittens. J. Neurophysiol. 68(5): 1603–1612.PubMedGoogle Scholar
  19. Yeung L-C, Shouval HZ, Blais BS, Cooper LN (2004) Synaptic homeostasis and input selectivity follow from a calcium-dependent plasticity model. Proc. Natl. Acad. Sci. USA 101(41): 14943–14948.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2006

Authors and Affiliations

  1. 1.Knowledge Engineering & Discovery Research InstituteAuckland University of TechnologyAucklandNew Zealand
  2. 2.Department of Applied Informatics, Faculty of Mathematics, Physics and InformaticsComenius UniversityBratislavaSlovakia
  3. 3.Department of PsychologyUniversity of OtagoDunedinNew Zealand

Personalised recommendations