article

Relating STDP to BCM

Authors:

Eugene M. Izhikevich,

Niraj S. DesaiAuthors Info & Claims

Neural Computation, Volume 15, Issue 7

Pages 1511 - 1523

https://doi.org/10.1162/089976603321891783

Published: 01 July 2003 Publication History

Abstract

We demonstrate that the BCM learning rule follows directly from STDP when pre- and postsynaptic neurons fire uncorrelated or weakly correlated Poisson spike trains, and only nearest-neighbor spike interactions are taken into account.

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Cited By

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Huang CLin C(2023)New biophysical rate-based modeling of long-term plasticity in mean-field neuronal population modelsComputers in Biology and Medicine10.1016/j.compbiomed.2023.107213163:COnline publication date: 1-Sep-2023
https://dl.acm.org/doi/10.1016/j.compbiomed.2023.107213
Albesa-González AFroc MWilliamson ORossum M(2022)Weight dependence in BCM leads to adjustable synaptic competitionJournal of Computational Neuroscience10.1007/s10827-022-00824-w50:4(431-444)Online publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1007/s10827-022-00824-w
Sohn WSanger T(2021)Constraint-induced intervention as an emergent phenomenon from synaptic competition in biological systemsJournal of Computational Neuroscience10.1007/s10827-021-00782-949:2(175-188)Online publication date: 1-May-2021
https://dl.acm.org/doi/10.1007/s10827-021-00782-9
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Index Terms

Relating STDP to BCM
1. Computer systems organization
  1. Architectures
    1. Other architectures
      1. Neural networks
2. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
      1. Neural networks

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Published In

Neural Computation Volume 15, Issue 7

July 2003

271 pages

ISSN:0899-7667

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Publisher

MIT Press

Cambridge, MA, United States

Publication History

Published: 01 July 2003

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Huang CLin C(2023)New biophysical rate-based modeling of long-term plasticity in mean-field neuronal population modelsComputers in Biology and Medicine10.1016/j.compbiomed.2023.107213163:COnline publication date: 1-Sep-2023
https://dl.acm.org/doi/10.1016/j.compbiomed.2023.107213
Albesa-González AFroc MWilliamson ORossum M(2022)Weight dependence in BCM leads to adjustable synaptic competitionJournal of Computational Neuroscience10.1007/s10827-022-00824-w50:4(431-444)Online publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1007/s10827-022-00824-w
Sohn WSanger T(2021)Constraint-induced intervention as an emergent phenomenon from synaptic competition in biological systemsJournal of Computational Neuroscience10.1007/s10827-021-00782-949:2(175-188)Online publication date: 1-May-2021
https://dl.acm.org/doi/10.1007/s10827-021-00782-9
Karbowski J(2021)Energetics of stochastic BCM type synaptic plasticity and storing of accurate informationJournal of Computational Neuroscience10.1007/s10827-020-00775-049:2(71-106)Online publication date: 1-May-2021
https://dl.acm.org/doi/10.1007/s10827-020-00775-0
Qiu HGarratt MHoward DAnavatti SCoello Coello C(2020)Towards crossing the reality gap with evolved plastic neurocontrollersProceedings of the 2020 Genetic and Evolutionary Computation Conference10.1145/3377930.3389843(130-138)Online publication date: 25-Jun-2020
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Tomko MJedlička PBeňušková L(2020)Meta-STDP Rule Stabilizes Synaptic Weights Under in Vivo-like Ongoing Spontaneous Activity in a Computational Model of CA1 Pyramidal CellArtificial Neural Networks and Machine Learning – ICANN 202010.1007/978-3-030-61616-8_54(670-680)Online publication date: 15-Sep-2020
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Sboev ARybka RSerenko A(2017)On the effect of stabilizing mean firing rate of a neuron due to STDPProcedia Computer Science10.1016/j.procs.2017.11.173119:C(166-173)Online publication date: 1-Dec-2017
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Robinson BBerger TSong D(2016)Identification of stable spike-timing-dependent plasticity from spiking activity with generalized multilinear modelingNeural Computation10.1162/NECO_a_0088328:11(2320-2351)Online publication date: 1-Nov-2016
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Shi QHan FWang ZLi C(2016)Rhythmic Oscillations of Excitatory Bursting Hodkin-Huxley Neuronal Network with Synaptic LearningComputational Intelligence and Neuroscience10.1155/2016/60235472016(9)Online publication date: 1-Mar-2016
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Krunglevicius D(2016)Modified STDP Triplet Rule Significantly Increases Neuron Training Stability in the Learning of Spatial PatternsAdvances in Artificial Neural Systems10.1155/2016/17465142016(1)Online publication date: 1-Aug-2016
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Show More Cited By

Abstract

References

Cited By

Index Terms

Recommendations

Reconciling the stdp and bcm models of synaptic plasticity in a spiking recurrent neural network

A calcium-influx-dependent plasticity model exhibiting multiple STDP curves

GABA inhibition modulates NMDA-R mediated spike timing dependent plasticity (STDP) in a biophysical model

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