Literature DB >> 31980990

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

Akke Mats Houben1, Matthias S Keil2.   

Abstract

Hebbian plasticity means that if the firing of two neurons is correlated, then their connection is strengthened. Conversely, uncorrelated firing causes a decrease in synaptic strength. Spike-timing-dependent plasticity (STDP) represents one instantiation of Hebbian plasticity. Under STDP, synaptic changes depend on the relative timing of the pre- and post-synaptic firing. By inducing pre- and post-synaptic firing at different relative times the STDP curves of many neurons have been determined, and it has been found that there are different curves for different neuron types or synaptic sites. Biophysically, strengthening (long-term potentiation, LTP) or weakening (long-term depression, LTD) of glutamatergic synapses depends on the post-synaptic influx of calcium (Ca2+): weak influx leads to LTD, while strong, transient influx causes LTP. The voltage-dependent NMDA receptors are the main source of Ca2+ influx, but they will only open if a post-synaptic depolarisation coincides with pre-synaptic neurotransmitter release. Here we present a computational mechanism for Ca2+-dependent plasticity in which the interplay between the pre-synaptic neurotransmitter release and the post-synaptic membrane potential leads to distinct Ca2+ time-courses, which in turn lead to the change in synaptic strength. It is shown that the model complies with classic STDP results, as well as with results obtained with triplets of spikes. Furthermore, the model is capable of displaying different shapes of STDP curves, as observed in different experimental studies.

Entities:  

Keywords:  Calcium-dependent-plasticity; STDP; Synaptic plasticity

Mesh:

Substances:

Year:  2020        PMID: 31980990     DOI: 10.1007/s10827-019-00737-1

Source DB:  PubMed          Journal:  J Comput Neurosci        ISSN: 0929-5313            Impact factor:   1.621


  58 in total

1.  Competitive Hebbian learning through spike-timing-dependent synaptic plasticity.

Authors:  S Song; K D Miller; L F Abbott
Journal:  Nat Neurosci       Date:  2000-09       Impact factor: 24.884

2.  A model of spike-timing dependent plasticity: one or two coincidence detectors?

Authors:  Uma R Karmarkar; Dean V Buonomano
Journal:  J Neurophysiol       Date:  2002-07       Impact factor: 2.714

Review 3.  LTP and LTD: an embarrassment of riches.

Authors:  Robert C Malenka; Mark F Bear
Journal:  Neuron       Date:  2004-09-30       Impact factor: 17.173

4.  Selective induction of LTP and LTD by postsynaptic [Ca2+]i elevation.

Authors:  S N Yang; Y G Tang; R S Zucker
Journal:  J Neurophysiol       Date:  1999-02       Impact factor: 2.714

5.  Biophysical and phenomenological models of multiple spike interactions in spike-timing dependent plasticity.

Authors:  Mathilde Badoual; Quan Zou; Andrew P Davison; Michael Rudolph; Thierry Bal; Yves Frégnac; Alain Destexhe
Journal:  Int J Neural Syst       Date:  2006-04       Impact factor: 5.866

6.  Modular competition driven by NMDA receptor subtypes in spike-timing-dependent plasticity.

Authors:  Richard C Gerkin; Pak-Ming Lau; David W Nauen; Yu Tian Wang; Guo-Qiang Bi
Journal:  J Neurophysiol       Date:  2007-01-31       Impact factor: 2.714

7.  Spine Ca2+ signaling in spike-timing-dependent plasticity.

Authors:  Thomas Nevian; Bert Sakmann
Journal:  J Neurosci       Date:  2006-10-25       Impact factor: 6.167

8.  A model for synaptic development regulated by NMDA receptor subunit expression.

Authors:  Shigeru Kubota; Tatsuo Kitajima
Journal:  J Comput Neurosci       Date:  2007-05-22       Impact factor: 1.621

Review 9.  The spike-timing dependence of plasticity.

Authors:  Daniel E Feldman
Journal:  Neuron       Date:  2012-08-23       Impact factor: 17.173

10.  Diverse synaptic plasticity mechanisms orchestrated to form and retrieve memories in spiking neural networks.

Authors:  Friedemann Zenke; Everton J Agnes; Wulfram Gerstner
Journal:  Nat Commun       Date:  2015-04-21       Impact factor: 14.919

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