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Modeling of Short-Term Synaptic Plasticity Using Dynamic Synapses

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Advances in Natural Computation (ICNC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3610))

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Abstract

This work presents a model of minimal time-continuous target-cell specific use-dependent short-term synaptic plasticity (STP) observed in the pyramidal cells that can account for both short-term depression and facilitation. In general it provides a concise and portable description that is useful for predicting synaptic responses to more complex patterns of simulation, for studies relating to circuit dynamics and for equating dynamic properties across different synaptic pathways between or within preparations. This model allows computation of postsynaptic responses by either facilitation or depression in the synapse thus exhibiting characteristics of dynamic synapses as that found during short-term synaptic plasticity, for any arbitrary pre-synaptic spike train in the presence of realistic background synaptic noise. Thus it allows us to see specific effect of the spike train on a neuronal lattice both small-scale and large-scale, so as to reveal the short-term plastic behavior in neurons.

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© 2005 Springer-Verlag Berlin Heidelberg

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Sengupta, B. (2005). Modeling of Short-Term Synaptic Plasticity Using Dynamic Synapses. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3610. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539087_55

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  • DOI: https://doi.org/10.1007/11539087_55

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28323-2

  • Online ISBN: 978-3-540-31853-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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