Encyclopedia of Computational Neuroscience

2015 Edition
| Editors: Dieter Jaeger, Ranu Jung

Spiking Network Models and Theory: Overview

Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-6675-8_792

Definition

Spiking neuronal networks are a type of neural network model where the neurons interact by sending and receiving the so-called spikes, short pulses that are only defined by their time of occurrence. Biologically, spikes correspond to the action potentials of neurons.

Neuron models that produce spikes are called spiking neuron models. Examples are the  Integrate and Fire Models, Deterministic; the Izhikevich model; and the  Hodgkin-Huxley Model.

The term spiking network was introduced to distinguish these models from formal neuron models which have graded activation functions.

Detailed Description

Historical Background

The first spiking neuron models were developed at the beginning of the twentieth century and focused on explaining the electrical behavior of isolated neurons. In 1907, Louis Lapicque proposed an electrical circuit model to describe the change in membrane potential after applying a current step. He assumed a fixed firing threshold to explain the occurrence of...

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Notes

Acknowledgments

This work was supported by the Blue Brain Project and EU grant FP7-269921 (BrainScaleS).

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Further Reading

  1. A thorough introduction to the theory of spiking networks can be found in the somewhat dated but still highly valuable textbooks Introduction to theoretical neurobiology by Tuckwell (1988). An equally thorough and more recent reference is the book Spiking neuron models: Single neurons, populations, plasticity by Gerstner and Kistler (2002) which also contains extensive treatment of learning and plasticity in spiking networks. A broader overview is given in the textbook Theoretical Neuroscience by Dayan and Abbot (2001)Google Scholar
  2. Burkitt AN (2006) A review of the integrate-and-fire neuron model: I. Homogeneous synaptic input. Biol Cybern 95(1):1–19PubMedGoogle Scholar
  3. Burkitt AN (2006) A review of the integrate-and-fire neuron model: II. Inhomogeneous synaptic input and network properties. Biol Cybern 95(2):97–112PubMedGoogle Scholar
  4. Burkitt (2006a, b) has written a set of comprehensive reviews of the integrate and fire neuron. The dynamic properties of spiking networks have been reviewed by Vogels et al. (2005)Google Scholar
  5. Dayan P, Abbot LF (2001) Theoretical neuroscience: computational and mathematical modeling of neural systems. MIT Press, Cambridge, MAGoogle Scholar
  6. Feldman (2012) provides an extensive review of spike-timing-dependent plasticity, with possible underlying synaptic and cellular mechanisms, as well as its potential role in learning. The reviews of Morrison et al. (2008) and Sjöström and Gerstner (2010) give good overview over theoretical models of spike-timing-dependent plasticityGoogle Scholar
  7. Vogels TP, Rajan K, Abbot LF (2005) Neural network dynamics. Annu Rev Neurosci 28:357–376PubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Blue Brain ProjectÉcole Polytechnique Fédéral de LausanneLausanneSwitzerland