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Spiking Network Models and Theory: Overview

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Encyclopedia of Computational Neuroscience

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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  • 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)

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  • 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 plasticity

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Acknowledgments

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

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Authors and Affiliations

  1. Blue Brain Project, École Polytechnique Fédéral de Lausanne, Lausanne, 1015, Switzerland

    Marc-Oliver Gewaltig

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  1. Marc-Oliver Gewaltig
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Correspondence to Marc-Oliver Gewaltig .

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Editors and Affiliations

  1. Department of Biology, Emory University, Atlanta, GA, USA

    Dieter Jaeger

  2. Department of Biomedical Engineering, Florida International University, Miami, FL, USA

    Ranu Jung

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Gewaltig, MO. (2015). Spiking Network Models and Theory: Overview. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6675-8_792

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