Associative memory in a network of ‘spiking’ neurons
By Wulfram Gerstner, J. van Hemmen. 1992
The Hopfield network provides a simple model of an associative memory in a neuronal structure. It is, however, based on highly artificial assumptions, especially the use of formal two-state neurons or graded-response neurons. The authors address the question of what happens if formal neurons are replaced by a model of ‘spiking’ neurons. They do so in two steps. First, they show how to include refractoriness and noise into a simple threshold model of neuronal spiking. The spike trains resulting from such a model reproduce the distribution of interspike intervals and gain functions found in real neurons. In a second step they connect the model neurons so as to form a large associative memory system. The spike transmission is described by a synaptic kernel which includes axonal delays, ‘Hebbian’ synaptic efficacies, and a realistic postsynaptic response. The collective behaviour of the system is predicted by a set of dynamical equations which are exact in the limit of a large and fully connected network that...
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- Filip Ponulak
- Andrzej J. Kasinski
- Moshe Abeles
- Yuval Aviel
- David Horn
- J. L. V. Hemmen
- Andreas Knoblauch
- Sergio Davies
Citations in the corpus
- Introduction to spiking neural networks: Information processing, learning and applications. (2011, methodology): “…maps (Ruf and Schmitt 1998, Choe and Introduction to spiking neural networks 417 Miikkulainen 2000, Sanchez-Montanes et al. 2002, Veredas et al. 2008) or formation of associative memories (Gerstner and van Hemmen 1992, Maass and Natschlaeger 1998, Sommer and Wennekers 2001, Zamani et al. 2010).”
- Modeling Synaptic Plasticity in Conjunction with the Timing of Pre- and Postsynaptic Action Potentials (2000, methodology): “Neural Computation 12, 385–405 (2000) c° 2000 Massachusetts Institute of Technology We are going to use a neuron model, the spike-response model, which is a generalization of the integrate-and- re model (Gerstner & van Hemmen, 1992; Gerstner, 1995; Kistler, Gerstner, & van Hemmen, 1997).”
- Memory Capacity of Balanced Networks (2005, background): “Gerstner ( Gerstner & van Hemmen, 1992 ) showed how the Hopfield model may be incorporated in a network of spiking neurons.”
- From Hebb Rules to Spike-Timing-Dependent Plasticity: A Personal Account (2010, unknown): “…2010 | Volume 2 | Article 151 | 1 SYNAPTIC NEUROSCIENCE OpiniOn Article published: 09 December 2010 doi: 10.3389/fnsyn.2010.00151 to translate Hopfield models into spiking networks where the intrinsic neuronal time scale would be clearly defined (Gerstner, 1991; Gerstner and van Hemmen, 1992).”