The DOI matches its Crossref record; 58 of the 58 references it cites were found in a registry or an index.
Hebbian learning and spiking neurons
Open accessAbstract
A correlation-based (``Hebbian'') learning rule at a spike level with millisecond resolution is formulated, mathematically analyzed, and compared with learning in a firing-rate description. The relative timing of presynaptic and postsynaptic spikes influences synaptic weights via an asymmetric ``learning window.'' A differential equation for the learning dynamics is derived under the assumption that the time scales of learning and neuronal spike dynamics can be separated. The differential equation is solved for a Poissonian neuron model with stochastic spike arrival. It is shown that correlations between input and output spikes tend to stabilize structure formation. With an appropriate choice of parameters, learning leads to an intrinsic normalization of the average weight and the output firing rate. Noise generates diffusion-like spreading of synaptic weights.
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Cites
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Deep learning in neural networks: an overview
Schmidhuber, J. (2015) · Neural Networks · doi:10.1016/j.neunet.2014.09.003 · Cited by 18,570
Competitive Hebbian learning through spike-timing-dependent synaptic plasticity
Song, S., Miller, K. D., & Abbott, L. F. (2000) · Nature Neuroscience · doi:10.1038/78829 · Cited by 2,729
Synaptic plasticity: taming the beast
Abbott, L. F., & Nelson, S. B. (2000) · Nature Neuroscience · doi:10.1038/81453 · Cited by 2,263
Neurophysiological and Computational Principles of Cortical Rhythms in Cognition
Wang, X.-J. (2010) · Physiological Reviews · doi:10.1152/physrev.00035.2008 · Cited by 1,939
The Spike-Timing Dependence of Plasticity
Feldman, D. E. (2012) · Neuron · doi:10.1016/j.neuron.2012.08.001 · Cited by 1,071
Metadata
- Authors
- Kempter, R., Gerstner, W., & van Hemmen, J. L.
- Venue
- Physical Review E
- Publisher
- American Physical Society (APS)
- Published
- 1999-04-01
- Volume
- 59
- Issue
- 4
- Pages
- 4498-4514
- ISSN
- 1063-651X (ISSN-L)
- 1095-3787
- OpenAlex
- W2123820663
- Cited by
- 664
- References
- 58
- FWCI
- 10.52
- Type
- journal article
- Language
- en
- Open access
- bronze
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
