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Improvement of signal transmission through spike-timing-dependent plasticity in neural networks

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Abstract.

We explore the effects of spike-timing-dependent plasticity (STDP) on weak signal transmission in a noisy neural network. We first consider the network where an ensemble of independent neurons, which are subjected to a common weak signal, are connected in parallel to a single postsynaptic neuron via excitatory synapses. STDP can make the signal transmission more efficient, and this effect is more prominent when the presynaptic activities exhibit some correlations. We further consider a two-layer network where there are only couplings between two layers and find that postsynaptic neurons can fire synchronously under suitable conditions. Both the reliability and timing precision of neuronal firing in the output layer are remarkably improved with STDP. These results indicate that STDP can play crucial roles in information processing in nervous systems.

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Authors and Affiliations

  1. National Laboratory of Solid State Microstructure and Department of Physics, Nanjing University, 210093, Nanjing, P.R. China

    S. Wang, J. Xu, F. Liu & W. Wang

Authors
  1. S. Wang
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  2. J. Xu
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  3. F. Liu
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  4. W. Wang
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Corresponding author

Correspondence to F. Liu.

Additional information

Received: 23 March 2004, Published online: 12 July 2004

PACS:

87.18.Sn Neural networks - 87.17.Aa Theory and modeling; computer simulation

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Wang, S., Xu, J., Liu, F. et al. Improvement of signal transmission through spike-timing-dependent plasticity in neural networks. Eur. Phys. J. B 39, 351–356 (2004). https://doi.org/10.1140/epjb/e2004-00200-4

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  • DOI: https://doi.org/10.1140/epjb/e2004-00200-4

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