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Learning and retrieval behavior in recurrent neural networks with pre-synaptic dependent homeostatic plasticity

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  • Mizusaki, Beatriz E.P.
  • Agnes, Everton J.
  • Erichsen, Rubem
  • Brunnet, Leonardo G.

Abstract

The plastic character of brain synapses is considered to be one of the foundations for the formation of memories. There are numerous kinds of such phenomenon currently described in the literature, but their role in the development of information pathways in neural networks with recurrent architectures is still not completely clear. In this paper we study the role of an activity-based process, called pre-synaptic dependent homeostatic scaling, in the organization of networks that yield precise-timed spiking patterns. It encodes spatio-temporal information in the synaptic weights as it associates a learned input with a specific response. We introduce a correlation measure to evaluate the precision of the spiking patterns and explore the effects of different inhibitory interactions and learning parameters. We find that large learning periods are important in order to improve the network learning capacity and discuss this ability in the presence of distinct inhibitory currents.

Suggested Citation

  • Mizusaki, Beatriz E.P. & Agnes, Everton J. & Erichsen, Rubem & Brunnet, Leonardo G., 2017. "Learning and retrieval behavior in recurrent neural networks with pre-synaptic dependent homeostatic plasticity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 279-286.
    • Handle: RePEc:eee:phsmap:v:479:y:2017:i:c:p:279-286
    DOI: 10.1016/j.physa.2017.02.035
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    References listed on IDEAS

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    1. Gina G. Turrigiano & Kenneth R. Leslie & Niraj S. Desai & Lana C. Rutherford & Sacha B. Nelson, 1998. "Activity-dependent scaling of quantal amplitude in neocortical neurons," Nature, Nature, vol. 391(6670), pages 892-896, February.
    2. Michael London & Arnd Roth & Lisa Beeren & Michael Häusser & Peter E. Latham, 2010. "Sensitivity to perturbations in vivo implies high noise and suggests rate coding in cortex," Nature, Nature, vol. 466(7302), pages 123-127, July.
    3. Ashok Litwin-Kumar & Brent Doiron, 2014. "Formation and maintenance of neuronal assemblies through synaptic plasticity," Nature Communications, Nature, vol. 5(1), pages 1-12, December.
    4. Markus Diesmann & Marc-Oliver Gewaltig & Ad Aertsen, 1999. "Stable propagation of synchronous spiking in cortical neural networks," Nature, Nature, vol. 402(6761), pages 529-533, December.
    5. Agnes, Everton J. & Erichsen, Rubem & Brunnet, Leonardo G., 2012. "Model architecture for associative memory in a neural network of spiking neurons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 843-848.
    6. Michael Wehr & Anthony M. Zador, 2003. "Balanced inhibition underlies tuning and sharpens spike timing in auditory cortex," Nature, Nature, vol. 426(6965), pages 442-446, November.
    7. Friedemann Zenke & Everton J. Agnes & Wulfram Gerstner, 2015. "Diverse synaptic plasticity mechanisms orchestrated to form and retrieve memories in spiking neural networks," Nature Communications, Nature, vol. 6(1), pages 1-13, November.
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