Effect of Feedback Strength in Coupled Spiking Neural Networks

  • Javier Iglesias
  • Jordi García-Ojalvo
  • Alessandro E. P. Villa
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5164)

Abstract

We simulated the coupling of two large spiking neural networks (104 units each) composed by 80% of excitatory units and 20% of inhibitory units, randomly connected by projections featuring spike-timing dependent plasticity, locality preference and synaptic pruning. Only the first network received a complex spatiotemporal stimulus and projected on the second network, in a setup akin to coupled semiconductor lasers. In a series of simulations, the strength of the feedback from the second network to the first was modified to evaluate the effect of the bidirectional coupling on the firing dynamics of the two networks. We observed that, unexpectedly, the number of neurons which activity is altered by the introduction of feedback increases in the second network more than in the first network, suggesting a qualitative change in the dynamics of the first network when feedback is increased.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Meucci, R., di Garbo, A., Allaria, E., Arecchi, F.T.: Autonomous bursting in a homoclinic system. Phys. Rev. Lett. 88(14), 144101 (2002)CrossRefGoogle Scholar
  2. 2.
    González, C.M., Torrent, M.C., García-Ojalvo, J.: Controlling the leader-laggard dynamics in delay-synchronized lasers. Chaos 17 ( 33122 ), 1–8 (2007)Google Scholar
  3. 3.
    Fischer, I., van Tartwijk, G.H., Levine, A.M., Elsässer, W., Gbel, E., Lenstra, D.: Fast pulsing and chaotic itinerancy with a drift in the coherence collapse of semiconductor lasers. Physical Review Letters 76 ( 2 ), 220–223 (1996)CrossRefGoogle Scholar
  4. 4.
    Iglesias, J., Eriksson, J., Grize, F., Tomassini, M., Villa, A.E.: Dynamics of pruning in simulated large-scale spiking neural networks. BioSystems 79(1), 11–20 (2005)CrossRefGoogle Scholar
  5. 5.
    Choi, D.W.: Glutamate neurotoxicity and diseases of the nervous system. Neuron 1(8), 623–634 (1988)CrossRefGoogle Scholar
  6. 6.
    Iglesias, J., Villa, A.: Neuronal cell death and synaptic pruning driven by spike-timing dependent plasticity. In: Kollias, S.D., Stafylopatis, A., Duch, W., Oja, E. (eds.) ICANN 2006. LNCS, vol. 4131, pp. 953–962. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  7. 7.
    Iglesias, J., Eriksson, J., Pardo, B., Tomassini, M., Villa, A.E.: Emergence of oriented cell assemblies associated with spike-timing-dependent plasticity. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds.) ICANN 2005. LNCS, vol. 3696, pp. 127–132. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  8. 8.
    Montgomery, J.M., Madison, D.V.: Discrete synaptic states define a major mechanism of synapse plasticity. Trends in Neurosciences 27(12), 744–750 (2004)CrossRefGoogle Scholar
  9. 9.
    Hill, S., Villa, A.E.: Dynamic transitions in global network activity influenced by the balance of excitation and inhibtion. Network: computational neural networks 8, 165–184 (1997)CrossRefGoogle Scholar
  10. 10.
    Iglesias, J., Chibirova, O., Villa, A.E.: Nonlinear dynamics emerging in large scale neural networks with ontogenetic and epigenetic processes. In: de Sá, J.M., Alexandre, L.A., Duch, W., Mandic, D.P. (eds.) ICANN 2007. LNCS, vol. 4668, pp. 579–588. Springer, Heidelberg (2007)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Javier Iglesias
    • 1
    • 2
  • Jordi García-Ojalvo
    • 2
  • Alessandro E. P. Villa
    • 1
  1. 1.Grenoble Institut des Neurosciences-GIN, NeuroHeuristic Research GroupUniversité Joseph FourierGrenobleFrance
  2. 2.Departament de Física i Enginyeria NuclearUniversitat Politècnica de CatalunyaTerrassaSpain

Personalised recommendations