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Dynamical Systems and Accurate Temporal Information Transmission in Neural Networks

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Advances in Cognitive Neurodynamics (II)

Abstract

We simulated the activity of hierarchically organized spiking neural networks characterized by an initial developmental phase featuring cell death followed by spike timing dependent synaptic plasticity in presence of background noise. Upstream networks receiving spatiotemporally organized external inputs projected to downstream networks disconnected from external inputs. The observation of precise firing sequences, formed by recurrent patterns of spikes intervals above chance levels, suggested the build-up of an unsupervised connectivity able to sustain and preserve temporal information processing.

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References

  1. Innocenti, G.M., Price, D.J.: Exuberance in the development of cortical networks. Nat. Rev. Neurosci. 6 (2005) 955–965.

    Article  CAS  PubMed  Google Scholar 

  2. Chechik, G., Meilijson, I., Ruppin, E.: Neuronal regulation: A mechanism for synaptic pruning during brain maturation. Neural. Comput. 11 (1999) 2061–2080.

    Article  CAS  PubMed  Google Scholar 

  3. Shatz, C.J.: Impulse activity and the patterning of connections during CNS development. Neuron 5 (1990) 745–756.

    Article  CAS  PubMed  Google Scholar 

  4. Roberts, P.D., Bell, C.C.: Spike timing dependent synaptic plasticity in biological systems. Biol. Cybern. 87 (2002) 392–403.

    Article  PubMed  Google Scholar 

  5. Abeles, M.: Corticonics: Neural Circuits of the Cerebral Cortex, 1st edn. New York, NY: Cambridge University Press (1991).

    Google Scholar 

  6. Villa, A.E.P.: Empirical evidence about temporal structure in multi-unit recordings. In Miller, R., ed.: Time and the Brain. Harwood Academic Publisher (2000) 1–51.

    Google Scholar 

  7. Segundo, J.P.: Nonlinear dynamics of point process systems and data. Int. J. Bifurcat. Chaos. 13 (2001) 2035–2116.

    Google Scholar 

  8. Tetko, I.V., Villa, A.E.P.: A pattern grouping algorithm for analysis of spatiotemporal patterns in neuronal spike trains. 1. detection of repeated patterns. J. Neurosci. Methods. 105 (2001) 1–14.

    Article  CAS  PubMed  Google Scholar 

  9. Asai, Y., Villa, A.E.P.: Reconstruction of underlying nonlinear deterministic dynamics embedded in noisy spike train. J. Biol. Phys. 34 (2008) 325–340.

    Article  PubMed  Google Scholar 

  10. Iglesias, J., Villa, A.: Emergence of preferred firing sequences in large spiking neural networks during simulated neuronal development. Int. J. Neural. Syst. 18 (2008) 267–277.

    Article  PubMed  Google Scholar 

  11. Chibirova, O.K., Iglesias, J., Shaposhnyk, V., Villa, A.E.P.: Dynamics of firing patterns in evolvable hierarchically organized neural networks. Lect. Notes. Comput. Sci. 5216 (2008) 296–307.

    Article  Google Scholar 

  12. Iglesias, J., Garcίa-Ojalvo, J., Villa, A.E.P.: Effect of feedback strength in coupled spiking neural networks. Lect. Notes. Comput. Sci. 5164 (2008) 646–654.

    Article  Google Scholar 

  13. Asai, Y., Guha, A., Villa, A.E.P.: Deterministic neural dynamics transmitted through neural networks. Neural. Netw. 21 (2008) 799–809.

    Article  PubMed  Google Scholar 

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Acknowledgments

The authors ackowledge the support by the EU FP6 grants #034632 PERPLEXUS and #043309 GABA.

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Correspondence to Alessandro E.P. Villa .

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© 2011 Springer Science+Business Media B.V.

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Villa, A.E. et al. (2011). Dynamical Systems and Accurate Temporal Information Transmission in Neural Networks. In: Wang, R., Gu, F. (eds) Advances in Cognitive Neurodynamics (II). Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9695-1_8

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