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A Method for Quantifying Temporal and Spatial Patterns of Spike Trains

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Advances in Natural Computation (ICNC 2005)

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Abstract

Spike trains are treated as exact time dependent stepwise functions called response functions. Five variables defined at sequential moments with equal interval are introduced to characterize features of response function; and these features can reflect temporal patterns of spike train. These variables have obvious geometric meaning in expressing the response and reasonable coding meaning in describing spike train since the well known ’firing rate’ is among them. The dissimilarity or distance between spike trains can be simply defined by means of these variables. The reconstruction of spike train with these variables demonstrates that information carried by spikes is preserved. If spikes of neuron ensemble are taken as a spatial sequence in each time bins, spatial patterns of spikes can also be quantified with a group of variables similar to temporal ones.

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References

  1. Rieke, F., Warland, D., de Ruyter van Steveninck, R., Bialek, W.: Spike: Exploring the Neural Code. MIT Press, Cambridge (1997)

    Google Scholar 

  2. Fernndez, E., Ferrandez, J.M., Ammermler, J., Norman, R.A.: Population coding in spike trains of simultaneously recorded retinal ganglion cells. Brain Res. 887, 222–229 (2000)

    Article  Google Scholar 

  3. Nicolelis, M.A., Ribeiro, S.: Multielectrode recordings: the next steps. Curr. Opin. Neurobiol. 12, 602–606 (2002)

    Article  Google Scholar 

  4. Panzeri, S., Schultz, S.R., Trevez, A., Rolls, E.T.: Correlation and the encoding of information in the nervous system. Proc. R. Soc. Lond. B 266, 1001–1012 (1999)

    Article  Google Scholar 

  5. Kralik, J.D., Dimitrov, D.F., Krupa, D.J., Katz, D.B., Cohen, D., Nicolelis, M.A.: Techniques for long-term multisite neuronal ensemble recordings in behaving animals. Methods 25, 121–151 (2001)

    Article  Google Scholar 

  6. Meister, M., Berry II, M.J.: The neural code of the retina. Neuron 22, 435–450 (1999)

    Article  Google Scholar 

  7. Abbot, L., Sejnowsky, T.J.: Neural code and distributed representations. MIT Press, Cambridge (1998)

    Google Scholar 

  8. Funke, E., Worgtter, F.: On the significance of temporally structured activity in the dorsal lateral geniculate nucleus (LGN). Prog. Neurobiol. 53, 67–119 (1997)

    Article  Google Scholar 

  9. Hatsopoulosa, N., Gemanb, S., Amarasinghamb, A., Bienenstockb, E.: At what time scale does the nervous system operate? Neurocomputing 52, 25–29 (2003)

    Article  Google Scholar 

  10. Brody, C.: Slow covariations in neuronal resting potentials can lead to artefactually fast cross-correlations in the spike trains. J. Neurophysiol. 80, 3345–3351 (1998)

    Google Scholar 

  11. Brody, C.: Correlations without synchrony. Neural Comput. 11, 1553–1577 (1999)

    Article  Google Scholar 

  12. Oram, M.W., Hatsopoulos, N.G., Richmond, B.J., Donoghue, J.P.: Excess synchrony in motor cortical neurons provides direction information that is redundant with the information from coarse temporal response measures. J. Neurophysiol. 86, 1700–1716 (2001)

    Google Scholar 

  13. Usrey, M.W., Reid, C.R.: Synchronous activity in the visual system. Annu. Rev. Physiol. 61, 435–456 (1999)

    Article  Google Scholar 

  14. Ortega, G.J., Bongard, M., Louis, E., Fernndez, E.: Conditioned spikes: a simple and fast method to represent rates and temporal patterns in multielectrode recordings. Journal of Neuroscience Methods 133, 135–141 (2004)

    Article  Google Scholar 

  15. Gruner, C.M., Baggerly, K., Johnson, D.H., Seshagiri, C.: Information-theoretic analysis of neural coding. J. of Computational Neuroscience 10, 47–69 (2001)

    Article  Google Scholar 

  16. Panzeri, S., et al.: Coding of stimulus location by spike timing in rat somatosensory cortex. Neurocomputing 573, 44–46 (2002)

    Google Scholar 

  17. Dimitrov, A.G., et al.: Spike pattern-based coding schemes in the cricket cerecal sensory system. Neurocomputing 373, 44–46 (2002)

    Google Scholar 

  18. Romero, R., Lee, T.S.: Spike train analysis for single trial data. Neurocomputing 597, 44–46 (2002)

    Google Scholar 

  19. Lestienne, R.: Spike timing, synchronization and information processing on the sensory side of the central nervous system. Progress in Neurobiology 65, 545–591 (2001)

    Article  Google Scholar 

  20. Segundo, J.P.: Nonlinear dynamics of point process systems and data I. J. of Bifurcation and Chaos 13, 2035 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  21. Christen, M., et al.: Fast spike pattern detection using the correlation integral. Physical Review E 70, 11901 (2004)

    Article  MathSciNet  Google Scholar 

  22. Aronov, D., Victor, J.D.: Non-Euclidean properties of spike train metric spaces. Physical Review E 69, 061905 (2004)

    Article  MathSciNet  Google Scholar 

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© 2005 Springer-Verlag Berlin Heidelberg

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Wang, Sm., Lu, QS., Du, Y. (2005). A Method for Quantifying Temporal and Spatial Patterns of Spike Trains. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3610. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539087_62

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  • DOI: https://doi.org/10.1007/11539087_62

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28323-2

  • Online ISBN: 978-3-540-31853-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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