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fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Publisher: American Physical Society
Types: Article
Subjects: QA, TA, QC Physics

Classified by OpenAIRE into

arxiv: Quantitative Biology::Neurons and Cognition
The problem of how to reconstruct the parameters of a stochastic nonlinear dynamical system when these are time-varying is considered in the context of online decoding of physiological information from neuron signaling activity. To model the spiking of neurons, a set of FitzHugh-Nagumo (FHN) oscillators is used. It is assumed that only a fast dynamical variable can be detected for each neuron, and that the monitored signals are mixed by an unknown measurement matrix. The Bayesian framework introduced in Paper I (Phys. Rev. E 77, 06110500 (2008)) is applied both for reconstruction of the model parameters and elements of the measurement matrix, and for inference of the time-varying parameters in the non-stationary system. It is shown that the proposed approach is able to reconstruct unmeasured (hidden) slow variables of the FHN oscillators, to learn to model each individual neuron, and to track continuous, random and step-wise variations of the control parameter for each neuron in real time.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • [1] R. Mukkamala and R. J. Cohen, Am. J. Physiol.: Heart. Circ. Physiol. 281, H2714 (2001).
    • [2] S. Lu and K. H. Chon, IEEE Trans. on Sig. Proc. 51, 3020 (2003).
    • [3] A. B. Schwartz, X. T. Cui, D. J. Weber, and D. W. Moran, Neuron 52, 205 (2006).
    • [4] F. Lotte et al., Journal of Neural Engineering R1 (2007).
    • [5] S. Eyal and S. Akselrod, Meth. of Inform. in Medicine 39, 118 (2000).
    • [6] D. G. Luchinsky, V. N. Smelyanskiy, A. Duggento, and P. V. E. McClintock, “Inferential framework for nonstationary dynamics. Part I. Theory”, Phys. Rev. E 77, 061105 (2008).
    • [7] R. FitzHugh, Biophys. J. 1, 445 (1961).
    • [8] J. Nagumo, S. Animoto, and S. Yoshizawa, Proc. Inst. Radio Engineers 50, 2061 (1962).
    • [9] A. T. Winfree, The Geometry of Biological Time (Springer-Verlag, New York, 1980).
    • [10] J. Keener and J. Sneyd, Mathematical Physiology (Springer-Verlag, New York, ADDRESS, 1998).
    • [11] E. N. Best, Biophys. J. 27, 87 (1979).
    • [12] J. Rogers and A. McCulloch, IEEE Trans. Biomed. Eng. 41, 743 (1994).
    • [13] R. R. Aliev and A. V. Panfilov, Journal of Theoretical Biology 181, 33 (1996).
    • [14] P. Chen, SIAM J. Math. Anal. 23, 81 (1992).
    • [15] O. Berenfeld and S. Abboud, Med. Eng. and Phys. 18, 615 (1996).
    • [16] D. Bullock, P. Cisek, and S. Grossberg, Cereb. Cortex 8, 48 (1998).
    • [17] S. Rajasekar and M. Lakshmanan, J. Theor. Biol. 166, 275 (1994).
    • [18] R. Mannella, Intern. J. Mod. Phys. C 13, 1177 (2002).
    • [19] D. M. Bates and D. G. Watts, Nonlinear Regression and Its Applications (Wiley, New York, 1988).
    • [20] D. G. Luchinsky et al., Phys. Rev. E 72, 021905 (2005).
    • [21] V. V. Osipov, D. G. Luchinsky, V. N. Smelyanskiy, and D. A. Timucin, Proc. AIAA/ASME/SAE/ASEE Joint Propulsion Conf. and Exhibit, AIAA Conference Proceedings (AIAA, Cincinnati, OH, 2007), p. 5823.
    • [22] D. G. Luchinsky et al., Proc. AIAA Inf otech@Aerospace 2007 Conf. and Exhibit, AIAA Conference Proceedings (AIAA, Robnert Park, CA, 2007), p. 2829.
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