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Quadratic sinusoidal analysis of voltage clamped neurons

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Abstract

Nonlinear biophysical properties of individual neurons are known to play a major role in the nervous system, especially those active at subthreshold membrane potentials that integrate synaptic inputs during action potential initiation. Previous electrophysiological studies have made use of a piecewise linear characterization of voltage clamped neurons, which consists of a sequence of linear admittances computed at different voltage levels. In this paper, a fundamentally new theory is developed in two stages. First, analytical equations are derived for a multi-sinusoidal voltage clamp of a Hodgkin–Huxley type model to reveal the quadratic response at the ionic channel level. Second, the resulting behavior is generalized to a novel Hermitian neural operator, which uses an algebraic formulation capturing the entire quadratic behavior of a voltage clamped neuron. In addition, this operator can also be used for a nonlinear identification analysis directly applicable to experimental measurements. In this case, a Hermitian matrix of interactions is built with paired frequency probing measurements performed at specific harmonic and interactive output frequencies. More importantly, eigenanalysis of the neural operator provides a concise signature of the voltage dependent conductances determined by their particular distribution on the dendritic and somatic membrane regions of neurons. Finally, the theory is concretely illustrated by an analysis of an experimentally measured vestibular neuron, providing a remarkably compact description of the quadratic responses involved in the nonlinear processing underlying the control of eye position during head rotation, namely the neural integrator.

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References

  • Ahrens, M. B., Linden, J. F., & Sahani, M. (2008). Nonlinearities and contextual influences in auditory cortical responses modeled with multilinear spectrotemporal methods. The Journal of Neuroscience, 28(8), 1929–1942.

    Article  PubMed  CAS  Google Scholar 

  • Aksay, E., Olasagasti, I., Mensh, B. D., Baker, R., Goldman, M. S., & Tank, D. W. (2007). Functional dissection of circuitry in a neural integrator. Nature Neuroscience, 10, 494–504.

    Article  PubMed  CAS  Google Scholar 

  • Bedrosian, E., & Rice, S. O. (1972). Applications of Volterra—System analysis. Report, Rand Corp., Santa Monica, CA.

  • Blackadar, B. (2009). Operator algebras. New York: Springer.

    Google Scholar 

  • Boyd, S., Tang, Y., & Chua, L. (1983). Measuring volterra kernels. IEEE Transactions on Circuits and Systems, 30(8), 571–577.

    Article  Google Scholar 

  • Erdmann, K. (2007). Introduction to lie algebras. New York: Springer.

    Google Scholar 

  • Fishman, H. M., Poussart, D. J., Moore, L. E., & Siebenga, E. (1977). K+ conduction description from the low frequency impedance and admittance of squid axon. Journal of Membrane Biology, 32(3–4), 255–290.

    PubMed  CAS  Google Scholar 

  • FitzHugh, R. (1983). Sinusoidal voltage clamp of the hodgkin-huxley model. Biophysics Journal, 42(1), 11–16.

    Article  CAS  Google Scholar 

  • French, A. S. (1976). Practical nonlinear system analysis by Wiener kernel estimation in the frequency domain. Biological Cybernetics, 24, 111–119.

    Article  Google Scholar 

  • Goldman, M. S., Levine, J. H., Major, G., Tank, D. W., & Seung, H. S. (2003). Robust persistent neural activity in a model integrator with multiple hysteretic dendrites per neuron. Cerebral Cortex, 13, 1185–1195.

    Article  PubMed  Google Scholar 

  • Hodgkin, A. L., & Huxley, A. F. (1952). A quantitative description of membrane current and its application to conduction and excitation in nerve. Journal of Physiology, 117(4), 500–544.

    PubMed  CAS  Google Scholar 

  • Idoux, E., Serafin, M., Fort, P., Vidal, P. P., Beraneck, M., Vibert, N., et al. (2006). Oscillatory and intrinsic membrane properties of guinea pig nucleus prepositus hypoglossi neurons in vitro. Journal of Neurophysiology, 96, 175–196.

    Article  PubMed  Google Scholar 

  • Idoux, E., Eugene, D., Chambaz, A., Magnani, C., White, J. A., & Moore, L. E. (2008). Control of neuronal persistent activity by voltage-dependent dendritic properties. Journal of Neurophysiology, 100(3), 1278–1286.

    Article  PubMed  Google Scholar 

  • Korenberg, M. J., Bruder, S. B., & Mcllroy, P. J. (1988). Exact orthogonal kernel estimation from finite data records: Extending Wiener’s identification of nonlinear systems. Annals of Biomedical Engineering, 16, 201–214.

    Article  PubMed  CAS  Google Scholar 

  • Koulakov, A. A., Raghavachari, S., Kepecs, A., & Lisman, J. E. (2002). Model for a robust neural integrator. Nature Neuroscience, 5, 775–782.

    Article  PubMed  CAS  Google Scholar 

  • Lang, S. (2002). Algebra. New York: Springer.

    Book  Google Scholar 

  • Mallat, S. (2008). A wavelet tour of signal processing. New York: Academic.

    Google Scholar 

  • Manin, Y. (2005) Introduction to modern number theory. New York: Springer.

    Google Scholar 

  • Marmarelis, P. Z., & Naka, K. I. (1973). Nonlinear analysis and synthesis of receptive-field responses in the catfish retina. I. Horizontal cell leads to ganglion cell chain. Journal of Neurophysiology, 36(4), 605–618.

    PubMed  CAS  Google Scholar 

  • Mauro, A., Conti, F., Dodge, F., & Schor, R. (1970). Subthreshold behavior and phenomenological impedance of the squid giant axon. The Journal of General Physiology, 55(4), 497–523.

    Article  PubMed  CAS  Google Scholar 

  • Moore, L. E., Fishman, H. M., & Poussart, D. J. (1980). Small-signal analysis of K+ conduction in squid axons. Journal of Membrane Biology, 54(2), 157–164.

    Article  PubMed  CAS  Google Scholar 

  • Murphey, C. R., Moore, L. E., & Buchanan, J. T. (1995). Quantitative analysis of electrotonic structure and membrane properties of nmda-activated lamprey spinal neurons. Neural Computation, 7(3), 486–506.

    Article  PubMed  CAS  Google Scholar 

  • Poggio, T., & Torre, V. (1977). A Volterra representation for some neuron models. Biological Cybernetics, 27, 113–124.

    Article  PubMed  CAS  Google Scholar 

  • Schetzen, M. (2006). The Volterra and Wiener theories of nonlinear systems. Malabar: Krieger.

    Google Scholar 

  • Victor, J. (1977). Nonlinear analysis of cat retinal ganglion cells in the frequency domain. Proceedings of the National Academy of Sciences of the United States of America, 74(7), 3068–3072.

    Article  PubMed  CAS  Google Scholar 

  • Victor, J. (1979). Nonlinear systems analysis: Comparison of white noise and sum of sinusoids in a biological system. Proceedings of the National Academy of Sciences of the United States of America, 76(2), 996–998.

    Article  PubMed  CAS  Google Scholar 

  • Victor, J., & Shapley, R. (1980). A method of nonlinear analysis in the frequency domain. Biophysics Journal, 29(3), 459–483.

    Article  CAS  Google Scholar 

  • Westwick, D. T., & Kearney, R. E. (2003). Identification of nonlinear physiological systems. Piscataway: IEEE.

    Book  Google Scholar 

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Acknowledgements

Professor Daniel Eugène provided experimental data over a wide range of stimulus amplitudes and steady state membrane potentials. The data of Figs. 2 and 3 were selected based on criteria described in this paper.

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Correspondence to Christophe Magnani.

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Action Editor: Jonathan D. Victor

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Magnani, C., Moore, L.E. Quadratic sinusoidal analysis of voltage clamped neurons. J Comput Neurosci 31, 595–607 (2011). https://doi.org/10.1007/s10827-011-0325-0

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  • DOI: https://doi.org/10.1007/s10827-011-0325-0

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