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Unique features of action potential initiation in cortical neurons

Nature volume 440, pages 1060–1063 (2006)Cite this article

Abstract

Neurons process and encode information by generating sequences of action potentials1,2. For all spiking neurons, the encoding of single-neuron computations into sequences of spikes is biophysically determined by the cell's action-potential-generating mechanism. It has recently been discovered that apparently minor modifications of this mechanism can qualitatively change the nature of neuronal encoding3,4. Here we quantitatively analyse the dynamics of action potential initiation in cortical neurons in vivo, in vitro and in computational models. Unexpectedly, key features of the initiation dynamics of cortical neuron action potentials—their rapid initiation and variable onset potential—are outside the range of behaviours described by the classical Hodgkin–Huxley theory. We propose a new model based on the cooperative activation of sodium channels that reproduces the observed dynamics of action potential initiation. This new model predicts that Hodgkin–Huxley-type dynamics of action potential initiation can be induced by artificially decreasing the effective density of sodium channels. In vitro experiments confirm this prediction, supporting the hypothesis that cooperative sodium channel activation underlies the dynamics of action potential initiation in cortical neurons.

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Figure 1: Dynamics of action potential initiation in neocortical neurons and in a Hodgkin–Huxley-type model of a neocortical neuron.
Figure 2: Different action potential initiation in visual cortex neurons recorded in vivo and in a Hodgkin–Huxley-type model subject to fluctuating synaptic inputs.
Figure 4: Action potential onset span and rapidness in cortical neurons and Hodgkin–Huxley-type models.
Figure 3: Effect of the shape of the sodium channel activation curve and effective peak conductance on action potential initiation in a Hodgkin–Huxley-type model.
Figure 5: Cooperative activation of voltage-gated sodium channels can account for the dynamics of action potential initiation in cortical neurons.

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References

  1. Bernstein, J. Ueber den zeitlichen Verlauf der negativen Schwankung des Nervenstroms. Pflugers Arch. 1, 173–207 (1868)

    Article  Google Scholar 

  2. Huxley, A. F. Nobel Lectures, Physiology or Medicine 1963–1970 (Elsevier, Amsterdam, 1972)

    Google Scholar 

  3. Fourcaud-Trocmé, N., Hansel, D., van Vreeswijk, C. & Brunel, N. How spike generation mechanisms determine the neuronal response to fluctuating inputs. J. Neurosci. 23, 11628–11640 (2003)

    Article  Google Scholar 

  4. Naundorf, B., Geisel, T. & Wolf, F. Action potential onset dynamics and the response speed of neuronal populations. J. Comput. Neurosci. 18, 297–309 (2005)

    Article  MathSciNet  CAS  Google Scholar 

  5. Destexhe, A. & Paré, D. Impact of network activity on the integrative properties of neocortical pyramidal neurons in vivo. J. Neurophysiol. 81, 1531–1547 (1999)

    Article  CAS  Google Scholar 

  6. Azouz, R. & Gray, C. M. Dynamic spike threshold reveals a mechanism for synaptic coincidence detection in cortical neurons in vivo. Proc. Natl Acad. Sci. USA 97, 8110–8115 (2000)

    Article  ADS  CAS  Google Scholar 

  7. Volgushev, M., Pernberg, J. & Eysel, U. T. A novel mechanism of response selectivity of neurons in cat visual cortex. J. Physiol. (Lond.) 540, 307–320 (2002)

    Article  CAS  Google Scholar 

  8. Azouz, R. & Gray, C. M. Adaptive coincidence detection and dynamic gain control in visual cortical neurons in vivo. Neuron 37, 513–532 (2003)

    Article  CAS  Google Scholar 

  9. Henze, D. A. & Buzsaki, G. Action potential threshold of hippocampal pyramidal cells in vivo is increased by recent spiking activity. Neuroscience 105, 121–130 (2001)

    Article  CAS  Google Scholar 

  10. Wang, X. J., Liu, Y., Sanchez-Vives, M. V. & McCormick, D. A. Adaptation and temporal decorrelation by single neurons in the primary visual cortex. J. Neurophysiol. 89, 3279–3293 (2003)

    Article  Google Scholar 

  11. Schneidman, E., Freedman, B. & Segev, I. Ion channel stochasticity may be critical in determining the reliability and precision of spike timing. Neural Comput. 10, 1679–1703 (1998)

    Article  CAS  Google Scholar 

  12. Patlak, J. Molecular kinetics of voltage-dependent Na+ channels. Physiol. Rev. 71, 1047–1080 (1991)

    Article  CAS  Google Scholar 

  13. Huguenard, J. R., Hamill, O. P. & Prince, D. A. Developmental changes in Na+ conductances in rat neocortical neurons: appearance of a slowly inactivating component. J. Neurophysiol. 59, 778–795 (1988)

    Article  CAS  Google Scholar 

  14. Colbert, C. M. & Pan, E. Ion channel properties underlying axonal action potential initiation in pyramidal neurons. Nature Neurosci. 5, 533–538 (2002)

    Article  CAS  Google Scholar 

  15. Aldrich, R. W., Corey, D. P. & Stevens, C. F. A reinterpretation of mammalian sodium channel gating based on single channel recording. Nature 306, 436–441 (1983)

    Article  ADS  CAS  Google Scholar 

  16. Goldman, L. Stationarity of sodium channel gating kinetics in excised patches from neurobastoma N1E 115. Biophys. J. 69, 2364–2368 (1995)

    Article  ADS  CAS  Google Scholar 

  17. Attwell, D. & Laughlin, S. B. An energy budget for signaling in the grey matter of the brain. J. Cereb. Blood Flow Metab. 21, 1133–1145 (2001)

    Article  CAS  Google Scholar 

  18. Lennie, P. The cost of cortical computation. Curr. Biol. 13, 493–497 (2003)

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We would like to thank A. Borst, M. Brecht, M. Chistiakova, T. Geisel, T. Kottos, T. Moser, E. Neher, W. Stühmer, I. Timofeev and C. van Vreeswijk for discussions, A. Borst, M. Brecht and E. Neher for comments on earlier versions of the manuscript, and A. Malyshev for help in some of the experiments. This study was supported by grants from the Deutsche Forschungsgemeinschaft to M.V., by grants from the Human Frontier Science Program and the Bundesministerium für Bildung und Forschung to F.W., and by the Max-Planck Society. Author Contributions B.N., F.W. and M.V. contributed equally to this work. All authors discussed the results and commented on the manuscript.

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Authors and Affiliations

  1. Max Planck Institute for Dynamics and Self-Organization,

    Björn Naundorf & Fred Wolf

  2. Department of Physics,

    Björn Naundorf & Fred Wolf

  3. Bernstein Center for Computational Neuroscience, University of Göttingen, Bunsenstr. 10, D-37073, Göttingen, Germany

    Björn Naundorf & Fred Wolf

  4. Department of Neurophysiology, Ruhr-University Bochum, D-44780, Bochum, Germany

    Maxim Volgushev

  5. Institute of Higher Nervous Activity and Neurophysiology Russian Academy of Sciences, 117485, Moscow, Russia

    Maxim Volgushev

Authors
  1. Björn Naundorf
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  2. Fred Wolf
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  3. Maxim Volgushev
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Corresponding author

Correspondence to Fred Wolf.

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Reprints and permissions information is available at npg.nature.com/reprintsandpermissions. The authors declare no competing financial interests.

Supplementary information

Supplementary Methods and Supplementary Data

This file describes in detail all experimental and data analysis methods used in this study. This includes a description of the stationarity criteria for MP recordings and the estimation of AP (action potential) onset potentials and rapidness. We characterize our data sample and show that rapid AP onset, and substantial variability of AP onset potential are found in all cortical cell classes and argue that they are genuine characteristics of cortical neurons. (PDF 406 kb)

Supplementary Notes 1

This file describes the Hodgkin–Huxley type conductance based models used in the study and the modifications which were applied to these models, such as changes of sodium channel activation curves and single channel stochasticity. We also describe parameter ranges explored. Finally, we show that rapidness and onset potential variability of AP initiation are strongly antagonistic in the whole class of Hodgkin–Huxley type conductance based models. (PDF 300 kb)

Supplementary Notes 2

This file introduces a model of AP initiation by cooperative activation of voltage-gated sodium channels and characterize its basic properties. Then we describe the computational consequences of the characteristic features of cortical action potential initiation. Using a novel phenomenological neuron model, we show that these features allow a neuronal population to encode rapidly varying signals and to suppress responses to slowly varying stimuli. (PDF 1108 kb)

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Naundorf, B., Wolf, F. & Volgushev, M. Unique features of action potential initiation in cortical neurons. Nature 440, 1060–1063 (2006). https://doi.org/10.1038/nature04610

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