IDEAS home Printed from https://ideas.repec.org/a/plo/pcbi00/1003338.html
   My bibliography  Save this article

Sharpness of Spike Initiation in Neurons Explained by Compartmentalization

Author

Listed:
  • Romain Brette

Abstract

In cortical neurons, spikes are initiated in the axon initial segment. Seen at the soma, they appear surprisingly sharp. A standard explanation is that the current coming from the axon becomes sharp as the spike is actively backpropagated to the soma. However, sharp initiation of spikes is also seen in the input–output properties of neurons, and not only in the somatic shape of spikes; for example, cortical neurons can transmit high frequency signals. An alternative hypothesis is that Na channels cooperate, but it is not currently supported by direct experimental evidence. I propose a simple explanation based on the compartmentalization of spike initiation. When Na channels are placed in the axon, the soma acts as a current sink for the Na current. I show that there is a critical distance to the soma above which an instability occurs, so that Na channels open abruptly rather than gradually as a function of somatic voltage.Author Summary: Spike initiation determines how the combined inputs to a neuron are converted to an output. Since the pioneering work of Hodgkin and Huxley, it is known that spikes are generated by the opening of sodium channels with depolarization. According to this standard theory, these channels should open gradually when the membrane potential increases, but spikes measured at the soma appear to suddenly rise from rest. This apparent contradiction has triggered a controversy about the origin of spike “sharpness.” This study shows with biophysical modelling that if sodium channels are placed in the axon rather than in the soma, they open all at once when the somatic membrane potential exceeds a critical value. This work explains the sharpness of spike initiation and provides another demonstration that morphology plays a critical role in neural function.

Suggested Citation

  • Romain Brette, 2013. "Sharpness of Spike Initiation in Neurons Explained by Compartmentalization," PLOS Computational Biology, Public Library of Science, vol. 9(12), pages 1-10, December.
  • Handle: RePEc:plo:pcbi00:1003338
    DOI: 10.1371/journal.pcbi.1003338
    as

    Download full text from publisher

    File URL: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003338
    Download Restriction: no

    File URL: https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1003338&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pcbi.1003338?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Björn Naundorf & Fred Wolf & Maxim Volgushev, 2006. "Unique features of action potential initiation in cortical neurons," Nature, Nature, vol. 440(7087), pages 1060-1063, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cristina Rueda & Itziar Fernández & Yolanda Larriba & Alejandro Rodríguez-Collado, 2021. "The FMM Approach to Analyze Biomedical Signals: Theory, Software, Applications and Future," Mathematics, MDPI, vol. 9(10), pages 1-13, May.
    2. Kee-Hyun Choi & Stuart Licht, 2012. "ATP-Sensitive Potassium Channels Exhibit Variance in the Number of Open Channels below the Limit Predicted for Identical and Independent Gating," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-6, May.
    3. Robert C Cannon & Giampaolo D'Alessandro, 2006. "The Ion Channel Inverse Problem: Neuroinformatics Meets Biophysics," PLOS Computational Biology, Public Library of Science, vol. 2(8), pages 1-8, August.
    4. Paul M Harrison & Laurent Badel & Mark J Wall & Magnus J E Richardson, 2015. "Experimentally Verified Parameter Sets for Modelling Heterogeneous Neocortical Pyramidal-Cell Populations," PLOS Computational Biology, Public Library of Science, vol. 11(8), pages 1-23, August.
    5. Skander Mensi & Olivier Hagens & Wulfram Gerstner & Christian Pozzorini, 2016. "Enhanced Sensitivity to Rapid Input Fluctuations by Nonlinear Threshold Dynamics in Neocortical Pyramidal Neurons," PLOS Computational Biology, Public Library of Science, vol. 12(2), pages 1-38, February.
    6. Tatjana Tchumatchenko & Fred Wolf, 2011. "Representation of Dynamical Stimuli in Populations of Threshold Neurons," PLOS Computational Biology, Public Library of Science, vol. 7(10), pages 1-19, October.
    7. Ahmed A Aldohbeyb & Jozsef Vigh & Kevin L Lear, 2021. "New methods for quantifying rapidity of action potential onset differentiate neuron types," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-20, April.
    8. Contoyiannis, Yiannis F. & Kosmidis, Efstratios K. & Diakonos, Fotios K. & Kampitakis, Myron & Potirakis, Stelios M., 2022. "A hybrid artificial neural network for the generation of critical fluctuations and inter-spike intervals," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    9. Lior Tiroshi & Joshua A Goldberg, 2019. "Population dynamics and entrainment of basal ganglia pacemakers are shaped by their dendritic arbors," PLOS Computational Biology, Public Library of Science, vol. 15(2), pages 1-29, February.
    10. Lucy J Colwell & Michael P Brenner, 2009. "Action Potential Initiation in the Hodgkin-Huxley Model," PLOS Computational Biology, Public Library of Science, vol. 5(1), pages 1-7, January.
    11. Maximilian Puelma Touzel & Fred Wolf, 2015. "Complete Firing-Rate Response of Neurons with Complex Intrinsic Dynamics," PLOS Computational Biology, Public Library of Science, vol. 11(12), pages 1-43, December.
    12. Jonathan Platkiewicz & Romain Brette, 2010. "A Threshold Equation for Action Potential Initiation," PLOS Computational Biology, Public Library of Science, vol. 6(7), pages 1-16, July.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pcbi00:1003338. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ploscompbiol (email available below). General contact details of provider: https://journals.plos.org/ploscompbiol/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.