IDEAS home Printed from https://ideas.repec.org/a/plo/pcbi00/1000265.html
   My bibliography  Save this article

Action Potential Initiation in the Hodgkin-Huxley Model

Author

Listed:
  • Lucy J Colwell
  • Michael P Brenner

Abstract

A recent paper of B. Naundorf et al. described an intriguing negative correlation between variability of the onset potential at which an action potential occurs (the onset span) and the rapidity of action potential initiation (the onset rapidity). This correlation was demonstrated in numerical simulations of the Hodgkin-Huxley model. Due to this antagonism, it is argued that Hodgkin-Huxley-type models are unable to explain action potential initiation observed in cortical neurons in vivo or in vitro. Here we apply a method from theoretical physics to derive an analytical characterization of this problem. We analytically compute the probability distribution of onset potentials and analytically derive the inverse relationship between onset span and onset rapidity. We find that the relationship between onset span and onset rapidity depends on the level of synaptic background activity. Hence we are able to elucidate the regions of parameter space for which the Hodgkin-Huxley model is able to accurately describe the behavior of this system.Author Summary: In 1952, Hodgkin and Huxley described the underlying mechanism for the firing of action potentials through which information is propagated in the nervous system. Hodgkin and Huxley's model relies on the opening and closing of channels, selectively allowing ions to move across the membrane. In the original picture, the channels open independently of one another. A recent paper argues that this model is incapable of modeling a set of action potential data recorded in the cortical neurons of cats. Instead the authors suggest that to model their data it is necessary to conclude that ion channels open cooperatively, so that opening one channel increases the chance that another channel opens. We analyze the initiation of action potentials using a method from theoretical physics, the path integral. We demonstrate that deviations of the data from the predictions of the Hodgkin-Huxley model hinge on measurement of the noise strength.

Suggested Citation

  • 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.
  • Handle: RePEc:plo:pcbi00:1000265
    DOI: 10.1371/journal.pcbi.1000265
    as

    Download full text from publisher

    File URL: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000265
    Download Restriction: no

    File URL: https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1000265&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pcbi.1000265?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)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.

    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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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).
    7. 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.
    8. 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:pcbi00:1000265. 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.