IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v632y2023ip1s0378437123009068.html
   My bibliography  Save this article

Neuronal plasticity features are independent of neuronal holding membrane potential

Author

Listed:
  • Vardi, Roni
  • Tugendhaft, Yael
  • Kanter, Ido

Abstract

Dynamical reversible neuronal features in vitro are typically examined using a fixed holding membrane potential, imitating the physiological conditions of intact brains in an awake state. Here, a set of neuronal plasticity features in synaptic blocked cultures are found to be independent of the holding membrane potential in the range [−95, −50] mV. Specifically, dendritic maximal firing frequency and its absolute refractory period are independent of the holding membrane potential. In addition, the stimulation threshold is also independent of the holding membrane potential in neurons that do not show membrane depolarization in response to sub-threshold stimulations. These robust dendritic plasticity features are a prerequisite for neuronal modeling and for their utilization in interconnected neural networks to realize higher-order functionalities.

Suggested Citation

  • Vardi, Roni & Tugendhaft, Yael & Kanter, Ido, 2023. "Neuronal plasticity features are independent of neuronal holding membrane potential," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).
  • Handle: RePEc:eee:phsmap:v:632:y:2023:i:p1:s0378437123009068
    DOI: 10.1016/j.physa.2023.129351
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437123009068
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2023.129351?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jackie Schiller & Guy Major & Helmut J. Koester & Yitzhak Schiller, 2000. "NMDA spikes in basal dendrites of cortical pyramidal neurons," Nature, Nature, vol. 404(6775), pages 285-289, March.
    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. Matteo Farinella & Daniel T Ruedt & Padraig Gleeson & Frederic Lanore & R Angus Silver, 2014. "Glutamate-Bound NMDARs Arising from In Vivo-like Network Activity Extend Spatio-temporal Integration in a L5 Cortical Pyramidal Cell Model," PLOS Computational Biology, Public Library of Science, vol. 10(4), pages 1-21, April.
    2. Linda Judák & Balázs Chiovini & Gábor Juhász & Dénes Pálfi & Zsolt Mezriczky & Zoltán Szadai & Gergely Katona & Benedek Szmola & Katalin Ócsai & Bernadett Martinecz & Anna Mihály & Ádám Dénes & Bálint, 2022. "Sharp-wave ripple doublets induce complex dendritic spikes in parvalbumin interneurons in vivo," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    3. Balázs Ujfalussy & Tamás Kiss & Péter Érdi, 2009. "Parallel Computational Subunits in Dentate Granule Cells Generate Multiple Place Fields," PLOS Computational Biology, Public Library of Science, vol. 5(9), pages 1-16, September.
    4. David M Santucci & Sridhar Raghavachari, 2008. "The Effects of NR2 Subunit-Dependent NMDA Receptor Kinetics on Synaptic Transmission and CaMKII Activation," PLOS Computational Biology, Public Library of Science, vol. 4(10), pages 1-16, October.
    5. Etay Hay & Sean Hill & Felix Schürmann & Henry Markram & Idan Segev, 2011. "Models of Neocortical Layer 5b Pyramidal Cells Capturing a Wide Range of Dendritic and Perisomatic Active Properties," PLOS Computational Biology, Public Library of Science, vol. 7(7), pages 1-18, July.
    6. Kirsten Bohmbach & Nicola Masala & Eva M. Schönhense & Katharina Hill & André N. Haubrich & Andreas Zimmer & Thoralf Opitz & Heinz Beck & Christian Henneberger, 2022. "An astrocytic signaling loop for frequency-dependent control of dendritic integration and spatial learning," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    7. Romain Daniel Cazé & Mark Humphries & Boris Gutkin, 2013. "Passive Dendrites Enable Single Neurons to Compute Linearly Non-separable Functions," PLOS Computational Biology, Public Library of Science, vol. 9(2), pages 1-15, February.
    8. Hang Zhou & Guo-Qiang Bi & Guosong Liu, 2024. "Intracellular magnesium optimizes transmission efficiency and plasticity of hippocampal synapses by reconfiguring their connectivity," Nature Communications, Nature, vol. 15(1), pages 1-20, December.

    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:eee:phsmap:v:632:y:2023:i:p1:s0378437123009068. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.