IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0021928.html
   My bibliography  Save this article

Local Field Potential Modeling Predicts Dense Activation in Cerebellar Granule Cells Clusters under LTP and LTD Control

Author

Listed:
  • Shyam Diwakar
  • Paola Lombardo
  • Sergio Solinas
  • Giovanni Naldi
  • Egidio D'Angelo

Abstract

Local field-potentials (LFPs) are generated by neuronal ensembles and contain information about the activity of single neurons. Here, the LFPs of the cerebellar granular layer and their changes during long-term synaptic plasticity (LTP and LTD) were recorded in response to punctate facial stimulation in the rat in vivo. The LFP comprised a trigeminal (T) and a cortical (C) wave. T and C, which derived from independent granule cell clusters, co-varied during LTP and LTD. To extract information about the underlying cellular activities, the LFP was reconstructed using a repetitive convolution (ReConv) of the extracellular potential generated by a detailed multicompartmental model of the granule cell. The mossy fiber input patterns were determined using a Blind Source Separation (BSS) algorithm. The major component of the LFP was generated by the granule cell spike Na+ current, which caused a powerful sink in the axon initial segment with the source located in the soma and dendrites. Reproducing the LFP changes observed during LTP and LTD required modifications in both release probability and intrinsic excitability at the mossy fiber-granule cells relay. Synaptic plasticity and Golgi cell feed-forward inhibition proved critical for controlling the percentage of active granule cells, which was 11% in standard conditions but ranged from 3% during LTD to 21% during LTP and raised over 50% when inhibition was reduced. The emerging picture is that of independent (but neighboring) trigeminal and cortical channels, in which synaptic plasticity and feed-forward inhibition effectively regulate the number of discharging granule cells and emitted spikes generating “dense” activity clusters in the cerebellar granular layer.

Suggested Citation

  • Shyam Diwakar & Paola Lombardo & Sergio Solinas & Giovanni Naldi & Egidio D'Angelo, 2011. "Local Field Potential Modeling Predicts Dense Activation in Cerebellar Granule Cells Clusters under LTP and LTD Control," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-13, July.
  • Handle: RePEc:plo:pone00:0021928
    DOI: 10.1371/journal.pone.0021928
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0021928
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0021928&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0021928?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. Chiara Saviane & R. Angus Silver, 2006. "Fast vesicle reloading and a large pool sustain high bandwidth transmission at a central synapse," Nature, Nature, vol. 439(7079), pages 983-987, February.
    2. Paul Chadderton & Troy W. Margrie & Michael Häusser, 2004. "Integration of quanta in cerebellar granule cells during sensory processing," Nature, Nature, vol. 428(6985), pages 856-860, 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. Claudia Clopath & Jean-Pierre Nadal & Nicolas Brunel, 2012. "Storage of Correlated Patterns in Standard and Bistable Purkinje Cell Models," PLOS Computational Biology, Public Library of Science, vol. 8(4), pages 1-10, April.
    2. A. Barri & M. T. Wiechert & M. Jazayeri & D. A. DiGregorio, 2022. "Synaptic basis of a sub-second representation of time in a neural circuit model," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    3. Claudia Clopath & Nicolas Brunel, 2013. "Optimal Properties of Analog Perceptrons with Excitatory Weights," PLOS Computational Biology, Public Library of Science, vol. 9(2), pages 1-6, February.
    4. Lloyd E. Russell & Mehmet Fişek & Zidan Yang & Lynn Pei Tan & Adam M. Packer & Henry W. P. Dalgleish & Selmaan N. Chettih & Christopher D. Harvey & Michael Häusser, 2024. "The influence of cortical activity on perception depends on behavioral state and sensory context," Nature Communications, Nature, vol. 15(1), pages 1-17, December.

    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:pone00:0021928. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.