IDEAS home Printed from https://ideas.repec.org/a/nat/nature/v452y2008i7186d10.1038_nature06725.html
   My bibliography  Save this article

Compartmentalized dendritic plasticity and input feature storage in neurons

Author

Listed:
  • Attila Losonczy

    (Howard Hughes Medical Institute, Janelia Farm Research Campus, 19700 Helix Dr Ashburn, Virginia 20147, USA)

  • Judit K. Makara

    (Howard Hughes Medical Institute, Janelia Farm Research Campus, 19700 Helix Dr Ashburn, Virginia 20147, USA)

  • Jeffrey C. Magee

    (Howard Hughes Medical Institute, Janelia Farm Research Campus, 19700 Helix Dr Ashburn, Virginia 20147, USA)

Abstract

Although information storage in the central nervous system is thought to be primarily mediated by various forms of synaptic plasticity, other mechanisms, such as modifications in membrane excitability, are available. Local dendritic spikes are nonlinear voltage events that are initiated within dendritic branches by spatially clustered and temporally synchronous synaptic input. That local spikes selectively respond only to appropriately correlated input allows them to function as input feature detectors and potentially as powerful information storage mechanisms. However, it is currently unknown whether any effective form of local dendritic spike plasticity exists. Here we show that the coupling between local dendritic spikes and the soma of rat hippocampal CA1 pyramidal neurons can be modified in a branch-specific manner through an N-methyl-d-aspartate receptor (NMDAR)-dependent regulation of dendritic Kv4.2 potassium channels. These data suggest that compartmentalized changes in branch excitability could store multiple complex features of synaptic input, such as their spatio-temporal correlation. We propose that this ‘branch strength potentiation’ represents a previously unknown form of information storage that is distinct from that produced by changes in synaptic efficacy both at the mechanistic level and in the type of information stored.

Suggested Citation

  • Attila Losonczy & Judit K. Makara & Jeffrey C. Magee, 2008. "Compartmentalized dendritic plasticity and input feature storage in neurons," Nature, Nature, vol. 452(7186), pages 436-441, March.
  • Handle: RePEc:nat:nature:v:452:y:2008:i:7186:d:10.1038_nature06725
    DOI: 10.1038/nature06725
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/nature06725
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1038/nature06725?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.

    Citations

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


    Cited by:

    1. Zhenrui Liao & Kevin C. Gonzalez & Deborah M. Li & Catalina M. Yang & Donald Holder & Natalie E. McClain & Guofeng Zhang & Stephen W. Evans & Mariya Chavarha & Jane Simko & Christopher D. Makinson & M, 2024. "Functional architecture of intracellular oscillations in hippocampal dendrites," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    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. 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.
    4. Ruy Gómez-Ocádiz & Massimiliano Trippa & Chun-Lei Zhang & Lorenzo Posani & Simona Cocco & Rémi Monasson & Christoph Schmidt-Hieber, 2022. "A synaptic signal for novelty processing in the hippocampus," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    5. Robert Legenstein & Niko Wilbert & Laurenz Wiskott, 2010. "Reinforcement Learning on Slow Features of High-Dimensional Input Streams," PLOS Computational Biology, Public Library of Science, vol. 6(8), pages 1-13, August.
    6. Dejan Pecevski & Lars Buesing & Wolfgang Maass, 2011. "Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons," PLOS Computational Biology, Public Library of Science, vol. 7(12), pages 1-25, December.
    7. Hanle Zheng & Zhong Zheng & Rui Hu & Bo Xiao & Yujie Wu & Fangwen Yu & Xue Liu & Guoqi Li & Lei Deng, 2024. "Temporal dendritic heterogeneity incorporated with spiking neural networks for learning multi-timescale dynamics," Nature Communications, Nature, vol. 15(1), pages 1-20, December.
    8. Ian Cone & Claudia Clopath, 2024. "Latent representations in hippocampal network model co-evolve with behavioral exploration of task structure," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    9. 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.
    10. Ting-Feng Lin & Silas E. Busch & Christian Hansel, 2024. "Intrinsic and synaptic determinants of receptive field plasticity in Purkinje cells of the mouse cerebellum," Nature Communications, Nature, vol. 15(1), pages 1-20, December.
    11. 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.

    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:nat:nature:v:452:y:2008:i:7186:d:10.1038_nature06725. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    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.