IDEAS home Printed from https://ideas.repec.org/a/nat/nature/v484y2012i7395d10.1038_nature11039.html
   My bibliography  Save this article

Multiple dynamic representations in the motor cortex during sensorimotor learning

Author

Listed:
  • D. Huber

    (Janelia Farm Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, Virginia 20147, USA
    Present address: Department of Basic Neurosciences, University of Geneva, CH-1211 Geneva, Switzerland.)

  • D. A. Gutnisky

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

  • S. Peron

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

  • D. H. O’Connor

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

  • J. S. Wiegert

    (Center for Molecular Neurobiology Hamburg, Falkenried 94, 20251 Hamburg, Germany)

  • L. Tian

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

  • T. G. Oertner

    (Center for Molecular Neurobiology Hamburg, Falkenried 94, 20251 Hamburg, Germany)

  • L. L. Looger

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

  • K. Svoboda

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

Abstract

The mechanisms linking sensation and action during learning are poorly understood. Layer 2/3 neurons in the motor cortex might participate in sensorimotor integration and learning; they receive input from sensory cortex and excite deep layer neurons, which control movement. Here we imaged activity in the same set of layer 2/3 neurons in the motor cortex over weeks, while mice learned to detect objects with their whiskers and report detection with licking. Spatially intermingled neurons represented sensory (touch) and motor behaviours (whisker movements and licking). With learning, the population-level representation of task-related licking strengthened. In trained mice, population-level representations were redundant and stable, despite dynamism of single-neuron representations. The activity of a subpopulation of neurons was consistent with touch driving licking behaviour. Our results suggest that ensembles of motor cortex neurons couple sensory input to multiple, related motor programs during learning.

Suggested Citation

  • D. Huber & D. A. Gutnisky & S. Peron & D. H. O’Connor & J. S. Wiegert & L. Tian & T. G. Oertner & L. L. Looger & K. Svoboda, 2012. "Multiple dynamic representations in the motor cortex during sensorimotor learning," Nature, Nature, vol. 484(7395), pages 473-478, April.
  • Handle: RePEc:nat:nature:v:484:y:2012:i:7395:d:10.1038_nature11039
    DOI: 10.1038/nature11039
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/nature11039
    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/nature11039?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. Bettina Voelcker & Ravi Pancholi & Simon Peron, 2022. "Transformation of primary sensory cortical representations from layer 4 to layer 2," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    2. Nathan G Clack & Daniel H O'Connor & Daniel Huber & Leopoldo Petreanu & Andrew Hires & Simon Peron & Karel Svoboda & Eugene W Myers, 2012. "Automated Tracking of Whiskers in Videos of Head Fixed Rodents," PLOS Computational Biology, Public Library of Science, vol. 8(7), pages 1-8, July.
    3. Trevor J Wardill & Tsai-Wen Chen & Eric R Schreiter & Jeremy P Hasseman & Getahun Tsegaye & Benjamin F Fosque & Reza Behnam & Brenda C Shields & Melissa Ramirez & Bruce E Kimmel & Rex A Kerr & Vivek J, 2013. "A Neuron-Based Screening Platform for Optimizing Genetically-Encoded Calcium Indicators," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-1, October.
    4. Fan Li & Jazlyn Gallego & Natasha N. Tirko & Jenna Greaser & Derek Bashe & Rudra Patel & Eric Shaker & Grace E. Valkenburg & Alanoud S. Alsubhi & Steven Wellman & Vanshika Singh & Camila Garcia Padill, 2024. "Low-intensity pulsed ultrasound stimulation (LIPUS) modulates microglial activation following intracortical microelectrode implantation," Nature Communications, Nature, vol. 15(1), pages 1-21, December.
    5. Ravi Pancholi & Lauren Ryan & Simon Peron, 2023. "Learning in a sensory cortical microstimulation task is associated with elevated representational stability," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    6. Aniruddha Das & Sarah Holden & Julie Borovicka & Jacob Icardi & Abigail O’Niel & Ariel Chaklai & Davina Patel & Rushik Patel & Stefanie Kaech Petrie & Jacob Raber & Hod Dana, 2023. "Large-scale recording of neuronal activity in freely-moving mice at cellular resolution," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    7. Andrea Comba & Syed M. Faisal & Patrick J. Dunn & Anna E. Argento & Todd C. Hollon & Wajd N. Al-Holou & Maria Luisa Varela & Daniel B. Zamler & Gunnar L. Quass & Pierre F. Apostolides & Clifford Abel , 2022. "Spatiotemporal analysis of glioma heterogeneity reveals COL1A1 as an actionable target to disrupt tumor progression," Nature Communications, Nature, vol. 13(1), pages 1-23, December.
    8. Xinzheng Zhang & Jianfen Zhang & Junpei Zhong, 2017. "Skill Learning for Intelligent Robot by Perception-Action Integration: A View from Hierarchical Temporal Memory," Complexity, Hindawi, vol. 2017, pages 1-16, November.

    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:484:y:2012:i:7395:d:10.1038_nature11039. 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.