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Multiple dynamic representations in the motor cortex during sensorimotor learning

Author

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  • 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
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    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. 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.
    5. 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.
    6. 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.
    7. 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.

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