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Cortical pattern generation during dexterous movement is input-driven

Author

Listed:
  • Britton A. Sauerbrei

    (Howard Hughes Medical Institute)

  • Jian-Zhong Guo

    (Howard Hughes Medical Institute)

  • Jeremy D. Cohen

    (Howard Hughes Medical Institute)

  • Matteo Mischiati

    (Howard Hughes Medical Institute)

  • Wendy Guo

    (Howard Hughes Medical Institute)

  • Mayank Kabra

    (Howard Hughes Medical Institute)

  • Nakul Verma

    (Columbia University)

  • Brett Mensh

    (Howard Hughes Medical Institute)

  • Kristin Branson

    (Howard Hughes Medical Institute)

  • Adam W. Hantman

    (Howard Hughes Medical Institute)

Abstract

The motor cortex controls skilled arm movement by sending temporal patterns of activity to lower motor centres1. Local cortical dynamics are thought to shape these patterns throughout movement execution2–4. External inputs have been implicated in setting the initial state of the motor cortex5,6, but they may also have a pattern-generating role. Here we dissect the contribution of local dynamics and inputs to cortical pattern generation during a prehension task in mice. Perturbing cortex to an aberrant state prevented movement initiation, but after the perturbation was released, cortex either bypassed the normal initial state and immediately generated the pattern that controls reaching or failed to generate this pattern. The difference in these two outcomes was probably a result of external inputs. We directly investigated the role of inputs by inactivating the thalamus; this perturbed cortical activity and disrupted limb kinematics at any stage of the movement. Activation of thalamocortical axon terminals at different frequencies disrupted cortical activity and arm movement in a graded manner. Simultaneous recordings revealed that both thalamic activity and the current state of cortex predicted changes in cortical activity. Thus, the pattern generator for dexterous arm movement is distributed across multiple, strongly interacting brain regions.

Suggested Citation

  • Britton A. Sauerbrei & Jian-Zhong Guo & Jeremy D. Cohen & Matteo Mischiati & Wendy Guo & Mayank Kabra & Nakul Verma & Brett Mensh & Kristin Branson & Adam W. Hantman, 2020. "Cortical pattern generation during dexterous movement is input-driven," Nature, Nature, vol. 577(7790), pages 386-391, January.
  • Handle: RePEc:nat:nature:v:577:y:2020:i:7790:d:10.1038_s41586-019-1869-9
    DOI: 10.1038/s41586-019-1869-9
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    Cited by:

    1. Alberto Lazari & Piergiorgio Salvan & Lennart Verhagen & Michiel Cottaar & Daniel Papp & Olof Jens van der Werf & Bronwyn Gavine & James Kolasinski & Matthew Webster & Charlotte J. Stagg & Matthew F. , 2022. "A macroscopic link between interhemispheric tract myelination and cortico-cortical interactions during action reprogramming," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    2. Harman Ghuman & Kyungsoo Kim & Sapeeda Barati & Karunesh Ganguly, 2023. "Emergence of task-related spatiotemporal population dynamics in transplanted neurons," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    3. 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.
    4. Tianwei Wang & Yun Chen & Yiheng Zhang & He Cui, 2024. "Multiplicative joint coding in preparatory activity for reaching sequence in macaque motor cortex," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    5. David Eriksson & Artur Schneider & Anupriya Thirumalai & Mansour Alyahyay & Brice Crompe & Kirti Sharma & Patrick Ruther & Ilka Diester, 2022. "Multichannel optogenetics combined with laminar recordings for ultra-controlled neuronal interrogation," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    6. Sanaya N. Shroff & Eric Lowet & Sudiksha Sridhar & Howard J. Gritton & Mohammed Abumuaileq & Hua-An Tseng & Cyrus Cheung & Samuel L. Zhou & Krishnakanth Kondabolu & Xue Han, 2023. "Striatal cholinergic interneuron membrane voltage tracks locomotor rhythms in mice," Nature Communications, Nature, vol. 14(1), pages 1-17, December.

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