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Robust neuronal dynamics in premotor cortex during motor planning

Author

Listed:
  • Nuo Li

    (Janelia Research Campus, Howard Hughes Medical Institute)

  • Kayvon Daie

    (Janelia Research Campus, Howard Hughes Medical Institute)

  • Karel Svoboda

    (Janelia Research Campus, Howard Hughes Medical Institute)

  • Shaul Druckmann

    (Janelia Research Campus, Howard Hughes Medical Institute)

Abstract

Neural activity maintains representations that bridge past and future events, often over many seconds. Network models can produce persistent and ramping activity, but the positive feedback that is critical for these slow dynamics can cause sensitivity to perturbations. Here we use electrophysiology and optogenetic perturbations in the mouse premotor cortex to probe the robustness of persistent neural representations during motor planning. We show that preparatory activity is remarkably robust to large-scale unilateral silencing: detailed neural dynamics that drive specific future movements were quickly and selectively restored by the network. Selectivity did not recover after bilateral silencing of the premotor cortex. Perturbations to one hemisphere are thus corrected by information from the other hemisphere. Corpus callosum bisections demonstrated that premotor cortex hemispheres can maintain preparatory activity independently. Redundancy across selectively coupled modules, as we observed in the premotor cortex, is a hallmark of robust control systems. Network models incorporating these principles show robustness that is consistent with data.

Suggested Citation

  • Nuo Li & Kayvon Daie & Karel Svoboda & Shaul Druckmann, 2016. "Robust neuronal dynamics in premotor cortex during motor planning," Nature, Nature, vol. 532(7600), pages 459-464, April.
  • Handle: RePEc:nat:nature:v:532:y:2016:i:7600:d:10.1038_nature17643
    DOI: 10.1038/nature17643
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    Cited by:

    1. João D. Semedo & Anna I. Jasper & Amin Zandvakili & Aravind Krishna & Amir Aschner & Christian K. Machens & Adam Kohn & Byron M. Yu, 2022. "Feedforward and feedback interactions between visual cortical areas use different population activity patterns," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    2. Huee Ru Chong & Yadollah Ranjbar-Slamloo & Malcolm Zheng Hao Ho & Xuan Ouyang & Tsukasa Kamigaki, 2023. "Functional alterations of the prefrontal circuit underlying cognitive aging in mice," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    3. R Becket Ebitz & Brianna J Sleezer & Hank P Jedema & Charles W Bradberry & Benjamin Y Hayden, 2019. "Tonic exploration governs both flexibility and lapses," PLOS Computational Biology, Public Library of Science, vol. 15(11), pages 1-37, November.
    4. Benjamin R Cowley & Matthew A Smith & Adam Kohn & Byron M Yu, 2016. "Stimulus-Driven Population Activity Patterns in Macaque Primary Visual Cortex," PLOS Computational Biology, Public Library of Science, vol. 12(12), pages 1-31, December.
    5. J. Tyler Boyd-Meredith & Alex T. Piet & Emily Jane Dennis & Ahmed El Hady & Carlos D. Brody, 2022. "Stable choice coding in rat frontal orienting fields across model-predicted changes of mind," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    6. Alyse Thomas & Weiguo Yang & Catherine Wang & Sri Laasya Tipparaju & Guang Chen & Brennan Sullivan & Kylie Swiekatowski & Mahima Tatam & Charles Gerfen & Nuo Li, 2023. "Superior colliculus bidirectionally modulates choice activity in frontal cortex," Nature Communications, Nature, vol. 14(1), pages 1-22, December.
    7. Ryan C Williamson & Benjamin R Cowley & Ashok Litwin-Kumar & Brent Doiron & Adam Kohn & Matthew A Smith & Byron M Yu, 2016. "Scaling Properties of Dimensionality Reduction for Neural Populations and Network Models," PLOS Computational Biology, Public Library of Science, vol. 12(12), pages 1-27, December.
    8. Christopher F. Angeloni & Wiktor Młynarski & Eugenio Piasini & Aaron M. Williams & Katherine C. Wood & Linda Garami & Ann M. Hermundstad & Maria N. Geffen, 2023. "Dynamics of cortical contrast adaptation predict perception of signals in noise," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    9. Tanner C Dixon & Christina M Merrick & Joni D Wallis & Richard B Ivry & Jose M Carmena, 2021. "Hybrid dedicated and distributed coding in PMd/M1 provides separation and interaction of bilateral arm signals," PLOS Computational Biology, Public Library of Science, vol. 17(11), pages 1-35, November.
    10. Xin Wei Chia & Jian Kwang Tan & Lee Fang Ang & Tsukasa Kamigaki & Hiroshi Makino, 2023. "Emergence of cortical network motifs for short-term memory during learning," Nature Communications, Nature, vol. 14(1), pages 1-17, December.

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