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Conserved structures of neural activity in sensorimotor cortex of freely moving rats allow cross-subject decoding

Author

Listed:
  • Svenja Melbaum

    (University of Freiburg
    University of Freiburg)

  • Eleonora Russo

    (University Medical Center, Johannes Gutenberg University
    University of Heidelberg)

  • David Eriksson

    (University of Freiburg
    University of Freiburg)

  • Artur Schneider

    (University of Freiburg
    University of Freiburg)

  • Daniel Durstewitz

    (University of Heidelberg)

  • Thomas Brox

    (University of Freiburg
    University of Freiburg)

  • Ilka Diester

    (University of Freiburg
    University of Freiburg
    University of Freiburg)

Abstract

Our knowledge about neuronal activity in the sensorimotor cortex relies primarily on stereotyped movements that are strictly controlled in experimental settings. It remains unclear how results can be carried over to less constrained behavior like that of freely moving subjects. Toward this goal, we developed a self-paced behavioral paradigm that encouraged rats to engage in different movement types. We employed bilateral electrophysiological recordings across the entire sensorimotor cortex and simultaneous paw tracking. These techniques revealed behavioral coupling of neurons with lateralization and an anterior–posterior gradient from the premotor to the primary sensory cortex. The structure of population activity patterns was conserved across animals despite the severe under-sampling of the total number of neurons and variations in electrode positions across individuals. We demonstrated cross-subject and cross-session generalization in a decoding task through alignments of low-dimensional neural manifolds, providing evidence of a conserved neuronal code.

Suggested Citation

  • Svenja Melbaum & Eleonora Russo & David Eriksson & Artur Schneider & Daniel Durstewitz & Thomas Brox & Ilka Diester, 2022. "Conserved structures of neural activity in sensorimotor cortex of freely moving rats allow cross-subject decoding," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-35115-6
    DOI: 10.1038/s41467-022-35115-6
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    References listed on IDEAS

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    1. Alon Rubin & Liron Sheintuch & Noa Brande-Eilat & Or Pinchasof & Yoav Rechavi & Nitzan Geva & Yaniv Ziv, 2019. "Revealing neural correlates of behavior without behavioral measurements," Nature Communications, Nature, vol. 10(1), pages 1-14, December.
    2. Patrick T. Sadtler & Kristin M. Quick & Matthew D. Golub & Steven M. Chase & Stephen I. Ryu & Elizabeth C. Tyler-Kabara & Byron M. Yu & Aaron P. Batista, 2014. "Neural constraints on learning," Nature, Nature, vol. 512(7515), pages 423-426, August.
    3. Mark M. Churchland & John P. Cunningham & Matthew T. Kaufman & Justin D. Foster & Paul Nuyujukian & Stephen I. Ryu & Krishna V. Shenoy, 2012. "Neural population dynamics during reaching," Nature, Nature, vol. 487(7405), pages 51-56, July.
    4. Jonathan A Michaels & Benjamin Dann & Hansjörg Scherberger, 2016. "Neural Population Dynamics during Reaching Are Better Explained by a Dynamical System than Representational Tuning," PLOS Computational Biology, Public Library of Science, vol. 12(11), pages 1-22, November.
    5. Jingfeng Zhou & Chunying Jia & Marlian Montesinos-Cartagena & Matthew P. H. Gardner & Wenhui Zong & Geoffrey Schoenbaum, 2021. "Evolving schema representations in orbitofrontal ensembles during learning," Nature, Nature, vol. 590(7847), pages 606-611, February.
    6. Juan A. Gallego & Matthew G. Perich & Stephanie N. Naufel & Christian Ethier & Sara A. Solla & Lee E. Miller, 2018. "Cortical population activity within a preserved neural manifold underlies multiple motor behaviors," Nature Communications, Nature, vol. 9(1), pages 1-13, December.
    7. Patrick A. Kells & Shree Hari Gautam & Leila Fakhraei & Jingwen Li & Woodrow L. Shew, 2019. "Strong neuron-to-body coupling implies weak neuron-to-neuron coupling in motor cortex," Nature Communications, Nature, vol. 10(1), pages 1-13, December.
    8. David Eriksson & Mona Heiland & Artur Schneider & Ilka Diester, 2021. "Distinct dynamics of neuronal activity during concurrent motor planning and execution," Nature Communications, Nature, vol. 12(1), pages 1-18, December.
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