IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-38586-3.html
   My bibliography  Save this article

Robust cortical encoding of 3D tongue shape during feeding in macaques

Author

Listed:
  • Jeffrey D. Laurence-Chasen

    (The University of Chicago)

  • Callum F. Ross

    (The University of Chicago)

  • Fritzie I. Arce-McShane

    (University of Washington
    University of Washington)

  • Nicholas G. Hatsopoulos

    (The University of Chicago
    The University of Chicago)

Abstract

Dexterous tongue deformation underlies eating, drinking, and speaking. The orofacial sensorimotor cortex has been implicated in the control of coordinated tongue kinematics, but little is known about how the brain encodes—and ultimately drives—the tongue’s 3D, soft-body deformation. Here we combine a biplanar x-ray video technology, multi-electrode cortical recordings, and machine-learning-based decoding to explore the cortical representation of lingual deformation. We trained long short-term memory (LSTM) neural networks to decode various aspects of intraoral tongue deformation from cortical activity during feeding in male Rhesus monkeys. We show that both lingual movements and complex lingual shapes across a range of feeding behaviors could be decoded with high accuracy, and that the distribution of deformation-related information across cortical regions was consistent with previous studies of the arm and hand.

Suggested Citation

  • Jeffrey D. Laurence-Chasen & Callum F. Ross & Fritzie I. Arce-McShane & Nicholas G. Hatsopoulos, 2023. "Robust cortical encoding of 3D tongue shape during feeding in macaques," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-38586-3
    DOI: 10.1038/s41467-023-38586-3
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-38586-3
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-023-38586-3?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
    ---><---

    References listed on IDEAS

    as
    1. Francis R. Willett & Donald T. Avansino & Leigh R. Hochberg & Jaimie M. Henderson & Krishna V. Shenoy, 2021. "High-performance brain-to-text communication via handwriting," Nature, Nature, vol. 593(7858), pages 249-254, May.
    2. Yuke Yan & James M. Goodman & Dalton D. Moore & Sara A. Solla & Sliman J. Bensmaia, 2020. "Unexpected complexity of everyday manual behaviors," Nature Communications, Nature, vol. 11(1), pages 1-8, December.
    3. Tejapratap Bollu & Brendan S. Ito & Samuel C. Whitehead & Brian Kardon & James Redd & Mei Hong Liu & Jesse H. Goldberg, 2021. "Cortex-dependent corrections as the tongue reaches for and misses targets," Nature, Nature, vol. 594(7861), pages 82-87, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhouheng Wang & Nanlin Shi & Yingchao Zhang & Ning Zheng & Haicheng Li & Yang Jiao & Jiahui Cheng & Yutong Wang & Xiaoqing Zhang & Ying Chen & Yihao Chen & Heling Wang & Tao Xie & Yijun Wang & Yinji M, 2023. "Conformal in-ear bioelectronics for visual and auditory brain-computer interfaces," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    2. Joshua Kosnoff & Kai Yu & Chang Liu & Bin He, 2024. "Transcranial focused ultrasound to V5 enhances human visual motion brain-computer interface by modulating feature-based attention," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    3. Félix Bigand & Elise Prigent & Bastien Berret & Annelies Braffort, 2021. "Decomposing spontaneous sign language into elementary movements: A principal component analysis-based approach," PLOS ONE, Public Library of Science, vol. 16(10), pages 1-18, October.
    4. Ege Altan & Sara A Solla & Lee E Miller & Eric J Perreault, 2021. "Estimating the dimensionality of the manifold underlying multi-electrode neural recordings," PLOS Computational Biology, Public Library of Science, vol. 17(11), pages 1-23, 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:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-38586-3. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.