IDEAS home Printed from https://ideas.repec.org/a/plo/pbio00/3000516.html
   My bibliography  Save this article

Data-driven analyses of motor impairments in animal models of neurological disorders

Author

Listed:
  • Hardeep Ryait
  • Edgar Bermudez-Contreras
  • Matthew Harvey
  • Jamshid Faraji
  • Behroo Mirza Agha
  • Andrea Gomez-Palacio Schjetnan
  • Aaron Gruber
  • Jon Doan
  • Majid Mohajerani
  • Gerlinde A S Metz
  • Ian Q Whishaw
  • Artur Luczak

Abstract

Behavior provides important insights into neuronal processes. For example, analysis of reaching movements can give a reliable indication of the degree of impairment in neurological disorders such as stroke, Parkinson disease, or Huntington disease. The analysis of such movement abnormalities is notoriously difficult and requires a trained evaluator. Here, we show that a deep neural network is able to score behavioral impairments with expert accuracy in rodent models of stroke. The same network was also trained to successfully score movements in a variety of other behavioral tasks. The neural network also uncovered novel movement alterations related to stroke, which had higher predictive power of stroke volume than the movement components defined by human experts. Moreover, when the regression network was trained only on categorical information (control = 0; stroke = 1), it generated predictions with intermediate values between 0 and 1 that matched the human expert scores of stroke severity. The network thus offers a new data-driven approach to automatically derive ratings of motor impairments. Altogether, this network can provide a reliable neurological assessment and can assist the design of behavioral indices to diagnose and monitor neurological disorders.This study demonstrates that a state-of-the-art neural network can provide automated scoring of motor deficits with an accuracy equivalent to that of human experts and has the potential teach us to develop more-sensitive behavioral tests.

Suggested Citation

  • Hardeep Ryait & Edgar Bermudez-Contreras & Matthew Harvey & Jamshid Faraji & Behroo Mirza Agha & Andrea Gomez-Palacio Schjetnan & Aaron Gruber & Jon Doan & Majid Mohajerani & Gerlinde A S Metz & Ian Q, 2019. "Data-driven analyses of motor impairments in animal models of neurological disorders," PLOS Biology, Public Library of Science, vol. 17(11), pages 1-30, November.
  • Handle: RePEc:plo:pbio00:3000516
    DOI: 10.1371/journal.pbio.3000516
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3000516
    Download Restriction: no

    File URL: https://journals.plos.org/plosbiology/article/file?id=10.1371/journal.pbio.3000516&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pbio.3000516?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. Jumpei Matsumoto & Susumu Urakawa & Yusaku Takamura & Renato Malcher-Lopes & Etsuro Hori & Carlos Tomaz & Taketoshi Ono & Hisao Nishijo, 2013. "A 3D-Video-Based Computerized Analysis of Social and Sexual Interactions in Rats," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-14, October.
    2. Jessica L. Nielson & Jesse Paquette & Aiwen W. Liu & Cristian F. Guandique & C. Amy Tovar & Tomoo Inoue & Karen-Amanda Irvine & John C. Gensel & Jennifer Kloke & Tanya C. Petrossian & Pek Y. Lum & Gun, 2015. "Topological data analysis for discovery in preclinical spinal cord injury and traumatic brain injury," Nature Communications, Nature, vol. 6(1), pages 1-12, December.
    3. Hueihan Jhuang & Estibaliz Garrote & Xinlin Yu & Vinita Khilnani & Tomaso Poggio & Andrew D. Steele & Thomas Serre, 2010. "Automated home-cage behavioural phenotyping of mice," Nature Communications, Nature, vol. 1(1), pages 1-10, December.
    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. Hristo Todorov & Emily Searle-White & Susanne Gerber, 2020. "Applying univariate vs. multivariate statistics to investigate therapeutic efficacy in (pre)clinical trials: A Monte Carlo simulation study on the example of a controlled preclinical neurotrauma trial," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-20, March.
    2. Han, Tian & Li, Ruimeng & Wang, Xiao & Wang, Ying & Chen, Kang & Peng, Huaiwu & Gao, Zhenxin & Wang, Nannan & Peng, Qinke, 2024. "Intra-hour solar irradiance forecasting using topology data analysis and physics-driven deep learning," Renewable Energy, Elsevier, vol. 224(C).
    3. Maarten Loos & Bastijn Koopmans & Emmeke Aarts & Gregoire Maroteaux & Sophie van der Sluis & Neuro-BSIK Mouse Phenomics Consortium & Matthijs Verhage & August B Smit, 2014. "Sheltering Behavior and Locomotor Activity in 11 Genetically Diverse Common Inbred Mouse Strains Using Home-Cage Monitoring," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-9, September.
    4. Andjelković, Miroslav & Maletić, Slobodan & Stosic, Tatijana & Stosic, Borko, 2024. "Rainfall dynamics in an ecologically vulnerable area using applied algebraic topology methods," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).

    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:plo:pbio00:3000516. 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: plosbiology (email available below). General contact details of provider: https://journals.plos.org/plosbiology/ .

    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.