IDEAS home Printed from https://ideas.repec.org/h/spr/spochp/978-0-387-88630-5_10.html
   My bibliography  Save this book chapter

Neural Network Modeling of Voluntary Single-Joint Movement Organization I. Normal Conditions

In: Computational Neuroscience

Author

Listed:
  • Vassilis Cutsuridis

    (Boston University)

Abstract

Motor learning and motor control have been the focus of intense study by researchers from various disciplines. The neural network model approach has been very successful in providing theoretical frameworks on motor learning and motor control by modeling neural and psychophysical data from multiple levels of biological complexity. Two neural network models of voluntary single-joint movement organization under normal conditions are summarized here. The models seek to explain detailed electromyographic data of rapid single-joint arm movement and identify their neural substrates. The models are successful in predicting several characteristics of voluntary movement.

Suggested Citation

  • Vassilis Cutsuridis, 2010. "Neural Network Modeling of Voluntary Single-Joint Movement Organization I. Normal Conditions," Springer Optimization and Its Applications, in: Wanpracha Chaovalitwongse & Panos M. Pardalos & Petros Xanthopoulos (ed.), Computational Neuroscience, chapter 0, pages 181-191, Springer.
    • Handle: RePEc:spr:spochp:978-0-387-88630-5_10
    DOI: 10.1007/978-0-387-88630-5_10
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:spochp:978-0-387-88630-5_10. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.springer.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.