Advanced Search
MyIDEAS: Login to save this article or follow this journal

Attractors In Song

Contents:

Author Info

  • KARL FRISTON

    ()
    (The Wellcome Trust Centre of Neuroimaging, University College London, Queen Square, London WC1N 3BG, London)

  • STEFAN KIEBEL

    ()
    (The Wellcome Trust Centre of Neuroimaging, University College London, Queen Square, London WC1N 3BG, London)

Registered author(s):

    Abstract

    This paper summarizes our recent attempts to integrate action and perception within a single optimization framework. We start with a statistical formulation of Helmholtz's ideas about neural energy to furnish a model of perceptual inference and learning that can explain a remarkable range of neurobiological facts. Using constructs from statistical physics it can be shown that the problems of inferring the causes of our sensory inputs and learning regularities in the sensorium can be resolved using exactly the same principles. Furthermore, inference and learning can proceed in a biologically plausible fashion. The ensuing scheme rests on Empirical Bayes and hierarchical models of how sensory information is generated. The use of hierarchical models enables the brain to construct prior expectations in a dynamic and context-sensitive fashion. This scheme provides a principled way to understand many aspects of the brain's organization and responses. We will demonstrate the brain-like dynamics that this scheme entails by using models of birdsongs that are based on chaotic attractors with autonomous dynamics. This provides a nice example of how non-linear dynamics can be exploited by the brain to represent and predict dynamics in the environment.

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://www.worldscinet.com/cgi-bin/details.cgi?type=pdf&id=pii:S1793005709001209
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: http://www.worldscinet.com/cgi-bin/details.cgi?type=html&id=pii:S1793005709001209
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Bibliographic Info

    Article provided by World Scientific Publishing Co. Pte. Ltd. in its journal New Mathematics and Natural Computation.

    Volume (Year): 05 (2009)
    Issue (Month): 01 ()
    Pages: 83-114

    as in new window
    Handle: RePEc:wsi:nmncxx:v:05:y:2009:i:01:p:83-114

    Contact details of provider:
    Web page: http://www.worldscinet.com/nmnc/nmnc.shtml

    Order Information:
    Email:

    Related research

    Keywords: Generative models; predictive coding; hierarchical; dynamic; non-linear; variational; birdsong;

    References

    No references listed on IDEAS
    You can help add them by filling out this form.

    Citations

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:wsi:nmncxx:v:05:y:2009:i:01:p:83-114. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Tai Tone Lim).

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.