IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0073309.html
   My bibliography  Save this article

Independent Component Analysis for Brain fMRI Does Indeed Select for Maximal Independence

Author

Listed:
  • Vince D Calhoun
  • Vamsi K Potluru
  • Ronald Phlypo
  • Rogers F Silva
  • Barak A Pearlmutter
  • Arvind Caprihan
  • Sergey M Plis
  • Tülay Adalı

Abstract

A recent paper by Daubechies et al. claims that two independent component analysis (ICA) algorithms, Infomax and FastICA, which are widely used for functional magnetic resonance imaging (fMRI) analysis, select for sparsity rather than independence. The argument was supported by a series of experiments on synthetic data. We show that these experiments fall short of proving this claim and that the ICA algorithms are indeed doing what they are designed to do: identify maximally independent sources.

Suggested Citation

  • Vince D Calhoun & Vamsi K Potluru & Ronald Phlypo & Rogers F Silva & Barak A Pearlmutter & Arvind Caprihan & Sergey M Plis & Tülay Adalı, 2013. "Independent Component Analysis for Brain fMRI Does Indeed Select for Maximal Independence," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-8, August.
    • Handle: RePEc:plo:pone00:0073309
    DOI: 10.1371/journal.pone.0073309
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0073309
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0073309&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0073309?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
    ---><---

    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:pone00:0073309. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.