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    Independent Components of Magnetoencephalography: Localization and Single-Trial Response Onset Detection


    Tang, Akaysha and Pearlmutter, Barak A. (2002) Independent Components of Magnetoencephalography: Localization and Single-Trial Response Onset Detection. In: Magnetic Source Imaging of the Human Brain. Psychology Press, pp. 159-201. ISBN 9780805845129

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    Abstract

    Independent component analysis (ICA) is a class of decomposition methods that separate sources from mixtures of signals. In this chapter, we used second order blind identification (SOBI), one of the ICA method, to demonstrate its advantages in identifying magnetic signals associated with neural information processing. Using 122-channel MEG data collected during both simple sensory activation and complex cognitive tasks, we explored SOBI’s ability to help isolate and localize underlying neuronal sources, particularly under relatively poor signal-to-noise conditions. For these identified and localized neuronal sources, we developed a simple threshold-crossing method, with which single-trial response onset times could be measured with a detection rate as high as 96%. These results demonstrated that, with the aid of ICA, it is possible to non-invasively measure human single trial response onset times with millisecond resolution for specific neuronal populations from multiple sensory modalities. This capability makes it possible to study a wide range of perceptual and memory functions that critically depend on the timing of discrete neuronal events.

    Item Type: Book Section
    Additional Information: Invited Chapter for a festschrift in honor of Samuel Williamson, edited by Lloyd Kaufman and Zhong Lin Lu. Lawrence Eribaum and Associated (LEA). This is the postprint version of the published chapter.
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Item ID: 10256
    Depositing User: Barak Pearlmutter
    Date Deposited: 29 Nov 2018 17:07
    Publisher: Psychology Press
    Refereed: Yes
    URI:
      Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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