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BRAIN CONNECTIVITY ANALYSIS OF FUNCTIONAL MAGNETIC RESONANCE DATA FOR STORY COMPREHENSION IN CHILDREN USING GROUP INDEPENDENT COMPONENT ANALYSIS AND STRUCTURAL EQUATION MODELING

KARUNANAYAKA, PRASANNA RASIKA
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1172599790

Abstract Details

2007, MS, University of Cincinnati, Engineering : Computer Science.
Structural Equation Modeling (SEM) is combined with Group Independent Component Analysis (ICA) to investigate the developmental trends in brain connectivity coefficients associated with the human language circuitry. A group of 313 children with ages 5-18 years was subjected to a large-scale functional magnetic resonance imaging (fMRI) study to investigate the age-related connectivity changes in brain activity triggered by the narrative language comprehension circuitry. In the developing brain, age-related differences in brain connectivity may either reflect local neuroplasticity changes or a more global transformation of brain activity related to neuroplasticity. The age-related differences were examined in terms of changes in path coefficients between brain regions. The components of the proposed SEM for narrative comprehension were based on five bilateral task-related cognitive modules identified by the group ICA (Schmithorst, V.J., Holland, S.K, et al., 2005. Cognitive modules utilized for narrative comprehension in children: a functional magnetic resonance imaging study. NeuroImage). The SEM is an extended version of the classical Wernicke-Geschwind (WG) model for speech processing involving two-routes: (1) a direct route between Broca’s and Wernicke’s area. (2) an indirect route involving the parietal lobe.
Dr. Anca Ralescu (Advisor)
106 p.
Brain Connectivity Analysis

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Citations

  • KARUNANAYAKA, P. R. (2007). BRAIN CONNECTIVITY ANALYSIS OF FUNCTIONAL MAGNETIC RESONANCE DATA FOR STORY COMPREHENSION IN CHILDREN USING GROUP INDEPENDENT COMPONENT ANALYSIS AND STRUCTURAL EQUATION MODELING [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1172599790

    APA Style (7th edition)

  • KARUNANAYAKA, PRASANNA. BRAIN CONNECTIVITY ANALYSIS OF FUNCTIONAL MAGNETIC RESONANCE DATA FOR STORY COMPREHENSION IN CHILDREN USING GROUP INDEPENDENT COMPONENT ANALYSIS AND STRUCTURAL EQUATION MODELING. 2007. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1172599790.

    MLA Style (8th edition)

  • KARUNANAYAKA, PRASANNA. "BRAIN CONNECTIVITY ANALYSIS OF FUNCTIONAL MAGNETIC RESONANCE DATA FOR STORY COMPREHENSION IN CHILDREN USING GROUP INDEPENDENT COMPONENT ANALYSIS AND STRUCTURAL EQUATION MODELING." Master's thesis, University of Cincinnati, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1172599790

    Chicago Manual of Style (17th edition)

ucin1172599790
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© 2007, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.