Anatomically Informed Models of Functional Connectivity in the Brain
Rykhlevskaia, Elena I.
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Permalink
https://hdl.handle.net/2142/82123
Description
Title
Anatomically Informed Models of Functional Connectivity in the Brain
Author(s)
Rykhlevskaia, Elena I.
Issue Date
2006
Doctoral Committee Chair(s)
Gratton, Gabriele
Department of Study
Psychology
Discipline
Psychology
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Biology, Anatomy
Language
eng
Abstract
In this dissertation we addressed issues of anatomical and functional connectivity in the brain and how brain connectivity changes with aging. This research effort involved statistical modeling of the dynamic cooperation among brain areas while exploiting probabilistic information about the presence of pathways that physically connect these areas. A statistical framework was developed for modeling spatiotemporal brain activation networks in a confirmatory fashion, and anatomical connectivity was incorporated into the paradigm. Our approach for modeling functional connectivity employed lagged covariance structure models, while the modeling of anatomical connectivity exploited either probabilistic tractography or, alternatively, measures of white matter integrity. To combine anatomical and functional connectivity, parameters of functional connectivity models were constrained by anatomical connectivity measures, so that the resulting models would be void of biologically implausible functional connectivity links. Various components of the proposed statistical framework were illustrated on simulated data, as well as on experimental anatomical data (collected with diffusion tensor imaging), and functional data (collected with optical imaging). These illustrations include: (1) Functional connectivity: Modeling (a) propagation of activity from the primary to secondary visual cortex in a visual task; (b) cross-activation and cross-inhibition between hemispheres in a task involving interhemispheric competition. Patterns of functional connectivity were shown to be different for subjects with differences in anatomical connectivity measured by MRI. (2) Anatomical connectivity: Investigating age-related differences in frontal and parietal interhemispheric connectivity by examining cortico-callosal projections revealed by diffusion tensor imaging. In older adults, callosal representation of dorsolateral prefrontal cortex was shown to decrease in volume, whereas corresponding representations of orbitofrontal, motor and superior parietal cortex increased in their spatial extent. (3) Constraining models of functional connectivity by anatomical connectivity-based constraints. On simulated data, we showed how incorporating interregional anatomical connectivity information into the models dramatically changes the interpretation of observed functional connectivity patterns.
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