Type of Document	Dissertation
Author	Striegel, Deborah A.
Author's Email Address	dsmith@math.fsu.edu
URN	etd-11092009-184905
Title	Modeling the Folding Pattern of the Cerebral Cortex
Degree	Doctor of Philosophy
Department	Mathematics, Department of
Advisory Committee	Advisor Name Title Monica K. Hurdal Committee Chair DeWitt Sumners Committee Member Jack Quine Committee Member Richard Bertram Committee Member Oliver Steinbock University Representative
Keywords	Cerebral Cortex Prolate Spheroid Turing System Cortical Folding Pattern Reaction-Diffusion
Date of Defense	2009-10-08
Availability	unrestricted
Abstract The mechanism for cortical folding pattern formation is not fully understood. Current models represent scenarios that describe pattern formation through local interactions and one recent model is the intermediate progenitor model. The intermediate progenitor (IP) model describes a local chemically-driven scenario, where an increase in intermediate progenitor cells in the subventricular zone (an area surrounding the lateral ventricles) correlates to gyral formation. This dissertation presents the Global Intermediate Progenitor (GIP) model, a theoretical biological model that uses features of the IP model and further captures global characteristics of cortical pattern formation. To illustrate how global features can eect the development of certain patterns, a mathematical model that incorporates a Turing system is used to examine pattern formation on a prolate spheroidal surface. Pattern formation in a biological system can be studied with a Turing reaction-diusion system which utilizes characteristics of domain size and shape to predict which pattern will form. The GIP model approximates the shape of the lateral ventricle with a prolate spheroid. This representation allows the capture of a key shape feature, lateral ventricular eccentricity, in terms of the focal distance of the prolate spheroid. A formula relating domain scale and focal distance of a prolate spheroidal surface to specic prolate spheroidal harmonics is developed. This formula allows the prediction of pattern formation with solutions in the form of prolate spheroidal harmonics based on the size and shape of the prolate spheroidal surface. By utilizing this formula a direct correlation between the size and shape of the lateral ventricle, which drives the shape of the ventricular zone, and cerebral cortical folding pattern formation is found. This correlation is illustrated in two dierent applications: (i) how the location and directionality of the initial cortical folds change with respect to evolutionary development and (ii) how the initial folds change with respect to certain diseases, such as Microcephalia Vera and Megalencephaly Polymicrogyria Polydactyly with Hydrocephalus. The signicance of the GIP model, presented in this dissertation, is that it elucidates the consistency of cortical patterns among healthy individuals within a species and addresses inter-species variability based on global characteristics. This model provides a critical piece to the puzzle of cortical pattern formation.
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