Computational Analysis of Gene Expression and Connectivity Patterns in the Convoluted Structures of Mouse Cerebellum
Date of Award
Master of Science (MS)
Call Number for Print
Special Collections LD4331.C65 Z46 2014
One significant difference between evolved mammalian brains and other species is that mammalian brains exhibit increasingly convoluted structures in the cerebral cortex. Groove and ridge shaped structures named gyri and sulci expand surface area of cerebral cortex, making more functions possible. Prior studies using neuroimaging techniques such as dMRI and DTI have revealed that neural fibers are heavily connected to gyri comparing to those connected to sulci, such macro-scale experiments indicates that gyri are involved in large scale information processing while sulci process information locally. However, molecular and cellar level evidences, namely, gene expression pattern and its resulting neuronal connectivity pertaining to such findings are still lacking. The Allen Mouse Brain Connectivity Atlas provides a comprehensive mouse brain neuronal connectivity map, which is build from brain-wide injection sites via anterograde tracers coupled with serial two-photon tomography. In addition, the Allen Mouse Brain Atlas offers a genome-wide gene expression database built upon a series of in situ hybridization images covering whole mouse brain. These concurrent and co-registered datasets provide an unparalleled opportunity for systematically analyzing and characterizing spatial neuronal connectivity and gene expression patterns. Inspired by recent macro-scale neuroimaging results showing that there are significantly different structural and functional connectivity patterns on the gyri and sulci of cerebral cortex in primate brains, this thesis research systematically examines the axonal connectivity and gene expression patterns on gyri and sulci of the cerebellum. the results demonstrate that the cerebellum gyri and sulci of rodent brains are significantly different in both axonal connectivity and gene expression patterns. This discovery enriches and extends prior findings in macro-scale neuroimaging studies in primates. Additionally, this work offers novel insights on the molecular and structural architectures of the cerebellum in particular and the brain in general.
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"Computational Analysis of Gene Expression and Connectivity Patterns in the Convoluted Structures of Mouse Cerebellum"
(2014). Master of Science (MS), Thesis, Computer Science, Old Dominion University, DOI: 10.25777/pc7t-c169