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DTI-Based Connectivity in Isolated Neural Ganglia

Title: DTI-Based Connectivity in Isolated Neural Ganglia: A Default Structural Graph in a Small World Framework.
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Name(s): Ould Ismail, Abdol Aziz O., author
Grant, Samuel C., professor directing thesis
Guan, Jingjiao, committee member
Li, Yan, committee member
Florida State University, degree granting institution
College of Engineering, degree granting college
Department of Chemical and Biomedical Engineering, degree granting department
Type of Resource: text
Genre: Text
Issuance: monographic
Date Issued: 2016
Publisher: Florida State University
Place of Publication: Tallahassee, Florida
Physical Form: computer
online resource
Extent: 1 online resource (58 pages)
Language(s): English
Abstract/Description: Diffusion Tensor Imaging (DTI) provides a unique contrast based on the restricted directionality of water movement in an anisotropic environment. As such, DTI-based tractography can be used to characterize and quantify the structural connectivity within neural tissue. Here, DTI-based connectivity within isolated abdominal ganglia (ABG) of aplysia Californica is analyzed using network theory. In addition to quantifying the regional physical proprieties of the fractional anisotropy (FA) and apparent diffusion coefficient (ADC), DTI tractography was used to probe inner-connections of local communities, yielding unweighted, undirected graphs that represent community structures. Local and global efficiency, characteristic path lengths and clustering analysis are performed on both experimental and simulated data. The relevant intensity and velocity by which these specific nodes communicate is probed through weighted clustering coefficient measurements for the descriptive weighted matrices. Both small-worldness and novel small world metrics were used as tools to verify the small-world properties for the experimental results. The aim of this manuscript is to categorize and quantify the properties exhibited by structural networks in a model neural tissue to derive unique mean field information that quantitatively describe macroscopic connectivity. For ABG, findings demonstrate a default structural network with preferential specific small-world properties when compared to simulated lattice and random networks that are equivalent in order and degree.
Identifier: FSU_2016SP_OuldIsmail_fsu_0071N_13048 (IID)
Submitted Note: A Thesis submitted to the Department of Chemical and Biomedical Engineering in partial fulfillment of the Master of Science.
Degree Awarded: Spring Semester 2016.
Date of Defense: February 17, 2016.
Keywords: Diffusion Tensor Imaging, Fractional Anisotropy, Graph Theory, Small World Networks, Structural Connectivity, Watts-Strogatz Model
Bibliography Note: Includes bibliographical references.
Advisory Committee: Samuel C. Grant, Professor Directing Thesis; Jingjiao Guan, Committee Member; Yan Li, Committee Member.
Subject(s): Biomedical engineering
Engineering
Applied mathematics
Persistent Link to This Record: http://purl.flvc.org/fsu/fd/FSU_2016SP_OuldIsmail_fsu_0071N_13048
Owner Institution: FSU

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Ould Ismail, A. A. O. (2016). DTI-Based Connectivity in Isolated Neural Ganglia: A Default Structural Graph in a Small World Framework. Retrieved from http://purl.flvc.org/fsu/fd/FSU_2016SP_OuldIsmail_fsu_0071N_13048