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Applying a Novel Integrated Persistent Feature to Understand Topographical Network Connectivity in Older Adults with Autism Spectrum Disorder

Abstract Autism spectrum disorder (ASD) is a developmental neuropsychiatric condition with early childhood onset, thus most research has focused on characterizing brain function in young individuals. Little is understood about brain function differences in middle age and older adults with ASD, despite evidence of persistent and worsening cognitive symptoms. Functional Magnetic Resonance Imaging (MRI) in younger persons with ASD demonstrate that large-scale brain networks containing the prefrontal cortex are affected. A novel, threshold-selection-free graph theory metric is proposed as a more robust and sensitive method for tracking brain aging in ASD and is compared against five well-accepted graph theoretical analysis methods in older men with ASD ... (more)
Created Date 2019
Contributor Catchings, Michael Thomas (Author) / Braden, Brittany B (Advisor) / Greger, Bradley (Advisor) / Schaefer, Sydney (Committee member) / Arizona State University (Publisher)
Subject Neurosciences / Computer engineering / Medical imaging / Adults / Aging / Autism / Biomarker / fMRI / Graph Theory
Type Masters Thesis
Extent 62 pages
Language English
Note Masters Thesis Biomedical Engineering 2019
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis