Graph theoretic analysis of the human brain's functional connectivity alteration due to sleep restriction / by Marwa Antar.

Author/creator Antar, Marwa author.
Other author Kim, Sunghan, 1975- degree supervisor.
Other author East Carolina University. Department of Engineering.
Format Theses and dissertations
Publication[Greenville, N.C.] : [East Carolina University], 2023.
Description1 online resource (100 pages) : illustrations (some color)
Supplemental ContentAccess via ScholarShip
Subjects

Summary Sleep plays a vital role in learning and memory consolidation. Several studies used brain models of sleep deprivation (SD) and insomnia to study the association between sleep deficiency and cognitive decline conditions. SD was found to cause similar, albeit subtle, cognitive decline symptoms displayed by dementia patients affecting attentional functions, decision making, working and long-term memory. This study examines the effect of sleep restriction (SR) on brain networks and utilizes Functional Connectivity (FC) analysis to identify patterns of information processing between different brain regions. It particularly applies weighted phase-lag index (wPLI) to quantify brain signals synchronization levels during a visual oddball paradigm task that evokes event-related potentials (ERPs) associated with face recognition. This study also examines the viability of graph theoretic analysis (GTA), which provides a holistic view on the brain network topology. GTA quantifies the brain connectivity features to assess the global efficiency and local efficiency of information processing, pre- and post- SR intervention. Significant alterations were found in all graph indices mainly in [alpha]-, [mu]- and [beta]- frequency bands due to induced mental fatigue. The obtained results reveal significantly lower local connections (p [less-than] 0.05) and lower global efficiency (p [less-than] 0.001), particularly in the [alpha]- band as a result of mental fatigue, reflecting the impact of sleep loss on attention and memory processing.
General notePresented to the Faculty of the Department of Engineering
General noteAdvisor: Sunghan Kim
General noteTitle from PDF t.p. (viewed August 1, 2024).
Dissertation noteM.S. East Carolina University 2023.
Bibliography noteIncludes bibliographical references.
Technical detailsSystem requirements: Adobe Reader.
Technical detailsMode of access: World Wide Web.

Availability

Library Location Call Number Status Item Actions
Electronic Resources Access Content Online ✔ Available