title: A Network Flow-based Analysis of Cognitive Reserve in Normal Ageing and Alzheimer's Disease.
abstract: Cognitive reserve is the ability to sustain cognitive function even with a certain amount of brain damages. Here we investigate the neural compensation mechanism of cognitive reserve from the perspective of structural brain connectivity. Our goal was to show that normal people with high education levels (i.e., cognitive reserve) maintain abundant pathways connecting any two brain regions, providing better compensation or resilience after brain damage. Accordingly, patients with high education levels show more deterioration in structural brain connectivity than those with low education levels before symptoms of Alzheimer's disease (AD) become apparent. To test this hypothesis, we use network flow measuring the number of alternative paths between two brain regions in the brain network. The experimental results show that for normal aging, education strengthens network reliability, as measured through flow values, in a subnetwork centered at the supramarginal gyrus. For AD, a subnetwork centered at the left middle frontal gyrus shows a negative correlation between flow and education, which implies more collapse in structural brain connectivity for highly educated patients. We conclude that cognitive reserve may come from the ability of network reorganization to secure the information flow within the brain network, therefore making it more resistant to disease progress.
authors.affiliation: 1] Department of Biomedical Engineering, Korea University, Seoul, Republic of Korea [2] Department of Computer Science, KAIST, Daejeon, Republic of Korea.
authors.forename: Sang
authors.initials: S
authors.lastname: Wook Yoo
authors.affiliation: Department of Biomedical Engineering, Korea University, Seoul, Republic of Korea.
authors.forename: Cheol E
authors.initials: CE
authors.lastname: Han
authors.affiliation: 1] Department of Computer Science, KAIST, Daejeon, Republic of Korea [2] Handong Global University, Pohang, Republic of Korea.
authors.forename: Joseph S
authors.initials: JS
authors.lastname: Shin
authors.affiliation: Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea.
authors.forename: Sang
authors.initials: S
authors.lastname: Won Seo
authors.affiliation: Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea.
authors.forename: Duk L
authors.initials: DL
authors.lastname: Na
authors.affiliation: 1] Department of Brain &Cognitive Sciences, Seoul National University, Seoul 151-747, South Korea [2] Interdisciplinary Computing and Complex BioSystems Research Group, School of Computing Science, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK.
authors.forename: Marcus
authors.initials: M
authors.lastname: Kaiser
authors.affiliation: Department of Bio and Brain Engineering, KAIST, Daejeon, Republic of Korea.
authors.forename: Yong
authors.initials: Y
authors.lastname: Jeong
authors.affiliation: Department of Biomedical Engineering, Korea University, Seoul, Republic of Korea.
authors.forename: Joon-Kyung
authors.initials: JK
authors.lastname: Seong
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000375:Aging; D000544:Alzheimer Disease / Q000503:physiopathology*; D001921:Brain / Q000000981:diagnostic imaging / Q000503:physiopathology; D058245:Cognitive Reserve / Q000502:physiology*; D003710:Demography; D005260:Female; D005625:Frontal Lobe / Q000503:physiopathology; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D009434:Neural Pathways; D011859:Radiography