Functional Parcellation of the Cerebral Cortex Across the Human Adult Lifespan. (11th October 2018)

• Record Type: Journal Article
• Authors: Han, Liang; Savalia, Neil K; Chan, Micaela Y; Agres, Phillip F; Nair, Anupama S; Wig, Gagan S
• Is Part Of: Cerebral cortex. Volume 28:Number 12(2018)
• Page Start: 4403
• Page End: 4423
• Publication Date: 2018-10-11
• Subjects: aging -- functional connectivity -- networks -- parcellation -- resting-state; Cerebral cortex -- Periodicals; Brain -- Periodicals; 612.825
• DOI: 10.1093/cercor/bhy218
• Languages: English
• ISSNs: 1047-3211

Abstract

Abstract: Adult aging is associated with differences in structure, function, and connectivity of brain areas. Age-based brain comparisons have typically rested on the assumption that brain areas exhibit a similar spatial organization across age; we evaluate this hypothesis directly. Area parcellation methods that identify locations where resting-state functional correlations (RSFC) exhibit abrupt transitions (boundary-mapping) are used to define cortical areas in cohorts of individuals sampled across a large range of the human adult lifespan (20–93 years). Most of the strongest areal boundaries are spatially consistent across age. Differences in parcellation boundaries are largely explained by differences in cortical thickness and anatomical alignment in older relative to younger adults. Despite the parcellation similarities, age-specific parcellations exhibit better internal validity relative to a young-adult parcellation applied to older adults' data, and age-specific parcels are better able to capture variability in task-evoked functional activity. Incorporating age-specific parcels as nodes in RSFC network analysis reveals that the spatial topography of the brain's large-scale system organization is comparable throughout aging, but confirms that the segregation of systems declines with increasing age. These observations demonstrate that many features of areal organization are consistent across adulthood, and reveal sources of age-related brain variation that contribute to the differences.