title: Discrete neuroanatomical networks are associated with specific cognitive abilities in old age.
abstract: There have been many attempts at explaining age-related cognitive decline on the basis of regional brain changes, with the usual but inconsistent findings being that smaller gray matter volumes in certain brain regions predict worse cognitive performance in specific domains. Additionally, compromised white matter integrity, as suggested by white matter hyperintensities or decreased regional white matter fractional anisotropy, has an adverse impact on cognitive functions. The human brain is, however, a network and it may be more appropriate to relate cognitive functions to properties of the network rather than specific brain regions. We report on graph theory-based analyses of diffusion tensor imaging tract-derived connectivity in a sample of 342 healthy individuals aged 72-92 years. The cognitive domains included processing speed, memory, language, visuospatial, and executive functions. We examined the association of these cognitive assessments with both the connectivity of the whole brain network and individual cortical regions. We found that the efficiency of the whole brain network of cortical fiber connections had an influence on processing speed and visuospatial and executive functions. Correlations between connectivity of specific regions and cognitive assessments were also observed, e.g., stronger connectivity in regions such as superior frontal gyrus and posterior cingulate cortex were associated with better executive function. Similar to the relationship between regional connectivity efficiency and age, greater processing speed was significantly correlated with better connectivity of nearly all the cortical regions. For the first time, regional anatomical connectivity maps related to processing speed and visuospatial and executive functions in the elderly are identified.
authors.affiliation: School of Psychiatry, University of New South Wales, Sydney, New South Wales 2052, Australia. w.wen@unsw.edu.au
authors.forename: Wei
authors.initials: W
authors.lastname: Wen
authors.forename: Wanlin
authors.initials: W
authors.lastname: Zhu
authors.forename: Yong
authors.initials: Y
authors.lastname: He
authors.forename: Nicole A
authors.initials: NA
authors.lastname: Kochan
authors.forename: Simone
authors.initials: S
authors.lastname: Reppermund
authors.forename: Melissa J
authors.initials: MJ
authors.lastname: Slavin
authors.forename: Henry
authors.initials: H
authors.lastname: Brodaty
authors.forename: John
authors.initials: J
authors.lastname: Crawford
authors.forename: Aihua
authors.initials: A
authors.lastname: Xia
authors.forename: Perminder
authors.initials: P
authors.lastname: Sachdev
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000502:physiology*; D001931:Brain Mapping; D002540:Cerebral Cortex / Q000502:physiology*; D003071:Cognition / Q000502:physiology*; D056324:Diffusion Tensor Imaging; D005260:Female; D006801:Humans; D008297:Male; D009415:Nerve Net / Q000502:physiology*