AUTHOR=Bajaj Sahil , Alkozei Anna , Dailey Natalie S. , Killgore William D. S. 

TITLE=Brain Aging: Uncovering Cortical Characteristics of Healthy Aging in Young Adults

JOURNAL=Frontiers in Aging Neuroscience

VOLUME=Volume 9 - 2017

YEAR=2017

URL=https://www.frontiersin.org/journals/aging-neuroscience/articles/10.3389/fnagi.2017.00412

DOI=10.3389/fnagi.2017.00412

ISSN=1663-4365

ABSTRACT=Despite extensive research in the field of aging neuroscience, it still remains unclear whether age related cortical changes can be detected in different functional networks of younger adults and whether these networks respond identically to healthy aging. We collected high-resolution brain anatomical data from fifty-six young healthy adults (mean age = 30.8±8.1 years, 29 males). We performed whole brain parcellation into seven functional networks, including visual, somatomotor, dorsal attention, ventral attention, limbic, frontoparietal and default mode networks, and estimated cortical thickness (CT), cortical surface area (CSA) and cortical volume (CV) for each network. Age was negatively correlated with CT for all functional networks (p < 0.05, corrected for multiple comparisons), apart from the limbic network. While age was unrelated to CSA it was negatively correlated with CV across several functional networks (p < 0.05, corrected for multiple comparisons). We also showed positive associations between CV and CT and between CV and CSA for all networks (p < 0.05, corrected for multiple comparisons). We interpret the lack of association between age and CT of the limbic network as evidence that the limbic system may be particularly resistant to age-related declines during this period of life, whereas the significant age-related declines in CT in other networks suggests that CT may serve as a reliable biomarker to capture the effect of normal aging. Due to the simultaneous dependence of CV on CT and CSA, CV was unable to identify such effects of normal aging consistently. Our findings suggest that the identification of early cortical changes within various functional networks during normal aging might be useful for predicting the effect of aging on the efficiency of functional performance even during early adulthood.