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Depthwise cortical iron relates to functional connectivity and fluid cognition in healthy aging

Jenna L. Merenstein, Jiayi Zhao, David J. Madden

2025Neurobiology of Aging12 citationsDOIOpen Access PDF

Abstract

Age-related differences in fluid cognition have been associated with both the merging of functional brain networks, defined from resting-state functional magnetic resonance imaging (rsfMRI), and with elevated cortical iron, assessed by quantitative susceptibility mapping (QSM). Limited information is available, however, regarding the depthwise profile of cortical iron and its potential relation to functional connectivity. Here, using an adult lifespan sample ( n = 138; 18–80 years), we assessed relations among graph theoretical measures of functional connectivity, column-based depthwise measures of cortical iron, and fluid cognition (i.e., tests of memory, perceptual-motor speed, executive function). Increased age was related both to less segregated functional networks and to increased cortical iron, especially for superficial depths. Functional network segregation mediated age-related differences in memory, whereas depthwise iron mediated age-related differences in general fluid cognition. Lastly, higher mean parietal iron predicted lower network segregation for adults younger than 45 years of age. These findings suggest that functional connectivity and depthwise cortical iron have distinct, complementary roles in the relation between age and fluid cognition in healthy adults. • Significant age-related decrease in resting-state functional system segregation. • Significant age-related increases in mean and depthwise measures of cortical iron. • Functional system segregation mediated age-related decline in memory. • Depthwise parietal iron mediated age-related decline in general fluid cognition. • System segregation and cortical iron have complementary roles in brain aging.

Topics & Concepts

NeuroscienceCognitionFunctional connectivityAging brainPsychologyFunctional Brain Connectivity StudiesEEG and Brain-Computer InterfacesHeart Rate Variability and Autonomic Control