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<p>The corpus callosum (CC), the brain’s largest white matter commissure, undergoes significant age-related atrophy that varies across subregions. However, how network-specific callosal connections age and relate to cognitive performance remains poorly understood. We analyzed diffusion-weighted imaging data from 718 healthy adults (ages 36-100 years) from the Human Connectome Project-Aging dataset. Using a tract-to-region approach, we quantified CC tract density within seven canonical functional networks. Cubic polynomial models examined network-specific aging trajectories, while correlation and moderation analyses investigated relationships with cognitive and motor performance across age groups. Network-specific CC tract densities showed distinct aging patterns. Somatomotor and Default Mode networks exhibited highest baseline tract density but steepest age-related declines (β = −0.068 and −0.025, respectively, <i>p</i> &lt; 0.001), while Visual and Limbic networks showed relative preservation. CC tract density showed small-to-medium associations with executive function, memory, and motor performance (r = −0.32 to 0.33). Critically, age moderated these brain-behavior relationships: associations were minimal in younger adults but became progressively stronger in older adults across cognitive domains. The CC follows network-specific aging trajectories, with high-order association networks showing accelerated decline while primary sensory networks remain preserved. Strengthening brain-behavior associations with advancing age suggest callosal integrity becomes increasingly critical for maintaining cognitive performance in later life.</p>

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Network-specific corpus callosum aging and age-moderated cognitive associations using tract-to-region analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月21日

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  • Mohammad Hadi Aarabi

摘要

The corpus callosum (CC), the brain’s largest white matter commissure, undergoes significant age-related atrophy that varies across subregions. However, how network-specific callosal connections age and relate to cognitive performance remains poorly understood. We analyzed diffusion-weighted imaging data from 718 healthy adults (ages 36-100 years) from the Human Connectome Project-Aging dataset. Using a tract-to-region approach, we quantified CC tract density within seven canonical functional networks. Cubic polynomial models examined network-specific aging trajectories, while correlation and moderation analyses investigated relationships with cognitive and motor performance across age groups. Network-specific CC tract densities showed distinct aging patterns. Somatomotor and Default Mode networks exhibited highest baseline tract density but steepest age-related declines (β = −0.068 and −0.025, respectively, p < 0.001), while Visual and Limbic networks showed relative preservation. CC tract density showed small-to-medium associations with executive function, memory, and motor performance (r = −0.32 to 0.33). Critically, age moderated these brain-behavior relationships: associations were minimal in younger adults but became progressively stronger in older adults across cognitive domains. The CC follows network-specific aging trajectories, with high-order association networks showing accelerated decline while primary sensory networks remain preserved. Strengthening brain-behavior associations with advancing age suggest callosal integrity becomes increasingly critical for maintaining cognitive performance in later life.