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openalexFrontiers in Aging Neuroscience2026-07-24Cited by 0

Disrupted structural covariance network in presbycusis patients: evidence from a large sample mri-based morphometric study

Qi Yan, Ying Wang, Li Xu, Baoxu Liu, Bin Zhu, Song’an Shang, Bing Guan

Background Presbycusis is characterized by progressive age-related hearing loss and is often associated with cognitive decline and mental health disorders. Objective This study aimed to investigate gray matter volume (GMV) alterations and structural covariance network (SCN) reorganization in presbycusis patients via magnetic resonance imaging (MRI) and graph theory analysis. Methods A total of 129 presbycusis patients and 121 age-matched healthy controls (HCs) underwent neuropsychological assessments and high-resolution T1-weighted MRI. The voxel-based morphometry (VBM) method at the region of interest (ROI) level and the graph theory analysis method of the SCN based on GMV were used to study the impact of presbycusis on brain structure. Results Patients presented altered nodal topological properties in multiple brain regions, including the right insula, left hippocampus, bilateral superior frontal gyrus, and occipital cortices. Significant differences were observed in the characteristic path length (Lp) and normalized characteristic path length (λ) between the groups ( p < 0.05). Cognitive assessments revealed impairments in executive function, memory, and visual-spatial abilities ( p < 0.05). Conclusion Presbycusis is associated with GMV reduction and SCN reorganization across sensory, cognitive, and emotional brain networks. Compensatory neural mechanisms, such as enhanced visual processing, may alleviate the adverse impacts of auditory deprivation. These findings elucidate the neuroanatomical basis of cognitive decline in presbycusis and highlight the necessity of early clinical intervention.

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openalexFrontiers in Aging Neuroscience2026-07-24

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openalexFrontiers in Aging Neuroscience2026-07-24

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openalexFrontiers in Aging Neuroscience2026-07-24

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openalexFrontiers in Aging Neuroscience2026-07-23

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