Human Rights First: Reflections from the Mobilization on Human Rights and Drug Policy Conference.

Presbycusis, the most prevalent age-related hearing disorder, affects more than 30% of individuals aged 65 and older, ranking third among the most common geriatric chronic conditions after hypertension and arthritis (). Presbycusis is not only a result of aging but also a disease that leads to hearing loss with age, characterized by an increased number of congenital cochlear nucleus neurons (; ). Presbycusis can lead to central nervous system processing disorders, resulting in poor discrimination and localization abilities in noisy environments (; ), beyond auditory deficits, it is linked to cognitive impairment, depression, and social isolation (; ). At the cortical level, hearing loss disturbs neural afferent inputs to the primary auditory cortex and receptive language regions, further impairing higher-order language association areas that mediate semantic processing and sound interpretation (). Cumulative clinical and neuroanatomical evidence indicated that presbycusis involves not only peripheral cochlear degeneration but also large-scale brain network remodeling, which critically contributes to disease progression. According to the Lancet Commission report on dementia prevention, intervention, and care, hearing loss is ranked among the leading modifiable risk factors for dementia (). Alterations in brain structure and function have been hypothesized to serve as the core causal mechanisms underlying the link between hearing loss and dementia (). A growing body of neuroimaging studies has explored the correlations between age-related hearing loss and brain structural and functional biomarkers, with existing reviews systematically summarizing relevant evidence, particularly functional MRI findings (). Consistent findings from clinical investigations and large-scale population cohorts demonstrate that hearing deficits correlate with adverse neuroimaging phenotypes, including cortical atrophy, reduced gray matter volume, and aberrant functional connectivity. Despite substantial progress in characterizing functional network abnormalities in presbycusis, prior studies have largely focused on functional connectivity rather than structural brain architecture. Given that brain structure fundamentally constrains neural function, the whole brain operates as an integrated structural and functional network for information transmission. Therefore, investigating structural brain patterns is indispensable for comprehensively understanding presbycusis-related neural remodeling. Magnetic resonance imaging (MRI), a pivotal tool in neuroimaging research, enables sensitive tracking of changes spanning from microstructural degradation to morphological atrophy. Structural covariance network (SCN), which reflect synchronized gray matter variations across brain regions, provide a novel framework to explore large-scale neural reorganization in presbycusis. Enabled by automated whole-brain analytical approaches for large-scale datasets, SCN analysis delineates macroscopic structural network architectures built upon anatomical connectivity and cross-regional functional integration (). Graph theoretical metrics derived from SCN data further reveal global topological organization of brain morphological covariation, as well as the spatial distribution of functional hubs that exhibit intensified structural coupling with distributed brain regions ().