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<p>Normal aging triggers substantial topological transformation within resting-state electroencephalography (rs-EEG) networks. Given that the small-world (SW) architecture of hemispheric EEG networks may reflect an evolutionarily and developmentally optimized organization, investigating their modulations with age offers critical insights into the dynamic reorganization of functional connectivity (FC) patterns throughout adulthood. Utilizing rs-EEG data from a single-site public repository collected under eyes-closed and eyes-open conditions, we employed graph-theory methods to delineate age-related alterations in the SW architecture of hemispheric functional networks across a broad adult age range (20–70&#xa0;years). In 539 cognitively intact individuals, undirected weighted FC networks were constructed using eLORETA-based lagged linear connectivity for each hemisphere and three subnetworks: default mode network (DMN), frontal network (FN), and attentional network (AN). Further quantitative analyses revealed that age-related changes in SW metrics were observed exclusively in the right hemisphere, evident during eyes-closed rest and in network reconfiguration upon eye opening (ΔSW). Right-hemispheric SW and ΔSW showed frequency- and network-specific modulation with age: in the alpha2 band, all three subnetworks exhibited increasing trends, with U-shaped trajectories in DMN and AN and a linear rise in FN. In other frequency bands, specific SW metrics displayed an inverted-U curve relationship with age (DMN: alpha1 SW, delta ΔSW; FN: gamma SW; AN: theta, alpha1, gamma SW, theta ΔSW) in later adulthood, whereas beta2 SW and gamma ΔSW in FN decreased linearly. These findings revealed a right-lateralized pattern of age-related changes in intrinsic SW architecture and provided an eyes-state-dependent baseline for evaluating hemispheric network impairments in age-related neuropsychiatric disorders.</p>

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Age-dependent modulations of hemispheric small-world networks in different eye states: resting-state electroencephalogram research

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月20日

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  • Chang Xu,
  • Chuqiao Li,
  • Tong Cui,
  • Shaoqi Li,
  • Xiaodong Han,
  • Boye Wen,
  • Cuibai Wei

摘要

Normal aging triggers substantial topological transformation within resting-state electroencephalography (rs-EEG) networks. Given that the small-world (SW) architecture of hemispheric EEG networks may reflect an evolutionarily and developmentally optimized organization, investigating their modulations with age offers critical insights into the dynamic reorganization of functional connectivity (FC) patterns throughout adulthood. Utilizing rs-EEG data from a single-site public repository collected under eyes-closed and eyes-open conditions, we employed graph-theory methods to delineate age-related alterations in the SW architecture of hemispheric functional networks across a broad adult age range (20–70 years). In 539 cognitively intact individuals, undirected weighted FC networks were constructed using eLORETA-based lagged linear connectivity for each hemisphere and three subnetworks: default mode network (DMN), frontal network (FN), and attentional network (AN). Further quantitative analyses revealed that age-related changes in SW metrics were observed exclusively in the right hemisphere, evident during eyes-closed rest and in network reconfiguration upon eye opening (ΔSW). Right-hemispheric SW and ΔSW showed frequency- and network-specific modulation with age: in the alpha2 band, all three subnetworks exhibited increasing trends, with U-shaped trajectories in DMN and AN and a linear rise in FN. In other frequency bands, specific SW metrics displayed an inverted-U curve relationship with age (DMN: alpha1 SW, delta ΔSW; FN: gamma SW; AN: theta, alpha1, gamma SW, theta ΔSW) in later adulthood, whereas beta2 SW and gamma ΔSW in FN decreased linearly. These findings revealed a right-lateralized pattern of age-related changes in intrinsic SW architecture and provided an eyes-state-dependent baseline for evaluating hemispheric network impairments in age-related neuropsychiatric disorders.