Hierarchical individual variation and socioeconomic impact on personalized functional network topography in children
Abstract Background The spatial layout of large-scale functional brain networks exhibits considerable inter-individual variability, especially in the association cortex. Research has demonstrated a link between early socioeconomic status (SES) and variations in both brain structure and function, whi...
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2024-11-01
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| Online Access: | https://doi.org/10.1186/s12916-024-03784-3 |
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| author | Shaoling Zhao Haowen Su Jing Cong Xue Wen Hang Yang Peiyu Chen Guowei Wu Qingchen Fan Yiyao Ma Xiaoyu Xu Chuanpeng Hu Hongming Li Arielle Keller Adam Pines Runsen Chen Zaixu Cui |
| author_facet | Shaoling Zhao Haowen Su Jing Cong Xue Wen Hang Yang Peiyu Chen Guowei Wu Qingchen Fan Yiyao Ma Xiaoyu Xu Chuanpeng Hu Hongming Li Arielle Keller Adam Pines Runsen Chen Zaixu Cui |
| author_sort | Shaoling Zhao |
| collection | DOAJ |
| description | Abstract Background The spatial layout of large-scale functional brain networks exhibits considerable inter-individual variability, especially in the association cortex. Research has demonstrated a link between early socioeconomic status (SES) and variations in both brain structure and function, which are further associated with cognitive and mental health outcomes. However, the extent to which SES is associated with individual differences in personalized functional network topography during childhood remains largely unexplored. Methods We used a machine learning approach—spatially regularized non-negative matrix factorization (NMF)—to delineate 17 personalized functional networks in children aged 9–10 years, utilizing high-quality functional MRI data from 6001 participants in the Adolescent Brain Cognitive Development study. Partial least square regression approach with repeated random twofold cross-validation was used to evaluate the association between the multivariate pattern of functional network topography and three SES factors, including family income-to-needs ratio, parental education, and neighborhood disadvantage. Results We found that individual variations in personalized functional network topography aligned with the hierarchical sensorimotor-association axis across the cortex. Furthermore, we observed that functional network topography significantly predicted the three SES factors from unseen individuals. The associations between functional topography and SES factors were also hierarchically organized along the sensorimotor-association cortical axis, exhibiting stronger positive associations in the higher-order association cortex. Additionally, we have made the personalized functional networks publicly accessible. Conclusions These results offer insights into how SES influences neurodevelopment through personalized functional neuroanatomy in childhood, highlighting the cortex-wide, hierarchically organized plasticity of the functional networks in response to diverse SES backgrounds. |
| format | Article |
| id | doaj-art-4e11ceee1c024178b99b65a733554a4d |
| institution | Kabale University |
| issn | 1741-7015 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medicine |
| spelling | doaj-art-4e11ceee1c024178b99b65a733554a4d2024-12-01T12:29:41ZengBMCBMC Medicine1741-70152024-11-0122111810.1186/s12916-024-03784-3Hierarchical individual variation and socioeconomic impact on personalized functional network topography in childrenShaoling Zhao0Haowen Su1Jing Cong2Xue Wen3Hang Yang4Peiyu Chen5Guowei Wu6Qingchen Fan7Yiyao Ma8Xiaoyu Xu9Chuanpeng Hu10Hongming Li11Arielle Keller12Adam Pines13Runsen Chen14Zaixu Cui15Beijing Institute for Brain Research, Chinese Academy of Medical Sciences & Peking Union Medical CollegeBeijing Institute for Brain Research, Chinese Academy of Medical Sciences & Peking Union Medical CollegeBeijing Institute for Brain Research, Chinese Academy of Medical Sciences & Peking Union Medical CollegeVanke School of Public Health, Tsinghua UniversityBeijing Institute for Brain Research, Chinese Academy of Medical Sciences & Peking Union Medical CollegeBeijing Institute for Brain Research, Chinese Academy of Medical Sciences & Peking Union Medical CollegeBeijing Institute for Brain Research, Chinese Academy of Medical Sciences & Peking Union Medical CollegeBeijing Institute for Brain Research, Chinese Academy of Medical Sciences & Peking Union Medical CollegeBeijing Institute for Brain Research, Chinese Academy of Medical Sciences & Peking Union Medical CollegeBeijing Institute for Brain Research, Chinese Academy of Medical Sciences & Peking Union Medical CollegeSchool of Psychology, Nanjing Normal UniversityDepartment of Radiology, University of PennsylvaniaDepartment of Psychological Sciences, University of ConnecticutDepartment of Psychiatry and Behavioral Sciences, Stanford UniversityVanke School of Public Health, Tsinghua UniversityBeijing Institute for Brain Research, Chinese Academy of Medical Sciences & Peking Union Medical CollegeAbstract Background The spatial layout of large-scale functional brain networks exhibits considerable inter-individual variability, especially in the association cortex. Research has demonstrated a link between early socioeconomic status (SES) and variations in both brain structure and function, which are further associated with cognitive and mental health outcomes. However, the extent to which SES is associated with individual differences in personalized functional network topography during childhood remains largely unexplored. Methods We used a machine learning approach—spatially regularized non-negative matrix factorization (NMF)—to delineate 17 personalized functional networks in children aged 9–10 years, utilizing high-quality functional MRI data from 6001 participants in the Adolescent Brain Cognitive Development study. Partial least square regression approach with repeated random twofold cross-validation was used to evaluate the association between the multivariate pattern of functional network topography and three SES factors, including family income-to-needs ratio, parental education, and neighborhood disadvantage. Results We found that individual variations in personalized functional network topography aligned with the hierarchical sensorimotor-association axis across the cortex. Furthermore, we observed that functional network topography significantly predicted the three SES factors from unseen individuals. The associations between functional topography and SES factors were also hierarchically organized along the sensorimotor-association cortical axis, exhibiting stronger positive associations in the higher-order association cortex. Additionally, we have made the personalized functional networks publicly accessible. Conclusions These results offer insights into how SES influences neurodevelopment through personalized functional neuroanatomy in childhood, highlighting the cortex-wide, hierarchically organized plasticity of the functional networks in response to diverse SES backgrounds.https://doi.org/10.1186/s12916-024-03784-3ChildrenFunctional MRIPersonalized functional networkIndividual variabilitySocioeconomic statusAdolescent Brain Cognitive Development study |
| spellingShingle | Shaoling Zhao Haowen Su Jing Cong Xue Wen Hang Yang Peiyu Chen Guowei Wu Qingchen Fan Yiyao Ma Xiaoyu Xu Chuanpeng Hu Hongming Li Arielle Keller Adam Pines Runsen Chen Zaixu Cui Hierarchical individual variation and socioeconomic impact on personalized functional network topography in children BMC Medicine Children Functional MRI Personalized functional network Individual variability Socioeconomic status Adolescent Brain Cognitive Development study |
| title | Hierarchical individual variation and socioeconomic impact on personalized functional network topography in children |
| title_full | Hierarchical individual variation and socioeconomic impact on personalized functional network topography in children |
| title_fullStr | Hierarchical individual variation and socioeconomic impact on personalized functional network topography in children |
| title_full_unstemmed | Hierarchical individual variation and socioeconomic impact on personalized functional network topography in children |
| title_short | Hierarchical individual variation and socioeconomic impact on personalized functional network topography in children |
| title_sort | hierarchical individual variation and socioeconomic impact on personalized functional network topography in children |
| topic | Children Functional MRI Personalized functional network Individual variability Socioeconomic status Adolescent Brain Cognitive Development study |
| url | https://doi.org/10.1186/s12916-024-03784-3 |
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