Segregation of the regional radiomics similarity network exhibited an increase from late childhood to early adolescence: A developmental investigation
Lei Chu,
Debin Zeng,
Yirong He,
Xiaoxi Dong,
Qiongling Li,
Xuhong Liao,
Tengda Zhao,
Xiaodan Chen,
Tianyuan Lei,
Weiwei Men,
Yanpei Wang,
Daoyang Wang,
Mingming Hu,
Zhiying Pan,
Shuping Tan,
Jia-Hong Gao,
Shaozheng Qin,
Sha Tao,
Qi Dong,
Yong He,
Shuyu Li
Affiliations
Lei Chu
Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science & Medical Engineering, Beihang University, Beijing 100083, China
Debin Zeng
Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science & Medical Engineering, Beihang University, Beijing 100083, China
Yirong He
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
Xiaoxi Dong
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
Qiongling Li
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
Xuhong Liao
School of Systems Science, Beijing Normal University, Beijing 100875, China
Tengda Zhao
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
Xiaodan Chen
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
Tianyuan Lei
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
Weiwei Men
Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China; Zhejiang Philosophy and Social Science Laboratory for Research in Early Development and Childcare, Hangzhou Normal University, Hangzhou 311121, China
Yanpei Wang
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
Daoyang Wang
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Zhejiang Philosophy and Social Science Laboratory for Research in Early Development and Childcare, Hangzhou Normal University, Hangzhou 311121, China
Mingming Hu
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
Zhiying Pan
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
Shuping Tan
Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing 100096, China
Jia-Hong Gao
Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China; IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
Shaozheng Qin
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; Chinese Institute for Brain Research, Beijing 102206, China
Sha Tao
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
Qi Dong
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
Yong He
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; Chinese Institute for Brain Research, Beijing 102206, China; Corresponding authors.
Shuyu Li
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Corresponding authors.
Brain development is characterized by an increase in structural and functional segregation, which supports the specialization of cognitive processes within the context of network neuroscience. In this study, we investigated age-related changes in morphological segregation using individual Regional Radiomics Similarity Networks (R2SNs) constructed with a longitudinal dataset of 494 T1-weighted MR scans from 309 typically developing children aged 6.2 to 13 years at baseline. Segertation indices were defined as the relative difference in connectivity strengths within and between modules and cacluated at the global, system and local levels. Linear mixed-effect models revealed longitudinal increases in both global and system segregation indices, particularly within the limbic and dorsal attention network, and decreases within the ventral attention network. Superior performance in working memory and inhibitory control was associated with higher system-level segregation indices in default, frontoparietal, ventral attention, somatomotor and subcortical systems, and lower local segregation indices in visual network regions, regardless of age. Furthermore, gene enrichment analysis revealed correlations between age-related changes in local segregation indices and regional expression levels of genes related to developmental processes. These findings provide novel insights into typical brain developmental changes using R2SN-derived segregation indices, offering a valuable tool for understanding human brain structural and cognitive maturation.
