计算机应用与软件2024，Vol.41Issue(11)：138-144,152,8.DOI:10.3969/j.issn.1000-386x.2024.11.019
基于贝叶斯先验NMF的ADHD儿童脑网络重叠社区检测
OVERLAPPING COMMUNITY DETECTION OF ADHD CHILDREN'S BRAIN NETWORK BASED ON BAYESIAN PRIOR NON-NEGATIVE MATRIX FACTORIZATION
摘要
Abstract
In order to explore the differences in brain function activities between ADHD children and normal children under visual stimulation,a study is carried out on the functional overlapped communities of the two groups of children's brain function networks.Task-state fMRI data of ADHD children and normal children was obtained,and data preprocessing was performed.Adaptive sparse representation was used to construct brain function networks.Bayesian prior-based non-negative matrix factorization(NMF)method was used.By presetting different numbers of overlapping communities,the brain function networks of the two groups of children were tested for overlapping communities.The experimental results show that the brain function overlap ratio index of ADHD children is 10.7%,which is slightly lower than that of normal children,indicating that ADHD children have a lower brain function coordination efficiency in the task,and the frontal lobe-amygdala-occipital lobe network of ADHD children is connected abnormally.The overlapping community values of the two groups of children are classified as characteristics,and the classification accuracy is higher than that of the traditional method,reaching 96.6%.关键词
ADHD/脑功能网络/重叠社区/贝叶斯先验/非负矩阵分解Key words
ADHD/Brain function network/Overlapping communities/Bayesian prior/Non-negative matrix factorization分类
信息技术与安全科学引用本文复制引用
罗锦宏,宋志伟,朱志豪,王苏弘,邹凌..基于贝叶斯先验NMF的ADHD儿童脑网络重叠社区检测[J].计算机应用与软件,2024,41(11):138-144,152,8.基金项目
江苏省科技厅社会发展项目(BE2018638) （BE2018638）
常州市社会发展项目(CE20195025) （CE20195025）
中国残联课题(CJFJRRB08-2020) （CJFJRRB08-2020）
浙江省脑机协同智能重点实验室开放基金资助项目(2020E10010-04) （2020E10010-04）
江苏省研究生培养创新计划项目(KYCX21_2817). （KYCX21_2817）
