{"title":"脑功能梯度去分化捕获认知表现和中风发生:英国生物银行研究","authors":"Chenye Shen , Chaoqiang Liu , Nanguang Chen , Anqi Qiu","doi":"10.1016/j.neuroimage.2025.121183","DOIUrl":null,"url":null,"abstract":"<div><div>Brain functional dedifferentiation, marked by reduced specificity of brain activity or greater similarity of functional connectivity (FC) among networks, is a hallmark of aging. Traditionally, task functional magnetic resonance imaging studies have explored functional dedifferentiation within specific cognitive domains, while FC-based approaches have focused on regional connectivity patterns. Here, we leverage the principal functional gradient to provide a macro-scale and integrative perspective on functional dedifferentiation in aging, offering a novel framework for understanding its relationship with aging, cognition, and disease. We utilized brain images and clinical data from the UK Biobank, comprising 23,578 participants aged 44–82. Linear regression was employed to assess relationships between the network dedifferentiation along the principal functional gradient and age, and cognitive performance across six domains in a normal aging population. We tested interactions between age, sex, and education to assess their influence on age-related dedifferentiation. Logistic regression was applied to classify stroke in participants with stroke and matched normal aging participants. Our findings revealed a reduced principal functional gradient range with age, indicating reduced FC variability of all brain regions. At the network level, the dedifferentiation between the frontoparietal and other networks was strongly linked to aging and cognitive performance. Males exhibited faster dedifferentiation than females across multiple networks. The somatomotor network was most affected by stroke-related dedifferentiation. Validation via covariate-matched subgroups confirmed the robustness of these findings. This research provides macro-scale insights into age-related brain functional changes, highlighting dedifferentiation along the principal gradient as a network-sensitive indicator of aging and the development of stroke.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"311 ","pages":"Article 121183"},"PeriodicalIF":4.7000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dedifferentiation of brain functional gradient captures cognition performance and stroke occurrence: A UK Biobank study\",\"authors\":\"Chenye Shen , Chaoqiang Liu , Nanguang Chen , Anqi Qiu\",\"doi\":\"10.1016/j.neuroimage.2025.121183\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Brain functional dedifferentiation, marked by reduced specificity of brain activity or greater similarity of functional connectivity (FC) among networks, is a hallmark of aging. Traditionally, task functional magnetic resonance imaging studies have explored functional dedifferentiation within specific cognitive domains, while FC-based approaches have focused on regional connectivity patterns. Here, we leverage the principal functional gradient to provide a macro-scale and integrative perspective on functional dedifferentiation in aging, offering a novel framework for understanding its relationship with aging, cognition, and disease. We utilized brain images and clinical data from the UK Biobank, comprising 23,578 participants aged 44–82. Linear regression was employed to assess relationships between the network dedifferentiation along the principal functional gradient and age, and cognitive performance across six domains in a normal aging population. We tested interactions between age, sex, and education to assess their influence on age-related dedifferentiation. Logistic regression was applied to classify stroke in participants with stroke and matched normal aging participants. Our findings revealed a reduced principal functional gradient range with age, indicating reduced FC variability of all brain regions. At the network level, the dedifferentiation between the frontoparietal and other networks was strongly linked to aging and cognitive performance. Males exhibited faster dedifferentiation than females across multiple networks. The somatomotor network was most affected by stroke-related dedifferentiation. Validation via covariate-matched subgroups confirmed the robustness of these findings. This research provides macro-scale insights into age-related brain functional changes, highlighting dedifferentiation along the principal gradient as a network-sensitive indicator of aging and the development of stroke.</div></div>\",\"PeriodicalId\":19299,\"journal\":{\"name\":\"NeuroImage\",\"volume\":\"311 \",\"pages\":\"Article 121183\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2025-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"NeuroImage\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1053811925001855\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"NEUROIMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"NeuroImage","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1053811925001855","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NEUROIMAGING","Score":null,"Total":0}
Dedifferentiation of brain functional gradient captures cognition performance and stroke occurrence: A UK Biobank study
Brain functional dedifferentiation, marked by reduced specificity of brain activity or greater similarity of functional connectivity (FC) among networks, is a hallmark of aging. Traditionally, task functional magnetic resonance imaging studies have explored functional dedifferentiation within specific cognitive domains, while FC-based approaches have focused on regional connectivity patterns. Here, we leverage the principal functional gradient to provide a macro-scale and integrative perspective on functional dedifferentiation in aging, offering a novel framework for understanding its relationship with aging, cognition, and disease. We utilized brain images and clinical data from the UK Biobank, comprising 23,578 participants aged 44–82. Linear regression was employed to assess relationships between the network dedifferentiation along the principal functional gradient and age, and cognitive performance across six domains in a normal aging population. We tested interactions between age, sex, and education to assess their influence on age-related dedifferentiation. Logistic regression was applied to classify stroke in participants with stroke and matched normal aging participants. Our findings revealed a reduced principal functional gradient range with age, indicating reduced FC variability of all brain regions. At the network level, the dedifferentiation between the frontoparietal and other networks was strongly linked to aging and cognitive performance. Males exhibited faster dedifferentiation than females across multiple networks. The somatomotor network was most affected by stroke-related dedifferentiation. Validation via covariate-matched subgroups confirmed the robustness of these findings. This research provides macro-scale insights into age-related brain functional changes, highlighting dedifferentiation along the principal gradient as a network-sensitive indicator of aging and the development of stroke.
期刊介绍:
NeuroImage, a Journal of Brain Function provides a vehicle for communicating important advances in acquiring, analyzing, and modelling neuroimaging data and in applying these techniques to the study of structure-function and brain-behavior relationships. Though the emphasis is on the macroscopic level of human brain organization, meso-and microscopic neuroimaging across all species will be considered if informative for understanding the aforementioned relationships.