{"title":"广泛性焦虑症患者边缘网络与前额叶/默认模式网络之间的神经回路动态变化","authors":"","doi":"10.1016/j.nicl.2024.103640","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Widespread functional alterations have been implicated in patients with generalized anxiety disorder (GAD). However, most studies have primarily focused on static brain network features in patients with GAD. The current research focused on exploring the dynamics within functional brain networks among individuals diagnosed with GAD.</p></div><div><h3>Methods</h3><p>Seventy-five participants were divided into patients with GAD and healthy controls (HCs), and resting-state functional magnetic resonance imaging data were collected. The severity of symptoms was measured using the Hamilton Anxiety Scale and the Patient Health Questionnaire. Co-activation pattern (CAP) analysis, centered on the bed nucleus of the stria terminalis, was applied to explore network dynamics. The capability of these dynamic characteristics to distinguish between patients with GAD and HCs was evaluated using a support vector machine.</p></div><div><h3>Results</h3><p>Patients with GAD exhibited disruptions in the limbic-prefrontal and limbic-default-mode network circuits. Particularly noteworthy was the marked reduction in dynamic indicators such as occurrence, EntriesFromBaseline, ExitsToBaseline, in-degree, out-degree, and resilience. Moreover, these decreased dynamic features effectively distinguished the GAD group from the HC in this study.</p></div><div><h3>Conclusions</h3><p>The current findings revealed the underlying brain networks associated with compromised emotion regulation in individuals with GAD. The dynamic reduction in connectivity between the limbic-default mode network and limbic-prefrontal networks could potentially act as a biomarker and therapeutic target for GAD in the future.</p></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2213158224000792/pdfft?md5=f5ef5f1bb8ef7d58b2f0a22e63624362&pid=1-s2.0-S2213158224000792-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Alterations in neural circuit dynamics between the limbic network and prefrontal/default mode network in patients with generalized anxiety disorder\",\"authors\":\"\",\"doi\":\"10.1016/j.nicl.2024.103640\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>Widespread functional alterations have been implicated in patients with generalized anxiety disorder (GAD). However, most studies have primarily focused on static brain network features in patients with GAD. The current research focused on exploring the dynamics within functional brain networks among individuals diagnosed with GAD.</p></div><div><h3>Methods</h3><p>Seventy-five participants were divided into patients with GAD and healthy controls (HCs), and resting-state functional magnetic resonance imaging data were collected. The severity of symptoms was measured using the Hamilton Anxiety Scale and the Patient Health Questionnaire. Co-activation pattern (CAP) analysis, centered on the bed nucleus of the stria terminalis, was applied to explore network dynamics. The capability of these dynamic characteristics to distinguish between patients with GAD and HCs was evaluated using a support vector machine.</p></div><div><h3>Results</h3><p>Patients with GAD exhibited disruptions in the limbic-prefrontal and limbic-default-mode network circuits. Particularly noteworthy was the marked reduction in dynamic indicators such as occurrence, EntriesFromBaseline, ExitsToBaseline, in-degree, out-degree, and resilience. Moreover, these decreased dynamic features effectively distinguished the GAD group from the HC in this study.</p></div><div><h3>Conclusions</h3><p>The current findings revealed the underlying brain networks associated with compromised emotion regulation in individuals with GAD. The dynamic reduction in connectivity between the limbic-default mode network and limbic-prefrontal networks could potentially act as a biomarker and therapeutic target for GAD in the future.</p></div>\",\"PeriodicalId\":54359,\"journal\":{\"name\":\"Neuroimage-Clinical\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2213158224000792/pdfft?md5=f5ef5f1bb8ef7d58b2f0a22e63624362&pid=1-s2.0-S2213158224000792-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neuroimage-Clinical\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2213158224000792\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"NEUROIMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuroimage-Clinical","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2213158224000792","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NEUROIMAGING","Score":null,"Total":0}
Alterations in neural circuit dynamics between the limbic network and prefrontal/default mode network in patients with generalized anxiety disorder
Background
Widespread functional alterations have been implicated in patients with generalized anxiety disorder (GAD). However, most studies have primarily focused on static brain network features in patients with GAD. The current research focused on exploring the dynamics within functional brain networks among individuals diagnosed with GAD.
Methods
Seventy-five participants were divided into patients with GAD and healthy controls (HCs), and resting-state functional magnetic resonance imaging data were collected. The severity of symptoms was measured using the Hamilton Anxiety Scale and the Patient Health Questionnaire. Co-activation pattern (CAP) analysis, centered on the bed nucleus of the stria terminalis, was applied to explore network dynamics. The capability of these dynamic characteristics to distinguish between patients with GAD and HCs was evaluated using a support vector machine.
Results
Patients with GAD exhibited disruptions in the limbic-prefrontal and limbic-default-mode network circuits. Particularly noteworthy was the marked reduction in dynamic indicators such as occurrence, EntriesFromBaseline, ExitsToBaseline, in-degree, out-degree, and resilience. Moreover, these decreased dynamic features effectively distinguished the GAD group from the HC in this study.
Conclusions
The current findings revealed the underlying brain networks associated with compromised emotion regulation in individuals with GAD. The dynamic reduction in connectivity between the limbic-default mode network and limbic-prefrontal networks could potentially act as a biomarker and therapeutic target for GAD in the future.
期刊介绍:
NeuroImage: Clinical, a journal of diseases, disorders and syndromes involving the Nervous System, provides a vehicle for communicating important advances in the study of abnormal structure-function relationships of the human nervous system based on imaging.
The focus of NeuroImage: Clinical is on defining changes to the brain associated with primary neurologic and psychiatric diseases and disorders of the nervous system as well as behavioral syndromes and developmental conditions. The main criterion for judging papers is the extent of scientific advancement in the understanding of the pathophysiologic mechanisms of diseases and disorders, in identification of functional models that link clinical signs and symptoms with brain function and in the creation of image based tools applicable to a broad range of clinical needs including diagnosis, monitoring and tracking of illness, predicting therapeutic response and development of new treatments. Papers dealing with structure and function in animal models will also be considered if they reveal mechanisms that can be readily translated to human conditions.