Ana Rita Barreiros , Isabella A. Breukelaar , Amourie Prentice , Prashanth Mayur , Yoshiro Tomimatsu , Kenta Funayama , Sheryl Foster , Gin S. Malhi , Martijn Arns , Anthony Harris , Mayuresh S. Korgaonkar
{"title":"默认模式网络的网络内和网络间连接可区分治疗耐受性抑郁症和治疗敏感性抑郁症","authors":"Ana Rita Barreiros , Isabella A. Breukelaar , Amourie Prentice , Prashanth Mayur , Yoshiro Tomimatsu , Kenta Funayama , Sheryl Foster , Gin S. Malhi , Martijn Arns , Anthony Harris , Mayuresh S. Korgaonkar","doi":"10.1016/j.nicl.2024.103656","DOIUrl":null,"url":null,"abstract":"<div><p>Understanding why some patients with depression remain resistant to antidepressant medication could be elucidated by investigating their associated neural features. Although research has consistently demonstrated abnormalities in the anterior cingulate cortex (ACC) – a region that is part of the default mode network (DMN) − in treatment-resistant depression (TRD), a considerable research gap exists in discerning how these neural networks distinguish TRD from treatment-sensitive depression (TSD). We aimed to evaluate the resting-state functional connectivity (rsFC) of the ACC with other regions of the DMN to better understand the role of this structure in the pathophysiology of TRD. 35 TRD patients, 35 TSD patients, and 38 healthy controls (HC) underwent a resting-state functional MRI protocol. Seed-based functional connectivity analyses were performed, comparing the three groups for the connectivity between two subregions of the ACC (the subgenual ACC (sgACC) and the rostral ACC (rACC)) and the DMN (<em>p</em> < 0.05 FWE corrected). Furthermore, inter-network connectivity of the DMN with other neural networks was explored by independent component (ICA) analyses (<em>p</em> < 0.01, FDR corrected). The results demonstrated hyperconnectivity between the rACC and the posterior cingulate cortex in TRD relative to TSD and HC (F(2,105) = 5.335, <em>p</em> < 0.05). ICA found DMN connectivity to regions of the visual network (TRD<TSD) and a parietal region of the DMN (TRD>TSD), differentiating the two clinical groups. These results provide confirmatory evidence of DMN hyperconnectivity and preliminary evidence for its interactions with other neural networks as key neural mechanisms underlying treatment non-responsiveness.</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/S2213158224000950/pdfft?md5=5654c168431acc8247d1c17d11992568&pid=1-s2.0-S2213158224000950-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Intra- and Inter-Network connectivity of the default mode network differentiates Treatment-Resistant depression from Treatment-Sensitive depression\",\"authors\":\"Ana Rita Barreiros , Isabella A. Breukelaar , Amourie Prentice , Prashanth Mayur , Yoshiro Tomimatsu , Kenta Funayama , Sheryl Foster , Gin S. Malhi , Martijn Arns , Anthony Harris , Mayuresh S. Korgaonkar\",\"doi\":\"10.1016/j.nicl.2024.103656\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Understanding why some patients with depression remain resistant to antidepressant medication could be elucidated by investigating their associated neural features. Although research has consistently demonstrated abnormalities in the anterior cingulate cortex (ACC) – a region that is part of the default mode network (DMN) − in treatment-resistant depression (TRD), a considerable research gap exists in discerning how these neural networks distinguish TRD from treatment-sensitive depression (TSD). We aimed to evaluate the resting-state functional connectivity (rsFC) of the ACC with other regions of the DMN to better understand the role of this structure in the pathophysiology of TRD. 35 TRD patients, 35 TSD patients, and 38 healthy controls (HC) underwent a resting-state functional MRI protocol. Seed-based functional connectivity analyses were performed, comparing the three groups for the connectivity between two subregions of the ACC (the subgenual ACC (sgACC) and the rostral ACC (rACC)) and the DMN (<em>p</em> < 0.05 FWE corrected). Furthermore, inter-network connectivity of the DMN with other neural networks was explored by independent component (ICA) analyses (<em>p</em> < 0.01, FDR corrected). The results demonstrated hyperconnectivity between the rACC and the posterior cingulate cortex in TRD relative to TSD and HC (F(2,105) = 5.335, <em>p</em> < 0.05). ICA found DMN connectivity to regions of the visual network (TRD<TSD) and a parietal region of the DMN (TRD>TSD), differentiating the two clinical groups. These results provide confirmatory evidence of DMN hyperconnectivity and preliminary evidence for its interactions with other neural networks as key neural mechanisms underlying treatment non-responsiveness.</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/S2213158224000950/pdfft?md5=5654c168431acc8247d1c17d11992568&pid=1-s2.0-S2213158224000950-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neuroimage-Clinical\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2213158224000950\",\"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/S2213158224000950","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NEUROIMAGING","Score":null,"Total":0}
Intra- and Inter-Network connectivity of the default mode network differentiates Treatment-Resistant depression from Treatment-Sensitive depression
Understanding why some patients with depression remain resistant to antidepressant medication could be elucidated by investigating their associated neural features. Although research has consistently demonstrated abnormalities in the anterior cingulate cortex (ACC) – a region that is part of the default mode network (DMN) − in treatment-resistant depression (TRD), a considerable research gap exists in discerning how these neural networks distinguish TRD from treatment-sensitive depression (TSD). We aimed to evaluate the resting-state functional connectivity (rsFC) of the ACC with other regions of the DMN to better understand the role of this structure in the pathophysiology of TRD. 35 TRD patients, 35 TSD patients, and 38 healthy controls (HC) underwent a resting-state functional MRI protocol. Seed-based functional connectivity analyses were performed, comparing the three groups for the connectivity between two subregions of the ACC (the subgenual ACC (sgACC) and the rostral ACC (rACC)) and the DMN (p < 0.05 FWE corrected). Furthermore, inter-network connectivity of the DMN with other neural networks was explored by independent component (ICA) analyses (p < 0.01, FDR corrected). The results demonstrated hyperconnectivity between the rACC and the posterior cingulate cortex in TRD relative to TSD and HC (F(2,105) = 5.335, p < 0.05). ICA found DMN connectivity to regions of the visual network (TRD<TSD) and a parietal region of the DMN (TRD>TSD), differentiating the two clinical groups. These results provide confirmatory evidence of DMN hyperconnectivity and preliminary evidence for its interactions with other neural networks as key neural mechanisms underlying treatment non-responsiveness.
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.