双相情感障碍患者注意网络的异常网络同质性。

IF 2.4 3区 医学 Q2 NEUROIMAGING
Brain Imaging and Behavior Pub Date : 2025-04-01 Epub Date: 2025-01-28 DOI:10.1007/s11682-025-00974-2
Mengling Tan, Yunxiao Guo, Sijun Liu, Wei Liu, Liang Cheng, Yujun Gao, Zhihong Ren
{"title":"双相情感障碍患者注意网络的异常网络同质性。","authors":"Mengling Tan, Yunxiao Guo, Sijun Liu, Wei Liu, Liang Cheng, Yujun Gao, Zhihong Ren","doi":"10.1007/s11682-025-00974-2","DOIUrl":null,"url":null,"abstract":"<p><p>Bipolar disorder (BD) is a complex psychiatric condition marked by significant mood fluctuations that deeply affect quality of life. Understanding the neural mechanisms underlying BD is critical for improving diagnostic accuracy and developing more effective treatments. This study utilized resting-state functional magnetic resonance imaging (rs-fMRI) to investigate functional connectivity within the ventral and dorsal attention networks in 52 patients with BD and 51 healthy controls. Independent Component Analysis (ICA) was employed to establish network templates, while Network Homogeneity (NH) analysis facilitated the comparison of NH values across various brain regions. We examined the association of NH values with clinical measures, including the Hamilton Depression Scale, Perceptual Deficit Questionnaire, and Young Mania Scale. Results indicated that BD patients exhibited lower NH values in the right inferior temporal gyrus of the dorsal attention network and the right middle temporal gyrus of the ventral attention network compared to controls. Notably, NH values in the right superior marginal gyrus of the ventral network were higher in the BD group. Although no significant correlations were found between NH values and clinical symptoms, Support Vector Machine (SVM) analysis demonstrated over 60% accuracy in differentiating BD patients based on NH values. These findings highlight the potential of NH measures as biomarkers for BD, underscore the importance of advanced neuroimaging in uncovering the disorder's complex neural dynamics, and point to the challenges and need for further research to improve predictive accuracy.</p>","PeriodicalId":9192,"journal":{"name":"Brain Imaging and Behavior","volume":" ","pages":"336-345"},"PeriodicalIF":2.4000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Abnormal network homogeneity in patients with bipolar disorder in attention network.\",\"authors\":\"Mengling Tan, Yunxiao Guo, Sijun Liu, Wei Liu, Liang Cheng, Yujun Gao, Zhihong Ren\",\"doi\":\"10.1007/s11682-025-00974-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Bipolar disorder (BD) is a complex psychiatric condition marked by significant mood fluctuations that deeply affect quality of life. Understanding the neural mechanisms underlying BD is critical for improving diagnostic accuracy and developing more effective treatments. This study utilized resting-state functional magnetic resonance imaging (rs-fMRI) to investigate functional connectivity within the ventral and dorsal attention networks in 52 patients with BD and 51 healthy controls. Independent Component Analysis (ICA) was employed to establish network templates, while Network Homogeneity (NH) analysis facilitated the comparison of NH values across various brain regions. We examined the association of NH values with clinical measures, including the Hamilton Depression Scale, Perceptual Deficit Questionnaire, and Young Mania Scale. Results indicated that BD patients exhibited lower NH values in the right inferior temporal gyrus of the dorsal attention network and the right middle temporal gyrus of the ventral attention network compared to controls. Notably, NH values in the right superior marginal gyrus of the ventral network were higher in the BD group. Although no significant correlations were found between NH values and clinical symptoms, Support Vector Machine (SVM) analysis demonstrated over 60% accuracy in differentiating BD patients based on NH values. These findings highlight the potential of NH measures as biomarkers for BD, underscore the importance of advanced neuroimaging in uncovering the disorder's complex neural dynamics, and point to the challenges and need for further research to improve predictive accuracy.</p>\",\"PeriodicalId\":9192,\"journal\":{\"name\":\"Brain Imaging and Behavior\",\"volume\":\" \",\"pages\":\"336-345\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2025-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Brain Imaging and Behavior\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s11682-025-00974-2\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/28 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"NEUROIMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brain Imaging and Behavior","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s11682-025-00974-2","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/28 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"NEUROIMAGING","Score":null,"Total":0}
引用次数: 0

摘要

双相情感障碍(BD)是一种复杂的精神疾病,以显著的情绪波动为特征,严重影响生活质量。了解双相障碍的神经机制对于提高诊断准确性和开发更有效的治疗方法至关重要。本研究利用静息状态功能磁共振成像(rs-fMRI)研究了52例双相障碍患者和51例健康对照者腹侧和背侧注意网络的功能连通性。采用独立成分分析(ICA)建立网络模板,网络同质性(NH)分析促进了不同脑区NH值的比较。我们研究了NH值与临床测量的关系,包括汉密尔顿抑郁量表、知觉缺陷问卷和青年躁狂症量表。结果表明,与对照组相比,BD患者在背侧注意网络右侧颞下回和腹侧注意网络右侧颞中回的NH值较低。值得注意的是,BD组腹侧网络右侧上边缘回的NH值较高。虽然NH值与临床症状之间没有明显的相关性,但支持向量机(SVM)分析显示,根据NH值区分BD患者的准确率超过60%。这些发现强调了NH测量作为双相障碍生物标志物的潜力,强调了先进的神经成像在揭示该疾病复杂的神经动力学中的重要性,并指出了进一步研究以提高预测准确性的挑战和需要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Abnormal network homogeneity in patients with bipolar disorder in attention network.

Bipolar disorder (BD) is a complex psychiatric condition marked by significant mood fluctuations that deeply affect quality of life. Understanding the neural mechanisms underlying BD is critical for improving diagnostic accuracy and developing more effective treatments. This study utilized resting-state functional magnetic resonance imaging (rs-fMRI) to investigate functional connectivity within the ventral and dorsal attention networks in 52 patients with BD and 51 healthy controls. Independent Component Analysis (ICA) was employed to establish network templates, while Network Homogeneity (NH) analysis facilitated the comparison of NH values across various brain regions. We examined the association of NH values with clinical measures, including the Hamilton Depression Scale, Perceptual Deficit Questionnaire, and Young Mania Scale. Results indicated that BD patients exhibited lower NH values in the right inferior temporal gyrus of the dorsal attention network and the right middle temporal gyrus of the ventral attention network compared to controls. Notably, NH values in the right superior marginal gyrus of the ventral network were higher in the BD group. Although no significant correlations were found between NH values and clinical symptoms, Support Vector Machine (SVM) analysis demonstrated over 60% accuracy in differentiating BD patients based on NH values. These findings highlight the potential of NH measures as biomarkers for BD, underscore the importance of advanced neuroimaging in uncovering the disorder's complex neural dynamics, and point to the challenges and need for further research to improve predictive accuracy.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Brain Imaging and Behavior
Brain Imaging and Behavior 医学-神经成像
CiteScore
7.20
自引率
0.00%
发文量
154
审稿时长
3 months
期刊介绍: Brain Imaging and Behavior is a bi-monthly, peer-reviewed journal, that publishes clinically relevant research using neuroimaging approaches to enhance our understanding of disorders of higher brain function. The journal is targeted at clinicians and researchers in fields concerned with human brain-behavior relationships, such as neuropsychology, psychiatry, neurology, neurosurgery, rehabilitation, and cognitive neuroscience.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信