• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

相似文献

1
Characterization of Resting-State Functional Connectivity Changes in Hypertension by a Modified Difference Degree Test.采用改进差异度检验法对高血压静息态功能连接变化的特征描述。
Brain Connect. 2023 Nov;13(9):563-573. doi: 10.1089/brain.2023.0001. Epub 2023 Sep 29.
2
Detecting Perfusion Pattern Based on the Background Low-Frequency Fluctuation in Resting-State Functional Magnetic Resonance Imaging Data and Its Influence on Resting-State Networks: An Iterative Postprocessing Approach.基于静息态功能磁共振成像数据背景低频波动的灌注模式检测及其对静息态网络的影响:一种迭代后处理方法。
Brain Connect. 2017 Dec;7(10):627-634. doi: 10.1089/brain.2017.0545.
3
Alterations in Resting-State Functional Brain Connectivity and Correlations with Vestibular/Ocular-Motor Screening Measures in Postconcussion Vestibular Dysfunction.脑震荡后前庭功能障碍患者静息态功能脑连接改变及其与前庭/眼动运动筛查指标的相关性
J Neuroimaging. 2021 Mar;31(2):277-286. doi: 10.1111/jon.12834. Epub 2021 Jan 21.
4
How restful is it with all that noise? Comparison of Interleaved silent steady state (ISSS) and conventional imaging in resting-state fMRI.在那样的噪音环境中休息,能有多安静?静息态 fMRI 中交错静默稳态(ISSS)与常规成像的比较。
Neuroimage. 2017 Feb 15;147:726-735. doi: 10.1016/j.neuroimage.2016.11.065. Epub 2016 Nov 27.
5
Presurgical brain mapping of the language network in pediatric patients with epilepsy using resting-state fMRI.使用静息态 fMRI 对癫痫患儿进行术前语言网络脑映射。
J Neurosurg Pediatr. 2021 Jan 8;27(3):259-268. doi: 10.3171/2020.8.PEDS20517. Print 2021 Mar 1.
6
Mapping cognitive and emotional networks in neurosurgical patients using resting-state functional magnetic resonance imaging.利用静息态功能磁共振成像对神经外科患者的认知和情感网络进行映射。
Neurosurg Focus. 2020 Feb 1;48(2):E9. doi: 10.3171/2019.11.FOCUS19773.
7
Manipulating brain connectivity with δ⁹-tetrahydrocannabinol: a pharmacological resting state FMRI study.用 δ⁹-四氢大麻酚操纵大脑连接:一项药物静息态 fMRI 研究。
Neuroimage. 2012 Nov 15;63(3):1701-11. doi: 10.1016/j.neuroimage.2012.07.051. Epub 2012 Aug 1.
8
Identifying patients with Alzheimer's disease using resting-state fMRI and graph theory.利用静息态功能磁共振成像和图论识别阿尔茨海默病患者。
Clin Neurophysiol. 2015 Nov;126(11):2132-41. doi: 10.1016/j.clinph.2015.02.060. Epub 2015 Apr 1.
9
Resting state network connectivity is attenuated by fMRI acoustic noise.静息态网络连接在 fMRI 声学噪声下减弱。
Neuroimage. 2022 Feb 15;247:118791. doi: 10.1016/j.neuroimage.2021.118791. Epub 2021 Dec 14.
10
Functional Connectivity Changes on Resting-State fMRI after Mild Traumatic Brain Injury: A Systematic Review.轻度创伤性脑损伤后静息态 fMRI 的功能连接变化:系统评价。
AJNR Am J Neuroradiol. 2024 Jun 7;45(6):795-801. doi: 10.3174/ajnr.A8204.

引用本文的文献

1
A novel integration of brain structural and functional connectivity for identifying traumatic brain injury induced perturbations.一种用于识别创伤性脑损伤所致扰动的脑结构与功能连接性的新型整合方法。
J Neurosci Methods. 2025 Jul;419:110459. doi: 10.1016/j.jneumeth.2025.110459. Epub 2025 Apr 22.
2
fMRI-based data-driven brain parcellation using independent component analysis.基于功能磁共振成像(fMRI),采用独立成分分析的数据驱动脑图谱绘制
J Neurosci Methods. 2025 May;417:110403. doi: 10.1016/j.jneumeth.2025.110403. Epub 2025 Feb 18.
3
Functional connectivity across the human subcortical auditory system using an autoregressive matrix-Gaussian copula graphical model approach with partial correlations.使用具有偏相关的自回归矩阵-高斯Copula图形模型方法对人类皮质下听觉系统进行功能连接分析。
Imaging Neurosci (Camb). 2024;2. doi: 10.1162/imag_a_00258. Epub 2024 Aug 12.

本文引用的文献

1
Nutritional supplement induced modulations in the functional connectivity of a porcine brain.营养补充剂对猪脑功能连接的调制作用。
Nutr Neurosci. 2024 Feb;27(2):147-158. doi: 10.1080/1028415X.2023.2166803. Epub 2023 Jan 19.
2
Joint estimation and regularized aggregation of brain network in FMRI data.基于功能磁共振成像数据的脑网络联合估计与正则化聚合。
J Neurosci Methods. 2021 Dec 1;364:109374. doi: 10.1016/j.jneumeth.2021.109374. Epub 2021 Sep 30.
3
Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants.全球高血压患病率趋势及 1990 至 2019 年治疗和控制进展情况:1040 万参与者、1201 项人群代表性研究的汇总分析
Lancet. 2021 Sep 11;398(10304):957-980. doi: 10.1016/S0140-6736(21)01330-1. Epub 2021 Aug 24.
4
Changes in brain functional connectivity and cognition related to white matter lesion burden in hypertensive patients from SPRINT.SPRINT 研究中高血压患者脑功能连接和认知变化与白质病变负荷的关系。
Neuroradiology. 2021 Jun;63(6):913-924. doi: 10.1007/s00234-020-02614-6. Epub 2021 Jan 6.
5
Brain Functional Magnetic Resonance Imaging Highlights Altered Connections and Functional Networks in Patients With Hypertension.脑功能磁共振成像突显高血压患者连接和功能网络的改变。
Hypertension. 2020 Nov;76(5):1480-1490. doi: 10.1161/HYPERTENSIONAHA.120.15296. Epub 2020 Sep 21.
6
A difference degree test for comparing brain networks.比较脑网络的差异度检验。
Hum Brain Mapp. 2019 Oct 15;40(15):4518-4536. doi: 10.1002/hbm.24718. Epub 2019 Jul 26.
7
Machine learning in resting-state fMRI analysis.静息态 fMRI 分析中的机器学习。
Magn Reson Imaging. 2019 Dec;64:101-121. doi: 10.1016/j.mri.2019.05.031. Epub 2019 Jun 5.
8
Pig Brains Have Homologous Resting-State Networks with Human Brains.猪脑具有与人类大脑同源的静息态网络。
Brain Connect. 2019 Sep;9(7):566-579. doi: 10.1089/brain.2019.0673. Epub 2019 Jun 24.
9
Integrative Bayesian analysis of brain functional networks incorporating anatomical knowledge.整合考虑解剖学知识的脑功能网络的贝叶斯分析。
Neuroimage. 2018 Nov 1;181:263-278. doi: 10.1016/j.neuroimage.2018.07.015. Epub 2018 Jul 11.
10
Resting-state functional brain networks in first-episode psychosis: A 12-month follow-up study.首发精神病患者的静息态功能脑网络:一项 12 个月随访研究。
Aust N Z J Psychiatry. 2018 Sep;52(9):864-875. doi: 10.1177/0004867418775833. Epub 2018 May 27.

采用改进差异度检验法对高血压静息态功能连接变化的特征描述。

Characterization of Resting-State Functional Connectivity Changes in Hypertension by a Modified Difference Degree Test.

机构信息

Department of Physics and Astronomy, University of Georgia Franklin College of Arts and Sciences, Athens, Georgia, USA.

University of Georgia Bio-Imaging Research Center, Athens, Georgia, USA.

出版信息

Brain Connect. 2023 Nov;13(9):563-573. doi: 10.1089/brain.2023.0001. Epub 2023 Sep 29.

DOI:10.1089/brain.2023.0001
PMID:37597202
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10664569/
Abstract

Hypertension affects over a billion people worldwide, and the application of neuroimaging may elucidate changes brought about by the disease. We have applied a graph theory approach to examine the organizational differences in resting-state functional magnetic resonance imaging (rs-fMRI) data between hypertensive and normotensive participants. To detect these groupwise differences, we performed statistical testing using a modified difference degree test (DDT). Structural and rs-fMRI data were collected from a cohort of 52 total (29 hypertensive and 23 normotensive) participants. Functional connectivity maps were obtained by partial correlation analysis of participant rs-fMRI data. We modified the DDT null generation algorithm and validated the change through different simulation schemes and then applied this modified DDT to our experimental data. Through a comparative analysis, the modified DDT showed higher true positivity rates (TPR) when compared with the base DDT while also maintaining false positivity rates below the nominal value of 5% in nearly all analytically thresholded trials. Applying the modified DDT to our rs-fMRI data showed differential organization in the hypertension group in the regions throughout the brain including the default mode network. These experimental findings agree with previous studies. While our findings agree with previous studies, the experimental results presented require more investigation to prove their link to hypertension. Meanwhile, our modification to the DDT results in higher accuracy and an increased ability to discern groupwise differences in rs-fMRI data. We expect this to be useful in studying groupwise organizational differences in future studies.

摘要

高血压影响着全球超过 10 亿人,神经影像学的应用可能阐明该疾病带来的变化。我们应用图论方法来研究高血压和正常血压参与者的静息态功能磁共振成像(rs-fMRI)数据之间的组织差异。为了检测这些组间差异,我们使用改进的差异度检验(DDT)进行了统计检验。结构和 rs-fMRI 数据是从 52 名参与者(29 名高血压和 23 名正常血压)的队列中收集的。通过对参与者 rs-fMRI 数据的部分相关分析获得功能连接图。我们修改了 DDT 零假设生成算法,并通过不同的模拟方案验证了这种变化,然后将这种改进的 DDT 应用于我们的实验数据。通过对比分析,改进的 DDT 在与基本 DDT 相比时显示出更高的真阳性率(TPR),同时在几乎所有分析阈值试验中,假阳性率仍保持在名义值 5%以下。将改进的 DDT 应用于我们的 rs-fMRI 数据显示,高血压组在包括默认模式网络在内的整个大脑区域的组织存在差异。这些实验结果与先前的研究一致。虽然我们的发现与先前的研究一致,但所呈现的实验结果需要进一步研究来证明它们与高血压之间的联系。同时,我们对 DDT 的改进提高了准确性,并提高了在 rs-fMRI 数据中辨别组间差异的能力。我们期望这在未来的研究中对研究组间组织差异有用。