阿尔茨海默病和轻度认知障碍患者的有效连通性:一项系统综述

Sayedeh-Zahra Kazemi-Harikandei , Parnian Shobeiri , Mohammad-Reza Salmani Jelodar , Seyed Mohammad Tavangar
{"title":"阿尔茨海默病和轻度认知障碍患者的有效连通性:一项系统综述","authors":"Sayedeh-Zahra Kazemi-Harikandei ,&nbsp;Parnian Shobeiri ,&nbsp;Mohammad-Reza Salmani Jelodar ,&nbsp;Seyed Mohammad Tavangar","doi":"10.1016/j.neuri.2022.100104","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Alzheimer's disease (AD) is the most common cause of dementia. Effective connectivity (EC) methods signify the direction of brain interactions. The identified inter-system mappings can be helpful in characterizing the pathophysiology of the disease.</p></div><div><h3>Methods and Results</h3><p>We conducted a systematic review of the alterations in EC findings in individuals with AD or Mild Cognitive Impairment (MCI) from PubMed, Scopus, and Google Scholar from fMRI studies. We extracted EC alterations and altered network findings related to specific cognitive impairments. Additionally, we brought a narrative synthesis on the clinical-pathologic relevance of the utilized computational methods. Thirty-nine studies retrieved from the full-text screening. A general pattern of disconnection in several hub centers and changes in inter-network interactions was identified.</p></div><div><h3>Conclusion</h3><p>In summary, this study demonstrated the beneficial role of EC analyses and network measures in understanding the pathophysiology of AD. Future studies are needed to bring out methodologically consistent data for more structured meta-analytic views.</p></div>","PeriodicalId":74295,"journal":{"name":"Neuroscience informatics","volume":"2 4","pages":"Article 100104"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772528622000668/pdfft?md5=4b2fd13b687332fa0a4be378f10b8576&pid=1-s2.0-S2772528622000668-main.pdf","citationCount":"2","resultStr":"{\"title\":\"Effective connectivity in individuals with Alzheimer's disease and mild cognitive impairment: A systematic review\",\"authors\":\"Sayedeh-Zahra Kazemi-Harikandei ,&nbsp;Parnian Shobeiri ,&nbsp;Mohammad-Reza Salmani Jelodar ,&nbsp;Seyed Mohammad Tavangar\",\"doi\":\"10.1016/j.neuri.2022.100104\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>Alzheimer's disease (AD) is the most common cause of dementia. Effective connectivity (EC) methods signify the direction of brain interactions. The identified inter-system mappings can be helpful in characterizing the pathophysiology of the disease.</p></div><div><h3>Methods and Results</h3><p>We conducted a systematic review of the alterations in EC findings in individuals with AD or Mild Cognitive Impairment (MCI) from PubMed, Scopus, and Google Scholar from fMRI studies. We extracted EC alterations and altered network findings related to specific cognitive impairments. Additionally, we brought a narrative synthesis on the clinical-pathologic relevance of the utilized computational methods. Thirty-nine studies retrieved from the full-text screening. A general pattern of disconnection in several hub centers and changes in inter-network interactions was identified.</p></div><div><h3>Conclusion</h3><p>In summary, this study demonstrated the beneficial role of EC analyses and network measures in understanding the pathophysiology of AD. Future studies are needed to bring out methodologically consistent data for more structured meta-analytic views.</p></div>\",\"PeriodicalId\":74295,\"journal\":{\"name\":\"Neuroscience informatics\",\"volume\":\"2 4\",\"pages\":\"Article 100104\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2772528622000668/pdfft?md5=4b2fd13b687332fa0a4be378f10b8576&pid=1-s2.0-S2772528622000668-main.pdf\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neuroscience informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772528622000668\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuroscience informatics","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772528622000668","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

阿尔茨海默病(AD)是痴呆症最常见的病因。有效连接(Effective connectivity, EC)方法表明了大脑相互作用的方向。确定的系统间映射可以帮助表征疾病的病理生理学。方法和结果我们从PubMed、Scopus和Google Scholar的fMRI研究中对AD或轻度认知障碍(MCI)患者EC发现的变化进行了系统回顾。我们提取了与特定认知障碍相关的EC改变和改变的网络发现。此外,我们带来了一个叙事综合的临床病理相关的利用计算方法。从全文筛选中检索到39项研究。确定了几个枢纽中心的一般断开模式和网络间相互作用的变化。综上所述,本研究证明了EC分析和网络测量在了解AD病理生理方面的有益作用。未来的研究需要为更结构化的元分析观点提供方法上一致的数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effective connectivity in individuals with Alzheimer's disease and mild cognitive impairment: A systematic review

Background

Alzheimer's disease (AD) is the most common cause of dementia. Effective connectivity (EC) methods signify the direction of brain interactions. The identified inter-system mappings can be helpful in characterizing the pathophysiology of the disease.

Methods and Results

We conducted a systematic review of the alterations in EC findings in individuals with AD or Mild Cognitive Impairment (MCI) from PubMed, Scopus, and Google Scholar from fMRI studies. We extracted EC alterations and altered network findings related to specific cognitive impairments. Additionally, we brought a narrative synthesis on the clinical-pathologic relevance of the utilized computational methods. Thirty-nine studies retrieved from the full-text screening. A general pattern of disconnection in several hub centers and changes in inter-network interactions was identified.

Conclusion

In summary, this study demonstrated the beneficial role of EC analyses and network measures in understanding the pathophysiology of AD. Future studies are needed to bring out methodologically consistent data for more structured meta-analytic views.

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
Neuroscience informatics
Neuroscience informatics Surgery, Radiology and Imaging, Information Systems, Neurology, Artificial Intelligence, Computer Science Applications, Signal Processing, Critical Care and Intensive Care Medicine, Health Informatics, Clinical Neurology, Pathology and Medical Technology
自引率
0.00%
发文量
0
审稿时长
57 days
×
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