Investigating Cortical Complexity in Mixed Dementia through Nonlinear Dynamic Analyses: A Resting-State EEG Study.

Q2 Medicine
Harikumar Pallathadka, Zhanna R Gardanova, Ahmed Read Al-Tameemi, Aiman Mohammed Baqir Al-Dhalimy, Eftikhaar Hasan Kadhum, Ahmed Huseen Redhee
{"title":"Investigating Cortical Complexity in Mixed Dementia through Nonlinear Dynamic Analyses: A Resting-State EEG Study.","authors":"Harikumar Pallathadka, Zhanna R Gardanova, Ahmed Read Al-Tameemi, Aiman Mohammed Baqir Al-Dhalimy, Eftikhaar Hasan Kadhum, Ahmed Huseen Redhee","doi":"10.18502/ijps.v19i3.15808","DOIUrl":null,"url":null,"abstract":"<p><p><b>Objective:</b> Dementia is a broad term referring to a decline in problem-solving abilities, language skills, memory, and other cognitive functions to a degree that it significantly disrupts everyday activities. The underlying cause of dementia is the impairment or loss of nerve cells and their connections within the brain. The particular symptoms experienced are contingent upon specific regions of the brain affected by this damage. In this research, we aimed to investigate the nonlinear dynamics of the mixed demented brain compared to healthy subjects using electroencephalogram (EEG) analysis. <b>Method</b> <b>:</b> For this purpose, EEG was recorded from 66 patients with mixed dementia and 65 healthy subjects during rest. After signal preprocessing, sample entropy and Katz fractal dimension analyses were applied to the preprocessed EEG data. Analysis of variance with repeated measures was utilized to compare the nonlinear dynamics of brain activity between dementia and healthy states and partial correlation analysis was employed to explore the relationship between EEG complexity measures and cognitive and neuropsychiatric symptoms of patients. <b>Results:</b> Based on repeated measures ANOVA, there was a significant main effect between groups for both Katz fractal dimension (F = 4.10, P = 0.01) and sample entropy (F = 4.81, P = 0.009) measures. Post hoc comparisons revealed that EEG complexity was significantly reduced in dementia mainly in the occipitoparietal and temporal areas (P < 0.05). MMSE scores were positively correlated with EEG complexity measures, while NPI scores were negatively correlated with EEG complexity measures, mainly in the occipitoparietal and temporal areas (P < 0.05). Moreover, using a KNN classifier, all significant complexity measures yielded the best classification performance with an accuracy of 98.05%, sensitivity of 97.03% and specificity of 99.16% in detecting dementia. <b>Conclusion:</b> This study demonstrated a unique dynamic system within the brain impacted by dementia that results in more predictable patterns of cortical activity mainly in the occipitoparietal and temporal areas. These abnormal patterns were associated with patients' cognitive capacity and neuropsychiatric symptoms.</p>","PeriodicalId":38866,"journal":{"name":"Iranian Journal of Psychiatry","volume":"19 3","pages":"327-336"},"PeriodicalIF":0.0000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11267120/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Iranian Journal of Psychiatry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18502/ijps.v19i3.15808","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0

Abstract

Objective: Dementia is a broad term referring to a decline in problem-solving abilities, language skills, memory, and other cognitive functions to a degree that it significantly disrupts everyday activities. The underlying cause of dementia is the impairment or loss of nerve cells and their connections within the brain. The particular symptoms experienced are contingent upon specific regions of the brain affected by this damage. In this research, we aimed to investigate the nonlinear dynamics of the mixed demented brain compared to healthy subjects using electroencephalogram (EEG) analysis. Method : For this purpose, EEG was recorded from 66 patients with mixed dementia and 65 healthy subjects during rest. After signal preprocessing, sample entropy and Katz fractal dimension analyses were applied to the preprocessed EEG data. Analysis of variance with repeated measures was utilized to compare the nonlinear dynamics of brain activity between dementia and healthy states and partial correlation analysis was employed to explore the relationship between EEG complexity measures and cognitive and neuropsychiatric symptoms of patients. Results: Based on repeated measures ANOVA, there was a significant main effect between groups for both Katz fractal dimension (F = 4.10, P = 0.01) and sample entropy (F = 4.81, P = 0.009) measures. Post hoc comparisons revealed that EEG complexity was significantly reduced in dementia mainly in the occipitoparietal and temporal areas (P < 0.05). MMSE scores were positively correlated with EEG complexity measures, while NPI scores were negatively correlated with EEG complexity measures, mainly in the occipitoparietal and temporal areas (P < 0.05). Moreover, using a KNN classifier, all significant complexity measures yielded the best classification performance with an accuracy of 98.05%, sensitivity of 97.03% and specificity of 99.16% in detecting dementia. Conclusion: This study demonstrated a unique dynamic system within the brain impacted by dementia that results in more predictable patterns of cortical activity mainly in the occipitoparietal and temporal areas. These abnormal patterns were associated with patients' cognitive capacity and neuropsychiatric symptoms.

通过非线性动态分析调查混合型痴呆的皮层复杂性:静息状态脑电图研究
目的:痴呆症是一个广义的术语,指解决问题的能力、语言能力、记忆力和其他认知功能下降,以至于严重影响日常活动。痴呆症的根本原因是大脑神经细胞及其连接功能受损或丧失。所出现的特殊症状取决于受这种损害影响的大脑特定区域。在这项研究中,我们旨在通过脑电图(EEG)分析,研究与健康受试者相比,混合型痴呆大脑的非线性动态变化。方法:为此,我们记录了 66 名混合型痴呆患者和 65 名健康受试者休息时的脑电图。信号预处理后,对预处理的脑电图数据进行样本熵和卡茨分形维度分析。利用重复测量的方差分析比较痴呆症和健康状态下大脑活动的非线性动态,并采用偏相关分析探讨脑电图复杂性测量与患者认知和神经精神症状之间的关系。结果显示基于重复测量方差分析,卡茨分形维度(F = 4.10,P = 0.01)和样本熵(F = 4.81,P = 0.009)测量值在组间存在显著主效应。事后比较显示,痴呆症患者的脑电图复杂性明显降低,主要集中在枕顶区和颞区(P < 0.05)。MMSE 评分与脑电图复杂性呈正相关,而 NPI 评分与脑电图复杂性呈负相关,主要集中在枕顶区和颞区(P < 0.05)。此外,使用 KNN 分类器,所有重要的复杂性指标在检测痴呆症方面的准确率为 98.05%,灵敏度为 97.03%,特异性为 99.16%,分类效果最佳。结论这项研究表明,受痴呆症影响的大脑中存在一个独特的动态系统,该系统主要在枕顶区和颞区产生更可预测的皮层活动模式。这些异常模式与患者的认知能力和神经精神症状有关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Iranian Journal of Psychiatry
Iranian Journal of Psychiatry Medicine-Psychiatry and Mental Health
CiteScore
4.00
自引率
0.00%
发文量
42
审稿时长
4 weeks
×
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