Hesun Erin Kim , Jae-Jin Kim , Jeong-Ho Seok , Jin Young Park , Jooyoung Oh
{"title":"Resting-state functional connectivity and cognitive performance in aging adults with cognitive decline: A data-driven multivariate pattern analysis","authors":"Hesun Erin Kim , Jae-Jin Kim , Jeong-Ho Seok , Jin Young Park , Jooyoung Oh","doi":"10.1016/j.comppsych.2023.152445","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Cognitive impairments occur on a continuous spectrum in multiple cognitive domains showing individual variability of the deteriorating patterns; however, often, cognitive domains are studied separately.</p></div><div><h3>Methods</h3><p>The present study investigated aging individual variations of cognitive abilities and related resting-state functional connectivity (rsFC) using data-driven approach. Cognitive and neuroimaging data were obtained from 62 elderly outpatients with cognitive decline. Principal component analysis (PCA) was conducted on the cognitive data to determine patterns of cognitive performance, then data-driven whole-brain connectome multivariate pattern analysis (MVPA) was applied on the neuroimaging data to discover neural regions associated with the cognitive characteristic.</p></div><div><h3>Results</h3><p>The first component (PC1) delineated an overall decline in all domains of cognition, and the second component (PC2) represented a compensatory relationship within basic cognitive functions. MVPA indicated rsFC of the cerebellum lobule VIII and insula with the default-mode network, frontoparietal network, and salience network inversely correlated with PC1 scores. Additionally, PC2 score was related to rsFC patterns with temporal pole and occipital cortex.</p></div><div><h3>Conclusions</h3><p>The featured primary cognitive characteristic depicted the importance of the cerebellum and insula connectivity patterns in of the general cognitive decline. The findings also discovered a secondary characteristic that communicated impaired interactions within the basic cognitive function, which was independent from the impairment severity.</p></div>","PeriodicalId":10554,"journal":{"name":"Comprehensive psychiatry","volume":"129 ","pages":"Article 152445"},"PeriodicalIF":4.3000,"publicationDate":"2023-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0010440X23000822/pdfft?md5=fb6be91a3903675bc1baa9cc2d76a2aa&pid=1-s2.0-S0010440X23000822-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Comprehensive psychiatry","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0010440X23000822","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHIATRY","Score":null,"Total":0}
引用次数: 0
Abstract
Background
Cognitive impairments occur on a continuous spectrum in multiple cognitive domains showing individual variability of the deteriorating patterns; however, often, cognitive domains are studied separately.
Methods
The present study investigated aging individual variations of cognitive abilities and related resting-state functional connectivity (rsFC) using data-driven approach. Cognitive and neuroimaging data were obtained from 62 elderly outpatients with cognitive decline. Principal component analysis (PCA) was conducted on the cognitive data to determine patterns of cognitive performance, then data-driven whole-brain connectome multivariate pattern analysis (MVPA) was applied on the neuroimaging data to discover neural regions associated with the cognitive characteristic.
Results
The first component (PC1) delineated an overall decline in all domains of cognition, and the second component (PC2) represented a compensatory relationship within basic cognitive functions. MVPA indicated rsFC of the cerebellum lobule VIII and insula with the default-mode network, frontoparietal network, and salience network inversely correlated with PC1 scores. Additionally, PC2 score was related to rsFC patterns with temporal pole and occipital cortex.
Conclusions
The featured primary cognitive characteristic depicted the importance of the cerebellum and insula connectivity patterns in of the general cognitive decline. The findings also discovered a secondary characteristic that communicated impaired interactions within the basic cognitive function, which was independent from the impairment severity.
期刊介绍：
"Comprehensive Psychiatry" is an open access, peer-reviewed journal dedicated to the field of psychiatry and mental health. Its primary mission is to share the latest advancements in knowledge to enhance patient care and deepen the understanding of mental illnesses. The journal is supported by a diverse team of international editors and peer reviewers, ensuring the publication of high-quality research with a strong focus on clinical relevance and the implications for psychopathology.
"Comprehensive Psychiatry" encourages authors to present their research in an accessible manner, facilitating engagement with clinicians, policymakers, and the broader public. By embracing an open access policy, the journal aims to maximize the global impact of its content, making it readily available to a wide audience and fostering scientific collaboration and public awareness beyond the traditional academic community. This approach is designed to promote a more inclusive and informed dialogue on mental health, contributing to the overall progress in the field.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
