scholarly journals Disrupted dynamic functional connectivity in distinguishing subjective cognitive decline and amnestic mild cognitive impairment based on the triple-network model

2021 ◽  
Author(s):  
Chen Xue ◽  
Wenzhang Qi ◽  
Qianqian Yuan ◽  
Guanjie Hu ◽  
Honglin Ge ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Cognitive Impairment ◽  
Executive Function ◽  
Mild Cognitive Impairment ◽  
Functional Connectivity ◽  
Episodic Memory ◽  
Amnestic Mild Cognitive Impairment ◽  
Subjective Cognitive Decline ◽  
Preclinical Ad

Abstract Background Subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) were wildly thought to be preclinical AD spectrum, who characterized by aberrant functional connectivity (FC) within the triple networks involving the default mode network (DMN), the salience network (SN), and the executive control network (ECN). Dynamic FC (DFC) analysis can capture the temporal fluctuation of brain FC during the scan that static FC analysis cannot provide. The purpose of the current study was to explore the changes of dynamic FC within the triple networks of preclinical AD spectrum, and further reveal its potential diagnostic value in the preclinical AD spectrum. Methods We collected resting-state functional magnetic resonance imaging data from 44 SCD, 49 aMCI, and 58 controls (HC). DFC analysis based on the sliding time-window correlation method were used to analyze the DFC variability within the triple networks among three groups. Then the correlation analysis was conducted to reveal the relationship between the altered DFC variability within the triple networks and the declined cognitive function. Furthermore, the logistic regression analysis was used to assess the diagnostic accuracy of altered DFC variability within the triple networks in SCD and aMCI. Results Compared to HC, SCD and aMCI both showed altered DFC variability within the triple networks. The DFC variability in the right middle temporal gyrus and left inferior frontal gyrus (IFG) within ECN were significantly different between SCD and aMCI. Moreover, the altered DFC variability in the left IFG within ECN was obviously associated with the decline in episodic memory and executive function. Last but not least, the logistic regression analysis showed multivariable analysis had high sensitivity and specificity in the diagnosis of SCD and aMCI. Conclusions SCD and aMCI showed similar and distinct trends in the DFC variability within the triple networks and the altered DFC variability within ECN involved episodic memory and executive function. More importantly, the altered DFC variability and triple-network model proved to be an important biomarker to diagnosis and identification of preclinical AD spectrum.

scholarly journals Disrupted Dynamic Functional Connectivity in Distinguishing Subjective Cognitive Decline and Amnestic Mild Cognitive Impairment Based on the Triple-Network Model

2021 ◽  
Vol 13 ◽  
Author(s):  
Chen Xue ◽  
Wenzhang Qi ◽  
Qianqian Yuan ◽  
Guanjie Hu ◽  
Honglin Ge ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Functional Connectivity ◽  
Cognitive Decline ◽  
Amnestic Mild Cognitive Impairment ◽  
Subjective Cognitive Decline ◽  
Preclinical Ad ◽  
Spectrum Disorders

Background: Subjective cognitive decline and amnestic mild cognitive impairment (aMCI) were widely thought to be preclinical AD spectrum disorders, characterized by aberrant functional connectivity (FC) within the triple networks of the default mode network (DMN), the salience network (SN), and the executive control network (ECN). Dynamic FC (DFC) analysis can capture temporal fluctuations in brain FC during the scan, which static FC analysis cannot. The purpose of the current study was to explore the changes in dynamic FC within the triple networks of the preclinical AD spectrum and further reveal their potential diagnostic value in diagnosing preclinical AD spectrum disorders.Methods: We collected resting-state functional magnetic resonance imaging data from 44 patients with subjective cognitive decline (SCD), 49 with aMCI, and 58 healthy controls (HCs). DFC analysis based on the sliding time-window correlation method was used to analyze DFC variability within the triple networks in the three groups. Then, correlation analysis was conducted to reveal the relationship between altered DFC variability within the triple networks and a decline in cognitive function. Furthermore, logistic regression analysis was used to assess the diagnostic accuracy of altered DFC variability within the triple networks in patients with SCD and aMCI.Results: Compared with the HC group, the groups with SCD and aMCI both showed altered DFC variability within the triple networks. DFC variability in the right middle temporal gyrus and left inferior frontal gyrus (IFG) within the ECN were significantly different between patients with SCD and aMCI. Moreover, the altered DFC variability in the left IFG within the ECN was obviously associated with a decline in episodic memory and executive function. The logistic regression analysis showed that multivariable analysis had high sensitivity and specificity for diagnosing SCD and aMCI.Conclusions: Subjective cognitive decline and aMCI showed varying degrees of change in DFC variability within the triple networks and altered DFC variability within the ECN involved episodic memory and executive function. More importantly, altered DFC variability and the triple-network model proved to be important biomarkers for diagnosing and identifying patients with preclinical AD spectrum disorders.

scholarly journals Disrupted Dynamic Functional Connectivity in Distinguishing Subjective Cognitive Decline and Amnestic Mild Cognitive Impairment Based on the Triple-Network Model

2021 ◽  
Author(s):  
Chen Xue ◽  
Wenzhang Qi ◽  
Qianqian Yuan ◽  
Guanjie Hu ◽  
Honglin Ge ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Functional Connectivity ◽  
Cognitive Decline ◽  
Network Model ◽  
Logistic Regression Analysis ◽  
Amnestic Mild Cognitive Impairment ◽  
Subjective Cognitive Decline

Abstract Aberrant static functional connectivity (FC) within the triple networks involving the default mode network (DMN), the salience network (SN), and the executive control network (ECN) was found in subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI). However, dynamic FC (DFC) analysis within triple networks of SCD and aMCI was absent. We collected resting-state functional magnetic resonance imaging data from 44 SCD, 49 aMCI, and 58 controls (HC). DFC analysis were used to analyze the DFC variability within the triple networks among three groups. Then the correlation analysis was conducted to reveal the relationship between the altered DFC variability within the triple networks and the declined cognitive function. Furthermore, the logistic regression analysis was used to assess the diagnostic accuracy of altered DFC variability within the triple networks in SCD and aMCI. Compared to HC, SCD and aMCI both showed altered DFC variability within the triple networks. The DFC variability in the right middle temporal gyrus and left inferior frontal gyrus (IFG) within ECN were significantly different between SCD and aMCI. Moreover, the altered DFC variability in the left IFG within ECN was obviously associated with the decline in episodic memory and executive function. Lastly, the logistic regression analysis showed multivariable analysis had high sensitivity and specificity in the diagnosis of SCD and aMCI. The altered DFC variability and triple-network model proved to be an important biomarker to diagnosis and identification of preclinical AD spectrum.

Joint effects of gray matter atrophy and altered functional connectivity on cognitive deficits in amnestic mild cognitive impairment patients

2014 ◽  
Vol 45 (9) ◽  
pp. 1799-1810 ◽  
Author(s):  
C. Xie ◽  
F. Bai ◽  
B. Yuan ◽  
H. Yu ◽  
Y. Shi ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Functional Connectivity ◽  
Episodic Memory ◽  
Cognitive Performance ◽  
Gray Matter ◽  
Cognitive Deficits ◽  
Amnestic Mild Cognitive Impairment ◽  
Multivariate Linear Regression Analysis

BackgroundGray matter (GM) atrophy and disrupted intrinsic functional connectivity (IFC) are often present in patients with amnestic mild cognitive impairment (aMCI), which shows high risk of developing into Alzheimer's disease. Little is known, however, about the relationship between GM atrophy and altered IFC, and whether they are related to cognitive decline.MethodA total of 30 aMCI and 26 cognitively normal (CN) subjects were recruited for this study. Optimized voxel-based morphometric and resting-state functional connectivity magnetic resonance imaging approaches were performed to measure the GM volumes (GMVs) and atrophy-related IFC, respectively. Multivariate linear regression analysis was used to examine the effects of GM atrophy and IFC on cognitive performance across subjects, after controlling for the effects of age, education, gender and group.ResultsCompared with CN subjects, aMCI subjects showed significantly reduced GMVs and decreased IFC in the frontal-parietal and medial temporal lobe systems. Multivariate regression analysis further demonstrated that the GMVs and decreased IFC simultaneously affected the cognitive function. Specifically, GMVs were positively correlated with cognitive performances, including global cognition and episodic memory, and showed a strong trend in correlation between GMVs and non-episodic memory, whilst IFC was positively correlated with the above three cognitive measures, across all subjects. In addition, significant correlation was found between GMVs and altered IFC strength across all subjects.ConclusionsOur findings demonstrated that GMVs and IFC jointly contribute to cognitive performance, and combining quantitative information about GMVs and the strength of functional connectivity may serve as an indicator of cognitive deficits in non-demented elderly.

Naturalistic Action Performance Distinguishes Amnestic Mild Cognitive Impairment from Healthy Aging

2015 ◽  
Vol 21 (6) ◽  
pp. 419-428 ◽  
Author(s):  
David A. Gold ◽  
Norman W. Park ◽  
Kelly J. Murphy ◽  
Angela K. Troyer
Keyword(s):  
Differential Diagnosis ◽  
Cognitive Impairment ◽  
Executive Function ◽  
Mild Cognitive Impairment ◽  
Episodic Memory ◽  
Healthy Aging ◽  
Group Membership ◽  
Binary Logistic Regression ◽  
Semantic Knowledge ◽  
Amnestic Mild Cognitive Impairment

AbstractIndividuals with amnestic mild cognitive impairment (aMCI) show minor decrements in their instrumental activities of daily living (IADL). Sensitive measures of IADL performance are needed to capture the mild difficulties observed in aMCI groups. Routine naturalistic actions (NAs) are familiar IADL-type activities that require individuals to enact everyday tasks such as preparing coffee. In the current study we examined the extent to which NAs could be used to help facilitate differential diagnosis of aMCI relative to composite measures of episodic memory, semantic knowledge, and executive function. Healthy older adults (n=24) and individuals with aMCI (n=24) enacted two highly familiar NAs and completed tests of episodic memory, semantic knowledge, and executive function. Binary logistic regression was used to predict group membership (aMCI vs. control participants). The regression analyses indicated that NA performance could reliably predict group membership, over and above measures of cognitive functioning. These findings indicated that NA performance can be used to help facilitate differential diagnosis of healthy aging and aMCI and used as an outcome measure in intervention studies. (JINS, 2015, 21, 419–428)

scholarly journals Lateralized Contributions of Medial Prefrontal Cortex Network to Episodic Memory Deficits in Subjects With Amnestic Mild Cognitive Impairment

2021 ◽  
Vol 13 ◽  
Author(s):  
Qing Ye ◽  
Haifeng Chen ◽  
Renyuan Liu ◽  
Ruomeng Qin ◽  
Caimei Luo ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Prefrontal Cortex ◽  
Executive Function ◽  
Mild Cognitive Impairment ◽  
Episodic Memory ◽  
Medial Prefrontal Cortex ◽  
Memory Deficits ◽  
Amnestic Mild Cognitive Impairment ◽  
Hippocampal Networks ◽  
The Right

Both episodic memory and executive function are impaired in amnestic mild cognitive impairment (aMCI) subjects, but it is unclear if these impairments are independent or interactive. The present study aimed to explore the relationship between episodic memory deficits and executive function deficits, and the underlying functional mechanisms in aMCI subjects. Thirty-one aMCI subjects and 27 healthy subjects underwent neuropsychological tests and multimodal magnetic resonance imaging (MRI) scans. Hippocampal networks and medial prefrontal cortex (MPFC) networks were identified based on resting-sate functional MRI (fMRI) data. AMCI subjects displayed lower episodic memory scores and executive function scores than control subjects, and the episodic memory scores were positively correlated with the executive function scores in aMCI subjects. Brain network analyses showed an interaction between the hippocampal networks and the MPFC networks, and the interaction was significantly associated with the episodic memory scores and the executive function scores. Notably, aMCI subjects displayed higher functional connectivity (FC) of the right hippocampal network with the right prefrontal cortex than did control subjects, but this difference disappeared when controlling for the MPFC networks. Furthermore, the effects of the MPFC networks on the hippocampal networks were significantly associated with the episodic memory scores in aMCI subjects. The present findings suggested that the episodic memory deficits in aMCI subjects could be partially underpinned by the modulation of the MPFC networks on the hippocampal networks.

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