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 ◽  
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 ◽  
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.

scholarly journals Altered Frequency-Dependent Brain Activation and White Matter Integrity Associated With Cognition in Characterizing Preclinical Alzheimer’s Disease Stages

2021 ◽  
Vol 15 ◽  
Author(s):  
Siyu Wang ◽  
Jiang Rao ◽  
Yingying Yue ◽  
Chen Xue ◽  
Guanjie Hu ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
White Matter ◽  
Cognitive Decline ◽  
Brain Activation ◽  
Amnestic Mild Cognitive Impairment ◽  
White Matter Integrity ◽  
Correlation Analyses ◽  
Preclinical Ad

BackgroundSubjective cognitive decline (SCD), non-amnestic mild cognitive impairment (naMCI), and amnestic mild cognitive impairment (aMCI) are regarded to be at high risk of converting to Alzheimer’s disease (AD). Amplitude of low-frequency fluctuations (ALFF) can reflect functional deterioration while diffusion tensor imaging (DTI) is capable of detecting white matter integrity. Our study aimed to investigate the structural and functional alterations to further reveal convergence and divergence among SCD, naMCI, and aMCI and how these contribute to cognitive deterioration.MethodsWe analyzed ALFF under slow-4 (0.027–0.073 Hz) and slow-5 (0.01–0.027 Hz) bands and white matter fiber integrity among normal controls (CN), SCD, naMCI, and aMCI groups. Correlation analyses were further utilized among paired DTI alteration, ALFF deterioration, and cognitive decline.ResultsFor ALFF calculation, ascended ALFF values were detected in the lingual gyrus (LING) and superior frontal gyrus (SFG) within SCD and naMCI patients, respectively. Descended ALFF values were presented mainly in the LING, SFG, middle frontal gyrus, and precuneus in aMCI patients compared to CN, SCD, and naMCI groups. For DTI analyses, white matter alterations were detected within the uncinate fasciculus (UF) in aMCI patients and within the superior longitudinal fasciculus (SLF) in naMCI patients. SCD patients presented alterations in both fasciculi. Correlation analyses revealed that the majority of these structural and functional alterations were associated with complicated cognitive decline. Besides, UF alterations were correlated with ALFF deterioration in the SFG within aMCI patients.ConclusionsSCD shares structurally and functionally deteriorative characteristics with aMCI and naMCI, and tends to convert to either of them. Furthermore, abnormalities in white matter fibers may be the structural basis of abnormal brain activation in preclinical AD stages. Combined together, it suggests that structural and functional integration may characterize the preclinical AD progression.

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