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

Author(s):  
Chen Xue ◽  
Wenzhang Qi ◽  
Qianqian Yuan ◽  
Guanjie Hu ◽  
Honglin Ge ◽  
...  

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.

2021 ◽  
Vol 13 ◽  
Author(s):  
Chen Xue ◽  
Wenzhang Qi ◽  
Qianqian Yuan ◽  
Guanjie Hu ◽  
Honglin Ge ◽  
...  

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.


2021 ◽  
Author(s):  
Chen Xue ◽  
Wenzhang Qi ◽  
Qianqian Yuan ◽  
Guanjie Hu ◽  
Honglin Ge ◽  
...  

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.


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