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.

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 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.

Early Microstructure Changes of White Matter Fiber Bundles in Patients with Amnestic Mild Cognitive Impairment Predicts Progression of Mild Cognitive Impairment to Alzheimer’s Disease

2021 ◽  
pp. 1-14
Author(s):  
Fangmei He ◽  
Yuchen Zhang ◽  
Xiaofeng Wu ◽  
Youjun Li ◽  
Jie Zhao ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
White Matter ◽  
Brain Regions ◽  
Amnestic Mild Cognitive Impairment ◽  
Microstructure Changes ◽  
Disease Trajectory ◽  
Development Trajectory ◽  
The Right

Background: Amnestic mild cognitive impairment (aMCI) is the transitional stage between normal aging and Alzheimer’s disease (AD). Some aMCI patients will progress into AD eventually, whereas others will not. If the trajectory of aMCI can be predicted, it would enable early diagnosis and early therapy of AD. Objective: To explore the development trajectory of aMCI patients, we used diffusion tensor imaging to analyze the white matter microstructure changes of patients with different trajectories of aMCI. Methods: We included three groups of subjects:1) aMCI patients who convert to AD (MCI-P); 2) aMCI patients who remain in MCI status (MCI-S); 3) normal controls (NC). We analyzed the fractional anisotropy and mean diffusion rate of brain regions, and we adopted logistic binomial regression model to predicate the development trajectory of aMCI. Results: The fraction anisotropy value is significantly reduced, the mean diffusivity value is significantly increased in the two aMCI patient groups, and the MCI-P patients presented greater changes. Significant changes are mainly located in the cingulum, fornix, hippocampus, and uncinate fasciculus. These changed brain regions significantly correlated with the patient’s Mini-Mental State Examination scores. Conclusion: The study predicted the disease trajectory of different types of aMCI patients based on the characteristic values of the above-mentioned brain regions. The prediction accuracy rate can reach 90.2%, and the microstructure characteristics of the right cingulate band and the right hippocampus may have potential clinical application value to predict the disease trajectory.

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