scholarly journals Functional connectivity for discrimination between mild cognitive impairment and subjective cognitive decline in Alzheimer disease: A study on resting‐state EEG rhythms in the Peruvian population

2020 ◽  
Vol 16 (S5) ◽  
Author(s):  
Brenda Nadia Chino Vilca ◽  
Ricardo Bruña Fernández ◽  
Fernando Maestú ◽  
Roxana Castillo Acobo
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Functional Connectivity ◽  
Alzheimer Disease ◽  
Cognitive Decline ◽  
Resting State ◽  
Subjective Cognitive Decline ◽  
Eeg Rhythms

Subjective Cognitive Impairment and Mild Cognitive Impairment (Predementias)

2017 ◽  
Author(s):  
Shashank Beesam ◽  
George Grossberg ◽  
Eric Marin
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Alzheimer Disease ◽  
Cognitive Decline ◽  
Treatment Modalities ◽  
Subjective Cognitive Decline ◽  
Neurocognitive Disorder ◽  
Subjective Cognitive Impairment ◽  
Individualized Care ◽  
Age Related

Alzheimer disease is thought to have an insidious progression, with asymptomatic brain changes occurring decades prior to formal diagnosis. In recent years, efforts have been made to identify and characterize these changes into a spectrum beginning with subjective cognitive decline through the development of major neurocognitive disorder. Through this process, progress has been made into the predictive factors, prevention, and treatment modalities for the various stages of cognitive decline. In addition to pharmacologic therapies, studies have shown the value in physical, mental, social, and spiritual activity combined with support from physicians, family, and caregivers. Furthermore, individualized care, open and honest physician-patient dialogue, and emphasis on lifestyle modifications have been shown to achieve optimal quality of life and may also decrease the rate of cognitive decline. This review contains 5 figures, 5 tables, and 36 references. Key words: age-related cognitive decline, Alzheimer disease, major neurocognitive disorder, mild cognitive impairment, mild neurocognitive disorder, senior moment, subjective cognitive impairment

scholarly journals Resting-state functional reorganisation in Alzheimer’s disease and amnestic mild cognitive impairment: protocol for a systematic review and meta-analysis

BMJ Open ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. e049798
Author(s):  
Diyang Lyu ◽  
Taoran Li ◽  
Xuanxin Lyu
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Decline ◽  
Resting State ◽  
Assessment Tool ◽  
Brain Regions ◽  
Amnestic Mild Cognitive Impairment ◽  
Subjective Cognitive Decline

IntroductionThe incidence of Alzheimer’s disease (AD) is increasing rapidly, causing a growing burden to health and economic worldwide. Several clinical trials in the past decade failed to find solutions, and there remains a lack of an effective treatment. The evidence suggests that early intervention for neurodegeneration would likely be effective in preventing cognitive decline. Cognitive decline in AD occurs continuously over a long period; however, there remains a lack of simple, rapid and accurate approach for diagnosis of amnestic mild cognitive impairment or subjective cognitive decline due to underlying Alzheimer’s pathology. Resting-state functional MRI (rs-fMRI) determines the functional activities of the human brain non-invasively. The amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF) and regional homogeneity (ReHo) are rs-fMRI indicators with high repeatability. They have been studied as early diagnostic imaging markers for other diseases and may be promising markers also for AD.Methods and analysisThe following electronic literature databases will be searched from inception to December 2021: Medline-Ovid, Medline-PubMed, EMBase-Ovid, Cochrane Central and ClinicalTrials.gov. Two independent reviewers will select studies with eligible criteria, extract data and assess the quality of the original studies with our quality assessment tool individually. Missing data will be requested by sending emails to the corresponding authors. Brain regions will be presented for ALFF/fALFF and ReHo by performing activation likelihood estimation with the Seed-based d Mapping-Permutation of subject images V.6.21 software. Meta-regression will be performed to determine the potential brain regions that may strongly correlate with cognitive decline progression. Subgroup analysis, funnel plot, Egger’s test and sensitivity analysis will be conducted to detect and explain potential heterogeneity.Ethics and disseminationThis study does not require formal ethical approval. The findings will be submitted to a peer-review journal.PROSPERO registration numberCRD42021229009.

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 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.

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