Using event-related potential P300 as an electrophysiological marker for differential diagnosis and to predict the progression of mild cognitive impairment: a meta-analysis

2015 ◽  
Vol 36 (7) ◽  
pp. 1105-1112 ◽  
Author(s):  
Shixiang Jiang ◽  
Changda Qu ◽  
Fengjun Wang ◽  
Yupeng Liu ◽  
Zhengxue Qiao ◽  
...  
2021 ◽  
pp. 1-30
Author(s):  
Hadeel Y. Tarawneh ◽  
Wilhelmina H.A.M. Mulders ◽  
Hamid R. Sohrabi ◽  
Ralph N. Martins ◽  
Dona M.P. Jayakody

Background: Objectively measuring auditory functions has been proposed as an avenue in differentiating normal age-related cognitive dysfunction from Alzheimer’s disease (AD) and its prodromal states. Previous research has suggested auditory event-related potentials (AERPs) to be non-invasive, cost-effective, and efficient biomarkers for the diagnosis of AD. Objective: The objective of this paper is to review the published literature on AERPs measures in older adults diagnosed with AD and those at higher risk of developing AD, i.e., mild cognitive impairment (MCI) and subjective cognitive decline. Methods: The search was performed on six major electronic databases (Ovid MEDLINE, OVID EMBASE, PsycINFO, PubMed, Scopus, and CINAHL Plus). Articles identified prior to 7 May 2019 were considered for this review. A random effects meta-analysis and analysis of between study heterogeneity was conducted using the Comprehensive Meta-Analysis software. Results: The search identified 1,076 articles; 74 articles met the full inclusion criteria and were included in the systematic review, and 47 articles were included into the analyses. Pooled analysis suggests that AD participants can be differentiated from controls due to significant delays in ABR, N100, P200, N200, and P300 latencies. P300 amplitude was significantly smaller in AD participants compared to controls. P300 latencies differed significantly between MCI participants and controls based on the pooled analysis. Conclusion: The findings of this review indicate that some AERPs may be valuable biomarkers of AD. In conjunction with currently available clinical and neuropsychological assessments, AERPs can aid in screening and diagnosis of prodromal AD.


2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Jiangyi Xia ◽  
Ali Mazaheri ◽  
Katrien Segaert ◽  
David P Salmon ◽  
Danielle Harvey ◽  
...  

Abstract Reliable biomarkers of memory decline are critical for the early detection of Alzheimer’s disease. Previous work has found three EEG measures, namely the event-related brain potential P600, suppression of oscillatory activity in the alpha frequency range (∼10 Hz) and cross-frequency coupling between low theta/high delta and alpha/beta activity, each of which correlates strongly with verbal learning and memory abilities in healthy elderly and patients with mild cognitive impairment or prodromal Alzheimer’s disease. In the present study, we address the question of whether event-related or oscillatory measures, or a combination thereof, best predict the decline of verbal memory in mild cognitive impairment and Alzheimer’s disease. Single-trial correlation analyses show that despite a similarity in their time courses and sensitivities to word repetition, the P600 and the alpha suppression components are minimally correlated with each other on a trial-by-trial basis (generally |rs| < 0.10). This suggests that they are unlikely to stem from the same neural mechanism. Furthermore, event-related brain potentials constructed from bandpass filtered (delta, theta, alpha, beta or gamma bands) single-trial data indicate that only delta band activity (1–4 Hz) is strongly correlated (r = 0.94, P < 0.001) with the canonical P600 repetition effect; event-related potentials in higher frequency bands are not. Importantly, stepwise multiple regression analyses reveal that the three event-related brain potential/oscillatory measures are complementary in predicting California Verbal Learning Test scores (overall R2’s in 0.45–0.63 range). The present study highlights the importance of combining EEG event-related potential and oscillatory measures to better characterize the multiple mechanisms of memory failure in individuals with mild cognitive impairment or prodromal Alzheimer’s disease.


2021 ◽  
Vol 55 (2) ◽  
pp. 79-91
Author(s):  
Yan Deng ◽  
Siqi Zhao ◽  
Guangwen Cheng ◽  
Jiajia Yang ◽  
Benchao Li ◽  
...  

<b><i>Background:</i></b> Mild cognitive impairment (MCI) induced the majority number of dementia patients. The prevalence of MCI in China varied across studies with different screening tools and diagnostic criteria. <b><i>Objective:</i></b> A systematic review and meta-analysis was conducted to estimate the pooled MCI prevalence among the population aged 55 years and older in China. <b><i>Methods:</i></b> PubMed, EMBASE, CNKI, Wanfang, CQVIP, and CBMdisc were searched for studies on prevalence of MCI among Chinese elderly between January 1, 1980, and February 10, 2020. The quality assessment was conducted via external validity, internal validity, and informativity, the pooled prevalence was calculated through the random-effect model, and the homogeneity was evaluated by Cochran’s <i>Q</i> test and <i>I</i><sup>2</sup>. <b><i>Results:</i></b> Fifty-three studies with 123,766 subjects were included. The pooled prevalence of MCI among Chinese elderly was 15.4% (95% CI: 13.5–17.4%). Subgroup analyses indicated that the prevalence calculated with different screening tools was 20.2% (95% CI: 15.1–25.9%) for Montreal Cognitive Assessment (MoCA) and 13.0% (95% CI: 10.7–15.5%) for Mini-Mental State Examination (MMSE). According to different diagnostic criteria, the prevalence was 14.8% (95% CI: 12.2–17.6%) for Petersen criteria, 15.0% (95% CI: 12.7–17.5%) for DSM-IV, and 21.2% (95% CI: 17.5–25.2%) for Chinese Expert Consensus on Cognitive Impairment (CECCI). Besides, women, older adults, illiterate people, rural residents, and those who lived with unhealthy lifestyles and morbidity showed higher prevalence. <b><i>Conclusions:</i></b> The prevalence of MCI in China was 15.4%, which varied by demographics, lifestyles, morbidity, screening tools, and diagnostic criteria. In further studies, screening tools and diagnosis criteria should be considered when estimating MCI prevalence.


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