Evidence map›Paper›PMID 38770525›Full record

ArticleFrontiers in neurology2024

EEG biomarkers analysis in different cognitive impairment after stroke: an exploration study.

Mengxue Xu, Yucheng Zhang, Yue Zhang, Xisong Liu, Kunqiang Qing

Abstract read
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Article in Frontiers in neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

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7citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Resting-state EEG markers of cognitive dysfunction in epilepsy: evidence from gamma power, alpha activity, and functional connectivity.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026
    Article
  4. Review
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  7. Article
4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Mengxue Xu *Department of Neurology, Chongqing Public Healthy Medical Center, Chongqing, China.
Yucheng Zhang *Department of Mathematics, College of Natural Sciences, University of Texas at Austin, Austin, TX, United States.
Yue ZhangDepartment of Psychology, School of Psychology, Shenzhen University, Shenzhen, China.
Xisong LiuIntensive Care Unit, Chongqing Public Healthy Medical Center, Chongqing, China.
Kunqiang QingAutomotive Software Innovation Center, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Stroke is a cerebrovascular illness that brings about the demise of brain tissue. It is the third most prevalent cause of mortality worldwide and a significant contributor to physical impairment. Generally, stroke is triggered by blood clots obstructing the brain's blood vessels, or when these vessels rupture. And, the cognitive impairment's evaluation and detection after stroke is crucial research issue and significant project. Thus, the objective of this work is to explore an potential neuroimage tool and find their EEG biomarkers to evaluate and detect four cognitive impairment levels after stroke. In this study, power density spectrum (PSD), functional connectivity map, and one-way ANOVA methods were proposed to analyze the EEG biomarker differences, and the number of patient participants were thirty-two human including eight healthy control, mild, moderate, severe cognitive impairment levels, respectively. Finally, healthy control has significant PSD differences compared to mid, moderate and server cognitive impairment groups. And, the theta and alpha bands of severe cognitive impairment groups have presented consistent superior PSD power at the right frontal cortex, and the theta and beta bands of mild, moderated cognitive impairment (MoCI) groups have shown significant similar superior PSD power tendency at the parietal cortex. The significant gamma PSD power difference has presented at the left-frontal cortex in the mild cognitive impairment (MCI) groups, and severe cognitive impairment (SeCI) group has shown the significant PSD power at the gamma band of parietal cortex. At the point of functional connectivity map, the SeCI group appears to have stronger functional connectivity compared to the other groups. In conclusion, EEG biomarkers can be applied to classify different cognitive impairment groups after stroke. These findings provide a new approach for early detection and diagnosis of cognitive impairment after stroke and also for the development of new treatment options.

Indexed as

cognitive impairmentEEGfunctional connectivityPSDstroke

Identifiers

PMID38770525
PMCPMC11104451

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.