Evidence map›Paper›PMID 41126224›Full record

ArticleJournal of neuroengineering and rehabilitation2025

Disruption of low-frequency narrowband EEG microstate networks in Parkinson's disease with mild cognitive impairment.

Guangying Pei, Mengxuan Hu, Yiliu He, Xiao Yang, Han Liu, Bo Jiang, Qi Xie, Qi Zhu, Boyan Fang, Tianyi Yan

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In one paragraph

Article in Journal of neuroengineering and rehabilitation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Guangying PeiSchool of Medical Technology, Beijing Institute of Technology, No. 5 Zhongguancun South Street, Haidian District, Beijing, 100144, China.
Mengxuan HuSchool of Medical Technology, Beijing Institute of Technology, No. 5 Zhongguancun South Street, Haidian District, Beijing, 100144, China.
Yiliu HeSchool of Medical Technology, Beijing Institute of Technology, No. 5 Zhongguancun South Street, Haidian District, Beijing, 100144, China.
Xiao YangSchool of Medical Technology, Beijing Institute of Technology, No. 5 Zhongguancun South Street, Haidian District, Beijing, 100144, China.
Han LiuSchool of Medical Technology, Beijing Institute of Technology, No. 5 Zhongguancun South Street, Haidian District, Beijing, 100144, China.
Bo JiangSchool of Medical Technology, Beijing Institute of Technology, No. 5 Zhongguancun South Street, Haidian District, Beijing, 100144, China.
Qi XieSchool of Medical Technology, Beijing Institute of Technology, No. 5 Zhongguancun South Street, Haidian District, Beijing, 100144, China.
Qi ZhuSchool of Medical Technology, Beijing Institute of Technology, No. 5 Zhongguancun South Street, Haidian District, Beijing, 100144, China.
Boyan FangParkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Badachu, Xixiazhuang, Shijingshan District, Beijing, 100144, China. fangboyanv@ccmu.edu.cn.
Tianyi YanSchool of Medical Technology, Beijing Institute of Technology, No. 5 Zhongguancun South Street, Haidian District, Beijing, 100144, China. yantianyi@bit.edu.cn.

Funding

National Natural Science Foundation of China 62336002National Natural Science Foundation of China 82202291Natural Science Foundation of Beijing Municipality 7242274STI 2030-Major Projects 2022ZD0208500
6 · The paper itself

Abstract

backgroundElectroencephalogram (EEG) microstates provide insights into large-scale brain network coordination, revealing distinct neural dynamics within specific frequency bands associated with cognitive processes and neurological disorders. Critical gaps remain regarding the abnormalities of narrowband microstate networks in Parkinson's disease with mild cognitive impairment (PD-MCI), a key prodromal stage of the development of PD dementia. Given the importance of early detection and understanding of cognitive decline in PD-MCI, this study investigated whether alterations in narrowband EEG microstate networks could serve as early electrophysiological biomarkers for cognitive decline in PD-MCI.

methodForty-seven individuals with PD (21 with MCI and 26 cognitively normal [PD-NC]) and 20 healthy controls were recruited. For both broadband and narrowband EEG microstates, the phase lag index was used to construct microstate brain networks, and their spatiotemporal variability was assessed.

resultsMicrostate analysis revealed significant divergence in narrowband parameters exclusively between the PD-MCI and PD-NC cohorts. PD-MCI showed a significant increase in low-frequency (delta/alpha-band) microstate class A, while delta-band microstate class D exhibited a significant reduction. The microstate network patterns of PD-MCI were characterized by diminished stability and disrupted synchronization in delta microstate class A within the frontal region, theta microstate class D within central region, and theta microstate class B within the occipital region. These neurophysiological markers specific to PD-MCI were significantly correlated with Montreal Cognitive Assessment scores, and machine learning-based analyses further validated their diagnostic efficacy, with accuracy ranging from 94 to 98%.

conclusionsThis study identified unique abnormalities in narrowband microstate dynamics within neural networks of individuals with PD-MCI, revealing promising electrophysiological markers for the early detection and longitudinal monitoring of cognitive decline. Furthermore, these findings suggest potential applications in precision rehabilitation, whereby frequency-specific microstate biomarkers could guide individualized interventions and monitor therapeutic efficacy.

Indexed as

BrainCognitive DysfunctionElectroencephalographyNerve NetParkinson DiseaseAgedFemaleHumansMaleMiddle AgedCognitionEEG microstate networkLow-frequency oscillationParkinson’s disease with mild cognitive impairment

Identifiers

PMID41126224
PMCPMC12542164

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LicenceCC BY-NC-ND
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Registered trials

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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.