Evidence map›Paper›PMID 38965489›Full record

ArticleBMC neuroscience2024

Changes of brain functional network in Alzheimer's disease and frontotemporal dementia: a graph-theoretic analysis.

Shijing Wu, Ping Zhan, Guojing Wang, Xiaohua Yu, Hongyun Liu, Weidong Wang

Abstract read
In one paragraph

Article in BMC neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–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

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

6 authors.

Shijing WuMedical Innovation Research Division, Chinese PLA General Hospital, Beijing, 100853, China.
Ping ZhanMedical Innovation Research Division, Chinese PLA General Hospital, Beijing, 100853, China.
Guojing WangMedical Innovation Research Division, Chinese PLA General Hospital, Beijing, 100853, China.
Xiaohua YuMedical Innovation Research Division, Chinese PLA General Hospital, Beijing, 100853, China.
Hongyun LiuMedical Innovation Research Division, Chinese PLA General Hospital, Beijing, 100853, China. ylooliu@163.com.
Weidong WangMedical Innovation Research Division, Chinese PLA General Hospital, Beijing, 100853, China. wangwd301@126.com.

Funding

National Key Research and Development Program of China 2022YFC2402202
6 · The paper itself

Abstract

backgroundAlzheimer's disease (AD) and frontotemporal dementia (FTD) are the two most common neurodegenerative dementias, presenting with similar clinical features that challenge accurate diagnosis. Despite extensive research, the underlying pathophysiological mechanisms remain unclear, and effective treatments are limited. This study aims to investigate the alterations in brain network connectivity associated with AD and FTD to enhance our understanding of their pathophysiology and establish a scientific foundation for their diagnosis and treatment.

methodsWe analyzed preprocessed electroencephalogram (EEG) data from the OpenNeuro public dataset, comprising 36 patients with AD, 23 patients with FTD, and 29 healthy controls (HC). Participants were in a resting state with eyes closed. We estimated the average functional connectivity using the Phase Lag Index (PLI) for lower frequencies (delta and theta) and the Amplitude Envelope Correlation with leakage correction (AEC-c) for higher frequencies (alpha, beta, and gamma). Graph theory was applied to calculate topological parameters, including mean node degree, clustering coefficient, characteristic path length, global and local efficiency. A permutation test was then utilized to assess changes in brain network connectivity in AD and FTD based on these parameters.

resultsBoth AD and FTD patients showed increased mean PLI values in the theta frequency band, along with increases in average node degree, clustering coefficient, global efficiency, and local efficiency. Conversely, mean AEC-c values in the alpha frequency band were notably diminished, which was accompanied by decreases average node degree, clustering coefficient, global efficiency, and local efficiency. Furthermore, AD patients in the occipital region showed an increase in theta band node degree and decreased alpha band clustering coefficient and local efficiency, a pattern not observed in FTD.

conclusionsOur findings reveal distinct abnormalities in the functional network topology and connectivity in AD and FTD, which may contribute to a better understanding of the pathophysiological mechanisms of these diseases. Specifically, patients with AD demonstrated a more widespread change in functional connectivity, while those with FTD retained connectivity in the occipital lobe. These observations could provide valuable insights for developing electrophysiological markers to differentiate between the two diseases.

Indexed as

Alzheimer DiseaseBrainElectroencephalographyFrontotemporal DementiaAgedFemaleHumansMaleMiddle AgedNerve NetNeural PathwaysAlzheimer’s diseaseEEGFrontotemporal dementiaFunctional connectivityGraph-theoretic analysis

Identifiers

PMID38965489
PMCPMC11223280

What OpenQuestion holds

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LicenceCC BY
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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.