Evidence map›Paper›PMID 35142691›Full record

ArticleNeural regeneration research2022

Abnormal characterization of dynamic functional connectivity in Alzheimer's disease.

Cui Zhao, Wei-Jie Huang, Feng Feng, Bo Zhou, Hong-Xiang Yao, Yan-E Guo, Pan Wang, Lu-Ning Wang, Ni Shu, Xi Zhang

Abstract read
In one paragraph

Article in Neural regeneration research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing 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

38 citing papers in PubMed.

  1. Article
  2. Ecologically-Valid Emotion Signatures Enhance Mood Disorder Diagnostics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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  9. Topological and geometric signatures of brain network dynamics in Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Article
  10. Article
  11. Dynamic functional connectivity is modulated by the amount of p-Tau231 in blood in cognitively intact participants.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2025
    Article
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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.

Cui ZhaoDepartment of Neurology, Second Medical Center, National Clinical Research Center for Geriatric Disease, Chinese PLA General Hospital, Beijing; Department of Geriatrics, Affiliated Hospital of Chengde Medical University, Chengde, Hebei Province, China.
Wei-Jie HuangState Key Laboratory of Cognitive Neuroscience and Learning; Center for Collaboration and Innovation in Brain and Learning Sciences; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China.
Feng FengDepartment of Neurology, First Medical Center, Chinese PLA General Hospital; Department of Neurology, PLA Rocket Force Characteristic Medical Center, Beijing, China.
Bo ZhouDepartment of Neurology, Second Medical Center, National Clinical Research Center for Geriatric Disease, Chinese PLA General Hospital, Beijing, China.
Hong-Xiang YaoDepartment of Radiology, Second Medical Center, Chinese PLA General Hospital, Beijing, China.
Yan-E GuoDepartment of Neurology, Second Medical Center, National Clinical Research Center for Geriatric Disease, Chinese PLA General Hospital, Beijing, China.
Pan WangDepartment of Neurology, Tianjin Huanhu Hospital, Tianjin, China.
Lu-Ning WangDepartment of Neurology, Second Medical Center, National Clinical Research Center for Geriatric Disease, Chinese PLA General Hospital, Beijing, China.
Ni ShuState Key Laboratory of Cognitive Neuroscience and Learning; Center for Collaboration and Innovation in Brain and Learning Sciences; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China.
Xi ZhangDepartment of Neurology, Second Medical Center, National Clinical Research Center for Geriatric Disease, Chinese PLA General Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Numerous studies have shown abnormal brain functional connectivity in individuals with Alzheimer's disease (AD) or amnestic mild cognitive impairment (aMCI). However, most studies examined traditional resting state functional connections, ignoring the instantaneous connection mode of the whole brain. In this case-control study, we used a new method called dynamic functional connectivity (DFC) to look for abnormalities in patients with AD and aMCI. We calculated dynamic functional connectivity strength from functional magnetic resonance imaging data for each participant, and then used a support vector machine to classify AD patients and normal controls. Finally, we highlighted brain regions and brain networks that made the largest contributions to the classification. We found differences in dynamic function connectivity strength in the left precuneus, default mode network, and dorsal attention network among normal controls, aMCI patients, and AD patients. These abnormalities are potential imaging markers for the early diagnosis of AD.

Indexed as

Alzheimer’s diseaseamnestic mild cognitive impairmentblood oxygen level-dependentdefault mode networkdynamic functional connectivityfrontoparietal networkresting-state functional magnetic resonance imagingsupport vector machine

Identifiers

PMID35142691
PMCPMC8848607

What OpenQuestion holds

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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.