Evidence map›Paper›PMID 36831808›Full record

ArticleBrain sciences2023

Effective Connectivity Evaluation of Resting-State Brain Networks in Alzheimer's Disease, Amnestic Mild Cognitive Impairment, and Normal Aging: An Exploratory Study.

Fatemeh Mohammadian, Maryam Noroozian, Arash Zare Sadeghi, Vahid Malekian, Azam Saffar, Mahsa Talebi, Hasan Hashemi, Hanieh Mobarak Salari, Fardin Samadi, Forough Sodaei and 1 more

Open access · goldAbstract read
In one paragraph

Article in Brain sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.3field-weighted citation impact, top 12% of its field
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

5 citing papers in PubMed, 13 citations in OpenAlex.

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  5. Review
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

11 authors at 6 institutions in 2 countries.

Fatemeh MohammadianDepartment of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran 1417613151, Iran.
Maryam NoroozianDepartment of Psychiatry, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran 13185/1741, Iran.
Arash Zare SadeghiMedical Physics Department, Iran University of Medical Sciences, Tehran 1449614535, Iran.ORCID 0000-0002-6558-2158
Vahid MalekianWellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UK.
Azam SaffarDepartment of Biostatistics, Faculty of Paramedical Sciences, Shahid Beheshti Medical University, Tehran 1971653313, Iran.
Mahsa TalebiDepartment of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran 1417613151, Iran.
Hasan HashemiDepartment of Radiology, Advanced Diagnostic and Interventional Radiology Research Center, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran 1417743855, Iran.
Hanieh Mobarak SalariQuantitative Magnetic Resonance Imaging/Spectroscopy Group, Tehran University of Medical Sciences, Tehran 1416753955, Iran.
Fardin SamadiDepartment of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran 1417613151, Iran.
Forough SodaeiDepartment of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran 1417613151, Iran.
Hamidreza Saligheh RadDepartment of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran 1417613151, Iran.
Tehran University of Medical Sciences · IRImam Khomeini Hospital · IRIran University of Medical Sciences · IRRoozbeh Hospital · IRShahid Beheshti University of Medical Sciences · IRWellcome Centre for Human Neuroimaging · GB

Funding

Tehran University of Medical Sciences and Health Services 99-3-101-45445
6 · The paper itself

Abstract

(1) Background: Alzheimer's disease (AD) is a neurodegenerative disease with a high prevalence. Despite the cognitive tests to diagnose AD, there are pitfalls in early diagnosis. Brain deposition of pathological markers of AD can affect the direction and intensity of the signaling. The study of effective connectivity allows the evaluation of intensity flow and signaling pathways in functional regions, even in the early stage, known as amnestic mild cognitive impairment (aMCI). (2) Methods: 16 aMCI, 13 AD, and 14 normal subjects were scanned using resting-state fMRI and T1-weighted protocols. After data pre-processing, the signal of the predefined nodes was extracted, and spectral dynamic causal modeling analysis (spDCM) was constructed. Afterward, the mean and standard deviation of the Jacobin matrix of each subject describing effective connectivity was calculated and compared. (3) Results: The maps of effective connectivity in the brain networks of the three groups were different, and the direction and strength of the causal effect with the progression of the disease showed substantial changes. (4) Conclusions: Impaired information flow in the resting-state networks of the aMCI and AD groups was found versus normal groups. Effective connectivity can serve as a potential marker of Alzheimer's pathophysiology, even in the early stages of the disease.

Indexed as

Alzheimer’s Diseaseamnestic mild cognitive impairmenteffective connectivityresting-state functional MRIspectral dynamic causal modeling

Identifiers

PMID36831808
PMCPMC9954618
OpenAlexW4319317523

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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.