Evidence map›Paper›PMID 30618711›Full record

ArticleFrontiers in aging neuroscience2018

Alterations in Brain Network Topology and Structural-Functional Connectome Coupling Relate to Cognitive Impairment.

Juan Wang, Reza Khosrowabadi, Kwun Kei Ng, Zhaoping Hong, Joanna Su Xian Chong, Yijun Wang, Chun-Yin Chen, Saima Hilal, Narayanaswamy Venketasubramanian, Tien Yin Wong and 3 more

Abstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing 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

50 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

13 authors.

Juan WangCenter for Cognitive Neuroscience, Neuroscience and Behavioral Disorders Program, Duke-National University of Singapore Medical School, Singapore, Singapore.
Reza KhosrowabadiCenter for Cognitive Neuroscience, Neuroscience and Behavioral Disorders Program, Duke-National University of Singapore Medical School, Singapore, Singapore.
Kwun Kei NgCenter for Cognitive Neuroscience, Neuroscience and Behavioral Disorders Program, Duke-National University of Singapore Medical School, Singapore, Singapore.
Zhaoping HongCenter for Cognitive Neuroscience, Neuroscience and Behavioral Disorders Program, Duke-National University of Singapore Medical School, Singapore, Singapore.
Joanna Su Xian ChongCenter for Cognitive Neuroscience, Neuroscience and Behavioral Disorders Program, Duke-National University of Singapore Medical School, Singapore, Singapore.
Yijun WangCenter for Cognitive Neuroscience, Neuroscience and Behavioral Disorders Program, Duke-National University of Singapore Medical School, Singapore, Singapore.
Chun-Yin ChenCenter for Cognitive Neuroscience, Neuroscience and Behavioral Disorders Program, Duke-National University of Singapore Medical School, Singapore, Singapore.
Saima HilalDepartment of Pharmacology, National University of Singapore, Singapore, Singapore.
Narayanaswamy VenketasubramanianNeuroscience Clinic, Raffles Hospital, Singapore, Singapore.
Tien Yin WongMemory Aging & Cognition Centre, National University Health System, Singapore, Singapore.
Christopher Li-Hsian ChenDepartment of Pharmacology, National University of Singapore, Singapore, Singapore.
Mohammad Kamran IkramDepartment of Pharmacology, National University of Singapore, Singapore, Singapore.
Juan ZhouCenter for Cognitive Neuroscience, Neuroscience and Behavioral Disorders Program, Duke-National University of Singapore Medical School, Singapore, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

According to the network-based neurodegeneration hypothesis, neurodegenerative diseases target specific large-scale neural networks, such as the default mode network, and may propagate along the structural and functional connections within and between these brain networks. Cognitive impairment no dementia (CIND) represents an early prodromal stage but few studies have examined brain topological changes within and between brain structural and functional networks. To this end, we studied the structural networks [diffusion magnetic resonance imaging (MRI)] and functional networks (task-free functional MRI) in CIND (61 mild, 56 moderate) and healthy older adults (97 controls). Structurally, compared with controls, moderate CIND had lower global efficiency, and lower nodal centrality and nodal efficiency in the thalamus, somatomotor network, and higher-order cognitive networks. Mild CIND only had higher nodal degree centrality in dorsal parietal regions. Functional differences were more subtle, with both CIND groups showing lower nodal centrality and efficiency in temporal and somatomotor regions. Importantly, CIND generally had higher structural-functional connectome correlation than controls. The higher structural-functional topological similarity was undesirable as higher correlation was associated with poorer verbal memory, executive function, and visuoconstruction. Our findings highlighted the distinct and progressive changes in brain structural-functional networks at the prodromal stage of neurodegenerative diseases.

Indexed as

cognitive impairment no dementiadiffusion tensor imaging (DTI)functional connectomestructural connectomestructural-functional couplingtask-free fMRI

Identifiers

PMID30618711
PMCPMC6300727

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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.