Evidence map›Paper›PMID 26437992›Full record

ReviewJournal of stroke2015

Stroke Connectome and Its Implications for Cognitive and Behavioral Sequela of Stroke.

Jae-Sung Lim, Dong-Wha Kang

Abstract readReview
In one paragraph

Review in Journal of stroke, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

32 citing papers in PubMed.

  1. Article
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  8. Simulated Attack Reveals How Lesions Affect Network Properties in Poststroke Aphasia.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022
    Article
  9. Review
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  12. Study on Active Components ofMolecules (Basel, Switzerland) · 2021
    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

2 authors.

Jae-Sung LimDepartment of Neurology, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul National University College of Medicine, Seoul, Korea.
Dong-Wha KangDepartment of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Systems-based approaches to neuroscience, using network analysis and the human connectome, have been adopted by many researchers by virtue of recent progress in neuroimaging and computational technologies. Various neurological disorders have been evaluated from a network perspective, including stroke, Alzheimer's disease, Parkinson's disease, and traumatic brain injury. Until now, dynamic processes after stroke and during recovery were investigated through multimodal neuroimaging techniques. Many studies have shown disruptions in structural and functional connectivity, including in large-scale neural networks, in patients with stroke sequela such as motor weakness, aphasia, hemianopia, neglect, and general cognitive dysfunction. A connectome-based approach might shed light on the underlying mechanisms of stroke sequela and the recovery process, and could identify candidates for individualized rehabilitation programs. In this review, we briefly outline the basic concepts of structural and functional connectivity, and the connectome. Then, we explore current evidence regarding how stroke lesions cause changes in connectivity and network architecture parameters. Finally, the clinical implications of perspectives on the connectome are discussed in relation to the cognitive and behavioral sequela of stroke.

Indexed as

ConnectivityConnectomeDiffusion tensor imagingNetworkResting-state functional MRIStroke

Identifiers

PMID26437992
PMCPMC4635721

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.