Evidence map›Paper›PMID 28514668›Full record

ReviewNeuroImage2018

Concurrent white matter bundles and grey matter networks using independent component analysis.

Jonathan O'Muircheartaigh, Saad Jbabdi

Abstract readReview
In one paragraph

Review in NeuroImage, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 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

2 authors.

Jonathan O'MuircheartaighDepartment of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, United Kingdom; Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, St. Thomas' Hospital, King's College London, London SE1 7EH, United Kingdom. Electronic address: JonathanOM@kcl.ac.uk.
Saad JbabdiOxford Centre for Functional MRI of the Brain, University of Oxford, Oxford OX3 9DU, United Kingdom.

Funding

Medical Research Council MR/L009013/1
6 · The paper itself

Abstract

Developments in non-invasive diffusion MRI tractography techniques have permitted the investigation of both the anatomy of white matter pathways connecting grey matter regions and their structural integrity. In parallel, there has been an expansion in automated techniques aimed at parcellating grey matter into distinct regions based on functional imaging. Here we apply independent component analysis to whole-brain tractography data to automatically extract brain networks based on their associated white matter pathways. This method decomposes the tractography data into components that consist of paired grey matter 'nodes' and white matter 'edges', and automatically separates major white matter bundles, including known cortico-cortical and cortico-subcortical tracts. We show how this framework can be used to investigate individual variations in brain networks (in terms of both nodes and edges) as well as their associations with individual differences in behaviour and anatomy. Finally, we investigate correspondences between tractography-based brain components and several canonical resting-state networks derived from functional MRI.

Indexed as

AdultDiffusion Tensor ImagingFemaleGray MatterHumansMaleNerve NetNeural PathwaysWhite MatterYoung Adult

Identifiers

PMID28514668
PMCPMC6318261

What OpenQuestion holds

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LicenceCC BY
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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.