Evidence map›Paper›PMID 25862259›Full record

ArticleNeuroImage2015

A symmetric multivariate leakage correction for MEG connectomes.

G L Colclough, M J Brookes, S M Smith, M W Woolrich

Abstract read
In one paragraph

Article in NeuroImage, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 208 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
208citing papers in PubMed, 1 pooled it
–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

208 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  9. Shared spatial and temporal principles govern connectome dynamics across timescales.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  18. Preoperative MEG reveals differential brain network characteristics in drug-resistant epilepsy patients based on vagus nerve stimulation response.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026
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148 more citing papers are in PubMed but not listed here.

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

4 authors.

G L ColcloughOxford Centre for Human Brain Activity (OHBA), University of Oxford, Oxford, UK; University of Oxford, Dept. Engineering Sciences, Parks Rd., Oxford, UK; Centre for the Functional Magnetic Resonance Imaging of the Brain (FMRIB), University of Oxford, Oxford, UK. Electronic address: giles.colclough@magd.ox.ac.uk.
M J BrookesSir Peter Mansfield Magnetic Resonance Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK.
S M SmithCentre for the Functional Magnetic Resonance Imaging of the Brain (FMRIB), University of Oxford, Oxford, UK.
M W WoolrichOxford Centre for Human Brain Activity (OHBA), University of Oxford, Oxford, UK; Centre for the Functional Magnetic Resonance Imaging of the Brain (FMRIB), University of Oxford, Oxford, UK.

Funding

Mapping the Human Connectome: Structure, Function, and HeritabilityU54MH091657 · NIMH · WASHINGTON UNIVERSITY · PI UGURBIL, KAMIL, VAN ESSEN, DAVID C · 2010 to 2014
$34.7M
Medical Research Council MR/K005464/1Medical Research Council MR/M006301/1NIMH NIH HHS 1U54MH091657NIMH NIH HHS U54 MH091657Wellcome Trust 098369
6 · The paper itself

Abstract

Ambiguities in the source reconstruction of magnetoencephalographic (MEG) measurements can cause spurious correlations between estimated source time-courses. In this paper, we propose a symmetric orthogonalisation method to correct for these artificial correlations between a set of multiple regions of interest (ROIs). This process enables the straightforward application of network modelling methods, including partial correlation or multivariate autoregressive modelling, to infer connectomes, or functional networks, from the corrected ROIs. Here, we apply the correction to simulated MEG recordings of simple networks and to a resting-state dataset collected from eight subjects, before computing the partial correlations between power envelopes of the corrected ROItime-courses. We show accurate reconstruction of our simulated networks, and in the analysis of real MEGresting-state connectivity, we find dense bilateral connections within the motor and visual networks, together with longer-range direct fronto-parietal connections.

Indexed as

Data Interpretation, StatisticalSignal Processing, Computer-AssistedComputer SimulationConnectomeHumansMagnetoencephalographyNerve Net

Identifiers

PMID25862259
PMCPMC4528074

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LicenceCC BY
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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.