Evidence map›Paper›PMID 24904268›Full record

ArticleFrontiers in neuroscience2014

Localization of MEG human brain responses to retinotopic visual stimuli with contrasting source reconstruction approaches.

Nela Cicmil, Holly Bridge, Andrew J Parker, Mark W Woolrich, Kristine Krug

Abstract read
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Article in Frontiers in neuroscience, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

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3 · Its place in the literature

Who cites it

12 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

5 authors.

Nela CicmilDepartment of Physiology, Anatomy and Genetics, University of Oxford Oxford, UK.
Holly BridgeNuffield Department of Clinical Neuroscience, FMRIB Centre, John Radcliffe Hospital, University of Oxford Oxford, UK.
Andrew J ParkerDepartment of Physiology, Anatomy and Genetics, University of Oxford Oxford, UK.
Mark W WoolrichNuffield Department of Clinical Neuroscience, FMRIB Centre, John Radcliffe Hospital, University of Oxford Oxford, UK ; Department of Psychiatry, Oxford Centre for Human Brain Activity, Warneford Hospital, University of Oxford Oxford, UK.
Kristine KrugDepartment of Physiology, Anatomy and Genetics, University of Oxford Oxford, UK.

Funding

Biotechnology and Biological Sciences Research Council BB/H016902/1Medical Research Council G0400132Medical Research Council G0700399Medical Research Council G0802171Medical Research Council MR/K014382/1Wellcome Trust
6 · The paper itself

Abstract

Magnetoencephalography (MEG) allows the physiological recording of human brain activity at high temporal resolution. However, spatial localization of the source of the MEG signal is an ill-posed problem as the signal alone cannot constrain a unique solution and additional prior assumptions must be enforced. An adequate source reconstruction method for investigating the human visual system should place the sources of early visual activity in known locations in the occipital cortex. We localized sources of retinotopic MEG signals from the human brain with contrasting reconstruction approaches (minimum norm, multiple sparse priors, and beamformer) and compared these to the visual retinotopic map obtained with fMRI in the same individuals. When reconstructing brain responses to visual stimuli that differed by angular position, we found reliable localization to the appropriate retinotopic visual field quadrant by a minimum norm approach and by beamforming. Retinotopic map eccentricity in accordance with the fMRI map could not consistently be localized using an annular stimulus with any reconstruction method, but confining eccentricity stimuli to one visual field quadrant resulted in significant improvement with the minimum norm. These results inform the application of source analysis approaches for future MEG studies of the visual system, and indicate some current limits on localization accuracy of MEG signals.

Indexed as

brain imagingfMRImagnetoencephalography (MEG)retinotopysource localizationvision (ocular)

Identifiers

PMID24904268
PMCPMC4034416

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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.