Evidence map›Paper›PMID 28027960›Full record

ArticleNeuroImage2017

Investigating resting-state functional connectivity in the cervical spinal cord at 3T.

Falk Eippert, Yazhuo Kong, Anderson M Winkler, Jesper L Andersson, Jürgen Finsterbusch, Christian Büchel, Jonathan C W Brooks, Irene Tracey

Abstract read
In one paragraph

Article in NeuroImage, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

0numbers the graph read from it
0cells of the map it votes in
47citing 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

47 citing papers in PubMed.

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  8. Characteristic BOLD signals are detectable in white matter of the spinal cord at rest and after a stimulus.Proceedings of the National Academy of Sciences of the United States of America · 2024
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  9. Article
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  12. Imaging neuroscience (Cambridge, Mass.) · 2024
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  15. Review
  16. Spinal Cord fMRI: A New Window into the Central Nervous System.The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry · 2023
    Review
  17. Article
  18. Review
  19. Article
  20. Article
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

8 authors.

Falk EippertOxford Centre for Functional Magnetic Resonance Imaging of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK. Electronic address: falk.eippert@ndcn.ox.ac.uk.
Yazhuo KongOxford Centre for Functional Magnetic Resonance Imaging of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Magnetic Resonance Imaging Research Centre, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.
Anderson M WinklerOxford Centre for Functional Magnetic Resonance Imaging of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
Jesper L AnderssonOxford Centre for Functional Magnetic Resonance Imaging of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
Jürgen FinsterbuschDepartment of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Christian BüchelDepartment of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Jonathan C W BrooksClinical Research and Imaging Centre, University of Bristol, Bristol, UK.
Irene TraceyOxford Centre for Functional Magnetic Resonance Imaging of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.

Funding

Medical Research Council G0700238Medical Research Council G0700399Medical Research Council MR/N026969/1Wellcome Trust 098369/Z/12/ZWellcome Trust 102645
6 · The paper itself

Abstract

The study of spontaneous fluctuations in the blood-oxygen-level-dependent (BOLD) signal has recently been extended from the brain to the spinal cord. Two ultra-high field functional magnetic resonance imaging (fMRI) studies in humans have provided evidence for reproducible resting-state connectivity between the dorsal horns as well as between the ventral horns, and a study in non-human primates has shown that these resting-state signals are impacted by spinal cord injury. As these studies were carried out at ultra-high field strengths using region-of-interest (ROI) based analyses, we investigated whether such resting-state signals could also be observed at the clinically more prevalent field strength of 3T. In a reanalysis of a sample of 20 healthy human participants who underwent a resting-state fMRI acquisition of the cervical spinal cord, we were able to observe significant dorsal horn connectivity as well as ventral horn connectivity, but no consistent effects for connectivity between dorsal and ventral horns, thus replicating the human 7T results. These effects were not only observable when averaging along the acquired length of the spinal cord, but also when we examined each of the acquired spinal segments separately, which showed similar patterns of connectivity. Finally, we investigated the robustness of these resting-state signals against variations in the analysis pipeline by varying the type of ROI creation, temporal filtering, nuisance regression and connectivity metric. We observed that - apart from the effects of band-pass filtering - ventral horn connectivity showed excellent robustness, whereas dorsal horn connectivity showed moderate robustness. Together, our results provide evidence that spinal cord resting-state connectivity is a robust and spatially consistent phenomenon that could be a valuable tool for investigating the effects of pathology, disease progression, and treatment response in neurological conditions with a spinal component, such as spinal cord injury.

Indexed as

AdultCervical CordConnectomeHumansMagnetic Resonance ImagingMaleSpinal Cord Dorsal HornSpinal Cord Ventral HornYoung Adult

Identifiers

PMID28027960
PMCPMC5315056

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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.