Evidence map›Paper›PMID 37662100›Full record

ArticleFrontiers in neuroscience2023

Resting-state networks representation of the global phenomena.

Shiori Amemiya, Hidemasa Takao, Shouhei Hanaoka, Osamu Abe

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Characterizing Hemodynamic Alterations in Glioma: Insights From Resting-State Functional MRI.Journal of neuroimaging : official journal of the American Society of Neuroimaging
    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

4 authors.

Shiori AmemiyaDepartment of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan.
Hidemasa TakaoDepartment of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan.
Shouhei HanaokaDepartment of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan.
Osamu AbeDepartment of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Resting-state functional magnetic resonance imaging (rsfMRI) has been widely applied to investigate spontaneous neural activity, often based on its macroscopic organization that is termed resting-state networks (RSNs). Although the neurophysiological mechanisms underlying the RSN organization remain largely unknown, accumulating evidence points to a substantial contribution from the global signals to their structured synchronization. This study further explored the phenomenon by taking advantage of the inter- and intra-subject variations of the time delay and correlation coefficient of the signal timeseries in each region using the global mean signal as the reference signal. Consistent with the hypothesis based on the empirical and theoretical findings, the time lag and correlation, which have consistently been proven to represent local hemodynamic status, were shown to organize networks equivalent to RSNs. The results not only provide further evidence that the local hemodynamic status could be the direct source of the RSNs' spatial patterns but also explain how the regional variations in the hemodynamics, combined with the changes in the global events' power spectrum, lead to the observations. While the findings pose challenges to interpretations of rsfMRI studies, they further support the view that rsfMRI can offer detailed information related to global neurophysiological phenomena as well as local hemodynamics that would have great potential as biomarkers.

Indexed as

blood oxygenation level-dependencycerebrovascular perfusionhemodynamic response functionneurovascular couplingresting-state functional magnetic resonance imaging

Identifiers

PMID37662100
PMCPMC10469869

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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.