Evidence map›Paper›PMID 31377556›Full record

ArticleNeuroImage. Clinical2019

Examining resting-state functional connectivity in first-episode schizophrenia with 7T fMRI and MEG.

Kristin K Lottman, Timothy J Gawne, Nina V Kraguljac, Jeffrey F Killen, Meredith A Reid, Adrienne C Lahti

Open access · goldAbstract read
In one paragraph

Article in NeuroImage. Clinical, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 1 pooled it
3.0field-weighted citation impact, top 9% of its field
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

36 citing papers in PubMed, 1 synthesis or guideline pooled it, 52 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Kristin K LottmanDepartment of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, AL, USA.
Timothy J GawneDepartment of Optometry and Vision Science, University of Alabama at Birmingham, Birmingham, AL, USA.
Nina V KraguljacDepartment of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA.
Jeffrey F KillenHealth Science Foundation Neurology, University of Alabama at Birmingham, Birmingham, AL, USA.
Meredith A ReidDepartment of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA.
Adrienne C LahtiDepartment of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA. Electronic address: alahti@uab.edu.
University of Alabama at Birmingham · USAuburn University · US

Funding

Glutamate, brain connectivity and duration of untreated psychosisR01MH102951 · NIMH · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI LAHTI, ADRIENNE C · 2014 to 2018
$2.9M
NIMH NIH HHS R01 MH102951
6 · The paper itself

Abstract

Schizophrenia is often characterized by dysconnections in the brain, which can be estimated via functional connectivity analyses. Commonly measured using resting-state functional magnetic resonance imaging (fMRI) in order to characterize the intrinsic or baseline function of the brain, fMRI functional connectivity has significantly contributed to the understanding of schizophrenia. However, these measures may not capture the full extent of functional connectivity abnormalities in schizophrenia as fMRI is temporally limited by the hemodynamic response. In order to extend fMRI functional connectivity findings, the complementary modality of magnetoencephalography (MEG) can be utilized to capture electrophysiological functional connectivity abnormalities in schizophrenia that are not obtainable with fMRI. Therefore, we implemented a multimodal functional connectivity analysis using resting-state 7 Tesla fMRI and MEG data in a sample of first-episode patients with schizophrenia (n = 19) and healthy controls (n = 24). fMRI and MEG data were decomposed into components reflecting resting state networks using a group spatial independent component analysis. Functional connectivity between resting-state networks was computed and group differences were observed. In fMRI, patients demonstrated hyperconnectivity between subcortical and auditory networks, as well as hypoconnectivity between interhemispheric homotopic sensorimotor network components. In MEG, patients demonstrated hypoconnectivity between sensorimotor and task positive networks in the delta frequency band. Results not only support the dysconnectivity hypothesis of schizophrenia, but also suggest the importance of jointly examining multimodal neuroimaging data as critical disorder-related information may not be detectable in a single modality alone.

Indexed as

AdultBrainBrain MappingFemaleHumansMagnetic Resonance ImagingMagnetoencephalographyMaleMultimodal ImagingNeural PathwaysRestSchizophreniaFirst-episodeFunctional connectivityFunctional magnetic resonance imagingIndependent component analysisMagnetoencephalographySchizophrenia

Identifiers

PMID31377556
PMCPMC6677917
OpenAlexW2964012034

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.