Evidence map›Paper›PMID 26644605›Full record

ArticleSchizophrenia bulletin2016

Structural Brain Network Disturbances in the Psychosis Spectrum.

Edwin van Dellen, Marc M Bohlken, Laurijn Draaisma, Prejaas K Tewarie, Remko van Lutterveld, René Mandl, Cornelis J Stam, Iris E Sommer

Open access · bronzeAbstract read
In one paragraph

Article in Schizophrenia bulletin, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
1.3field-weighted citation impact, top 20% 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

20 citing papers in PubMed, 40 citations in OpenAlex.

  1. Article
  2. Article
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  4. Altered Brain-Behavior Association During Resting State is a Potential Psychosis Risk Marker.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
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  14. Review
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  20. Application of Graph Theory to Assess Static and Dynamic Brain Connectivity: Approaches for Building Brain Graphs.Proceedings of the IEEE. Institute of Electrical and Electronics Engineers · 2018
    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 at 4 institutions in 2 countries.

Edwin van DellenDepartment of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands; Department of Psychiatry, Brain Center Rudolf Magnus, Utrecht, The Netherlands; E.vanDellen@umcutrecht.nl.
Marc M BohlkenDepartment of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands; Department of Psychiatry, Brain Center Rudolf Magnus, Utrecht, The Netherlands;
Laurijn DraaismaDepartment of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands; Department of Psychiatry, Brain Center Rudolf Magnus, Utrecht, The Netherlands;
Prejaas K TewarieDepartment of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands;
Remko van LutterveldCenter for Mindfulness, University of Massachusetts School of Medicine, Shrewsbury, MA;
René MandlDepartment of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands; Department of Psychiatry, Brain Center Rudolf Magnus, Utrecht, The Netherlands;
Cornelis J StamDepartment of Clinical Neurophysiology and MEG Center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.
Iris E SommerDepartment of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands; Department of Psychiatry, Brain Center Rudolf Magnus, Utrecht, The Netherlands;
University Medical Center Utrecht · NLAmsterdam Neuroscience · NLHersenstichting · NLShrewsbury College · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIndividuals with subclinical psychotic symptoms provide a unique window on the pathophysiology of psychotic experiences as these individuals are free of confounders such as hospitalization, negative and cognitive symptoms and medication use. Brain network disturbances of white matter connections are thought to play a central role in the pathophysiology of psychosis. Based on the structural network disconnection hypothesis in schizophrenia, we expect less and weaker connections, and altered brain network organization in individuals with clinical and those with subclinical psychotic symptoms.

methodsWe used diffusion tensor imaging to study 35 patients with a psychotic disorder, 35 subjects with subclinical psychotic symptoms, and 36 healthy controls. The structural brain network was analyzed on 3 levels: connection density, white matter microstructure (fractional anisotropy, mean diffusivity, and magnetic transfer ratio), and network organization. Network organization was studied with minimum spanning tree analysis, a method to reconstruct a backbone of structural highways in the brain.

resultsDecreased fractional anisotropy and increased mean diffusivity was found in both groups with psychotic symptoms, while their network topology showed decreased overlap with a healthy reference network. Decreased centrality was found in several brain regions, including parietal hubs and language areas, in both groups with psychotic symptoms. Deviation of network characteristics was more apparent in clinical subjects than in subclinical subjects. DISCUSSION: Weaker connections and decreased centrality of parietal hubs characterize the structural brain network in subjects with psychotic symptoms. These differences are more notable in clinical than in subclinical subjects with psychotic experiences.

Indexed as

AdultAgedDiffusion Tensor ImagingFemaleHumansMaleMiddle AgedNerve NetParietal LobePsychotic DisordersWhite MatterYoung Adultbrain networksdiffusion tensor imagingfractional anisotropyhubsminimum spanning treepsychosis continuum

Identifiers

PMID26644605
PMCPMC4838099
OpenAlexW2216897486

What OpenQuestion holds

Textmetadata
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.