Evidence map›Paper›PMID 36971857›Full record

ArticleBrain topography2023

Abnormal Structural Network Communication Reflects Cognitive Deficits in Schizophrenia.

Nabi Zorlu, Adem Bayrakçı, Merve Karakılıç, Andrew Zalesky, Caio Seguin, Ye Tian, Funda Gülyüksel, Berna Yalınçetin, Elif Oral, Fazıl Gelal and 1 more

Abstract read
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In one paragraph

Article in Brain topography, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 26% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
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

11 authors at 4 institutions in 3 countries.

Nabi ZorluDepartment of Psychiatry, Katip Celebi University, Ataturk Education and Research Hospital, Izmir, Turkey. zorlunabi@hotmail.com.
Adem BayrakçıDepartment of Psychiatry, Katip Celebi University, Ataturk Education and Research Hospital, Izmir, Turkey.
Merve KarakılıçDepartment of Psychiatry, Katip Celebi University, Ataturk Education and Research Hospital, Izmir, Turkey.
Andrew ZaleskyDepartment of Psychiatry, Melbourne Neuropsychiatry Centre, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.
Caio SeguinDepartment of Psychiatry, Melbourne Neuropsychiatry Centre, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.
Ye TianDepartment of Psychiatry, Melbourne Neuropsychiatry Centre, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.
Funda GülyükselDepartment of Psychiatry, Katip Celebi University, Ataturk Education and Research Hospital, Izmir, Turkey.
Berna YalınçetinDepartment of Neuroscience, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey.
Elif OralDepartment of Psychiatry, Katip Celebi University, Ataturk Education and Research Hospital, Izmir, Turkey.
Fazıl GelalDepartment of Radiodiagnostics, Katip Celebi University, Ataturk Education and Research Hospital, Izmir, Turkey.
Emre BoraDepartment of Psychiatry, Melbourne Neuropsychiatry Centre, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.
Izmir Kâtip Çelebi University · TRMelbourne Health · AUDokuz Eylül University · TRUniversity of Melbourne · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Schizophrenia has long been thought to be a disconnection syndrome and several previous studies have reported widespread abnormalities in white matter tracts in individuals with schizophrenia. Furthermore, reductions in structural connectivity may also impair communication between anatomically unconnected pairs of brain regions, potentially impacting global signal traffic in the brain. Therefore, we used different communication models to examine direct and indirect structural connections (polysynaptic) communication in large-scale brain networks in schizophrenia. Diffusion-weighted magnetic resonance imaging scans were acquired from 62 patients diagnosed with schizophrenia and 35 controls. In this study, we used five network communication models including, shortest paths, navigation, diffusion, search information and communicability to examine polysynaptic communication in large-scale brain networks in schizophrenia. We showed less efficient communication between spatially widespread brain regions particulary encompassing cortico-subcortical basal ganglia network in schizophrenia group relative to controls. Then, we also examined whether reduced communication efficiency was related to clinical symptoms in schizophrenia group. Among different measures of communication efficiency, only navigation efficiency was associated with global cognitive impairment across multiple cognitive domains including verbal learning, processing speed, executive functions and working memory, in individuals with schizophrenia. We did not find any association between communication efficiency measures and positive or negative symptoms within the schizophrenia group. Our findings are important for improving our mechanistic understanding of neurobiological process underlying cognitive symptoms in schizophrenia.

Indexed as

Cognition DisordersCognitive DysfunctionSchizophreniaBrainCognitionHumansMagnetic Resonance ImagingCognitionCommunication modelsDiffusion tensor imagingSchizophrenia

Identifiers

PMID36971857
OpenAlexW4360985726

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.