Evidence map›Paper›PMID 32813156›Full record

ArticleBrain structure & function2020

Abnormal dynamic resting-state brain network organization in auditory verbal hallucination.

Haiyang Geng, Pengfei Xu, Iris E Sommer, Yue-Jia Luo, André Aleman, Branislava Ćurčić-Blake

Open access · hybridAbstract read
In one paragraph

Article in Brain structure & function, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

14 citing papers in PubMed, 28 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Biomarkers of Auditory-Verbal Hallucinations.Advances in neurobiology · 2024
    Review
  7. Article
  8. Review
  9. Advances in Hallucination Research.Schizophrenia bulletin · 2023
    Article
  10. Article
  11. Article
  12. [The measurements of the similarity of dynamic brain functional network].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2022
    Article
  13. Article
  14. 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

6 authors at 3 institutions in 2 countries.

Haiyang GengCenter for Brain Disorders and Cognitive Sciences, Shenzhen University, Shenzhen, China. h.geng@umcg.nl.ORCID http://orcid.org/0000-0001-6115-807X
Pengfei XuBeijing Key Laboratory of Applied Experimental Psychology, Faculty of Psychology, Beijing Normal University, Beijing, China. xupf@szu.edu.cn.
Iris E SommerDepartment of Biomedical Sciences of Cells and Systems, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Yue-Jia LuoCenter for Brain Disorders and Cognitive Sciences, Shenzhen University, Shenzhen, China.
André AlemanCenter for Brain Disorders and Cognitive Sciences, Shenzhen University, Shenzhen, China.
Branislava Ćurčić-BlakeDepartment of Biomedical Sciences of Cells and Systems, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
University Medical Center Groningen · NLApplied Science and Technology Research Institute · CNShenzhen University · CN

Funding

Dutch MS Research Foundation 16 - 949 MSGuangdong Province Introduction of Innovative R&D Team (CN) 2016ZT06S220National Natural Science Foundation of China 31530031National Natural Science Foundation of China 31871137National Natural Science Foundation of China 31920103009Shenzhen Peacock Plan (CN) 827-000235Shenzhen Peacock Program KQTD2015033016104926Shenzhen Science and Technology Research Funding Program JCYJ20180507183500566Young Elite Scientists Sponsorship Program by China Association for Science and Technology YESS 2018ZonMW Memorable grant 733050836
6 · The paper itself

Abstract

Auditory-verbal hallucinations (AVH) are a key symptom of schizophrenia. Recent neuroimaging studies examining dynamic functional connectivity suggest that disrupted dynamic interactions between brain networks characterize complex symptoms in mental illness including schizophrenia. Studying dynamic connectivity may be especially relevant for hallucinations, given their fluctuating phenomenology. Indeed, it remains unknown whether AVH in schizophrenia are directly related to altered dynamic connectivity within and between key brain networks involved in auditory perception and language, emotion processing, and top-down control. In this study, we used dynamic connectivity approaches including sliding window and k-means to examine dynamic interactions among brain networks in schizophrenia patients with and without a recent history of AVH. Dynamic brain network analysis revealed that patients with AVH spent less time in a 'network-antagonistic' brain state where the default mode network (DMN) and the language network were anti-correlated, and had lower probability to switch into this brain state. Moreover, patients with AVH showed a lower connectivity within the language network and the auditory network, and lower connectivity was observed between the executive control and the language networks in certain dynamic states. Our study provides the first neuroimaging evidence of altered dynamic brain networks for understanding neural mechanisms of AVH in schizophrenia. The findings may inform and further strengthen cognitive models of AVH that aid the development of new coping strategies for patients.

Indexed as

AdultBrainBrain MappingDefault Mode NetworkFemaleFunctional NeuroimagingHallucinationsHumansMagnetic Resonance ImagingMaleNerve NetSchizophreniaYoung AdultAuditory-verbal hallucinationsDefault model networkDynamic connectivityLanguage networkNetwork-antagonistic state

Identifiers

PMID32813156
PMCPMC7544708
OpenAlexW3062972014

What OpenQuestion holds

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LicenceCC BY
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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.