Evidence map›Paper›PMID 38077180›Full record

ArticleBasic and clinical neuroscience

Functional Connectivity Alterations of Within and Between Networks in Schizophrenia: A Retrospective Study.

Farzaneh Keyvanfard, Anna-Katharina Schmid, Abbas Nasiraei-Moghaddam

Open access · diamondAbstract read
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Article in Basic and clinical neuroscience. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 31% 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

5 citing papers in PubMed, 7 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

3 authors at 2 institutions in 1 country.

Farzaneh KeyvanfardSchool of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.ORCID 0000-0001-8516-5709
Anna-Katharina SchmidDepartment of Health Sciences and Technology (D-HEST), ETH Zürich, Zürich, Switzerland.ORCID 0009-0000-7146-5102
Abbas Nasiraei-MoghaddamDepartment of Biomedical Engineering, Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran.ORCID 0000-0002-6423-3458
Amirkabir University of Technology · IRInstitute for Research in Fundamental Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Schizophrenia (SZ) is a chronic brain disorder characterized by diverse cognitive dysfunctions due to abnormal brain connectivity. Evaluating these connectivity alterations between and within such networks (intra- and inter-connectivity) may improve the understanding of disrupted information processing patterns in SZ patients. Methods: Resting-state fMRI analysis was performed on 24 SZ patients and 27 matched healthy controls. A functional connectivity matrix was constructed for each participant based on 129 gray matter regions. All regions were classified into eight distinct functional networks. Afterward, all functional connections were segregated into inter- and intra-network connections considering the eight networks. The Mean values of connectivity weights and nodal strength were examined for within- and between-network connections in SZ patients and healthy controls. Results: This analysis revealed that the within-network connections in the somatomotor (SM) network significantly reduced (P<0.001) in SZ patients. Additionally, intra-network connections within the visual and the ventral attention (VA) networks were significantly lower (P<0.01) in the SZ group. Moreover, disrupted intra-network connectivity was detected between the following network pairs: The visual-limbic, the somatomotor-limbic, the dorsal attention-limbic, and the ventral attention-dorsal attention system. Conclusion: The results showed an extensive reduction in functional connectivity strength for SZ patients, with a particularly significant decrease in intra-network connections when compared to the inter-networks. These findings can impact the understanding of the important dysregulated connections that are implicated in the incidence of schizophrenia. Highlights: Intra-network connections are more altered in schizophrenia (SZ) compared to inter-network.The visual, somatomotor (SM), and ventral attention (VA) networks are more affected in SZ.The interactions between the limbic system and three resting-state networks (RSNs) are altered significantly.The nodal strengths in different regions of RSNs are reduced significantly in SZ. Plain Language Summary: Brain functional connectivity is altered in several brain disorders. Looking for these changes may help in better understanding the disorder effects, its diagnostic and treatment. Our brain can be organized into distinct functional modules, known as resting-state networks (RSNs). These RSNs include visual, somatomotor (SM), fronto-parietal, dorsal attention, ventral attention, default mode (DMN), and limbic functional systems. In this study, we examined the alteration of functional connectivity in schizophrenia disorder considering these brain RSNs. The functional connections were classified in two groups, the inter- and intra-network connections. Inter-network connections are defined as the links between pairs of regions from two different brain subnetworks, whereas intra- network connections are determined as the connections between pairs of regions inside each network. Our analysis indicated that the functional connectivity strengths of intra-network connections reduced more in schizophrenia. It was also found that the connection between the limbic network and others is more disrupted compared to other inter-network links. These findings can help us in better understanding the effect of schizophrenia on the brain and therefore its treatment.

Indexed as

Cognitive dysfunctionfMRIInter-network connectivityResting state networksSchizophrenia

Identifiers

PMID38077180
PMCPMC10700811
OpenAlexW4282838178

What OpenQuestion holds

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LicenceCC BY-NC
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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.