Evidence map›Paper›PMID 29159045›Full record

ArticleNeuroImage. Clinical2018

Identifying functional network changing patterns in individuals at clinical high-risk for psychosis and patients with early illness schizophrenia: A group ICA study.

Yuhui Du, Susanna L Fryer, Dongdong Lin, Jing Sui, Qingbao Yu, Jiayu Chen, Barbara Stuart, Rachel L Loewy, Vince D Calhoun, Daniel H Mathalon

Open access · goldAbstract read
In one paragraph

Article in NeuroImage. Clinical, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
3.0field-weighted citation impact, top 8% 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

19 citing papers in PubMed, 49 citations in OpenAlex.

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  9. A deep learning fusion model for brain disorder classification: Application to distinguishing schizophrenia and autism spectrum disorder.ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2020
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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

10 authors at 2 institutions in 2 countries.

Yuhui DuThe Mind Research Network, Albuquerque, NM, USA; Shanxi University, School of Computer & Information Technology, Taiyuan, China. Electronic address: ydu@mrn.org.
Susanna L FryerDepartment of Psychiatry, University of California San Francisco, San Francisco, CA, USA; The Mental Health Service, San Francisco VA Healthcare System, San Francisco, CA, USA.
Dongdong LinThe Mind Research Network, Albuquerque, NM, USA.
Jing SuiThe Mind Research Network, Albuquerque, NM, USA; Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
Qingbao YuThe Mind Research Network, Albuquerque, NM, USA.
Jiayu ChenThe Mind Research Network, Albuquerque, NM, USA.
Barbara StuartDepartment of Psychiatry, University of California San Francisco, San Francisco, CA, USA.
Rachel L LoewyDepartment of Psychiatry, University of California San Francisco, San Francisco, CA, USA.
Vince D CalhounThe Mind Research Network, Albuquerque, NM, USA; Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA.
Daniel H MathalonDepartment of Psychiatry, University of California San Francisco, San Francisco, CA, USA; The Mental Health Service, San Francisco VA Healthcare System, San Francisco, CA, USA. Electronic address: daniel.mathalon@ucsf.edu.
Mind Research Network · USUniversity of California, San Francisco · US

Funding

Transcranial Direct Current Stimulation for Treatment of Auditory Verbal HalluciP20GM103472 · NIGMS · THE MIND RESEARCH NETWORK · PI CALHOUN, VINCE D · 2012 to 2017
$14.3M
Multivariate methods for identifying multitask/multimodal brain imaging biomarkersR01EB006841 · NIBIB · THE MIND RESEARCH NETWORK · PI VINCE D CALHOUN, Sergey Plis · 2007 to 2026
$9.8M
NEURAL MECHANISMS OF SCHIZOPHRENIAP20RR021938 · NCRR · THE MIND RESEARCH NETWORK · PI JUNG, REX · 2008 to 2011
$9.4M
Male/Female differences in psychosis and mood disorders:Dynamic imaging-genomic models for characterizing and predicting psychosis and mood dR01MH118695 · NIMH · GEORGIA STATE UNIVERSITY · PI ADALI, TULAY, CALHOUN, VINCE D · 2019 to 2023
$3.8M
Unified multivariate data-driven solutions for static and dynamic brain connectivityR01EB020407 · NIBIB · THE MIND RESEARCH NETWORK · PI ADALI, TULAY, CALHOUN, VINCE D · 2015 to 2018
$2.7M
Functional Brain Abnormalities in the Schizophrenia ProdromeR01MH076989 · NIMH · YALE UNIVERSITY · PI MATHALON, DANIEL H · 2007 to 2014
$2.3M
NCRR NIH HHS P20 RR021938NIBIB NIH HHS R01 EB006841NIBIB NIH HHS R01 EB020407NIGMS NIH HHS P20 GM103472NIMH NIH HHS R01 MH076989NIMH NIH HHS R01 MH118695
6 · The paper itself

Abstract

Although individuals at clinical high risk (CHR) for psychosis exhibit a psychosis-risk syndrome involving attenuated forms of the positive symptoms typical of schizophrenia (SZ), it remains unclear whether their resting-state brain intrinsic functional networks (INs) show attenuated or qualitatively distinct patterns of functional dysconnectivity relative to SZ patients. Based on resting-state functional magnetic imaging data from 70 healthy controls (HCs), 53 CHR individuals (among which 41 subjects were antipsychotic medication-naive), and 58 early illness SZ (ESZ) patients (among which 53 patients took antipsychotic medication) within five years of illness onset, we estimated subject-specific INs using a novel group information guided independent component analysis (GIG-ICA) and investigated group differences in INs. We found that when compared to HCs, both CHR and ESZ groups showed significant differences, primarily in default mode, salience, auditory-related, visuospatial, sensory-motor, and parietal INs. Our findings suggest that widespread INs were diversely impacted. More than 25% of voxels in the identified significant discriminative regions (obtained using all 19 possible changing patterns excepting the no-difference pattern) from six of the 15 interrogated INs exhibited monotonically decreasing Z-scores (in INs) from the HC to CHR to ESZ, and the related regions included the left lingual gyrus of two vision-related networks, the right postcentral cortex of the visuospatial network, the left thalamus region of the salience network, the left calcarine region of the fronto-occipital network and fronto-parieto-occipital network. Compared to HCs and CHR individuals, ESZ patients showed both increasing and decreasing connectivity, mainly hypo-connectivity involving 15% of the altered voxels from four INs. The left supplementary motor area from the sensory-motor network and the right inferior occipital gyrus in the vision-related network showed a common abnormality in CHR and ESZ groups. Some brain regions also showed a CHR-unique alteration (primarily the CHR-increasing connectivity). In summary, CHR individuals generally showed intermediate connectivity between HCs and ESZ patients across multiple INs, suggesting that some dysconnectivity patterns evident in ESZ predate psychosis in attenuated form during the psychosis risk stage. Hence, these connectivity measures may serve as possible biomarkers to predict schizophrenia progression.

Indexed as

AdultAntipsychotic AgentsBrainBrain MappingDisease ProgressionFemaleHumansMagnetic Resonance ImagingMaleNeural PathwaysPsychotic DisordersRisk FactorsSchizophreniaYoung AdultAntipsychotic AgentsBrain intrinsic functional networksFunctional magnetic resonance imagingIndependent component analysisPsychosis-risk syndromeResting-stateSchizophrenia

Identifiers

PMID29159045
PMCPMC5681342
OpenAlexW2765394911

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.