Evidence map›Paper›PMID 41309710›Full record

ArticleNature communications2025

Stage-dependent patterns of cognitive network connectivity in early psychosis.

XiaoChen Tang, YanYan Wei, JiaoYan Pang, LiHua Xu, HuiRu Cui, MingLiang Ju, HaiChun Liu, Qiang Hu, LingYun Zeng, YingYing Tang and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

14 authors.

XiaoChen Tang *Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.
YanYan Wei *Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.
JiaoYan PangSchool of Government, Shanghai University of Political Science and Law, Shanghai, China.
LiHua XuShanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.
HuiRu CuiShanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.
MingLiang JuShanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.
HaiChun LiuDepartment of Automation, Shanghai Jiao Tong University, Shanghai, China.
Qiang HuDepartment of Psychiatry, ZhenJiang Mental Health Center, Zhenjiang, China.
LingYun ZengDepartment of Psychiatric Rehabilitation, Shenzhen Kangning Hospital, ShenZhen, China.
YingYing TangShanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.
ZhengHui YiShanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.
ChunBo LiShanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.
JiJun WangShanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China. jijunwang27@163.com.ORCID 0000-0001-5427-7425
TianHong ZhangShanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China. zhang_tianhong@126.com.ORCID 0000-0002-5379-7119

Funding

Ministry of Science and Technology of the People's Republic of China (Chinese Ministry of Science and Technology) 2023YFC2506800National Natural Science Foundation of China (National Science Foundation of China) 82171544, 82371505, 82151314, 82101623
6 · The paper itself

Abstract

Cognitive impairments in early psychosis are common, yet prior studies have focused mainly on domain-specific deficits rather than inter-domain relationships. Analyzing cognitive network connectivity may uncover insights into early psychosis mechanisms. Cognitive functions were assessed from 2,518 participants, including 988 first-episode schizophrenia (FES), 767 clinical high-risk (CHR), and 763 healthy controls (HC), using the Chinese version of the Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery (MCCB). Results revealed a stage-dependent "dedifferentiation" pattern: mean inter-domain correlation increased from HC (0.28) to CHR (0.33) to FES (0.40). Confirmatory factor analysis revealed a common "g" factor across groups, with significantly reduced strength in FES compared to CHR and HC. The reduction in the "g" factor was associated with increased connectivity and stronger inter-domain correlations. These findings highlight cognitive network dedifferentiation and "g" factor decline as key features of early psychosis.

Indexed as

CognitionCognitive DysfunctionPsychotic DisordersSchizophreniaAdolescentAdultCase-Control StudiesFemaleHumansMaleNeuropsychological TestsYoung Adult

Identifiers

PMID41309710
PMCPMC12749795

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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.