Evidence map›Paper›PMID 40048582›Full record

ArticleSchizophrenia bulletin2026

Clarifying Fundamental Role of Symbol Coding in Cognitive Networks in Schizophrenia and Healthy Controls Leveraging Gaussian Graphical Models and Bayesian Networks.

Yuyanan Zhang, Yaoyao Sun, Zhe Lu, Guorui Zhao, Junyuan Sun, Xiao Zhang, Yang Yang, Zhewei Kang, Xiaoyang Feng, Rui Yuan and 4 more

Abstract read
In one paragraph

Article in Schizophrenia bulletin, 2026. 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.

Yuyanan ZhangPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Yaoyao SunPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Zhe LuPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Guorui ZhaoPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Junyuan SunPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Xiao ZhangPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Yang YangPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Zhewei KangPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Xiaoyang FengPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Rui YuanPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Yundan LiaoPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Yunqing ZhuPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Jing GuoPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Weihua YuePeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.

Funding

Beijing Municipal Health Commission Research BMU2022DJXK007China Postdoctoral Science Foundation 2022M720302
6 · The paper itself

Abstract

background and hypothesisCognitive impairments in patients with schizophrenia initiate a cascade of effects on daily functioning. A single impairment can affect the functioning of the entire cognitive system. However, the relative interdependence among individual neuropsychological measures-whether the performance of a specific test depends on other tests-remains poorly understood. STUDY

designThe study included a total of 1027 participants (522 patients with schizophrenia and 505 healthy controls) from China. All participants completed the comprehensive 9-test Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery. To examine cognitive relationships, we employed Gaussian Graphical Models for undirected relationships and Bayesian networks for directed relationships among cognitive tests. STUDY

resultsSymbol Coding played a central role and exhibited downstream associations with other cognitive tests in both patients and controls. Network analysis showed significant between-group edge differences in undirected networks, particularly between Continuous Performance and Spatial Span (SS), and between Symbol Coding and Managing Emotions (P = .018). A consistent sequential pattern (Symbol Coding → SS → Maze → Trail Making) was identified in both networks. Notably, the Symbol Coding → Managing Emotions connection was uniquely present in the patient's network. Importantly, Symbol Coding and SS were identified as central variables in schizophrenia, showing extensive connectivity with other cognitive tests.

conclusionsSymbol Coding is a fundamental cognitive test in both patients and controls. The association between Symbol Coding and Managing Emotions appears to be a stable feature in schizophrenia. These findings may inform mechanistic insights into cognitive architecture.

Indexed as

Cognitive DysfunctionSchizophreniaAdultBayes TheoremFemaleHumansMaleMiddle AgedNeuropsychological TestsNormal DistributionYoung AdultBayesian networkcognitionGaussian graphical modelschizophreniasymbol coding

Identifiers

PMID40048582
PMCPMC12809797

What OpenQuestion holds

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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.