ArticlePsychological medicine2024
Clarifying directional dependence among measures of early auditory processing and cognition in schizophrenia: leveraging Gaussian graphical models and Bayesian networks.
Article in Psychological medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 8 citations in OpenAlex.
- Symptom network for psychological distress in college freshmen: a large sample bayesian network analysis.BMC psychology · 2026Article
- Exploring the Pathways Between Early Auditory Processing, Processing Speed, Social Cognition, and Negative Symptoms on Social Functioning in Individuals at Clinical High Risk for Psychosis: A Structural Equation Modeling Approach.Biological psychiatry · 2026Article
- Clarifying Fundamental Role of Symbol Coding in Cognitive Networks in Schizophrenia and Healthy Controls Leveraging Gaussian Graphical Models and Bayesian Networks.Schizophrenia bulletin · 2026Article
- Gender differences in parent-child alienation and its relationship to depressive symptoms in left-behind children: a comparative analysis of undirected and directed networks.BMC public health · 2025Article
- Factors Associated With the Level of Trust in Health Information Robots Among the General Population From a Socioecological Model Perspective: Network Analysis.Journal of medical Internet research · 2025Article
- A CNN-Transformer Fusion Model for Proactive Detection of Schizophrenia Relapse from EEG Signals.Bioengineering (Basel, Switzerland) · 2025Article
- Relationship Between Schizotypal Traits, Emotion Regulation, and Negative Affect in Children: A Network Analysis.Schizophrenia bulletin · 2025Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundResearch using latent variable models demonstrates that pre-attentive measures of early auditory processing (EAP) and cognition may initiate a cascading effect on daily functioning in schizophrenia. However, such models fail to account for relationships among individual measures of cognition and EAP, thereby limiting their utility. Hence, EAP and cognition may function as complementary and interacting measures of brain function rather than independent stages of information processing. Here, we apply a data-driven approach to identifying directional relationships among neurophysiologic and cognitive variables.
methodsUsing data from the Consortium on the Genetics of Schizophrenia 2, we estimated Gaussian Graphical Models and Bayesian networks to examine undirected and directed connections between measures of EAP, including mismatch negativity and P3a, and cognition in 663 outpatients with schizophrenia and 630 control participants.
resultsChain structures emerged among EAP and attention/vigilance measures in schizophrenia and control groups. Concerning differences between the groups, object memory was an influential variable in schizophrenia upon which other cognitive domains depended, and working memory was an influential variable in controls.
conclusionsMeasures of EAP and attention/vigilance are conditionally independent of other cognitive domains that were used in this study. Findings also revealed additional causal assumptions among measures of cognition that could help guide statistical control and ultimately help identify early-stage targets or surrogate endpoints in schizophrenia.
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