ArticleJournal of psychiatry & neuroscience : JPN
Action selection in early stages of psychosis: an active inference approach.
Article in Journal of psychiatry & neuroscience : JPN. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- A transdiagnostic conflict-square algorithm: a four-node computational framework for psychotherapy and functional diagnosis.Frontiers in psychiatry · 2026Article
- Neurobiological illness models of schizophrenia and stigma reduction: has that ship sailed?Schizophrenia (Heidelberg, Germany) · 2025Review
- Pavlovian bias is associated with symptom severity but not diagnostic status in individuals with both anxious and non-anxious depression.Translational psychiatry · 2025Article
- Temporal stability of semantic predictions in subclinical autistic and schizotypal personality traits.Schizophrenia (Heidelberg, Germany) · 2025Article
- How do inner screens enable imaginative experience? Applying the free-energy principle directly to the study of conscious experience.Neuroscience of consciousness · 2025Article
- Active Inference in Psychology and Psychiatry: Progress to Date?Entropy (Basel, Switzerland) · 2024Review
- Cognitive subgroups of affective and non-affective psychosis show differences in medication and cortico-subcortical brain networks.Scientific reports · 2024Article
- Interpersonal coordination in schizophrenia: a concise update on paradigms, computations, and neuroimaging findings.Psychoradiology · 2023Review
- Striatal correlates of Bayesian beliefs in self-efficacy in adolescents and their relation to mood and autonomy: a pilot study.Cerebral cortex communications · 2023Article
- Naturalistic computational psychiatry: How to get there?Journal of psychiatry & neuroscience : JPNArticle
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Authors and funding
11 authors.
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Abstract
backgroundTo interact successfully with their environment, humans need to build a model to make sense of noisy and ambiguous inputs. An inaccurate model, as suggested to be the case for people with psychosis, disturbs optimal action selection. Recent computational models, such as active inference, have emphasized the importance of action selection, treating it as a key part of the inferential process. Based on an active inference framework, we sought to evaluate previous knowledge and belief precision in an action-based task, given that alterations in these parameters have been linked to the development of psychotic symptoms. We further sought to determine whether task performance and modelling parameters would be suitable for classification of patients and controls.
methodsTwenty-three individuals with an at-risk mental state, 26 patients with first-episode psychosis and 31 controls completed a probabilistic task in which action choice (go/no-go) was dissociated from outcome valence (gain or loss). We evaluated group differences in performance and active inference model parameters and performed receiver operating characteristic (ROC) analyses to assess group classification.
resultsWe found reduced overall performance in patients with psychosis. Active inference modelling revealed that patients showed increased forgetting, reduced confidence in policy selection and less optimal general choice behaviour, with poorer action-state associations. Importantly, ROC analysis showed fair-to-good classification performance for all groups, when combining modelling parameters and performance measures. LIMITATIONS: The sample size is moderate.
conclusionActive inference modelling of this task provides further explanation for dysfunctional mechanisms underlying decision-making in psychosis and may be relevant for future research on the development of biomarkers for early identification of psychosis.
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