ArticleScientific reports2025
An experimental and computational investigation of executive functions and inner speech in schizophrenia spectrum disorders.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Application of artificial intelligence in schizophrenia rehabilitation management: a systematic scoping review.Translational psychiatry · 2026Article
- Modeling metacognition and executive functions in the metacognitive wisconsin card sorting test using the neuropsychological digital-twin method.Scientific reports · 2026Article
- Driving Performance in Schizophrenia: The Role of Neurocognitive Correlates-A Systematic Review.Brain sciences · 2025Review
- Assessing executive functions and metacognition: translational potential of the Metacognitive Wisconsin Card Sorting Test for developmental neuropsychology.Frontiers in behavioral neuroscience · 2025Review
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Authors and funding
7 authors.
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Abstract
Flexible goal-directed human cognition is supported by many forms of self-directed manipulation of representations. Among them, Inner-Speech (IS; covert self-directed speech) acts on second-order representations (e.g., goals/sub-goals), empowering attention and feedback processing. Interestingly, patients with Schizophrenia Spectrum Disorders (SSD) show impaired Executive Functions (EF; e.g., cognitive flexibility) and, probably, a related IS alteration. However, fragmentary evidence and no computational modeling prevent a clear assessment of these processes and focused therapeutic interventions. Here, we address these issues by exploiting a translational approach that integrates experimental clinical data, machine learning, and computational modeling. First, we administered the Wisconsin Cards Sorting Test (WCST; a neuropsychological test probing cognitive flexibility) to 162 SSD patients and 108 healthy control participants, and we computed the clinical behavioural data with a data-driven clustering algorithm. Second, we extracted the cluster neuropsychological profiles with our theory-based validated computational model of the WCST. Finally, we exploited our model to emulate an IS-based psychotherapeutic intervention for SSD subpopulations. We identified different SSD sub-populations and global trends (e.g., a descending feedback sensitivity); however, extremely different neuropsychological profiles emerged. In particular, 'Relatively Intact' patients showed an unexpected profile (distraction/reasoning failures), quite divergent from the perseverative/rigid profile of the others. Importantly, the former showed no impact of Interfering-IS, while the others showed increased Interfering-IS strongly affecting their cognition. These differences highlight that SSD populations require a cluster-dependent individualisation of the intervention to achieve adequate cognitive performance. Overall, these results support a clear definition of neuropsychological profiles and the related Interfering-IS impact in SSD subpopulations, thus showing important implications for basic research (e.g., cognitive neuroscience) and clinical fields (clinical psychology and psychiatry).
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