Evidence map›Paper›PMID 41634247›Full record

ArticleScientific reports2026

Modeling metacognition and executive functions in the metacognitive wisconsin card sorting test using the neuropsychological digital-twin method.

Giovanni Granato, Andrea Mattera, Emilio Cartoni, Gianluca Baldassarre

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Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Giovanni GranatoLaboratory of Embodied Natural and Artificial Intelligence, Institute of Cognitive Sciences and Technologies, National Research Council of Italy, Rome, Italy. giovanni.granato@istc.cnr.it.
Andrea MatteraLaboratory of Embodied Natural and Artificial Intelligence, Institute of Cognitive Sciences and Technologies, National Research Council of Italy, Rome, Italy.
Emilio CartoniLaboratory of Embodied Natural and Artificial Intelligence, Institute of Cognitive Sciences and Technologies, National Research Council of Italy, Rome, Italy.
Gianluca BaldassarreLaboratory of Embodied Natural and Artificial Intelligence, Institute of Cognitive Sciences and Technologies, National Research Council of Italy, Rome, Italy.

Funding

European Union B51E22000150006Ministero dell'Istruzione, dell'Università e della Ricerca B53D23033920006
6 · The paper itself

Abstract

Executive functions rely on goal-directed manipulation of representations, while metacognition reflects the evaluation and control of one’s own representations. Several studies have examined these processes separately, but none formalise the neuro-representational computations underlying their interaction during goal-directed behaviour. This gap prevents comprehensive frameworks and extended model-based neuropsychological investigations. Here we address these issues by introducing a neuropsychological digital-twin method - a translational modelling framework that integrates clinical and experimental data, theoretical formalisation, and computational modelling for neuropsychological profiling and prediction. We formalised the three-component theory of metacognitive and flexible goal-directed cognition - grounded in theoretical and neuroscientific literature - and developed a neuro-inspired computational model tested with a standard neuropsychological task (Metacognitive Wisconsin Card Sorting Test, Meta-WCST). We further corroborated the proposal by reproducing experimental data from healthy controls and psychiatric populations (Anorexia Nervosa and Schizophrenia). Finally, we generated three digital-twins - computational models fitted to human data and reproducing behavioural and neuro-cognitive features - for neuropsychological profiling and intervention prediction. Our results support an integrated framework of executive functions and metacognition in healthy and pathological goal-directed behaviour and provide the first theory-based computational model of the Meta-WCST. They also reveal that Anorexia Nervosa and Schizophrenia share hidden cognitive and metacognitive similarities (motivational impairment and over-confidence) alongside differences (perseveration and poor self-improvement in the former; distraction and poor self-evaluation in the latter). Consistently, simulations predict differential benefits from metacognitive-based psychotherapy, highlighting the importance of personalised interventions. Finally, our contributions have implications for cognitive science (e.g., consciousness studies) and emerging technologies (digital-twin healthcare and autonomous robotics).

Indexed as

Executive FunctionMetacognitionWisconsin Card Sorting TestAdultAutonomous RobotsComputer SimulationDigital HealthHumansModels, PsychologicalNeuropsychological Tests

Identifiers

PMID41634247
PMCPMC12921055

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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.