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Pragmatics, Theory of Mind and executive functions in schizophrenia: Disentangling the puzzle using machine learning

OBJECTIVE: Schizophrenia is associated with a severe impairment in the communicative-pragmatic domain. Recent research has tried to disentangle the relationship between communicative impairment and other domains usually impaired in schizophrenia, i.e. Theory of Mind (ToM) and cognitive functions. Ho...

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Autores principales: Parola, Alberto, Salvini, Rogerio, Gabbatore, Ilaria, Colle, Livia, Berardinelli, Laura, Bosco, Francesca M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7053733/
https://www.ncbi.nlm.nih.gov/pubmed/32126068
http://dx.doi.org/10.1371/journal.pone.0229603
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author Parola, Alberto
Salvini, Rogerio
Gabbatore, Ilaria
Colle, Livia
Berardinelli, Laura
Bosco, Francesca M.
author_facet Parola, Alberto
Salvini, Rogerio
Gabbatore, Ilaria
Colle, Livia
Berardinelli, Laura
Bosco, Francesca M.
author_sort Parola, Alberto
collection PubMed
description OBJECTIVE: Schizophrenia is associated with a severe impairment in the communicative-pragmatic domain. Recent research has tried to disentangle the relationship between communicative impairment and other domains usually impaired in schizophrenia, i.e. Theory of Mind (ToM) and cognitive functions. However, the results are inconclusive and this relationship is still unclear. Machine learning (ML) provides novel opportunities for studying complex relationships among phenomena and representing causality among multiple variables. The present research explored the potential of applying ML, specifically Bayesian network (BNs) analysis, to characterize the relationship between cognitive, ToM and pragmatic abilities in individuals with schizophrenia and healthy controls, and to identify the cognitive and pragmatic abilities that are most informative in discriminating between schizophrenia and controls. METHODS: We provided a comprehensive assessment of different aspects of pragmatic performance, i.e. linguistic, extralinguistic, paralinguistic, contextual and conversational, ToM and cognitive functions, i.e. Executive Functions (EF)—selective attention, planning, inhibition, cognitive flexibility, working memory and speed processing—and general intelligence, in a sample of 32 individuals with schizophrenia and 35 controls. RESULTS: The results showed that the BNs classifier discriminated well between patients with schizophrenia and healthy controls. The network structure revealed that only pragmatic Linguistic ability directly influenced the classification of patients and controls, while diagnosis determined performance on ToM, Extralinguistic, Paralinguistic, Selective Attention, Planning, Inhibition and Cognitive Flexibility tasks. The model identified pragmatic, ToM and cognitive abilities as three distinct domains independent of one another. CONCLUSION: Taken together, our results confirmed the importance of considering pragmatic linguistic impairment as a core dysfunction in schizophrenia, and demonstrated the potential of applying BNs in investigating the relationship between pragmatic ability and cognition.
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spelling pubmed-70537332020-03-12 Pragmatics, Theory of Mind and executive functions in schizophrenia: Disentangling the puzzle using machine learning Parola, Alberto Salvini, Rogerio Gabbatore, Ilaria Colle, Livia Berardinelli, Laura Bosco, Francesca M. PLoS One Research Article OBJECTIVE: Schizophrenia is associated with a severe impairment in the communicative-pragmatic domain. Recent research has tried to disentangle the relationship between communicative impairment and other domains usually impaired in schizophrenia, i.e. Theory of Mind (ToM) and cognitive functions. However, the results are inconclusive and this relationship is still unclear. Machine learning (ML) provides novel opportunities for studying complex relationships among phenomena and representing causality among multiple variables. The present research explored the potential of applying ML, specifically Bayesian network (BNs) analysis, to characterize the relationship between cognitive, ToM and pragmatic abilities in individuals with schizophrenia and healthy controls, and to identify the cognitive and pragmatic abilities that are most informative in discriminating between schizophrenia and controls. METHODS: We provided a comprehensive assessment of different aspects of pragmatic performance, i.e. linguistic, extralinguistic, paralinguistic, contextual and conversational, ToM and cognitive functions, i.e. Executive Functions (EF)—selective attention, planning, inhibition, cognitive flexibility, working memory and speed processing—and general intelligence, in a sample of 32 individuals with schizophrenia and 35 controls. RESULTS: The results showed that the BNs classifier discriminated well between patients with schizophrenia and healthy controls. The network structure revealed that only pragmatic Linguistic ability directly influenced the classification of patients and controls, while diagnosis determined performance on ToM, Extralinguistic, Paralinguistic, Selective Attention, Planning, Inhibition and Cognitive Flexibility tasks. The model identified pragmatic, ToM and cognitive abilities as three distinct domains independent of one another. CONCLUSION: Taken together, our results confirmed the importance of considering pragmatic linguistic impairment as a core dysfunction in schizophrenia, and demonstrated the potential of applying BNs in investigating the relationship between pragmatic ability and cognition. Public Library of Science 2020-03-03 /pmc/articles/PMC7053733/ /pubmed/32126068 http://dx.doi.org/10.1371/journal.pone.0229603 Text en © 2020 Parola et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Parola, Alberto
Salvini, Rogerio
Gabbatore, Ilaria
Colle, Livia
Berardinelli, Laura
Bosco, Francesca M.
Pragmatics, Theory of Mind and executive functions in schizophrenia: Disentangling the puzzle using machine learning
title Pragmatics, Theory of Mind and executive functions in schizophrenia: Disentangling the puzzle using machine learning
title_full Pragmatics, Theory of Mind and executive functions in schizophrenia: Disentangling the puzzle using machine learning
title_fullStr Pragmatics, Theory of Mind and executive functions in schizophrenia: Disentangling the puzzle using machine learning
title_full_unstemmed Pragmatics, Theory of Mind and executive functions in schizophrenia: Disentangling the puzzle using machine learning
title_short Pragmatics, Theory of Mind and executive functions in schizophrenia: Disentangling the puzzle using machine learning
title_sort pragmatics, theory of mind and executive functions in schizophrenia: disentangling the puzzle using machine learning
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7053733/
https://www.ncbi.nlm.nih.gov/pubmed/32126068
http://dx.doi.org/10.1371/journal.pone.0229603
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