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Disruptions of frontoparietal control network and default mode network linking the metacognitive deficits with clinical symptoms in schizophrenia

The metacognitive deficit in awareness of one's own mental states is a core feature of schizophrenia (SZ). The previous studies suggested that the metacognitive deficit associates with clinical symptoms. However, the neural mechanisms underlying the relationship remain largely unknown. We here...

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Autores principales: Jia, Wenbin, Zhu, Hong, Ni, Yinmei, Su, Jie, Xu, Rui, Jia, Hongxiao, Wan, Xiaohong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7267896/
https://www.ncbi.nlm.nih.gov/pubmed/31789478
http://dx.doi.org/10.1002/hbm.24887
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author Jia, Wenbin
Zhu, Hong
Ni, Yinmei
Su, Jie
Xu, Rui
Jia, Hongxiao
Wan, Xiaohong
author_facet Jia, Wenbin
Zhu, Hong
Ni, Yinmei
Su, Jie
Xu, Rui
Jia, Hongxiao
Wan, Xiaohong
author_sort Jia, Wenbin
collection PubMed
description The metacognitive deficit in awareness of one's own mental states is a core feature of schizophrenia (SZ). The previous studies suggested that the metacognitive deficit associates with clinical symptoms. However, the neural mechanisms underlying the relationship remain largely unknown. We here investigated the neural activities associated with the metacognitive deficit and the neural signatures associated with clinical symptoms in 38 patients with SZ using functional magnetic resonance imaging with a perceptual decision‐making task accompanied with metacognition, in comparison to 38 age, gender, and education matched healthy control subjects. The metacognitive deficit in patients with SZ was associated with reduced regional activity in both the frontoparietal control network (FPCN) and the default mode network. Critically, the anticorrelational balance between the two disrupted networks was substantially altered during metacognition, and the extent of alteration positively scaled with negative symptoms. Conversely, decoupling between the two networks was impaired when metacognitive monitoring was not required, and the strength of excessive neural activity positively scaled with positive symptoms. Thus, disruptions of the FPCN and the default mode network underlie the metacognitive deficit, and alternations of network balance between the two networks correlate with clinical symptoms in SZ. These findings implicate that rebalancing these networks holds important clinical potential in developing more efficacious therapeutic treatments.
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spelling pubmed-72678962020-06-12 Disruptions of frontoparietal control network and default mode network linking the metacognitive deficits with clinical symptoms in schizophrenia Jia, Wenbin Zhu, Hong Ni, Yinmei Su, Jie Xu, Rui Jia, Hongxiao Wan, Xiaohong Hum Brain Mapp Research Articles The metacognitive deficit in awareness of one's own mental states is a core feature of schizophrenia (SZ). The previous studies suggested that the metacognitive deficit associates with clinical symptoms. However, the neural mechanisms underlying the relationship remain largely unknown. We here investigated the neural activities associated with the metacognitive deficit and the neural signatures associated with clinical symptoms in 38 patients with SZ using functional magnetic resonance imaging with a perceptual decision‐making task accompanied with metacognition, in comparison to 38 age, gender, and education matched healthy control subjects. The metacognitive deficit in patients with SZ was associated with reduced regional activity in both the frontoparietal control network (FPCN) and the default mode network. Critically, the anticorrelational balance between the two disrupted networks was substantially altered during metacognition, and the extent of alteration positively scaled with negative symptoms. Conversely, decoupling between the two networks was impaired when metacognitive monitoring was not required, and the strength of excessive neural activity positively scaled with positive symptoms. Thus, disruptions of the FPCN and the default mode network underlie the metacognitive deficit, and alternations of network balance between the two networks correlate with clinical symptoms in SZ. These findings implicate that rebalancing these networks holds important clinical potential in developing more efficacious therapeutic treatments. John Wiley & Sons, Inc. 2019-12-02 /pmc/articles/PMC7267896/ /pubmed/31789478 http://dx.doi.org/10.1002/hbm.24887 Text en © 2019 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Research Articles
Jia, Wenbin
Zhu, Hong
Ni, Yinmei
Su, Jie
Xu, Rui
Jia, Hongxiao
Wan, Xiaohong
Disruptions of frontoparietal control network and default mode network linking the metacognitive deficits with clinical symptoms in schizophrenia
title Disruptions of frontoparietal control network and default mode network linking the metacognitive deficits with clinical symptoms in schizophrenia
title_full Disruptions of frontoparietal control network and default mode network linking the metacognitive deficits with clinical symptoms in schizophrenia
title_fullStr Disruptions of frontoparietal control network and default mode network linking the metacognitive deficits with clinical symptoms in schizophrenia
title_full_unstemmed Disruptions of frontoparietal control network and default mode network linking the metacognitive deficits with clinical symptoms in schizophrenia
title_short Disruptions of frontoparietal control network and default mode network linking the metacognitive deficits with clinical symptoms in schizophrenia
title_sort disruptions of frontoparietal control network and default mode network linking the metacognitive deficits with clinical symptoms in schizophrenia
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7267896/
https://www.ncbi.nlm.nih.gov/pubmed/31789478
http://dx.doi.org/10.1002/hbm.24887
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