Literature DB >> 33686409

The representation of mental state information in schizophrenia and first-degree relatives: a multivariate pattern analysis of fMRI data.

David Dodell-Feder1,2, Laura M Tully3, Emily Dudek1, Christine I Hooker4.   

Abstract

Individuals with a schizophrenia-spectrum disorder (SSD) and those at familial high risk (FHR) for SSDs experience social difficulties that are related to neural abnormalities in the network of brain regions recruited during theory of mind (ToM). Prior work with these groups has focused almost exclusively on characterizing the involvement of these regions in ToM. Here, we examine the representational content of these regions using multivariate pattern analysis. We analyzed two previously collected datasets of SSD, FHR and control participants who, while undergoing functional magnetic resonance imaging, completed the false-belief task in which they read stories describing beliefs or physical representations (e.g. photographs). Univariate and multivariate analyses were performed in regions of interest to evaluate group differences in task-based activation and representational content, respectively. Compared to non-SSDs, SSDs showed reduced decoding accuracy for the category of mental states in the right temporo-parietal junction-which was related to false-belief accuracy-and the dorsal medial prefrontal cortex (DMPFC) and reduced involvement of DMPFC for mental state understanding. FHR showed no differences in decoding accuracy or involvement compared to non-FHR. Given prior studies of disrupted neural involvement in FHR and the lack of decoding differences observed here, the onset of illness may involve processes that corrupt how mental state information is represented.
© The Author(s) 2021. Published by Oxford University Press.

Entities:  

Keywords:  fMRI; familial risk; multivariate pattern analysis; schizophrenia; theory of mind

Year:  2021        PMID: 33686409     DOI: 10.1093/scan/nsab028

Source DB:  PubMed          Journal:  Soc Cogn Affect Neurosci        ISSN: 1749-5016            Impact factor:   3.436


  2 in total

1.  Resting-State Networks Associated with Behavioral and Self-Reported Measures of Persecutory Ideation in Psychosis.

Authors:  Lingyan Yu; Rebecca Kazinka; Danielle Pratt; Anita Kwashie; Angus W MacDonald
Journal:  Brain Sci       Date:  2021-11-11

2.  Intelligent Analysis of Exercise Health Big Data Based on Deep Convolutional Neural Network.

Authors:  Cui Cui
Journal:  Comput Intell Neurosci       Date:  2022-06-28
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.