Literature DB >> 32456505

Parietal-Prefrontal Feedforward Connectivity in Association With Schizophrenia Genetic Risk and Delusions.

Danielle L B Greenman1, Michelle A N La1, Shefali Shah1, Qiang Chen1, Karen F Berman1, Daniel R Weinberger1, Hao Yang Tan1.   

Abstract

OBJECTIVE: Conceptualizations of delusion formation implicate deficits in feedforward information updating across the posterior to prefrontal cortices, resulting in dysfunctional integration of new information about contexts in working memory and, ultimately, failure to update overfamiliar prior beliefs. The authors used functional MRI and machine learning models to address individual variability in feedforward parietal-prefrontal information updating in patients with schizophrenia. They examined relationships between feedforward connectivity, and delusional thinking and polygenic risk for schizophrenia.
METHODS: The authors studied 66 schizophrenia patients and 143 healthy control subjects during performance of context updating in working memory. Dynamic causal models of effective connectivity were focused on regions of the prefrontal and parietal cortex potentially implicated in delusion processes. The effect of polygenic risk for schizophrenia on connectivity was examined in healthy individuals. The authors then leveraged support vector regression models to define optimal normalized target connectivity tailored for each patient and tested the extent to which deviation from this target could predict individual variation in severity of delusions.
RESULTS: In schizophrenia patients, updating and manipulating context information was disproportionately less accurate than was working memory maintenance, with an interaction of task accuracy by diagnosis. Patients with delusions also tended to have relatively reduced parietal-prefrontal feedforward effective connectivity during context updating in working memory manipulation. The same connectivity was adversely influenced by polygenic risk for schizophrenia in healthy subjects. Individual patients' deviation from predicted "normal" feedforward connectivity based on the support vector regression models correlated with severity of delusions.
CONCLUSIONS: These computationally derived observations support a role for feedforward parietal-prefrontal information processing deficits in delusional psychopathology and in genetic risk for schizophrenia.

Entities:  

Keywords:  Computational Psychiatry; Delusions; Schizophrenia Spectrum and Other Psychotic Disorders

Year:  2020        PMID: 32456505      PMCID: PMC7704895          DOI: 10.1176/appi.ajp.2020.19111176

Source DB:  PubMed          Journal:  Am J Psychiatry        ISSN: 0002-953X            Impact factor:   18.112


  40 in total

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2.  Dorsolateral prefrontal cortex activity during maintenance and manipulation of information in working memory in patients with schizophrenia.

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4.  Effective connectivity during working memory and resting states: A DCM study.

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Journal:  Neuroimage       Date:  2017-12-25       Impact factor: 6.556

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Review 6.  Building a Science of Individual Differences from fMRI.

Authors:  Julien Dubois; Ralph Adolphs
Journal:  Trends Cogn Sci       Date:  2016-04-30       Impact factor: 20.229

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Authors:  Hao-Yang Tan; Joseph H Callicott; Daniel R Weinberger
Journal:  Cereb Cortex       Date:  2007-09       Impact factor: 5.357

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Authors:  W D Penny; K E Stephan; A Mechelli; K J Friston
Journal:  Neuroimage       Date:  2004-07       Impact factor: 6.556

9.  Common polygenic variation contributes to risk of schizophrenia and bipolar disorder.

Authors:  Shaun M Purcell; Naomi R Wray; Jennifer L Stone; Peter M Visscher; Michael C O'Donovan; Patrick F Sullivan; Pamela Sklar
Journal:  Nature       Date:  2009-07-01       Impact factor: 49.962

10.  Symptom dimensions of the psychotic symptom rating scales in psychosis: a multisite study.

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Journal:  Schizophr Bull       Date:  2014-07       Impact factor: 9.306

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1.  Air pollution interacts with genetic risk to influence cortical networks implicated in depression.

Authors:  Zhi Li; Hao Yan; Xiao Zhang; Shefali Shah; Guang Yang; Qiang Chen; Shizhong Han; Dai Zhang; Daniel R Weinberger; Weihua Yue; Hao Yang Tan
Journal:  Proc Natl Acad Sci U S A       Date:  2021-11-16       Impact factor: 11.205

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