State-Dependent Functional Dysconnectivity in Youth With Psychosis Spectrum Symptoms

Abstract Psychosis spectrum disorders are conceptualized as neurodevelopmental disorders accompanied by disruption of large-scale functional brain networks. Dynamic functional dysconnectivity has been described in patients with schizophrenia and in help-seeking individuals at clinical high risk for...

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Published inSchizophrenia bulletin Vol. 46; no. 2; pp. 408 - 421
Main Authors Mennigen, Eva, Jolles, Dietsje D, Hegarty, Catherine E, Gupta, Mohan, Jalbrzikowski, Maria, Olde Loohuis, Loes M, Ophoff, Roel A, Karlsgodt, Katherine H, Bearden, Carrie E
Format Journal Article
LanguageEnglish
Published US Oxford University Press 01.03.2020
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Online AccessGet full text
ISSN0586-7614
1745-1701
1745-1701
DOI10.1093/schbul/sbz052

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Abstract Abstract Psychosis spectrum disorders are conceptualized as neurodevelopmental disorders accompanied by disruption of large-scale functional brain networks. Dynamic functional dysconnectivity has been described in patients with schizophrenia and in help-seeking individuals at clinical high risk for psychosis. Less is known, about developmental aspects of dynamic functional network connectivity (dFNC) associated with psychotic symptoms (PS) in the general population. Here, we investigate resting state functional magnetic resonance imaging data using established dFNC methods in the Philadelphia Neurodevelopmental Cohort (ages 8–22 years), including 129 participants experiencing PS and 452 participants without PS (non-PS). Functional networks were identified using group spatial independent component analysis. A sliding window approach and k-means clustering were applied to covariance matrices of all functional networks to identify recurring whole-brain connectivity states. PS-associated dysconnectivity of default mode, salience, and executive networks occurred only in a few states, whereas dysconnectivity in the sensorimotor and visual systems in PS youth was more pervasive, observed across multiple states. This study provides new evidence that disruptions of dFNC are present even at the less severe end of the psychosis continuum in youth, complementing previous work on help-seeking and clinically diagnosed cohorts that represent the more severe end of this spectrum.
AbstractList Psychosis spectrum disorders are conceptualized as neurodevelopmental disorders accompanied by disruption of large-scale functional brain networks. Dynamic functional dysconnectivity has been described in patients with schizophrenia and in help-seeking individuals at clinical high risk for psychosis. Less is known, about developmental aspects of dynamic functional network connectivity (dFNC) associated with psychotic symptoms (PS) in the general population. Here, we investigate resting state functional magnetic resonance imaging data using established dFNC methods in the Philadelphia Neurodevelopmental Cohort (ages 8–22 years), including 129 participants experiencing PS and 452 participants without PS (non-PS). Functional networks were identified using group spatial independent component analysis. A sliding window approach and k-means clustering were applied to covariance matrices of all functional networks to identify recurring whole-brain connectivity states. PS-associated dysconnectivity of default mode, salience, and executive networks occurred only in a few states, whereas dysconnectivity in the sensorimotor and visual systems in PS youth was more pervasive, observed across multiple states. This study provides new evidence that disruptions of dFNC are present even at the less severe end of the psychosis continuum in youth, complementing previous work on help-seeking and clinically diagnosed cohorts that represent the more severe end of this spectrum.
Psychosis spectrum disorders are conceptualized as neurodevelopmental disorders accompanied by disruption of large-scale functional brain networks. Dynamic functional dysconnectivity has been described in patients with schizophrenia and in help-seeking individuals at clinical high risk for psychosis. Less is known, about developmental aspects of dynamic functional network connectivity (dFNC) associated with psychotic symptoms (PS) in the general population. Here, we investigate resting state functional magnetic resonance imaging data using established dFNC methods in the Philadelphia Neurodevelopmental Cohort (ages 8-22 years), including 129 participants experiencing PS and 452 participants without PS (non-PS). Functional networks were identified using group spatial independent component analysis. A sliding window approach and k-means clustering were applied to covariance matrices of all functional networks to identify recurring whole-brain connectivity states. PS-associated dysconnectivity of default mode, salience, and executive networks occurred only in a few states, whereas dysconnectivity in the sensorimotor and visual systems in PS youth was more pervasive, observed across multiple states. This study provides new evidence that disruptions of dFNC are present even at the less severe end of the psychosis continuum in youth, complementing previous work on help-seeking and clinically diagnosed cohorts that represent the more severe end of this spectrum.Psychosis spectrum disorders are conceptualized as neurodevelopmental disorders accompanied by disruption of large-scale functional brain networks. Dynamic functional dysconnectivity has been described in patients with schizophrenia and in help-seeking individuals at clinical high risk for psychosis. Less is known, about developmental aspects of dynamic functional network connectivity (dFNC) associated with psychotic symptoms (PS) in the general population. Here, we investigate resting state functional magnetic resonance imaging data using established dFNC methods in the Philadelphia Neurodevelopmental Cohort (ages 8-22 years), including 129 participants experiencing PS and 452 participants without PS (non-PS). Functional networks were identified using group spatial independent component analysis. A sliding window approach and k-means clustering were applied to covariance matrices of all functional networks to identify recurring whole-brain connectivity states. PS-associated dysconnectivity of default mode, salience, and executive networks occurred only in a few states, whereas dysconnectivity in the sensorimotor and visual systems in PS youth was more pervasive, observed across multiple states. This study provides new evidence that disruptions of dFNC are present even at the less severe end of the psychosis continuum in youth, complementing previous work on help-seeking and clinically diagnosed cohorts that represent the more severe end of this spectrum.
Abstract Psychosis spectrum disorders are conceptualized as neurodevelopmental disorders accompanied by disruption of large-scale functional brain networks. Dynamic functional dysconnectivity has been described in patients with schizophrenia and in help-seeking individuals at clinical high risk for psychosis. Less is known, about developmental aspects of dynamic functional network connectivity (dFNC) associated with psychotic symptoms (PS) in the general population. Here, we investigate resting state functional magnetic resonance imaging data using established dFNC methods in the Philadelphia Neurodevelopmental Cohort (ages 8–22 years), including 129 participants experiencing PS and 452 participants without PS (non-PS). Functional networks were identified using group spatial independent component analysis. A sliding window approach and k-means clustering were applied to covariance matrices of all functional networks to identify recurring whole-brain connectivity states. PS-associated dysconnectivity of default mode, salience, and executive networks occurred only in a few states, whereas dysconnectivity in the sensorimotor and visual systems in PS youth was more pervasive, observed across multiple states. This study provides new evidence that disruptions of dFNC are present even at the less severe end of the psychosis continuum in youth, complementing previous work on help-seeking and clinically diagnosed cohorts that represent the more severe end of this spectrum.
Author Olde Loohuis, Loes M
Ophoff, Roel A
Jolles, Dietsje D
Jalbrzikowski, Maria
Hegarty, Catherine E
Bearden, Carrie E
Mennigen, Eva
Gupta, Mohan
Karlsgodt, Katherine H
AuthorAffiliation 3 Department of Psychiatry, University of Pittsburgh , Pittsburgh, PA
4 Center for Neurobehavioral Genetics, University of California , Los Angeles, Los Angeles, CA
1 Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California , Los Angeles, Los Angeles, CA
2 Department of Psychology, University of California , Los Angeles, Los Angeles, CA
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– name: 4 Center for Neurobehavioral Genetics, University of California , Los Angeles, Los Angeles, CA
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CitedBy_id crossref_primary_10_3389_fpsyt_2023_1305359
crossref_primary_10_3389_fnins_2022_770468
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Copyright The Author(s) 2019. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. 2019
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Issue 2
Keywords adolescence
psychosis spectrum
independent component analysis
dynamic functional network connectivity
Language English
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Snippet Abstract Psychosis spectrum disorders are conceptualized as neurodevelopmental disorders accompanied by disruption of large-scale functional brain networks....
Psychosis spectrum disorders are conceptualized as neurodevelopmental disorders accompanied by disruption of large-scale functional brain networks. Dynamic...
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StartPage 408
SubjectTerms Adolescent
Adult
Brain - diagnostic imaging
Brain - physiopathology
Child
Cohort Studies
Connectome
Female
Help seeking behavior
Humans
Magnetic Resonance Imaging
Male
Nerve Net - diagnostic imaging
Nerve Net - physiopathology
Neurodevelopmental Disorders - diagnostic imaging
Neurodevelopmental Disorders - physiopathology
Psychosis
Psychotic Disorders - diagnostic imaging
Psychotic Disorders - physiopathology
Regular
Young Adult
Title State-Dependent Functional Dysconnectivity in Youth With Psychosis Spectrum Symptoms
URI https://www.ncbi.nlm.nih.gov/pubmed/31219595
https://www.proquest.com/docview/3191358874
https://www.proquest.com/docview/2244153506
https://pubmed.ncbi.nlm.nih.gov/PMC7442416
Volume 46
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