Kareen Heinze1, Renate L E P Reniers2, Barnaby Nelson3, Alison R Yung4, Ashleigh Lin5, Ben J Harrison6, Christos Pantelis6, Dennis Velakoulis6, Patrick D McGorry3, Stephen J Wood7. 1. School of Psychology, University of Birmingham, Birmingham, United Kingdom. Electronic address: kxh114@bham.ac.uk. 2. School of Psychology, University of Birmingham, Birmingham, United Kingdom. 3. Orygen Youth Health Research Centre, University of Melbourne, Melbourne, Victoria, Australia. 4. Orygen Youth Health Research Centre, University of Melbourne, Melbourne, Victoria, Australia; Institute of Brain, Behavior and Mental Health, University of Manchester, Manchester, United Kingdom. 5. Telethon Kids Institute, University of Western Australia, Perth, Western Australia. 6. Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia. 7. School of Psychology, University of Birmingham, Birmingham, United Kingdom; Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia.
Abstract
BACKGROUND: Investigation of aberrant large-scale brain networks offers novel insight into the role these networks play in diverse psychiatric disorders such as schizophrenia. Although studies report altered functional brain connectivity in participants at ultra-high risk (UHR) for psychosis, it is unclear whether these alterations extend to structural brain networks. METHODS: Whole-brain structural covariance patterns of 133 participants at UHR for psychosis (51 of whom subsequently developed psychosis) and 65 healthy control (HC) subjects were studied. Following data preprocessing (using VBM8 toolbox), the mean signal in seed regions relating to specific networks (visual, auditory, motor, speech, semantic, executive control, salience, and default-mode) were extracted, and voxel-wise analyses of covariance were conducted to compare the association between whole-brain signal and each seed region for UHR and HC individuals. The UHR participants who transitioned to psychosis were compared with the UHR participants who did not. RESULTS: Significantly reduced structural covariance was observed in the UHR sample compared with the HC sample for the default-mode network, and increased covariance was observed for the motor and executive control networks. When the UHR participants who transitioned to psychosis were compared with the UHR participants who did not, aberrant structural covariance was observed in the salience, executive control, auditory, and motor networks. CONCLUSIONS: Whole-brain structural covariance analyses revealed subtle changes of connectivity of the default-mode, executive control, salience, motor, and auditory networks in UHR individuals for psychosis. Although we found significant differences, these are small changes and tend to reflect largely intact structural networks.
BACKGROUND: Investigation of aberrant large-scale brain networks offers novel insight into the role these networks play in diverse psychiatric disorders such as schizophrenia. Although studies report altered functional brain connectivity in participants at ultra-high risk (UHR) for psychosis, it is unclear whether these alterations extend to structural brain networks. METHODS: Whole-brain structural covariance patterns of 133 participants at UHR for psychosis (51 of whom subsequently developed psychosis) and 65 healthy control (HC) subjects were studied. Following data preprocessing (using VBM8 toolbox), the mean signal in seed regions relating to specific networks (visual, auditory, motor, speech, semantic, executive control, salience, and default-mode) were extracted, and voxel-wise analyses of covariance were conducted to compare the association between whole-brain signal and each seed region for UHR and HC individuals. The UHR participants who transitioned to psychosis were compared with the UHR participants who did not. RESULTS: Significantly reduced structural covariance was observed in the UHR sample compared with the HC sample for the default-mode network, and increased covariance was observed for the motor and executive control networks. When the UHR participants who transitioned to psychosis were compared with the UHR participants who did not, aberrant structural covariance was observed in the salience, executive control, auditory, and motor networks. CONCLUSIONS: Whole-brain structural covariance analyses revealed subtle changes of connectivity of the default-mode, executive control, salience, motor, and auditory networks in UHR individuals for psychosis. Although we found significant differences, these are small changes and tend to reflect largely intact structural networks.
Authors: Ruiyang Ge; Paul Kot; Xiang Liu; Donna J Lang; Jane Z Wang; William G Honer; Fidel Vila-Rodriguez Journal: Hum Brain Mapp Date: 2019-05-22 Impact factor: 5.038
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Authors: Leonhard Schilbach; Birgit Derntl; Andre Aleman; Svenja Caspers; Mareike Clos; Kelly M J Diederen; Oliver Gruber; Lydia Kogler; Edith J Liemburg; Iris E Sommer; Veronika I Müller; Edna C Cieslik; Simon B Eickhoff Journal: Schizophr Bull Date: 2016-03-02 Impact factor: 9.306