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Associations between long-term psychosis risk, probabilistic category learning, and attenuated psychotic symptoms with cortical surface morphometry

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Abstract

Neuroimaging studies have consistently found structural cortical abnormalities in individuals with schizophrenia, especially in structural hubs. However, it is unclear what abnormalities predate psychosis onset and whether abnormalities are related to behavioral performance and symptoms associated with psychosis risk. Using surface-based morphometry, we examined cortical volume, gyrification, and thickness in a psychosis risk group at long-term risk for developing a psychotic disorder (n = 18; i.e., extreme positive schizotypy plus interview-rated attenuated psychotic symptoms [APS]) and control group (n = 19). Overall, the psychosis risk group exhibited cortical abnormalities in multiple structural hub regions, with abnormalities associated with poorer probabilistic category learning, a behavioral measure strongly associated with psychosis risk. For instance, the psychosis risk group had hypogyria in a right posterior midcingulate cortical hub and left superior parietal cortical hub, as well as decreased volume in a right pericalcarine hub. Morphometric measures in all of these regions were also associated with poorer probabilistic category learning. In addition to decreased right pericalcarine volume, the psychosis risk group exhibited a number of other structural abnormalities in visual network structural hub regions, consistent with previous evidence of visual perception deficits in psychosis risk. Further, severity of APS hallucinations, delusional ideation, and suspiciousness/persecutory ideas were associated with gyrification abnormalities, with all domains associated with hypogyria of the right lateral orbitofrontal cortex. Thus, current results suggest that structural abnormalities, especially in structural hubs, are present in psychosis risk and are associated both with poor learning on a psychosis risk-related task and with APS severity.

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Data availability

The data generated and analyzed during the current study are available in the Open Science Framework repository, osf.io/v8zfp.

References

  • Antzoulatos, E. G., & Miller, E. K. (2014). Increases in functional connectivity between prefrontal cortex and striatum during category learning. Neuron, 83(1), 216–225.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Asami, T., Bouix, S., Whitford, T. J., Shenton, M. E., Salisbury, D. F., & McCarley, R. W. (2012). Longitudinal loss of gray matter volume in patients with first-episode schizophrenia: DARTEL automated analysis and ROI validation. NeuroImage, 59(2), 986–996.

    Article  PubMed  Google Scholar 

  • Bakker, G., Caan, M. W., Vingerhoets, W. A., da Silva-Alves, F., de Koning, M., Boot, E., et al. (2016). Cortical morphology differences in subjects at increased vulnerability for developing a psychotic disorder: A comparison between subjects with ultra-high risk and 22q11.2 deletion syndrome. PLoS One, 11(11), e0159928.

    Article  PubMed  PubMed Central  Google Scholar 

  • Barnes, J., Ridgway, G. R., Bartlett, J., Henley, S. M., Lehrmann, M., Hobbs, N., et al. (2010). Head size, age and gender adjustment in MRI studies: A necessary nuisance? NeuroImage, 53(4), 1244–1255.

    Article  PubMed  Google Scholar 

  • Behrens, T. E., Woolrich, M. W., Walton, M. E., & Rushworth, M. F. (2007). Learning the value of information in an uncertain world. Nature Neuroscience, 10(9), 1214–1221.

    Article  CAS  PubMed  Google Scholar 

  • Bois, C., Whalley, H. C., McIntosh, A. M., & Lawrie, S. M. (2015). Structural magnetic resonance imaging markers of susceptability and transition to schizophrenia: A review of familial and clinical high risk populations studies. Journal of Psychopharmacology, 29(2), 144–154.

    Article  CAS  PubMed  Google Scholar 

  • Boksa, P. (2009). On the neurobiology of hallucinations. Journal of Psychiatry & Neuroscience, 34(4), 260–262.

    Google Scholar 

  • Cannon, T. D., Chung, Y., He, G., Sun, D., Jacobson, A., van Erp, T. G. M., et al. (2015). Progressive reduction in cortical thickness as psychosis develops: A multisite longitudinal neuroimaging study of youth at elevated clinical risk. Biological Psychiatry, 77(2), 147–157.

    Article  PubMed  Google Scholar 

  • Cannon, T. D., Yu, C., Addington, J., Bearden, C. E., Cadenhead, K. S., Cornblatt, B. A., et al. (2016). An individualized risk calculator for research in prodromal psychosis. American Journal of Psychiatry, 173(10), 980–988.

    Article  Google Scholar 

  • Chapman, L. J., Chapman, J. P., & Raulin, M. L. (1978). Body-image aberration in schizophrenia. Journal of Abnormal Psychology, 87(4), 399–407.

    Article  CAS  PubMed  Google Scholar 

  • Chapman L. J., & Chapman J. P. (1983). Infrequency scale. Unpublished test.

  • Chapman, L. J., Chapman, J. P., Kwapil, T. R., Eckblad, M., & Zinser, M. (1994). Putatively psychosis-prone subjects 10 years later. Journal of Abnormal Psychology, 103(2), 171–183.

    Article  CAS  PubMed  Google Scholar 

  • Coltheart, M. (2010). The neuropsychology of delusions. Annals of the New York Academy of Sciences, 1191, 16–26.

    Article  PubMed  Google Scholar 

  • Coltheart, M., Cox, R., Sowman, P., Morgan, H., Barnier, A., Langdon, R., et al. (2018). Belief, delusion, hypnosis, and the right dorsolateral prefrontal cortex: A transcranial magnetic stimulation study. Cortex, 101, 234–248.

    Article  PubMed  Google Scholar 

  • Corlett, P. R., Taylor, J. R., Wang, X.-J., Fletcher, P. C., & Krystal, J. H. (2010). Toward a neurobiology of delusions. Progress in Neurobiology, 92, 345–369.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Corlett, P. R., Horga, G., Fletcher, P. C., Alderson-Day, B., Schmack, K., & Powers, A. R., 3rd. (2019). Hallucinations and strong priors. Trends in Cognitive Sciences, 23(2), 114–127.

    Article  PubMed  Google Scholar 

  • Crossley, N. A., Mechelli, A., Scott, J., Carletti, F., Fox, P. T., McGuire, P., & Bullmore, E. T. (2014). The hubs of the human connectome are generally implicated in the anatomy of brain disorders. Brain, 137(Pt 8), 2382–2395.

    Article  PubMed  PubMed Central  Google Scholar 

  • Dale, A. M., & Sereno, M. I. (1993). Improved localization of cortical activity by combining EEG and MEG with MRI cortical surface reconstruction: A linear approach. Journal of Cognitive Neuroscience, 5(2), 162–176.

    Article  CAS  PubMed  Google Scholar 

  • Dale, A. M., Fischl, B., & Sereno, M. I. (1999). Cortical surface-based analysis: I. Segmentation and Surface Reconstruction. Neuroimage, 9(2), 179–194.

    Article  CAS  Google Scholar 

  • Damme, K. S. F., Gupta, T., Nusslock, R., Bernard, J. A., Orr, J. M., & Mittal, V. A. (2019). Cortical morphometry in the psychosis risk period: A comprehensive perspective of surface features. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 4(5), 434–443.

    Google Scholar 

  • Das, T., Borgwardt, S., Hauke, D. J., Harrisberger, F., Lang, U. E., Riecher-Rössler, A., et al. (2018). Disorganized gyrification network properties during the transition to psychosis. JAMA Psychiatry, 75(6), 613–622.

    Article  PubMed  PubMed Central  Google Scholar 

  • DeCross, S. N., Farabaugh, A. H., Holmes, A. J., Ward, M., Boeke, E. A., Wolthusen, R. P. F., et al. (2020). Increased amygdala-visual cortex connectivity in youth with persecutory ideation. Psychological Medicine, 50(2), 273–283.

    Article  PubMed  Google Scholar 

  • Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., et al. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage, 31(3), 968–980.

    Article  PubMed  Google Scholar 

  • Dietsche, B., Kircher, T., & Falkenberg, I. (2017). Structural brain changes in schizophrenia at different stages of the illness: A selective review of longitudinal magnetic resonance imaging studies. The Australian and New Zealand Journal of Psychiatry, 51(5), 500–508.

    Article  PubMed  Google Scholar 

  • Dixon, M. L., Thiruchselvam, R., Todd, R., & Christoff, K. (2017). Emotion and the prefrontal cortex: An integrative review. Psychological Bulletin, 143(10), 1033–1081.

    Article  PubMed  Google Scholar 

  • Dorph-Petersen, K. A., Pierri, J. N., Wu, Q., Sampson, A. R., & Lewis, D. A. (2007). Primary visual cortex volume and total neuron number are reduced in schizophrenia. The Journal of Comparative Neurology, 501(2), 290–301.

    Article  PubMed  Google Scholar 

  • Eckblad, M., & Chapman, L. J. (1983). Magical ideation as an indicator of schizotypy. Journal of Consulting and Clinical Psychology, 51(2), 215–225.

    Article  CAS  PubMed  Google Scholar 

  • Ermakova, A. O., Knolle, E., Justicia, A., Bullmore, E. T., Jones, P. B., Robbins, T. W., et al. (2018). Abnormal reward prediction-error signaling in antipsychotic naïve individuals with first-episode psychosis or clinical risk for psychosis. Neuropsychopharmacology, 43(8), 1691–1699.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Fischl, B., & Dale, A. M. (2000). Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proceedings of the National Academy of Sciences, 97(20), 11050–11055.

    Article  CAS  Google Scholar 

  • Fischl, B., Sereno, M. I., & Dale, A. M. (1999a). Cortical surface-based analysis. II: Inflation, flattening, and a surface-based coordinate system. NeuroImage, 9(2), 195–207.

    Article  CAS  PubMed  Google Scholar 

  • Fischl, B., Sereno, M. I., Tootell, R. B., & Dale, A. M. (1999b). High-resolution intersubject averaging and a coordinate system for the cortical surface. Human Brain Mapping, 8(4), 272–284.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Fischl, B., Liu, A., & Dale, A. M. (2001). Automated manifold surgery: Constructing geometrically accurate and topologically correct models of the human cerebral cortex. IEEE Transactions on Medical Imaging, 20(1), 70–80.

    Article  CAS  PubMed  Google Scholar 

  • Fischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., et al. (2002). Whole brain segmentation: Automated labeling of neuroanatomical structures in the human brain. Neuron, 33(3), 341–355.

    Article  CAS  PubMed  Google Scholar 

  • Fischl, B., Salat, D. H., van der Kouwe, A. J. W., Makris, N., Ségonne, F., Quinn, B. T., et al. (2004a). Sequence-independent segmentation of magnetic resonance images. NeuroImage, 23, S69–S84.

    Article  PubMed  Google Scholar 

  • Fischl, B., van der Kouwe, A., Destrieux, C., Halgren, E., Ségonne, F., Salat, D. H., et al. (2004b). Automatically parcellating the human cerebral cortex. Cerebral Cortex, 14(1), 11–22.

    Article  PubMed  Google Scholar 

  • Fish, J. L., Dehay, C., Kennedy, H., & Huttner, W. B. (2008). Making bigger brains: The evolution of neural-progenitor-cell division. Journal of Cell Science, 121, 2783–2793.

    Article  CAS  PubMed  Google Scholar 

  • Foerde, K., & Shohamy, D. (2011). The role of the basal ganglia in learning and memory: Insight from Parkinson’s Disease. Neurobiology of Learning and Memory, 96(4), 624–636.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Fornito, A., Yoon, J., Zalesky, A., Bulmore, E. T., & Carter, C. S. (2011). General and specific functional connectivity disturbances in first-episode schizophrenia during cognitive control performance. Biological Psychiatry, 70(1), 64–72.

    Article  PubMed  PubMed Central  Google Scholar 

  • Fornito, A., Zalesky, A., Pantelis, C., & Bullmore, E. T. (2012). Schizophrenia, neuroimaging and connectomics. NeuroImage, 62(4), 2296–2314.

    Article  PubMed  Google Scholar 

  • Friston, K., Brown, H. R., Siemerkus, J., & Stephan, K. E. (2016). The dysconnection hypothesis (2016). Schizophrenia Research, 176(2–3), 83–94.

    Article  PubMed  Google Scholar 

  • Fusar-Poli, P., Borgwardt, S., Crescini, A., Deste, G., Kempton, M. J., Lawrie, S., et al. (2011). Neuroanatomy of vulnerability to psychosis: A voxel-based meta-analysis. Neuroscience and Biobehavioral Reviews, 35, 1175–1185.

    Article  CAS  PubMed  Google Scholar 

  • Gautam, P., Anstey, K. J., Wen, W., Sachdev, P. S., & Cherbuin, N. (2015). Cortical gyrification and its relationships with cortical volume, cortical thickness, and cognitive performance in healthy mid-life adults. Behavioural Brain Research, 287, 331–339.

    Article  PubMed  Google Scholar 

  • Gisselgård, J., Lebedev, A. V., Kurz, K. D., Joa, I., Johannesseen, J. O., & Bronnick, K. (2018). Structural and functional alterations in the brain during working memory in medication-naïve patients at clinical high-risk for psychosis. PLoS ONE, 13(5), e0196289.

    Article  PubMed  PubMed Central  Google Scholar 

  • Goldberg, L. R. (1999). A broad-bandwidth, public domain, personality inventory measuring the lower-level facets of several five-factor models. In I. Mervielde, I. Deary, F. D. Fruyt, & F. Ostendorf (Eds.), Personality psychology in Europe (pp. 7–28). Tilburg : Tilbur University Press.

    Google Scholar 

  • Goldman, A. L., Pezawas, L., Mattay, V. S., Fischl, B., Verchinski, B. A., Chen, Q., et al. (2009). Widespread reductions of cortical thickness in schizophrenia and spectrum disorders and evidence of heritability. Archives of General Psychiatry, 66(5), 467–477.

    Article  PubMed  PubMed Central  Google Scholar 

  • Gollo, L. L., Roberts, J. A., Cropley, V. L., Di Biase, M. A., Pantelis, C., Zalesky, A., et al. (2018). Fragility and volatility of structural hubs in the human connectome. Nature Neuroscience, 21(8), 1107–1116.

    Article  CAS  PubMed  Google Scholar 

  • Greve, D. N., & Fischl, B. (2018). False positive rates in surface-based anatomical analysis. NeuroImage, 171, 6–14.

    Article  PubMed  Google Scholar 

  • Hagler, D. J., Jr., Saygin, A. P., & Sereno, M. I. (2006). Smoothing and cluster thresholding for cortical surface-based group analysis of fMRI data. NeuroImage, 33, 1093–1103.

    Article  PubMed  Google Scholar 

  • Hajima, S. V., Van Haren, N., Cahn, W., Koolschijn, P. C., Hulshoff Pol, H. E., & Kahn, R. S. (2013). Brain volumes in schizophrenia: A meta-analysis in over 18000 subjects. Schizophrenia Bulletin, 39(5), 1129–1138.

    Article  Google Scholar 

  • Hamilton, H. K., Woods, S. W., Roach, B. J., Lierena, K., McGlashan, T. H., Srihari, V. H., et al. (2019). Auditory and visual oddball stimulus processing deficits in schizophrenia and the psychosis risk syndrome: Forecasting psychosis risk with P300. Schizophrenia Bulletin, 45(5), 1068–1080.

    Article  PubMed  Google Scholar 

  • Han, X., Jovicich, J., Salat, D., van der Kouwe, A., Quinn, B., Czanner, S., et al. (2006). Reliability of MRI-derived measurements of human cerebral cortical thickness: The effects of field strength, scanner upgrade and manufacturer. NeuroImage, 32(1), 180–194.

    Article  PubMed  Google Scholar 

  • Harris, J. M., Whalley, H., Yates, S., Miller, P., Johnstone, E. C., & Lawrie, S. M. (2004). Abnormal cortical folding in high-risk individuals: A predictor of the development of schizophrenia? Biological Psychiatry, 56(3), 182–189.

    Article  PubMed  Google Scholar 

  • Harris, J. M., Moorhead, T. W., Miller, P., McIntosh, A. M., Bonnici, H. M., Owens, D. G., et al. (2007). Increased prefrontal gyrification in a large high-risk cohort characterized those who develop schizophrenia and reflects abnormal prefrontal development. Biological Psychiatry, 62(7), 722–729.

    Article  PubMed  Google Scholar 

  • Hatton, S. N., Lagopoulos, J., Hermens, D. F., Naismith, S. L., Bennett, M. R., & Hickie, I. B. (2012). Correlating anterior insula gray matter volume changes in young people with clinical and neurocognitivee outcomes: An MRI study. BMC Psychiatry, 12, 45.

    Article  PubMed  PubMed Central  Google Scholar 

  • Hayasaka, S., & Nichols, T. E. (2003). Validating cluster size inference: Random field permutation methods. NeuroImage, 20(4), 2343–2356.

    Article  PubMed  Google Scholar 

  • Henry, J. D., & Crawford, J. R. (2005). The short-form version of the Depression Anxiety Stress Scales (DASS-21): Construct validity and normative data in a large non-clinical sample. British Journal of Clinical Psychology, 44(2), 227–239.

    Article  Google Scholar 

  • Hogstrom, L. J., Westlye, L. T., Wahlovd, K. B., & Fjell, A. M. (2013). The structure of the cerebral cortex across adult life: Age-related patterns of surface area, thickness, and gyrification. Cerebral Cortex, 23(11), 2521–2530.

    Article  PubMed  Google Scholar 

  • Honea, R., Crow, T. J., Passingham, D., & Mackay, C. E. (2005). Regional deficits in brain volume in schizophrenia: A meta-analysis of voxel-based morphometry studies. American Journal of Psychiatry, 162(12), 2233–2245.

    Article  Google Scholar 

  • Hua, J. P. Y., Karcher, N. R., Straub, K. T., & Kerns, J. G. (2019, April 12). Data for: Associations between long-term psychosis risk, probabilistic category learning, and attenuated psychotic symptoms with cortical surface morphometry. Retrieved from osf.io/v8zfp. [dataset].

  • Im, K., Lee, J. M., Lyttelton, O., Kim, S. H., Evans, A. C., & Kim, S. I. (2008). Brain size and cortical structure in the adult human brain. Cerebral Cortex, 18(9), 2181–2191.

    Article  PubMed  Google Scholar 

  • Jalbrzikowski, M., Jonas, R., Senturk, D. D., Patel, A., Chow, C., Green, M. F., & Bearden, C. E. (2013). Structural abnormalities in corticall volume, thickness, an dsurface area in 22q11.2 microddeletion syndrome: Relationship with psychotic symptoms. NeuroImage: Clinical, 3, 405–415.

    Article  Google Scholar 

  • Jovicich, J., Czanner, S., Greve, D., Haley, E., van der Kouwe, A., Gollub, R., et al. (2006). Reliability in multi-site structural MRI studies: Effects of gradient non-linearity correction on phantom and human data. NeuroImage, 30(2), 436–443.

    Article  PubMed  Google Scholar 

  • Jung, W. H., Kim, J. S., Jang, J. H., Choi, J. S., Jung, M. H., Park, J. Y., et al. (2011). Cortical thickness reduction in individuals at ultra-high-risk for psychosis. Schizophrenia Bulletin, 37(4), 839–849.

    Article  PubMed  Google Scholar 

  • Karcher, N. R., Martin, E. A., & Kerns, J. G. (2015). Examining associations between psychosis risk, social anhedonia, and performance of striatum-related behavioral tasks. Journal of Abnormal Psychology, 124(3), 507–518.

    Article  PubMed  PubMed Central  Google Scholar 

  • Karcher, N. R., Hua, J. P. Y., & Kerns, J. G. (2019). Probabilistic category learning and striatal functional activation in psychosis risk. Schizophrenia Bulletin, 45(2), 396–404.

    Article  PubMed  Google Scholar 

  • Klauser, P., Zhou, J., Lim, J. K., Poh, J. S., Zheng, H., Tng, H. Y., et al. (2015). Lack of evidence for regional brain volume or cortical thickness abnormalities in youths at clinical high risk for psychosis: Findings from the Longitudinal Youth at Risk Study. Schizophrenia Bulletin, 41(6), 1285–1293.

    Article  PubMed  PubMed Central  Google Scholar 

  • Klein, D., Rotarska-Jagiela, A., Genc, E., Sritharan, S., Mohr, H., Roux, F., et al. (2014). Adolescent brain maturation and cortical folding: Evidence for reductions in gyrification. PLoS ONE, 9(1), e84914.

    Article  PubMed  PubMed Central  Google Scholar 

  • Knowlton, B. J., Squire, L. R., & Gluck, M. A. (1994). Probabilistic classification learning in amnesia. Learning & Memory, 1, 106–120.

    Article  CAS  Google Scholar 

  • Knowlton, B. J., Mangels, J. A., & Squire, L. R. (1996). A neostriatal habit learning system in humans. Science, 273(5280), 1399–1402.

    Article  CAS  PubMed  Google Scholar 

  • Konishi, J., del Re, E. C., Bouix, S., Blokland, G. A. M., Mesholam-Gately, R., Woodberry, K., et al. (2018). Abnormal relationships between local and global brain measures in subjects at clinical high risk for psychosis: A pilot study. Brain Imaging and Behavior, 12(4), 974–988.

    Article  PubMed  PubMed Central  Google Scholar 

  • Köse, G., Jessen, K., Ebdrup, B. H., & Nielsen, M. O. (2018). Associations between cortical thickness and auditory verbal hallucinations in patients with schizophrenia: A systematic review. Psychiatry Research. Neuroimaging, 282, 31–39.

    Article  PubMed  Google Scholar 

  • Kwak, Y. B., Kim, M., Cho, K. I. K., Lee, J., Lee, T. Y., & Kwon, J. S. (2019). Reduced cortical thickness in subjects at clinical high risk for psychosis and clinical attributes. Australian and New Zealand Journal of Psychiatry, 53(3), 219–227.

    Article  Google Scholar 

  • Lin, A., Ching, C. R. K., Vajdi, A., Sun, D., Jonas, R. K., Jalbrzikowski, M., et al. (2017). Mapping 22q11.2 gene dosage effects on brain morphometry. Journal of Neuroscience, 37(26), 6183–6199.

    Article  CAS  PubMed  Google Scholar 

  • Luders, E., Narr, K. L., Thompson, P. M., Rex, D. E., Jancke, L., Steinmetz, H., et al. (2004). Gender differences in cortical complexity. Nature Neuroscience, 7(8), 799–800.

    Article  CAS  PubMed  Google Scholar 

  • Lynall, M. E., Bassett, D. S., Kerwin, R., McKenna, P. J., Kitzbichler, M., Muller, U., & Bullmore, E. (2010). Functional connectivity and brain networks in schizophrenia. Journal of Neuroscience, 30(28), 9477–9487.

    Article  CAS  PubMed  Google Scholar 

  • Martinez, A., Gaspar, P. A., Hillyard, S. A., Andersen, S. K., Lopez-Calderon, J., Corcoran, C. M., & Javitt, D. C. (2018). Impaired motion processing in schizophrenia and the attenuated psychosis syndrome: Etiologial and clinical implications. The American Journal of Psychiatry, 175(12), 1243–1254.

    Article  PubMed  PubMed Central  Google Scholar 

  • Matsuda, Y., & Ohi, K. (2018). Cortical gyrification in schizophrenia: Current perspectives. Neuropsychiatric Disease and Treatment, 14, 1861–1869.

    Article  PubMed  PubMed Central  Google Scholar 

  • Menon, V., & Uddin, L. Q. (2010). Saliency, switching, attention and control: A network model of insula function. Brain Structure & Function, 214(5–6), 655–667.

    Article  Google Scholar 

  • Miller, T. J., McGlashan, T. H., Rosen, J. L., Cadenhead, K., Ventura, J., McFarlane, W., et al. (2003). Prodromal assessment with the structured interview for prodromal syndromes and the scale of prodromal symptoms: Predictive validity, interrater reliability, and training to reliability. Schizophrenia Bulletin, 29(4), 703–715.

    Article  PubMed  Google Scholar 

  • Mittal, V. A., Gupta, T., Keane, B. P., & Silverstein, S. M. (2015). Visual context processing dysfunctions in your at risk for psychosis: Resistance to the Ebbinhaus illusion and its symptom and social and role functioning correlates. Journal of Abnormal Pscyhollogy, 124(4), 953–960.

    Article  Google Scholar 

  • Modinos, G., Costafreda, S. G., van Tol, M. J., McGuire, P. K., Aleman, A., & Allen, P. (2013). Neuroanatomy of auditory verbal hallucinations in schizophrenia: A quantitative meta-analysis of voxel-based morphometry studies. Cortex, 49(4), 1046–1055.

    Article  PubMed  Google Scholar 

  • Neilson, E., Bois, C., Clarke, T.-K., Hall, L., Johnstone, E. C., Owens, D. G. C., et al. (2018). Polygenic risk for schizophrenia, transition and corticall gyrification: A high-risk study. Psychological Medicine, 48(9), 1532–1539.

    Article  CAS  PubMed  Google Scholar 

  • Nelson, B. G., Bassett, D. S., Camchong, J., Bullmore, E. T., & Lim, K. O. (2017). Comparison of large-scale human brain functional and anatomical networks in schizophrenia. NeuroImage. Clinical, 15, 439–448.

    Article  PubMed  PubMed Central  Google Scholar 

  • Onitsuka, T., Shenton, M. E., Salisbury, D. F., Dickey, C. C., Kasai, K., Toner, S. K., et al. (2004). Middle and inferior temporal gyrus gray matter volume abnormalities in chronic schizophrenia: An MRI study. American Journal of Psychiatry, 161(9), 1603–1611.

    Article  Google Scholar 

  • Padula, M. C., Schaer, M., Armando, M., Sandini, C., Zöller, D., Scariati, E., et al. (2018). Cortical morphology development in patients with 22q11.2 deletion syndrome at ultra-high risk of psycohsis. Psychological Medicine, 48(14), 2375–2383.

    Article  PubMed  Google Scholar 

  • Pomarol-Clotet, E., Canales-Rodríguez, E. J., Salvador, R., Sarró, S., Gomar, J. J., Vila, F., et al. (2010). Medial prefrontal cortex pathology in schizophrenia as revealed by convergent findings from multimodal imaging. Molecular Psychiatry, 15(8), 823–830.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Powers, A. R., Mathys, C., & Corlett, P. R. (2017). Pavlovian conditioning-induced hallucinations result from overweighting of perceptual priors. Science, 357(6351), 596–600.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Rakic, P. (1995). Radial versus tangential migration of neuronal clones in the developing cerebral cortex. Proceedings of the National Academy of Sciences of the United States of America, 92(25), 11323–11327.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Ritchie, S. J., Cox, S. R., Shen, X., Lombardo, M. V., Reus, L. M., Alloza, C., et al. (2018). Sex differences in the adult human brain: Evidence from 5216 UK biobank participants. Cerebral Cortex, 28(8), 2959–2975.

    Article  PubMed  PubMed Central  Google Scholar 

  • Rubinov, M., & Bullmore, E. (2013). Schizophrenia and abnormal brain network hubs. Dialogues in Clinical Neuroscience, 15(3), 339–349.

    Article  PubMed  PubMed Central  Google Scholar 

  • Sasabayashi, D., Takayanagi, Y., Takahashi, T., Koike, S., Yamasue, H., Katagiri, N., et al. (2017). Increased occipital gyrification and development of psychotic disorders in individuals with an at-risk mental state: A multicenter study. Biological Psychiatry, 82, 737–745.

    Article  PubMed  Google Scholar 

  • Schaer, M., Cuadra, M. B., Tamarit, L., Lazeyras, F., Eliez, S., & Thiran, J. P. (2008). A surface-based approach to quantify local cortical gyrification. IEEE Transactions on Medical Imaging, 27(2), 161–170.

    Article  PubMed  Google Scholar 

  • Schaer, M., Cuadra, M. B., Schmansky, N., Fischl, B., Thiran, J. P., & Eliez, S. (2012). How to measure cortical folding from MR images: A step-by-step tutorial to compute local gyrificationn index. Journal of Visualized Experiments, 59, e3417.

    Google Scholar 

  • Schaer, M., Otter, M. C., Scariati, E., Dukes, D., Fanchini, M., Eliez, S., et al. (2013). Decreased frontal gyrification correaltes with altered connectivity in children with autism. Frontiers in Human Neuroscience, 7, 750.

    Article  PubMed  PubMed Central  Google Scholar 

  • Scheinost, D., Tokoglu, F., Hampson, M., Hoffman, R., & Constable, R. T. (2019). Data-driven analysis of functional connectivity reveals a potential auditory verbal hallucination network. Schizophrenia Bulletin, 45(2), 416–424.

    Article  Google Scholar 

  • Schmack, K., Rothkirch, M., Priller, J., & Sterzer, P. (2017). Enhanced predictive signalling in schizophrenia. Human Brain Mapping, 38(4), 1767–1779.

    Article  PubMed  PubMed Central  Google Scholar 

  • Schmidt, A., Crossley, N. A., Harrisberger, B., Smieskova, R., Lenz, C., Riecher-Rössler, A., et al. (2017). Structural network disorganization in subjects at clinical high risk for psychosis. Schizophrenia Bulletin, 43(3), 583–591.

    PubMed  Google Scholar 

  • Ségonne, F., Dale, A. M., Busa, E., Glessner, M., Salat, D., Hahn, H. K., & Fischl, B. (2004). A hybrid approach to the skull stripping problem in MRI. NeuroImage, 22(3), 1060–1075.

    Article  PubMed  Google Scholar 

  • Ségonne, F., Pacheco, J., & Fischl, B. (2007). Geometrically accurate topology-correction of cortical surfaces using nonseparating loops. IEEE Transactions on Medical Imaging, 26(4), 518–529.

    Article  PubMed  Google Scholar 

  • Silverstein, S. M. (2016). Visual perception disturbances in schizophrenia: A unified model. Nebraska Symposium on Motivation, 63, 77–132. https://doi.org/10.1007/978-3-319-30596-7_4

  • Sled, J. G., Zijdenbos, A. P., & Evans, A. C. (1998). A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Transactions on Medical Imaging, 17(1), 87–97.

    Article  CAS  PubMed  Google Scholar 

  • Song, J., Han, D. H., Hong, J. S., Cheong, J. H., & Kim, B. N. (2015). Differences in gray matter volume corresponding to delusion and hallucination in patients with schizophrenia compared with patients who have bipolar disorder. Neuropsychiatric Disease and Treatment, 18(11), 1211–1219.

    Article  Google Scholar 

  • Spalthoff, R., Gaser, C., & Nenadić. (2018). Altered gyrification in schizophrenia and its relation to other morphometric markers. Schizophrenia Research, 202, 195–202.

    Article  PubMed  Google Scholar 

  • Sterzer, P., Adams, R. A., Fletcher, P., Frith, C., Lawrie, S. M., Muckli, L., et al. (2018). The predictive coding account of psychosis. Biological Psychiatry, 84(9), 634–643.

    Article  PubMed  PubMed Central  Google Scholar 

  • Sterzer, P., Voss, M., Schlagenhauf, F., & Heinz, A. (2019). Decision-making in schizophrenia: A predictive coding perspective. NeuroImage, 190, 133–143.

    Article  PubMed  Google Scholar 

  • Sun, D., Ching, C. R. K., Lin, A., Forsyth, J. K., Kushan, L., Vajdi, A., et al. (2020). Large-scale mapping of cortical alterations in 22q11.2 deletion syndrome: Convergence with idiopathic psychosis and effects of deletion size. Molecular Psychiatry, 25(8), 1822–1834.

    Article  CAS  PubMed  Google Scholar 

  • Tohid, H., Faizan, M., & Faizan, U. (2015). Alterations of the occipital lobe in schizophrenia. Neurosciences (riyadh), 20(3), 213–224.

    Article  Google Scholar 

  • Tohka, J. (2014). Partial volume effect modeling for segmentation and tissue calssification of brain magnetic resonance images: A review. World Journal of Radiology, 6(11), 855–864.

    Article  PubMed  PubMed Central  Google Scholar 

  • Toro, R., & Burnod, Y. (2005). A morphogenetic model for the development of cortical convolutions. Cerebral Cortex, 15(12), 1900–1913.

    Article  PubMed  Google Scholar 

  • Toro, R., Perron, M., Pike, B., Richer, L., Veillette, S., Pausova, Z., et al. (2008). Brain size and folding of the human cerebral cortex. Cerebral Cortex, 18(10), 2352–2357.

    Article  PubMed  Google Scholar 

  • Van, D. C., & Essen. (1997). A tension-based theory of morphogenesis and compact wiring in the central nervous system. Nature, 385, 313–318.

    Article  Google Scholar 

  • van den Heuvel, M. P., & Sporns, O. (2013). Network hubs in the human brain. Trends in Cognitive Sciences, 17(12), 683–696.

    Article  PubMed  Google Scholar 

  • van den Heuvel, M. P., Mandl, R. C., Stam, C. J., Kahn, R. S., & Hulshoff Pol, H. E. (2010). Aberrant frontal and temporal complex network structure in schizophrenia: A graph theoretical analysis. Journal of Neuroscience, 30(47), 15915–15926.

    Article  PubMed  Google Scholar 

  • van Erp, T. G. M., Walton, E., Hibar, D. P., Schmaal, L., Jiang, W., Glahn, D. C., et al. (2018). Cortical brain abnormalities in 4474 individuals with schizophrenia and 5098 control subjects via the Enhancing Neuro Imaging Genetics through Meta Analysis (ENIGMA) consortium. Biological Psychiatry, 84(9), 644–654.

    Article  PubMed  PubMed Central  Google Scholar 

  • Vogt, B. A. (2016). Midcingulate cortex: Structure, connections, homologies, functions and diseases. Journal of Chemical Neuroanatomy, 74, 28–46.

    Article  CAS  PubMed  Google Scholar 

  • Weickert, T. W. (2018). Probabilistic association learning in schizophrenia. Current Opinion in Behavioral Sciences, 20, 1–8.

    Article  Google Scholar 

  • Weickert, T. W., Goldberg, T. E., Callicott, J. H., Chen, Q., Apud, J. A., Das, S., et al. (2009). Neural correlates of probabilistic category learning in patients with schizophrenia. Journal of Neuroscience, 29(4), 1244–1254.

    Article  CAS  PubMed  Google Scholar 

  • Wierenga, L. M., Langen, M., Oranje, B., & Durston, S. (2014). Unique developmental trajectories of cortical thickness and surface area. NeuroImage, 87, 120–126.

    Article  PubMed  Google Scholar 

  • Winkler, A. M., Kochunov, P., Blangero, J., Almasy, L., Zilles, K., Fox, P. T., et al. (2010). Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies. NeuroImage, 53(3), 1135–1146.

    Article  PubMed  Google Scholar 

  • Winkler, A. M., Greve, D. N., Bjuland, K. J., Nichols, T. E., Sabuncu, M. R., Håberg, A. K., et al. (2018). Joint analysis of cortical area and thickness as a replacement for the analysis of the volume of the cerebral cortex. Cerebral Cortex, 28(2), 738–749.

    Article  PubMed  Google Scholar 

  • Woodward, N. D., & Heckers, S. (2016). Mapping thalamocortical functional connectivity in chronic and early stages of psychotic disorders. Biological Psychiatry, 79(12), 1016–1025.

    Article  PubMed  Google Scholar 

  • Yeo, B. T. T., Krienen, F. M., Sepulcre, J., Sabuncu, M. R., Lashkari, D., Hollinshead, M., et al. (2011). The organization of the human cerebral cortex estimated by intrinsic functional connectivity. Journal of Neurophysiology, 106, 1125–1165.

    Article  PubMed  Google Scholar 

  • Ziermans, T. B., Schothorst, P. F., Schnack, H. G., Koolschijn, P. C., Kahn, R. S., van Engeland, H., et al. (2012). Progressive structural brain changes during development of psychosis. Schizophrenia Bulletin, 38(3), 519–530.

    Article  PubMed  Google Scholar 

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Acknowledgements

This research was supported by National Institute of Mental Health grant R21 MH100359 (JGK), University of Missouri research funds (JGK), University of Missouri dissertation research funds (JPYH), and National Institute of Mental Health grant T32 MH014677 (NRK).

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Authors and Affiliations

  1. Department of Psychological Sciences, University of Missouri, Columbia, MO, 65211, USA

    Jessica P. Y. Hua, Nicole R. Karcher, Kelsey T. Straub & John G. Kerns

  2. Department of Mental Health, San Francisco VA Medical Center, San Francisco, CA, 94121, USA

    Jessica P. Y. Hua

  3. Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, 63110, USA

    Nicole R. Karcher

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Correspondence to John G. Kerns.

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This study was supported by NIMH grant R21 MH100359 (JGK), University of Missouri research funds (JGK), University of Missouri dissertation research funds (JPYH), and NIMH grant T32 MH014677 (NRK).

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Hua, J.P.Y., Karcher, N.R., Straub, K.T. et al. Associations between long-term psychosis risk, probabilistic category learning, and attenuated psychotic symptoms with cortical surface morphometry. Brain Imaging and Behavior 16, 91–106 (2022). https://doi.org/10.1007/s11682-021-00479-8

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