Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Original Article
  • Published:

Connectome-wide network analysis of youth with Psychosis-Spectrum symptoms

Molecular Psychiatry volume 20, pages 1508–1515 (2015)Cite this article

Subjects

Abstract

Adults with psychotic disorders have dysconnectivity in critical brain networks, including the default mode (DM) and the cingulo-opercular (CO) networks. However, it is unknown whether such deficits are present in youth with less severe symptoms. We conducted a multivariate connectome-wide association study examining dysconnectivity with resting state functional magnetic resonance imaging in a population-based cohort of 188 youths aged 8–22 years with psychosis-spectrum (PS) symptoms and 204 typically developing (TD) comparators. We found evidence for multi-focal dysconnectivity in PS youths, implicating the bilateral anterior cingulate, frontal pole, medial temporal lobe, opercular cortex and right orbitofrontal cortex. Follow-up seed-based and network-level analyses demonstrated that these results were driven by hyper-connectivity among DM regions and diminished connectivity among CO regions, as well as diminished coupling between frontal and DM regions. Collectively, these results provide novel evidence for functional dysconnectivity in PS youths, which show marked correspondence to abnormalities reported in adults with established psychotic disorders.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1
Figure 2
Figure 3
Figure 4

Similar content being viewed by others

References

  1. Addington J, Cadenhead KS, Cannon TD, Cornblatt B, McGlashan TH, Perkins DO et al. North american prodrome longitudinal study: a collaborative multisite approach to prodromal schizophrenia research. Schizophr Bull 2007; 33: 665–672.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Insel TR . Translating scientific opportunity into public health impact: a strategic plan for research on mental illness. Arch Gen Psychiatry 2009; 66: 128–133.

    Article  PubMed  Google Scholar 

  3. Insel TR . Rethinking schizophrenia. Nature 2010; 468: 187–193.

    Article  CAS  PubMed  Google Scholar 

  4. Calkins ME, Moore TM, Merikangas KR, Burstein M, Satterthwaite TD, Bilker WB et al. The psychosis spectrum in a young U.S. Community sample: findings from the philadelphia neurodevelopmental cohort. World Psychiatry 2014; 13: 296–305.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Gur RC, Richard J, Calkins ME, Chiavacci R, Hansen JA, Bilker WB et al. Age group and sex differences in performance on a computerized neurocognitive battery in children age 8-21. Neuropsychology 2012; 26: 251–265.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Gur RC, Calkins ME, Satterthwaite TD, Ruparel K, Bilker WB, Moore TM et al. Neurocognitive growth charting in psychosis spectrum youths. JAMA Psychiatry 2014; 71: 366–374.

    Article  PubMed  Google Scholar 

  7. Casey BJ, Oliveri ME, Insel T . A neurodevelopmental perspective on the research domain criteria (rdoc) framework. Biol Psychiatry 2014; 76: 350–353.

    Article  CAS  PubMed  Google Scholar 

  8. Cuthbert BN, Insel TR . Toward new approaches to psychotic disorders: the NIMH research domain criteria project. Schizophr Bull 2010; 36: 1061–1062.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Insel T, Cuthbert B, Garvey M, Heinssen R, Pine DS, Quinn K et al. Research domain criteria (rdoc): toward a new classification framework for research on mental disorders. Am J Psychiatry 2010; 167: 748–751.

    Article  PubMed  Google Scholar 

  10. McGlashan TH, Miller TJ, Woods SW . Pre-onset detection and intervention research in schizophrenia psychoses: current estimates of benefit and risk. Schizophr Bull 2001; 27: 563–570.

    Article  CAS  PubMed  Google Scholar 

  11. Rapoport JL, Giedd JN, Gogtay N . Neurodevelopmental model of schizophrenia: update 2012. Mol Psychiatry 2012; 17: 1228–1238.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Haijma SV, Van Haren N, Cahn W, Koolschijn PCMP, Hulshoff Pol HE, Kahn RS . Brain volumes in schizophrenia: a meta-analysis in over 18 000 subjects. Schizophr Bull 2013; 39: 1129–1138.

    Article  PubMed  Google Scholar 

  13. Vita A, De Peri L, Deste G, Sacchetti E . Progressive loss of cortical gray matter in schizophrenia: a meta-analysis and meta-regression of longitudinal MRI studies. Transl Psychiatry 2012; 2: e190.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Callicott JH, Bertolino A, Mattay VS, Langheim FJ, Duyn J, Coppola R et al. Physiological dysfunction of the dorsolateral prefrontal cortex in schizophrenia revisited. Cereb Cortex 2000; 10: 1078–1092.

    Article  CAS  PubMed  Google Scholar 

  15. Satterthwaite TD, Wolf DH, Loughead J, Ruparel K, Valdez JN, Siegel SJ et al. Association of enhanced limbic response to threat with decreased cortical facial recognition memory response in schizophrenia. Am J Psychiatry 2010; 167: 418–426.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Cooper D, Barker V, Radua J, Fusar-Poli P, Lawrie SM . Multimodal voxel-based meta-analysis of structural and functional magnetic resonance imaging studies in those at elevated genetic risk of developing schizophrenia. Psychiatry Res 2014; 221: 69–77.

    Article  PubMed  Google Scholar 

  17. Nekovarova T, Fajnerova I, Horacek J, Spaniel F . Bridging disparate symptoms of schizophrenia: a triple network dysfunction theory. Front Behav Neurosci 2014; 8: 171.

    PubMed  PubMed Central  Google Scholar 

  18. Baker JT, Holmes AJ, Masters GA, Yeo BTT, Krienen F, Buckner RL et al. Disruption of cortical association networks in schizophrenia and psychotic bipolar disorder. JAMA Psychiatry 2014; 71: 109–118.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Calhoun VD, Sui J, Kiehl K, Turner J, Allen E, Pearlson G . Exploring the psychosis functional connectome: aberrant intrinsic networks in schizophrenia and bipolar disorder. Front Psychiatry 2011; 2: 75.

    PubMed  Google Scholar 

  20. Rubinov M, Bullmore E . Fledgling pathoconnectomics of psychiatric disorders. Trends Cogn Sci 2013; 17: 641–647.

    Article  PubMed  Google Scholar 

  21. Fornito A, Zalesky A, Pantelis C, Bullmore ET . Schizophrenia, neuroimaging and connectomics. Neuroimage 2012; 62: 2296–2314.

    Article  PubMed  Google Scholar 

  22. Garrity AG, Pearlson GD, McKiernan K, Lloyd D, Kiehl KA, Calhoun VD . Aberrant ‘default mode’ functional connectivity in schizophrenia. Am J Psychiatry 2007; 164: 450–457.

    Article  PubMed  Google Scholar 

  23. Woodward ND, Rogers B, Heckers S . Functional resting-state networks are differentially affected in schizophrenia. Schizophr Res 2011; 130: 86–93.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Ren W, Lui S, Deng W, Li F, Li M, Huang X et al. Anatomical and functional brain abnormalities in drug-naive first-episode schizophrenia. Am J Psychiatry 2013; 170: 1308–1316.

    Article  PubMed  Google Scholar 

  25. Zhou Y, Liang M, Jiang T, Tian L, Liu Y, Liu Z et al. Functional dysconnectivity of the dorsolateral prefrontal cortex in first-episode schizophrenia using resting-state fMRI. Neurosci Lett 2007; 417: 297–302.

    Article  CAS  PubMed  Google Scholar 

  26. Alonso-Solís A, Corripio I, de Castro-Manglano P, Duran-Sindreu S, Garcia-Garcia M, Proal E et al. Altered default network resting state functional connectivity in patients with a first episode of psychosis. Schizophr Res 2012; 139: 13–18.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Fornito A, Yoon J, Zalesky A, Bullmore ET, Carter CS . General and specific functional connectivity disturbances in first-episode schizophrenia during cognitive control performance. Biol Psychiatry 2011; 70: 64–72.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Whitfield-Gabrieli S, Thermenos HW, Milanovic S, Tsuang MT, Faraone SV, McCarley RW et al. Hyperactivity and hyperconnectivity of the default network in schizophrenia and in first-degree relatives of persons with schizophrenia. Proc Natl Acad Sci USA 2009; 106: 1279–1284.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. van Buuren M, Vink M, Kahn RS . Default-mode network dysfunction and self-referential processing in healthy siblings of schizophrenia patients. Schizophr Res 2012; 142: 237–243.

    Article  PubMed  Google Scholar 

  30. Shim G, Oh JS, Jung WH, Jang JH, Choi C-H, Kim E et al. Altered resting-state connectivity in subjects at ultra-high risk for psychosis: an fMRI study. Behav Brain Funct 2010; 6: 58.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Wotruba D, Michels L, Buechler R, Metzler S, Theodoridou A, Gerstenberg M et al. Aberrant coupling within and across the default mode, task-positive, and salience network in subjects at risk for psychosis. Schizophr Bull 2013; 40: 1095–1104.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Tang J, Liao Y, Song M, Gao J-H, Zhou B, Tan C et al. Aberrant default mode functional connectivity in early onset schizophrenia. PLoS One 2013; 8: e71061.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Tu P-C, Lee Y-C, Chen Y-S, Li C-T, Su T-P . Schizophrenia and the brain's control network: aberrant within- and between-network connectivity of the frontoparietal network in schizophrenia. Schizophr Res 2013; 147: 339–347.

    Article  PubMed  Google Scholar 

  34. Cole MW, Yarkoni T, Repovs G, Anticevic A, Braver TS . Global connectivity of prefrontal cortex predicts cognitive control and intelligence. J Neurosci 2012; 32: 8988–8999.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Hampson M, Driesen NR, Skudlarski P, Gore JC, Constable RT . Brain connectivity related to working memory performance. J Neurosci 2006; 26: 13338–13343.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Saykin AJ, Gur RC, Gur RE, Mozley PD, Mozley LH, Resnick SM et al. Neuropsychological function in schizophrenia. Selective impairment in memory and learning. Arch Gen Psychiatry 1991; 48: 618–624.

    Article  CAS  PubMed  Google Scholar 

  37. Saykin AJ, Shtasel DL, Gur RE, Kester DB, Mozley LH, Stafiniak P et al. Neuropsychological deficits in neuroleptic naive patients with first-episode schizophrenia. Arch Gen Psychiatry 1994; 51: 124–131.

    Article  CAS  PubMed  Google Scholar 

  38. Greenwood TA, Lazzeroni LC, Murray SS, Cadenhead KS, Calkins ME, Dobie DJ et al. Analysis of 94 candidate genes and 12 endophenotypes for schizophrenia from the consortium on the genetics of schizophrenia. Am J Psychiatry 2011; 168: 930–946.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Shehzad Z, Kelly C, Reiss PT, Cameron Craddock R, Emerson JW, McMahon K et al. A multivariate distance-based analytic framework for connectome-wide association studies. Neuroimage 2014; 93: 74–94.

    Article  PubMed  Google Scholar 

  40. Zapala MA, Schork NJ . Statistical properties of multivariate distance matrix regression for high-dimensional data analysis. Front Genet 2012; 3: 190.

    Article  PubMed  PubMed Central  Google Scholar 

  41. van Os J, Linscott RJ, Myin-Germeys I, Delespaul P, Krabbendam L . A systematic review and meta-analysis of the psychosis continuum: evidence for a psychosis proneness-persistence-impairment model of psychotic disorder. Psychol Med 2009; 39: 179–195.

    Article  CAS  PubMed  Google Scholar 

  42. Kelleher I, Connor D, Clarke MC, Devlin N, Harley M, Cannon M . Prevalence of psychotic symptoms in childhood and adolescence: a systematic review and meta-analysis of population-based studies. Psychol Med 2012; 42: 1857–1863.

    Article  CAS  PubMed  Google Scholar 

  43. Kelleher I, Murtagh A, Molloy C, Roddy S, Clarke MC, Harley M et al. Identification and characterization of prodromal risk syndromes in young adolescents in the community: a population-based clinical interview study. Schizophr Bull 2012; 38: 239–246.

    Article  PubMed  Google Scholar 

  44. Kelleher I, Cannon M, Cannon M . Psychotic-like experiences in the general population: characterizing a high-risk group for psychosis. Psychol Med 2011; 41: 1–6.

    Article  CAS  PubMed  Google Scholar 

  45. Kelleher I, Corcoran P, Keeley H, Wigman JT, Devlin N, Ramsay H et al. Psychotic symptoms and population risk for suicide attempt: a prospective cohort study. JAMA Psychiatry 2013; 70: 940–948.

    Article  PubMed  Google Scholar 

  46. Jacobson McEwen SC, Connolly CG, Kelly AMC, Kelleher I, O'Hanlon E, Clarke M et al. Resting-state connectivity deficits associated with impaired inhibitory control in non-treatment-seeking adolescents with psychotic symptoms. Acta Psychiatr Scand 2014; 129: 134–142.

    Article  CAS  PubMed  Google Scholar 

  47. Satterthwaite TD, Elliott MA, Ruparel K, Loughead J, Prabhakaran K, Calkins ME et al. Neuroimaging of the philadelphia neurodevelopmental cohort. Neuroimage 2014; 86: 544–553.

    Article  PubMed  Google Scholar 

  48. Satterthwaite TD, Wolf DH, Loughead J, Ruparel K, Elliott MA, Hakonarson H et al. Impact of in-scanner head motion on multiple measures of functional connectivity: relevance for studies of neurodevelopment in youth. Neuroimage 2012; 60: 623–632.

    Article  PubMed  Google Scholar 

  49. Satterthwaite TD, Elliott MA, Gerraty RT, Ruparel K, Loughead J, Calkins ME et al. An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data. Neuroimage 2013; 64: 240–256.

    Article  PubMed  Google Scholar 

  50. Satterthwaite TD, Wolf DH, Roalf DR, Ruparel K, Erus G, Vandekar S et al. Linked sex differences in cognition and functional connectivity in youth. Cereb Cortex 2014 (in press).

  51. Jenkinson M, Beckmann CF, Behrens TEJ, Woolrich MW, Smith SM . FSL. Neuroimage 2012; 62: 782–790.

    Article  PubMed  Google Scholar 

  52. Greve DN, Fischl B . Accurate and robust brain image alignment using boundary-based registration. Neuroimage 2009; 48: 63–72.

    Article  PubMed  Google Scholar 

  53. Avants BB, Epstein CL, Grossman M, Gee JC . Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Med Image Anal 2008; 12: 26–41.

    Article  CAS  PubMed  Google Scholar 

  54. Avants BB, Tustison NJ, Song G, Cook PA, Klein A, Gee JC . A reproducible evaluation of ants similarity metric performance in brain image registration. Neuroimage 2011; 54: 2033–2044.

    Article  PubMed  Google Scholar 

  55. Klein A, Andersson J, Ardekani BA, Ashburner J, Avants B, Chiang M-C et al. Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration. Neuroimage 2009; 46: 786–802.

    Article  PubMed  Google Scholar 

  56. Satterthwaite TD, Wolf DH, Ruparel K, Erus G, Elliott MA, Eickhoff SB et al. Heterogeneous impact of motion on fundamental patterns of developmental changes in functional connectivity during youth. Neuroimage 2013; 83: 45–57.

    Article  PubMed  Google Scholar 

  57. Cox RW . AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput Biomed Res 1996; 29: 162–173.

    Article  CAS  PubMed  Google Scholar 

  58. Van Essen DC, Drury HA, Dickson J, Harwell J, Hanlon D, Anderson CH . An integrated software suite for surface-based analyses of cerebral cortex. J Am Med Inform Assoc 2001; 8: 443–459.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Yeo BTT, Krienen FM, Sepulcre J, Sabuncu MR, Lashkari D, Hollinshead M et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J Neurophysiol 2011; 106: 1125–1165.

    Article  PubMed  Google Scholar 

  60. Bastian M, Heymann S, Jacomy M . Gephi: an open source software for exploring and manipulating networks. ICWSM 2009; 8: 361–362.

    Google Scholar 

  61. Bassett DS, Porter MA, Wymbs NF, Grafton ST, Carlson JM, Mucha PJ . Robust detection of dynamic community structure in networks. Chaos 2013; 23: 013142.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Gur RC, Richard J, Hughett P, Calkins ME, Macy L, Bilker WB et al. A cognitive neuroscience-based computerized battery for efficient measurement of individual differences: standardization and initial construct validation. J Neurosci Methods 2010; 187: 254–262.

    Article  PubMed  Google Scholar 

  63. Moore TM, Reise SP, Gur RE, Hakonarson H, Gur RC . Psychometric properties of the penn computerized neurocognitive battery. Neuropsychology 2014; 29: 235–246.

    Article  PubMed  PubMed Central  Google Scholar 

  64. Wolf DH, Satterthwaite TD, Calkins ME, Ruparel K, Elliott MA, Hopson RD et al. Functional neuroimaging abnormalities in psychosis spectrum youth. JAMA Psychiatry 2015; 72: 456–465.

    Article  PubMed  PubMed Central  Google Scholar 

  65. Anticevic A, Hu X, Xiao Y, Hu J, Li F, Bi F et al. Early-course unmedicated schizophrenia patients exhibit elevated prefrontal connectivity associated with longitudinal change. J Neurosci 2015; 35: 267–286.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Anticevic A, Repovs G, Barch DM . Working memory encoding and maintenance deficits in schizophrenia: neural evidence for activation and deactivation abnormalities. Schizophr Bull 2013; 39: 168–178.

    Article  PubMed  Google Scholar 

  67. Seidman LJ, Rosso IM, Thermenos HW, Makris N, Juelich R, Gabrieli JDE et al. Medial temporal lobe default mode functioning and hippocampal structure as vulnerability indicators for schizophrenia: a MRI study of non-psychotic adolescent first-degree relatives. Schizophr Res 2014; 159: 426–434.

    Article  PubMed  Google Scholar 

  68. Orliac F, Naveau M, Joliot M, Delcroix N, Razafimandimby A, Brazo P et al. Links among resting-state default-mode network, salience network, and symptomatology in schizophrenia. Schizophr Res 2013; 148: 74–80.

    Article  PubMed  Google Scholar 

  69. Di Martino A, Shehzad Z, Kelly C, Roy AK, Gee DG, Uddin LQ et al. Relationship between cingulo-insular functional connectivity and autistic traits in neurotypical adults. Am J Psychiatry 2009; 166: 891–899.

    Article  PubMed  PubMed Central  Google Scholar 

  70. Gordon EM, Laumann TO, Adeyemo B, Huckins JF, Kelley WM, Petersen SE . Generation and evaluation of a cortical area parcellation from resting-state correlations. Cereb Cortex 2014 (in press).

  71. Craddock RC, James G, Holtzheimer PE, Hu XP, Mayberg HS . A whole brain fMRI atlas generated via spatially constrained spectral clustering. Hum Brain Mapp 2012; 33: 1914–1928.

    Article  PubMed  Google Scholar 

  72. Power JD, Cohen AL, Nelson SM, Wig GS, Barnes KA, Church JA et al. Functional network organization of the human brain. Neuron 2011; 72: 665–678.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Honnorat N, Eavani H, Satterthwaite TD, Gur RE, Gur RC, Davatzikos C . GraSP: geodesic graph-based segmentation with shape priors for the functional parcellation of the cortex. Neuroimage 2014; 106: 207–221.

    Article  PubMed  Google Scholar 

  74. Paus T, Keshavan M, Giedd JN . Why do many psychiatric disorders emerge during adolescence? Nat Rev Neurosci 2008; 9: 947–957.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Cannon TD, Chung Y, He G, Sun D, Jacobson A, van Erp TGM et al. Progressive reduction in cortical thickness as psychosis develops: a multisite longitudinal neuroimaging study of youth at elevated clinical risk. Biol Psychiatry 2015; 77: 147–157.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

Thanks to the acquisition and recruitment team: Karthik Prabhakaran, Ryan Hopson, Jeff Valdez, Raphael Gerraty, Marisa Riley, Jack Keefe, Elliott Yodh and Rosetta Chiavacci. Thanks to Mark Elliott for image acquisition support. Thanks to Frank Mentch for data management. This work was supported by RC2 grants from the National Institute of Mental Health MH089983 and MH089924 and P50MH096891. Support for developing statistical analyses (SNV, RTS, TDS) was provided by a seed grant by the Center for Biomedical Computing and Image Analysis (CBICA) at Pennsylvania. Support for network analytics was provided by the Institute for Translational Medicine and Therapeutics (ITMAT) at Pennsylvania to DSB and TDS. Additional support was provided by K23MH098130 to TDS, R01MH101111 to DHW, K01MH102609 to DRR, K08MH079364 to MEC, R01NS085211 to RTS, T32MH065218-11 to SNV and the Dowshen Program for Neuroscience.

Author information

Authors and Affiliations

  1. Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    T D Satterthwaite, S N Vandekar, D H Wolf, K Ruparel, T M Moore, E D Gennatas, C Jackson, D R Roalf, M E Calkins, R C Gur & R E Gur

  2. Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA, USA

    S N Vandekar & R T Shinohara

  3. Departments of Bioengineering and Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA

    D S Bassett

  4. Department of Psychology, Yale University, New Haven, CT, USA

    Z Shehzad

  5. Center for the Developing Brain, Child Mind Institute, New York, NY, USA

    Z Shehzad, R C Craddock & M P Milham

  6. Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research,

    R C Craddock & M P Milham

  7. Orangeburg, NY, USA

    R C Craddock & M P Milham

  8. Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA

    H Hakonarson

  9. Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    H Hakonarson

  10. Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    R C Gur & R E Gur

  11. Philadelphia Veterans Administration Medical Center, Philadelphia, PA, USA

    R C Gur

Authors
  1. T D Satterthwaite
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S N Vandekar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. D H Wolf
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. D S Bassett
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. K Ruparel
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Z Shehzad
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. R C Craddock
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. R T Shinohara
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. T M Moore
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. E D Gennatas
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. C Jackson
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. D R Roalf
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. M P Milham
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. M E Calkins
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. H Hakonarson
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. R C Gur
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. R E Gur
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to T D Satterthwaite.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Additional information

Supplementary Information accompanies the paper on the Molecular Psychiatry website

Supplementary information

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Satterthwaite, T., Vandekar, S., Wolf, D. et al. Connectome-wide network analysis of youth with Psychosis-Spectrum symptoms. Mol Psychiatry 20, 1508–1515 (2015). https://doi.org/10.1038/mp.2015.66

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/mp.2015.66

This article is cited by

Search

Advanced search

Quick links