Correction: To address methodologic error in study reporting structural brain abnormalities in youth with psychosis spectrum symptoms (JAMA Psychiatry (2016) 73:5 (515-524) DOI: 10.1001/jamapsychiatry.2015.3463);Structural brain abnormalities in youth with psychosis spectrum symptoms

JAMA Psychiatry

Volumn 73, Issue 5, 2016, Pages 515-524

  Satterthwaite, Theodore D ^a   Wolf, Daniel H ^a   Calkins, Monica E ^a   Vandekar, Simon N ^b   Erus, Guray ^b   Ruparel, Kosha ^a   Roalf, David R ^a   Linn, Kristin A ^b   Elliott, Mark A ^b   Moore, Tyler M ^a   Hakonarson, Hakon ^c   Shinohara, Russell T ^b   Davatzikos, Christos ^b   Gur, Ruben C ^a,b   Gur, Raquel E ^a,b  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

^c CHILDREN S HOSPITAL OF PHILADELPHIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADOLESCENT; ARTICLE; BRAIN DEVELOPMENT; BRAIN DISEASE; BRAIN REGION; BRAIN SIZE; CEREBROSPINAL FLUID; COMORBIDITY; DISEASE SEVERITY; DORSOLATERAL PREFRONTAL CORTEX; FEMALE; FRONTAL CORTEX; GRAY MATTER; HUMAN; IMAGE QUALITY; MAJOR CLINICAL STUDY; MALE; MEDIAL TEMPORAL LOBE; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; ORBITAL CORTEX; PARIETAL CORTEX; POSITIVE SYNDROME; POSTERIOR CINGULATE; PSYCHOSIS; PSYCHOSIS SPECTRUM SYMPTOM; STRUCTURAL BRAIN ABNORMALITY; TEMPORAL CORTEX; VENTROMEDIAL PREFRONTAL CORTEX; WHITE MATTER; ABNORMALITIES; BRAIN; CHILD; COHORT ANALYSIS; DIAGNOSTIC IMAGING; PROSPECTIVE STUDY; REFERENCE VALUE; YOUNG ADULT;

ADOLESCENT; BRAIN; CHILD; COHORT STUDIES; FEMALE; HUMANS; MAGNETIC RESONANCE IMAGING; MALE; PROSPECTIVE STUDIES; PSYCHOTIC DISORDERS; REFERENCE VALUES; YOUNG ADULT;

EID: 84973386988     PISSN: 2168622X     EISSN: None     Source Type: Journal    
DOI: 10.1001/jamapsychiatry.2017.0007     Document Type: Erratum

References (113)

1. Freedman R. Schizophrenia. N Engl J Med. 2003; 349 (18): 1738-1749.
2. Kessler RC, Avenevoli S, Costello EJ, et al. Prevalence, persistence, and sociodemographic correlates of DSM-IV disorders in the National Comorbidity Survey Replication Adolescent Supplement. Arch Gen Psychiatry. 2012; 69 (4): 372-380.
3. Kessler RC, Avenevoli S, Costello J, et al. Severity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication Adolescent Supplement. Arch Gen Psychiatry. 2012; 69 (4): 381-389.
4. Casey BJ, OliveriME, Insel T. A neurodevelopmental perspective on the Research Domain Criteria (RDoC) framework. Biol Psychiatry. 2014; 76 (5): 350-353.
5. Di Martino A, Fair DA, Kelly C, et al. Unraveling themiswired connectome: a developmental perspective. Neuron. 2014; 83 (6): 1335-1353.
6. Insel TR. Rethinking schizophrenia. Nature. 2010; 468 (7321): 187-193.
7. Rapoport JL, Giedd JN, Gogtay N. Neurodevelopmental model of schizophrenia: update 2012. Mol Psychiatry. 2012; 17 (12): 1228-1238.
8. McGlashan TH, Johannessen JO. Early detection and intervention with schizophrenia: rationale. Schizophr Bull. 1996; 22 (2): 201-222.
9. Addington J, Cadenhead KS, Cannon TD, et al; North American Prodrome Longitudinal Study. North American Prodrome Longitudinal Study: a collaborative multisite approach to prodromal schizophrenia research. Schizophr Bull. 2007; 33 (3): 665-672.
10. RuggeriM, Bonetto C, Lasalvia A, et al; GET UP Group. Feasibility and effectiveness of a multi-element psychosocial intervention for first-episode psychosis: results from the cluster-randomized controlled GET UP PIANO Trial in a catchment area of 10 million inhabitants. Schizophr Bull. 2015; 41 (5): 1192-1203.
11. Bora E, Fornito A, Radua J, et al. Neuroanatomical abnormalities in schizophrenia: a multimodal voxelwisemeta-analysis and meta-regression analysis. Schizophr Res. 2011; 127 (1-3): 46-57.
12. Chan RC, Di X, McAlonan GM, Gong QY. Brain anatomical abnormalities in high-risk individuals, first-episode, and chronic schizophrenia: an activation likelihood estimationmeta-analysis of illness progression. Schizophr Bull. 2011; 37 (1): 177-188.
13. Glahn DC, Laird AR, Ellison-Wright I, et al. Meta-analysis of gray matter anomalies in schizophrenia: application of anatomic likelihood estimation and network analysis. Biol Psychiatry. 2008; 64 (9): 774-781.
14. Gur RE, Maany V, Mozley PD, Swanson C, BilkerW, Gur RC. Subcortical MRI volumes in neuroleptic-naive and treated patientswith schizophrenia.AmJ Psychiatry. 1998; 155 (12): 1711-1717.
15. Haijma SV, Van Haren N, CahnW, Koolschijn PC, Hulshoff Pol HE, Kahn RS. Brain volumes in schizophrenia: ameta-analysis in over 18 000 subjects. Schizophr Bull. 2013; 39 (5): 1129-1138.
16. Honea R, Crow TJ, Passingham D, Mackay CE. Regional deficits in brain volume in schizophrenia: ameta-analysis of voxel-based morphometry studies. Am J Psychiatry. 2005; 162 (12): 2233-2245.
17. Gur RE, Cowell P, Turetsky BI, et al. A follow-up magnetic resonance imaging study of schizophrenia: relationship of neuroanatomical changes to clinical and neurobehavioral measures. Arch Gen Psychiatry. 1998; 55 (2): 145-152.
18. Gur RE, Turetsky BI, Cowell PE, et al. Temporolimbic volume reductions in schizophrenia. Arch Gen Psychiatry. 2000; 57 (8): 769-775.
19. Thompson PM, Stein JL, Medland SE, et al; Alzheimer's Disease Neuroimaging Initiative; EPIGEN Consortium; IMAGEN Consortium; Saguenay Youth Study (SYS) Group. The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data. Brain Imaging Behav. 2014; 8 (2): 153-182.
20. van Erp TG, Hibar DP, Rasmussen JM, et al. Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA Consortium [published online June 2, 2015]. Mol Psychiatry. 2015.
21. Medoff DR, Holcomb HH, Lahti AC, Tamminga CA. Probing the human hippocampus using rCBF: contrasts in schizophrenia. Hippocampus. 2001; 11 (5): 543-550.
22. Knable MB, Barci BM, WebsterMJ, Meador-Woodruff J, Torrey EF; Stanley Neuropathology Consortium. Molecular abnormalities of the hippocampus in severe psychiatric illness: postmortem findings from the Stanley Neuropathology Consortium. Mol Psychiatry. 2004; 9 (6): 609-620.
23. Heckers S, Rauch SL, Goff D, et al. Impaired recruitment of the hippocampus during conscious recollection in schizophrenia. Nat Neurosci. 1998; 1 (4): 318-323.
24. Heckers S. Neuroimaging studies of the hippocampus in schizophrenia. Hippocampus. 2001; 11 (5): 520-528.
25. Gao XM, Sakai K, Roberts RC, Conley RR, Dean B, Tamminga CA. Ionotropic glutamate receptors and expression of N-methyl-D-aspartate receptor subunits in subregions of human hippocampus: effects of schizophrenia. Am J Psychiatry. 2000; 157 (7): 1141-1149.
26. Ganzola R, Maziade M, Duchesne S. Hippocampus and amygdala volumes in children and young adults at high-risk of schizophrenia: research synthesis. Schizophr Res. 2014; 156 (1): 76-86.
27. Dean DJ, Orr JM, Bernard JA, et al. Hippocampal shape abnormalities predict symptom progression in neuroleptic-free youth at ultrahigh risk for psychosis. Schizophr Bull. 2016; 42 (1): 161-169.
28. Boos HB, Aleman A, CahnW, Hulshoff Pol H, Kahn RS. Brain volumes in relatives of patients with schizophrenia: ameta-analysis. Arch Gen Psychiatry. 2007; 64 (3): 297-304.
29. McDonald C, Dineen B, Hallahan B. Meta-analysis of brain volumes in unaffected first-degree relatives of patients with schizophrenia overemphasizes hippocampal deficits. Arch Gen Psychiatry. 2008; 65 (5): 603-604.
30. Roalf DR, Vandekar SN, Almasy L, et al. Heritability of subcortical and limbic brain volume and shape in multiplex-multigenerational families with schizophrenia. Biol Psychiatry. 2015; 77 (2): 137-146.
31. Palaniyappan L, Maayan N, Bergman H, Davenport C, Adams CE, Soares-Weiser K. Voxel-based morphometry for separation of schizophrenia from other types of psychosis in first episode psychosis. Cochrane Database Syst Rev. 2015; 8: CD011021.
32. Nenadic I, Dietzek M, Schönfeld N, et al. Brain structure in people at ultra-high risk of psychosis, patients with first-episode schizophrenia, and healthy controls: a VBM study. Schizophr Res. 2015; 161 (2-3): 169-176.
33. Bois C, Levita L, Ripp I, et al. Hippocampal, amygdala and nucleus accumbens volume in first-episode schizophrenia patients and individuals at high familial risk: a cross-sectional comparison. Schizophr Res. 2015; 165 (1): 45-51.
34. Cannon TD, Chung Y, He G, et al; North American Prodrome Longitudinal Study Consortium. Progressive reduction in cortical thickness as psychosis develops: a multisite longitudinal neuroimaging study of youth at elevated clinical risk. Biol Psychiatry. 2015; 77 (2): 147-157.
35. 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 (2): 179-195.
36. Calkins ME, Moore TM, Merikangas KR, et al. The psychosis spectrum in a young U.S. community sample: findings from the Philadelphia Neurodevelopmental Cohort.World Psychiatry. 2014; 13 (3): 296-305.
37. Calkins ME, Merikangas KR, Moore TM, et al. The Philadelphia Neurodevelopmental Cohort: constructing a deep phenotyping collaborative. J Child Psychol Psychiatry. 2015; 56 (12): 1356-1369.
38. 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 (4): 563-570.
39. Satterthwaite TD, Vandekar SN, Wolf DH, et al. Connectome-wide network analysis of youth with psychosis-spectrum symptoms. Mol Psychiatry. 2015; 20 (12): 1508-1515.
40. Wolf DH, Satterthwaite TD, Calkins ME, et al. Functional neuroimaging abnormalities in youth with psychosis spectrum symptoms. JAMA Psychiatry. 2015; 72 (5): 456-465.
41. O'Hanlon E, Leemans A, Kelleher I, et al. White matter differences among adolescents reporting psychotic experiences: a population-based diffusion magnetic resonance imaging study. JAMA Psychiatry. 2015; 72 (7): 668-677.
42. Jacobson S, Kelleher I, HarleyM, et al. Structural and functional brain correlates of subclinical psychotic symptoms in 11-13 year old schoolchildren. Neuroimage. 2010; 49 (2): 1875-1885.
43. Satterthwaite TD, Elliott MA, Ruparel K, et al. Neuroimaging of the Philadelphia Neurodevelopmental Cohort. Neuroimage. 2014; 86: 544-553.
44. Kelleher I, Cannon M. Psychotic-like experiences in the general population: characterizing a high-risk group for psychosis. Psychol Med. 2011; 41 (1): 1-6.
45. Kelleher I, Connor D, Clarke MC, Devlin N, HarleyM, Cannon M. Prevalence of psychotic symptoms in childhood and adolescence: a systematic review and meta-analysis of population-based studies. Psychol Med. 2012; 42 (9): 1857-1863.
46. Kelleher I, Murtagh A, Molloy C, 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 (2): 239-246.
47. Kelleher I, Corcoran P, Keeley H, et al. Psychotic symptoms and population risk for suicide attempt: a prospective cohort study. JAMA Psychiatry. 2013; 70 (9): 940-948.
48. Cuthbert BN. The RDoC framework: facilitating transition from ICD/DSMto dimensional approaches that integrate neuroscience and psychopathology. World Psychiatry. 2014; 13 (1): 28-35.
49. Insel T, Cuthbert B, GarveyM, et al. Research Domain Criteria (RDoC): toward a new classification framework for research on mental disorders. Am J Psychiatry. 2010; 167 (7): 748-751.
50. Gur RE, Kaltman D, Melhem ER, et al. Incidental findings in youths volunteering for brain MRI research. AJNR Am J Neuroradiol. 2013; 34 (10): 2021-2025.
51. Gur RC, Calkins ME, Satterthwaite TD, et al. Neurocognitive growth charting in psychosis spectrum youths. JAMA Psychiatry. 2014; 71 (4): 366-374.
52. Miller TJ, McGlashan TH, Rosen JL, et al. Prodromal assessment with the structured interview for prodromal syndromes and the scale of prodromal symptoms: predictive validity, interrater reliability, and training to reliability. [published correction appears in Schizophr Bull. 2004; 30 (2): 217]. Schizophr Bull. 2003; 29 (4): 703-715.
53. Kobayashi H, Nemoto T, Koshikawa H, et al. A self-reported instrument for prodromal symptoms of psychosis: testing the clinical validity of the PRIME Screen-Revised (PS-R) in a Japanese population. Schizophr Res. 2008; 106 (2-3): 356-362.
54. Kaufman J, Birmaher B, Brent D, et al. Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version (K-SADS-PL): initial reliability and validity data. J Am Acad Child Adolesc Psychiatry. 1997; 36 (7): 980-988.
55. Doshi J, Erus G, Ou Y, Gaonkar B, Davatzikos C. Multi-atlas skull-stripping. Acad Radiol. 2013; 20 (12): 1566-1576.
56. Li C, Gore JC, Davatzikos C. Multiplicative intrinsic component optimization (MICO) for MRI bias field estimation and tissue segmentation. Magn Reson Imaging. 2014; 32 (7): 913-923.
57. Satterthwaite TD, Connolly JJ, Ruparel K, et al. The Philadelphia Neurodevelopmental Cohort: a publicly available resource for the study of normal and abnormal brain development in youth. Neuroimage. 2016; 124 (pt B): 1115-1119.
58. Doshi JJ, Erus G, Ou Y, Davatzikos C. Ensemble-based medical image labeling via sampling morphological appearance manifolds. In: MICCAI ChallengeWorkshop on Segmentation: Algorithms, Theory and Applications. Nagoya, Japan: Medical Image Computing and Computer Assisted Intervention Society; 2013.
59. Davatzikos C, Genc A, Xu D, Resnick SM. Voxel-based morphometry using the RAVENS maps: methods and validation using simulated longitudinal atrophy. Neuroimage. 2001; 14 (6): 1361-1369.
60. Ou Y, Sotiras A, Paragios N, Davatzikos C. DRAMMS: Deformable Registration via Attribute Matching and Mutual-SaliencyWeighting. Med Image Anal. 2011; 15 (4): 622-639.
61. Erus G, Battapady H, Satterthwaite TD, et al. Imaging patterns of brain development and their relationship to cognition. Cereb Cortex. 2015; 25 (6): 1676-1684.
62. Lenroot RK, Gogtay N, Greenstein DK, et al. Sexual dimorphism of brain developmental trajectories during childhood and adolescence. Neuroimage. 2007; 36 (4): 1065-1073.
63. Giedd JN, Blumenthal J, Jeffries NO, et al. Brain development during childhood and adolescence: a longitudinal MRI study. Nat Neurosci. 1999; 2 (10): 861-863.
64. Vandekar SN, Shinohara RT, Raznahan A, et al. Topologically dissociable patterns of development of the human cerebral cortex. J Neurosci. 2015; 35 (2): 599-609.
65. Wood SN. Stable and efficient multiple smoothing parameter estimation for generalized additivemodels. J AmStat Assoc. 2004; 99: 673-686.
66. Wood SN. Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. J R Stat Soc Series B StatMethodol. 2011; 73 (1): 3-36.
67. Satterthwaite TD, Shinohara RT, Wolf DH, et al. Impact of puberty on the evolution of cerebral perfusion during adolescence. Proc Natl Acad Sci U S A. 2014; 111 (23): 8643-8648.
68. SanfilipoMP, Benedict RH, Zivadinov R, Bakshi R. Correction for intracranial volume in analysis of whole brain atrophy in multiple sclerosis: the proportion vs residual method. Neuroimage. 2004; 22 (4): 1732-1743.
69. Voevodskaya O, Simmons A, Nordenskjöld R, et al; Alzheimer's Disease Neuroimaging Initiative. The effects of intracranial volume adjustment approaches on multiple regional MRI volumes in healthy aging and Alzheimer's disease. Front Aging Neurosci. 2014; 6: 264.
70. Cox RW. AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput Biomed Res. 1996; 29 (3): 162-173.
71. 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 AmMed Inform Assoc. 2001; 8 (5): 443-459.
72. Ho D, Imai K, King G, Stuart E. Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference. Polit Anal. 2007; 15 (3): 199-236. http://gking.harvard.edu/files /abs/matchp-abs.shtml. Accessed February 3, 2016.
73. RaichleME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL. A default mode of brain function. Proc Natl Acad Sci U S A. 2001; 98 (2): 676-682.
74. Buckner RL, Andrews-Hanna JR, Schacter DL. The brain's default network: anatomy, function, and relevance to disease. Ann N Y Acad Sci. 2008; 1124: 1-38.
75. Garrity AG, Pearlson GD, McKiernan K, Lloyd D, Kiehl KA, Calhoun VD. Aberrant "default mode" functional connectivity in schizophrenia. Am J Psychiatry. 2007; 164 (3): 450-457.
76. Whitfield-Gabrieli S, Thermenos HW, Milanovic S, et al. Hyperactivity and hyperconnectivity of the default network in schizophrenia and in first-degree relatives of persons with schizophrenia. Proc Natl Acad Sci U S A. 2009; 106 (4): 1279-1284.
77. Ongür D, Lundy M, Greenhouse I, et al. Default mode network abnormalities in bipolar disorder and schizophrenia. Psychiatry Res. 2010; 183 (1): 59-68.
78. Salgado-Pineda P, Fakra E, Delaveau P, McKenna PJ, Pomarol-Clotet E, Blin O. Correlated structural and functional brain abnormalities in the default mode network in schizophrenia patients. Schizophr Res. 2011; 125 (2-3): 101-109.
79. Giedd JN, Jeffries NO, Blumenthal J, et al. Childhood-onset schizophrenia: progressive brain changes during adolescence. Biol Psychiatry. 1999; 46 (7): 892-898.
80. Rapoport JL, Gogtay N. Childhood onset schizophrenia: support for a progressive neurodevelopmental disorder. Int J Dev Neurosci. 2011; 29 (3): 251-258.
81. Koutsouleris N, Davatzikos C, Borgwardt S, et al. Accelerated brain aging in schizophrenia and beyond: a neuroanatomical marker of psychiatric disorders. Schizophr Bull. 2014; 40 (5): 1140-1153.
82. Thompson PM, Vidal C, Giedd JN, et al. Mapping adolescent brain change reveals dynamic wave of accelerated gray matter loss in very early-onset schizophrenia. Proc Natl Acad Sci U S A. 2001; 98 (20): 11650-11655.
83. Sun D, Stuart GW, Jenkinson M, et al. Brain surface contraction mapped in first-episode schizophrenia: a longitudinal magnetic resonance imaging study. Mol Psychiatry. 2009; 14 (10): 976-986.
84. Zipursky RB, Marsh L, Lim KO, et al. Volumetric MRI assessment of temporal lobe structures in schizophrenia. Biol Psychiatry. 1994; 35 (8): 501-516.
85. Marsh L, Harris D, Lim KO, et al. Structural magnetic resonance imaging abnormalities in men with severe chronic schizophrenia and an early age at clinical onset. Arch Gen Psychiatry. 1997; 54 (12): 1104-1112.
86. Altshuler LL, Bartzokis G, Grieder T, et al. An MRI study of temporal lobe structures in men with bipolar disorder or schizophrenia. Biol Psychiatry. 2000; 48 (2): 147-162.
87. Ellison-Wright I, Glahn DC, Laird AR, Thelen SM, Bullmore E. The anatomy of first-episode and chronic schizophrenia: an anatomical likelihood estimationmeta-analysis. Am J Psychiatry. 2008; 165 (8): 1015-1023.
88. Meisenzahl EM, Koutsouleris N, Bottlender R, et al. Structural brain alterations at different stages of schizophrenia: a voxel-based morphometric study. Schizophr Res. 2008; 104 (1-3): 44-60.
89. Meisenzahl EM, Seifert D, Bottlender R, et al. Differences in hippocampal volume between major depression and schizophrenia: a comparative neuroimaging study. Eur Arch Psychiatry Clin Neurosci. 2010; 260 (2): 127-137.
90. Wheeler AL, Voineskos AN. A review of structural neuroimaging in schizophrenia: from connectivity to connectomics. Front Hum Neurosci. 2014; 8: 653.
91. Ho NF, Hooker JM, Sahay A, Holt DJ, Roffman JL. In vivo imaging of adult human hippocampal neurogenesis: progress, pitfalls and promise. Mol Psychiatry. 2013; 18 (4): 404-416.
92. Holt DJ, Weiss AP, Rauch SL, et al. Sustained activation of the hippocampus in response to fearful faces in schizophrenia. Biol Psychiatry. 2005; 57 (9): 1011-1019.
93. Holt DJ, Kunkel L, Weiss AP, et al. Increased medial temporal lobe activation during the passive viewing of emotional and neutral facial expressions in schizophrenia. Schizophr Res. 2006; 82 (2-3): 153-162.
94. Hall J, Whalley HC, Marwick K, et al. Hippocampal function in schizophrenia and bipolar disorder. Psychol Med. 2010; 40 (5): 761-770.
95. Seidman LJ, Rosso IM, Thermenos HW, 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 (2-3): 426-434.
96. Allen P, Seal ML, Valli I, et al. Altered prefrontal and hippocampal function during verbal encoding and recognition in peoplewith prodromal symptoms of psychosis. Schizophr Bull. 2011; 37 (4): 746-756.
97. Meisenzahl EM, Koutsouleris N, Gaser C, et al. Structural brain alterations in subjects at high-risk of psychosis: a voxel-based morphometric study. Schizophr Res. 2008; 102 (1-3): 150-162.
98. Schobel SA, Chaudhury NH, Khan UA, et al. Imaging patients with psychosis and a mouse model establishes a spreading pattern of hippocampal dysfunction and implicates glutamate as a driver. Neuron. 2013; 78 (1): 81-93.
99. Heckers S, Konradi C. GABAergic mechanisms of hippocampal hyperactivity in schizophrenia. Schizophr Res. 2015; 167 (1-3): 4-11.
100. Krystal JH, Anticevic A. Toward illness phase-specific pharmacotherapy for schizophrenia. Biol Psychiatry. 2015; 78 (11): 738-740.
101. Fornito A, Yücel M, Patti J, Wood SJ, Pantelis C. Mapping grey matter reductions in schizophrenia: an anatomical likelihood estimation analysis of voxel-based morphometry studies. Schizophr Res. 2009; 108 (1-3): 104-113.
102. Sheline YI, Wang PW, Gado MH, Csernansky JG, VannierMW. Hippocampal atrophy in recurrent major depression. Proc Natl Acad Sci U S A. 1996; 93 (9): 3908-3913.
103. Mathew I, Gardin TM, Tandon N, et al. Medial temporal lobe structures and hippocampal subfields in psychotic disorders: findings from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) study. JAMA Psychiatry. 2014; 71 (7): 769-777.
104. Weinberger DR, Radulescu E. Finding the elusive psychiatric "lesion" with 21st-century neuroanatomy: a note of caution. Am J Psychiatry. 2016; 173 (1): 27-33.
105. Anticevic A, Hu X, Xiao Y, et al. Early-course unmedicated schizophrenia patients exhibit elevated prefrontal connectivity associated with longitudinal change. J Neurosci. 2015; 35 (1): 267-286.
106. Anticevic A, Tang Y, Cho YT, et al. Amygdala connectivity differs among chronic, early course, and individuals at risk for developing schizophrenia. Schizophr Bull. 2014; 40 (5): 1105-1116.
107. Chung Y, Cannon TD. Brain imaging during the transition from psychosis prodrome to schizophrenia. JNervMent Dis. 2015; 203 (5): 336-341.
108. Cannon TD, Sun F, McEwen SJ, et al. Reliability of neuroanatomical measurements in a multisite longitudinal study of youth at risk for psychosis. Hum Brain Mapp. 2014; 35 (5): 2424-2434.
109. Stein JL, Medland SE, Vasquez AA, et al; Alzheimer's Disease Neuroimaging Initiative; EPIGEN Consortium; IMAGEN Consortium; Saguenay Youth Study Group; Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium; Enhancing Neuro Imaging Genetics through Meta-Analysis Consortium. Identification of common variants associated with human hippocampal and intracranial volumes. Nat Genet. 2012; 44 (5): 552-561.
110. Hibar DP, Stein JL, Renteria ME, et al; Alzheimer's Disease Neuroimaging Initiative; CHARGE Consortium; EPIGEN; IMAGEN; SYS. Common genetic variants influence human subcortical brain structures. Nature. 2015; 520 (7546): 224-229.
111. Ripke S, O'Dushlaine C, Chambert K, et al; Multicenter Genetic Studies of Schizophrenia Consortium; Psychosis Endophenotypes International Consortium; Wellcome Trust Case Control Consortium 2. Genome-wide association analysis identifies 13 new risk loci for schizophrenia. Nat Genet. 2013; 45 (10): 1150-1159.
112. SchizophreniaWorking Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014; 511 (7510): 421-427.
113. Zhang T, Koutsouleris N, Meisenzahl E, Davatzikos C. Heterogeneity of structural brain changes in subtypes of schizophrenia revealed usingmagnetic resonance imaging pattern analysis. Schizophr Bull. 2015; 41 (1): 74-84.