Skip to main content

Thank you for visiting 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.

Cerebellar volume and cerebellocerebral structural covariance in schizophrenia: a multisite mega-analysis of 983 patients and 1349 healthy controls


Although cerebellar involvement across a wide range of cognitive and neuropsychiatric phenotypes is increasingly being recognized, previous large-scale studies in schizophrenia (SZ) have primarily focused on supratentorial structures. Hence, the across-sample reproducibility, regional distribution, associations with cerebrocortical morphology and effect sizes of cerebellar relative to cerebral morphological differences in SZ are unknown. We addressed these questions in 983 patients with SZ spectrum disorders and 1349 healthy controls (HCs) from 14 international samples, using state-of-the-art image analysis pipelines optimized for both the cerebellum and the cerebrum. Results showed that total cerebellar grey matter volume was robustly reduced in SZ relative to HCs (Cohens’s d=−0.35), with the strongest effects in cerebellar regions showing functional connectivity with frontoparietal cortices (d=−0.40). Effect sizes for cerebellar volumes were similar to the most consistently reported cerebral structural changes in SZ (e.g., hippocampus volume and frontotemporal cortical thickness), and were highly consistent across samples. Within groups, we further observed positive correlations between cerebellar volume and cerebral cortical thickness in frontotemporal regions (i.e., overlapping with areas that also showed reductions in SZ). This cerebellocerebral structural covariance was strongest in SZ, suggesting common underlying disease processes jointly affecting the cerebellum and the cerebrum. Finally, cerebellar volume reduction in SZ was highly consistent across the included age span (16–66 years) and present already in the youngest patients, a finding that is more consistent with neurodevelopmental than neurodegenerative etiology. Taken together, these novel findings establish the cerebellum as a key node in the distributed brain networks underlying SZ.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5


  1. 1

    Buckner RL . The cerebellum and cognitive function: 25 years of insight from anatomy and neuroimaging. Neuron 2013; 80: 807–815.

    CAS  Article  PubMed  Google Scholar 

  2. 2

    Moberget T, Gullesen EH, Andersson S, Ivry RB, Endestad T . Generalized role for the cerebellum in encoding internal models: evidence from semantic processing. J Neurosci 2014; 34: 2871–2878.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  3. 3

    Adamaszek M, D'Agata F, Ferrucci R, Habas C, Keulen S, Kirkby KC et al. Consensus Paper: cerebellum and emotion. Cerebellum 2017; 16: 552–576.

    CAS  Article  PubMed  Google Scholar 

  4. 4

    Andreasen NC, Pierson R . The role of the cerebellum in schizophrenia. Biol Psychiatry 2008; 64: 81–88.

    Article  PubMed  PubMed Central  Google Scholar 

  5. 5

    Andreasen NC, Paradiso S, O’Leary DS . Cognitive dysmetria as an integrative theory of schizophrenia: a dysfunction in cortical-subcortical-cerebellar circuitry? Schizophr Bull 1998; 24: 203–218.

    CAS  Article  PubMed  Google Scholar 

  6. 6

    Kendler KS . Phenomenology of schizophrenia and the representativeness of modern diagnostic criteria. JAMA Psychiatry 2016; 73: 1082–1092.

    Article  PubMed  Google Scholar 

  7. 7

    Tosato S, Dazzan P . The psychopathology of schizophrenia and the presence of neurological soft signs: a review. Curr Opin Psychiatry 2005; 18: 285–288.

    Article  PubMed  Google Scholar 

  8. 8

    Chan RCK, Xu T, Heinrichs RW, Yu Y, Wang Y . Neurological soft signs in schizophrenia: a meta-analysis. Schizophr Bull 2010; 36: 1089–1104.

    Article  PubMed  Google Scholar 

  9. 9

    Gowen E, Miall RC . The cerebellum and motor dysfunction in neuropsychiatric disorders. Cerebellum 2007; 6: 268–279.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  10. 10

    Bernard JA, Dean DJ, Kent JS, Orr JM, Pelletier-Baldelli A, Lunsford-Avery JR et al. Cerebellar networks in individuals at ultra high-risk of psychosis: Impact on postural sway and symptom severity. Hum Brain Mapp 2014; 35: 4064–4078.

    Article  PubMed  PubMed Central  Google Scholar 

  11. 11

    Dean DJ, Kent JS, Bernard JA, Orr JM, Gupta T, Pelletier-Baldelli A et al. Increased postural sway predicts negative symptom progression in youth at ultrahigh risk for psychosis. Schizophr Res 2015; 162: 86–89.

    Article  PubMed  PubMed Central  Google Scholar 

  12. 12

    Yang Y, Lisberger SG . Purkinje-cell plasticity and cerebellar motor learning are graded by complex-spike duration. Nature 2014; 510: 529–532.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  13. 13

    Forsyth JK, Bolbecker AR, Mehta CS, Klaunig MJ, Steinmetz JE, O'Donnell BF et al. Cerebellar-dependent eyeblink conditioning deficits in schizophrenia spectrum disorders. Schizophr Bull 2012; 38: 751–759.

    Article  PubMed  Google Scholar 

  14. 14

    Parker KL, Andreasen NC, Liu D, Freeman JH, O’Leary DS . Eyeblink conditioning in unmedicated schizophrenia patients: a positron emission tomography study. Psychiatry Res 2013; 214: 402–409.

    Article  PubMed  PubMed Central  Google Scholar 

  15. 15

    Coesmans M, Röder CH, Smit AE, Koekkoek SKE, De Zeeuw CI, Frens MA et al. Cerebellar motor learning deficits in medicated and medication-free men with recent-onset schizophrenia. J Psychiatry Neurosci 2014; 39: E3–E11.

    Article  PubMed  PubMed Central  Google Scholar 

  16. 16

    Bolbecker AR, Kent JS, Petersen IT, Klaunig MJ, Forsyth JK, Howell JM et al. Impaired cerebellar-dependent eyeblink conditioning in first-degree relatives of individuals with schizophrenia. Schizophr Bull 2014; 40: 1001–1010.

    Article  PubMed  Google Scholar 

  17. 17

    Whalley HC, Simonotto E, Flett S, Marshall I, Ebmeier KP, Owens DG et al. fMRI correlates of state and trait effects in subjects at genetically enhanced risk of schizophrenia. Brain 2004; 127 (Part 3): 478–490.

    CAS  PubMed  Google Scholar 

  18. 18

    Anticevic A, Cole MW, Repovs G, Murray JD, Brumbaugh MS, Winkler AM et al. Characterizing thalamo-cortical disturbances in schizophrenia and bipolar illness. Cereb Cortex 2014; 24: 3116–3130.

    Article  PubMed  Google Scholar 

  19. 19

    Anticevic A, Yang G, Savic A, Murray JD, Cole MW, Repovs G et al. Mediodorsal and visual thalamic connectivity differ in schizophrenia and bipolar disorder with and without psychosis history. Schizophr Bull 2014; 40: 1227–1243.

    Article  PubMed  PubMed Central  Google Scholar 

  20. 20

    Shen H, Wang L, Liu Y, Hu D . Discriminative analysis of resting-state functional connectivity patterns of schizophrenia using low dimensional embedding of fMRI. Neuroimage 2010; 49: 3110–3121.

    Article  PubMed  Google Scholar 

  21. 21

    Repovs G, Csernansky JG, Barch DM . Brain network connectivity in individuals with schizophrenia and their siblings. Biol Psychiatry 2011; 69: 967–973.

    Article  PubMed  Google Scholar 

  22. 22

    Woodward ND, Heckers S . Mapping thalamocortical functional connectivity in chronic and early stages of psychotic disorders. Biol Psychiatry 2016; 79: 1016–1025.

    Article  PubMed  Google Scholar 

  23. 23

    Shinn AK, Baker JT, Lewandowski KE, Ongur D, Cohen BM . Aberrant cerebellar connectivity in motor and association networks in schizophrenia. Front Hum Neurosci 2015; 9: 134.

    Article  PubMed  PubMed Central  Google Scholar 

  24. 24

    Collin G, Hulshoff Pol HE, Haijma SV, Cahn W, Kahn RS, van den Heuvel MP . Impaired cerebellar functional connectivity in schizophrenia patients and their healthy siblings. Front Psychiatry 2011; 2: 73.

    Article  PubMed  PubMed Central  Google Scholar 

  25. 25

    Anticevic A, Haut K, Murray JD, Repovs G, Yang GJ, Diehl C et al. Association of thalamic dysconnectivity and conversion to psychosis in youth and young adults at elevated clinical risk. JAMA Psychiatry 2015; 72: 882–891.

    Article  PubMed  PubMed Central  Google Scholar 

  26. 26

    Whalley HC, Simonotto E, Marshall I, Owens DG, Goddard NH, Johnstone EC et al. Functional disconnectivity in subjects at high genetic risk of schizophrenia. Brain 2005; 128 (Part 9): 2097–2108.

    Article  PubMed  Google Scholar 

  27. 27

    Shenton ME, Dickey CC, Frumin M, McCarley RW . A review of MRI findings in schizophrenia. Schizophr Res 2001; 49: 1–52.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  28. 28

    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 

  29. 29

    Shepherd AM, Laurens KR, Matheson SL, Carr VJ, Green MJ . Systematic meta-review and quality assessment of the structural brain alterations in schizophrenia. Neurosci Biobehav Rev 2012; 36: 1342–1356.

    Article  PubMed  Google Scholar 

  30. 30

    Honea R, Crow TJ, Passingham D, Mackay CE . Regional deficits in brain volume in schizophrenia: a meta-analysis of voxel-based morphometry studies. Am J Psychiatry 2005; 162: 2233–2245.

    Article  PubMed  Google Scholar 

  31. 31

    Nenadic I, Dietzek M, Schönfeld N, Lorenz C, Gussew A, Reichenbach JR 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: 169–176.

    Article  PubMed  Google Scholar 

  32. 32

    Kühn S, Romanowski A, Schubert F, Gallinat J . Reduction of cerebellar grey matter in Crus I and II in schizophrenia. Brain Struct Funct 2012; 217: 523–529.

    Article  PubMed  Google Scholar 

  33. 33

    Yüksel C, McCarthy J, Shinn A, Pfaff DL, Baker JT, Heckers S et al. Gray matter volume in schizophrenia and bipolar disorder with psychotic features. Schizophr Res 2012; 138: 177–182.

    Article  PubMed  PubMed Central  Google Scholar 

  34. 34

    Laidi C, d'Albis M-A, Wessa M, Linke J, Phillips ML, Delavest M et al. Cerebellar volume in schizophrenia and bipolar I disorder with and without psychotic features. Acta Psychiatr Scand 2015; 131: 223–233.

    CAS  Article  PubMed  Google Scholar 

  35. 35

    Varnas K, Okugawa G, Hammarberg A, Nesvag R, Rimol LM, Franck J et al. Cerebellar volumes in men with schizophrenia and alcohol dependence. Psychiatry Clin Neurosci 2007; 61: 326–329.

    Article  PubMed  Google Scholar 

  36. 36

    Lawyer G, Nesvag R, Varnas K, Okugawa G, Agartz I . Grey and white matter proportional relationships in the cerebellar vermis altered in schizophrenia. Cerebellum 2009; 8: 52–60.

    Article  PubMed  Google Scholar 

  37. 37

    Okugawa G, Sedvall G, Nordstrom M, Andreasen N, Pierson R, Magnotta V et al. Selective reduction of the posterior superior vermis in men with chronic schizophrenia. Schizophr Res 2002; 55: 61–67.

    Article  PubMed  Google Scholar 

  38. 38

    Okugawa G, Sedvall GC, Agartz I . Smaller cerebellar vermis but not hemisphere volumes in patients with chronic schizophrenia. Am J Psychiatry 2003; 160: 1614–1617.

    Article  PubMed  Google Scholar 

  39. 39

    Womer FY, Tang Y, Harms MP, Bai C, Chang M, Jiang X et al. Sexual dimorphism of the cerebellar vermis in schizophrenia. Schizophr Res 2016; 176: 164–170.

    Article  PubMed  Google Scholar 

  40. 40

    Gupta CN, Calhoun VD, Rachakonda S, Chen J, Patel V, Liu J et al. Patterns of gray matter abnormalities in schizophrenia based on an international mega-analysis. Schizophr Bull 2015; 41: 1133–1142.

    Article  PubMed  Google Scholar 

  41. 41

    James AC, James S, Smith DM, Javaloyes A . Cerebellar, prefrontal cortex, and thalamic volumes over two time points in adolescent-onset schizophrenia. Am J Psychiatry 2004; 161: 1023–1029.

    Article  PubMed  Google Scholar 

  42. 42

    Hulshoff Pol HE, Schnack HG, Bertens MG, van Haren NE, van der Tweel I, Staal WG et al. Volume changes in gray matter in patients with schizophrenia. Am J Psychiatry 2002; 159: 244–250.

    Article  PubMed  Google Scholar 

  43. 43

    Sullivan EV, Deshmukh A, Desmond JE, Lim KO, Pfefferbaum A . Cerebellar volume decline in normal aging, alcoholism, and Korsakoff's syndrome: relation to ataxia. Neuropsychology 2000; 14: 341–352.

    CAS  Article  PubMed  Google Scholar 

  44. 44

    Staal WG, Hulshoff Pol HE, Schnack HG, van Haren NE, Seifert N, Kahn RS . Structural brain abnormalities in chronic schizophrenia at the extremes of the outcome spectrum. Am J Psychiatry 2001; 158: 1140–1142.

    CAS  Article  PubMed  Google Scholar 

  45. 45

    Cahn W, Hulshoff Pol HE, Bongers M, Schnack HG, Mandl RC, Van Haren NE et al. Brain morphology in antipsychotic-naive schizophrenia: a study of multiple brain structures. Br J Psychiatry Suppl 2002; 43: s66–s72.

    CAS  Article  PubMed  Google Scholar 

  46. 46

    Levitt JJ, McCarley RW, Nestor PG, Petrescu C, Donnino R, Hirayasu Y et al. Quantitative volumetric MRI study of the cerebellum and vermis in schizophrenia: clinical and cognitive correlates. Am J Psychiatry 1999; 156: 1105–1107.

    CAS  PubMed  PubMed Central  Google Scholar 

  47. 47

    van Erp TG, Hibar DP, Rasmussen JM, Glahn DC, Pearlson GD, Andreassen OA et al. Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium. Mol Psychiatry 2016; 21: 585.

    CAS  Article  PubMed  Google Scholar 

  48. 48

    Hibar DP, Westlye LT, van Erp TG, Rasmussen J, Leonardo CD, Faskowitz J et al. Subcortical volumetric abnormalities in bipolar disorder. Mol Psychiatry 2016; 21: 1710–1716.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  49. 49

    Alexander-Bloch A, Giedd JN, Bullmore E . Imaging structural co-variance between human brain regions. Nat Rev Neurosci 2013; 14: 322–336.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  50. 50

    Guo CC, Tan R, Hodges JR, Hu X, Sami S, Hornberger M . Network-selective vulnerability of the human cerebellum to Alzheimer's disease and frontotemporal dementia. Brain 2016; 139: 1527–1538.

    Article  PubMed  PubMed Central  Google Scholar 

  51. 51

    Poldrack RA, Gorgolewski KJ . OpenfMRI: open sharing of task fMRI data. Neuroimage 2017; 144 (Part B): 259–261.

    Article  PubMed  Google Scholar 

  52. 52

    Wang L, Alpert KI, Calhoun VD, Cobia DJ, Keator DB, King MD et al. SchizConnect: mediating neuroimaging databases on schizophrenia and related disorders for large-scale integration. Neuroimage 2016; 124 (Part B): 1155–1167.

    Article  PubMed  Google Scholar 

  53. 53

    van Erp TG, Preda A, Nguyen D, Faziola L, Turner J, Bustillo J et al. Converting positive and negative symptom scores between PANSS and SAPS/SANS. Schizophr Res 2014; 152: 289–294.

    Article  PubMed  Google Scholar 

  54. 54

    Desikan RS, Ségonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 2006; 31: 968–980.

    Article  PubMed  Google Scholar 

  55. 55

    Fischl B, Salat DH, Busa E, Albert M, Dieterich M, Haselgrove C et al. Whole brain segmentation: automated labeling of neuroanatomical structures in the humanbrain. Neuron 2002; 33: 341–355.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  56. 56

    Buckner RL, Head D, Parker J, Fotenos AF, Marcus D, Morris JC et al. A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: reliability and validation against manual measurement of total intracranial volume. Neuroimage 2004; 23: 724–738.

    Article  PubMed  Google Scholar 

  57. 57

    Fischl B, Dale AM . Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc Natl Acad Sci USA 2000; 97: 11050–11055.

    CAS  Article  PubMed  Google Scholar 

  58. 58

    Winkler AM, Kochunov P, Blangero J, Almasy L, Zilles K, Fox PT et al. Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies. Neuroimage 2010; 53: 1135–1146.

    Article  PubMed  Google Scholar 

  59. 59

    Diedrichsen J . A spatially unbiased atlas template of the human cerebellum. Neuroimage 2006; 33: 127–138.

    Article  PubMed  Google Scholar 

  60. 60

    Buckner RL, Krienen FM, Castellanos A, Diaz JC, Yeo BTT . The organization of the human cerebellum estimated by intrinsic functional connectivity. J Neurophysiol 2011; 106: 2322–2345.

    Article  PubMed  PubMed Central  Google Scholar 

  61. 61

    Nakagawa S, Cuthill IC . Effect size, confidence interval and statistical significance: a practical guide for biologists. Biol Rev Camb Philos Soc 2007; 82: 591–605.

    Article  PubMed  Google Scholar 

  62. 62

    Higgins JP, Thompson SG . Quantifying heterogeneity in a meta-analysis. Stat Med 2002; 21: 1539–1558.

    Article  PubMed  PubMed Central  Google Scholar 

  63. 63

    Viechtbauer W . Conducting meta-analyses in R with the metafor package. J Stat Softw 2010; 36: 1–48.

    Article  Google Scholar 

  64. 64

    Smith SM, Jenkinson M, Woolrich MW, Beckmann CF, Behrens TEJ, Johansen-Berg H et al. Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 2004; 23: S208–S219.

    Article  PubMed  PubMed Central  Google Scholar 

  65. 65

    Winkler AM, Ridgway GR, Webster MA, Smith SM, Nichols TE . Permutation inference for the general linear model. Neuroimage 2014; 92: 381–397.

    Article  PubMed  PubMed Central  Google Scholar 

  66. 66

    Rimol LM, Nesvåg R, Hagler DJ, Bergmann Ø, Fennema-Notestine C, Hartberg CB et al. Cortical volume, surface area, and thickness in schizophrenia and bipolar disorder. Biol Psychiatry 2012; 71: 552–560.

    Article  PubMed  Google Scholar 

  67. 67

    Shah C, Zhang W, Xiao Y, Yao L, Zhao Y, Gao X et al. Common pattern of gray-matter abnormalities in drug-naive and medicated first-episode schizophrenia: a multimodal meta-analysis. Psychol Med 2016; 47: 1–13.

    Google Scholar 

  68. 68

    Buckner RL . The cerebellum and cognitive function: 25 years of insight from anatomy and neuroimaging. Neuron 2013; 80: 807–815.

    CAS  Article  PubMed  Google Scholar 

  69. 69

    Fusar-Poli P, Meyer-Lindenberg A . Forty years of structural imaging in psychosis: promises and truth. Acta Psychiatr Scand 2016; 134: 207–224.

    CAS  Article  PubMed  Google Scholar 

  70. 70

    Limperopoulos C, Chilingaryan G, Sullivan N, Guizard N, Robertson RL, du Plessis AJ . Injury to the premature cerebellum: outcome is related to remote cortical development. Cerebral Cortex 2014; 24: 728–736.

    Article  PubMed  Google Scholar 

  71. 71

    Limperopoulos C, Chilingaryan G, Guizard N, Robertson RL, du Plessis AJ . Cerebellar injury in the premature infant is associated with impaired growth of specific cerebral regions. Pediatr Res 2010; 68: 145–150.

    Article  PubMed  Google Scholar 

  72. 72

    Moberget T, Andersson S, Lundar T, Due-Tønnessen BJ, Heldal A, Endestad T et al. Long-term supratentorial brain structure and cognitive function following cerebellar tumour resections in childhood. Neuropsychologia 2015; 69C: 218–231.

    Article  Google Scholar 

  73. 73

    Hawrylycz M, Miller JA, Menon V, Feng D, Dolbeare T, Guillozet-Bongaarts AL et al. Canonical genetic signatures of the adult human brain. Nat Neurosci 2015; 18: 1832–1844.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  74. 74

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

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  75. 75

    Knoll JLt, Garver DL, Ramberg JE, Kingsbury SJ, Croissant D, McDermott B . Heterogeneity of the psychoses: is there a neurodegenerative psychosis? Schizophr Bull 1998; 24: 365–379.

    Article  PubMed  Google Scholar 

  76. 76

    Okada N, Fukunaga M, Yamashita F, Koshiyama D, Yamamori H, Ohi K et al. Abnormal asymmetries in subcortical brain volume in schizophrenia. Mol Psychiatry 2016; 21: 1460–1466.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  77. 77

    Diedrichsen J, Zotow E . Surface-based display of volume-averaged cerebellar imaging data. PLoS ONE 2015; 10: e0133402.

    Article  PubMed  PubMed Central  Google Scholar 

  78. 78

    Thomas Yeo BT, 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 Central  Google Scholar 

Download references


We thank the participants of the study for their contribution, and the clinicians who were involved in patient recruitment and clinical assessments. The study has received funding from the European Commission’s 7th Framework Programme (No. 602450, IMAGEMEND), Research Council of Norway (213837, 223273, 204966/F20, 249795/F20), the South-Eastern Norway Regional Health Authority (2013-123, 2014-097, 2015-073, 2016-083) and KG Jebsen Foundation. Data used in preparation of this article were obtained from the SchizConnect ( and OpenfMRI ( databases. As such, the investigators within SchizConnect and OpenfMRI contributed to the design and implementation of SchizConnect/OpenfMRI and/or provided data but did not participate in analysis or writing of this report. The respective SchizConnect/OpenfMRI samples were supported by the following grants: NIH Grants 5P20RR021938 and P20GM103472 (COBRE), NIMH Grant 1R01 MH084803 (NÙSDAST), Department of Energy Award Number DE-FG02-08ER64581 (MCIC), NIH Roadmap for Medical Research Grants UL1-DE019580, RL1MH083268, RL1MH083269, RL1DA024853, RL1MH083270, RL1LM009833, PL1MH083271 and PL1NS062410 (CNP), NIH Grants P50 MH071616 and R01 MH56584 (CCNMD).

Author information




Corresponding author

Correspondence to T Moberget.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Additional information

MEMBERS OF THE KAROLINSKA SCHIZOPHRENIA PROJECT (KaSP): COLLABORATORS Drs Flyckt, Fatouros-Bergman, and Agartz are members of KASP. The other members are L Farde1, G Engberg2, S Erhardt2, S Cervenka1, L Schwieler2, F Piehl3, P Ikonen1, K Collste1, F Orhan2, A Malmqvist1 and M Hedberg1. 1Center for Psychiatric Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; 2Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden; 3Neuroimmunology Unit, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.

Supplementary Information accompanies the paper on the Molecular Psychiatry website

Supplementary information

PowerPoint slides

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Moberget, T., Doan, N., Alnæs, D. et al. Cerebellar volume and cerebellocerebral structural covariance in schizophrenia: a multisite mega-analysis of 983 patients and 1349 healthy controls. Mol Psychiatry 23, 1512–1520 (2018).

Download citation

Further reading


Quick links