Corrigendum to "Spatiotemporal linear mixed effects modeling for the mass-univariate analysis of longitudinal neuroimage data" [NeuroImage 81 (1 November 2013) 358-370] doi: 10.1016/j.neuroimage.2013.05.049;Spatiotemporal linear mixed effects modeling for the mass-univariate analysis of longitudinal neuroimage data

NeuroImage

Volumn 81, Issue , 2013, Pages 358-370

  Bernal Rusiel, Jorge L ^a   Reuter, Martin ^a,b   Greve, Douglas N ^a   Fischl, Bruce ^a,c   Sabuncu, Mert R ^a,c  

^a MASSACHUSETTS GENERAL HOSPITAL   (United States)

^b Massachusetts Institute of Technology Cambridge   (United States)

^c MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Linear Mixed Effects models; Longitudinal studies; Mass univariate analysis; Statistical analysis

Indexed keywords

AGED; ARTICLE; BRAIN CORTEX; COMPUTER PROGRAM; CONTROLLED STUDY; DATA ANALYSIS; FALSE POSITIVE RESULT; FEMALE; HUMAN; IMAGE ANALYSIS; LONGITUDINAL STUDY; MAJOR CLINICAL STUDY; MALE; MASS UNIVARIATE ANALYSIS; MEASUREMENT; MEASUREMENT REPEATABILITY; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; SPATIOTEMPORAL LINEAR MIXED EFFECTS MODELING; STATISTICAL ANALYSIS; STATISTICAL MODEL; SURFACE PROPERTY; THICKNESS; BIOLOGICAL MODEL; BRAIN; COMPUTER ASSISTED DIAGNOSIS; PATHOLOGY; PHYSIOLOGY; PROCEDURES;

BRAIN; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; LINEAR MODELS; MAGNETIC RESONANCE IMAGING; MODELS, NEUROLOGICAL; SOFTWARE;

EID: 84879346787     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2014.12.052     Document Type: Erratum

References (91)

1. Asami T., Bouix S., Whitford T.J., Shenton M.E., Salisbury D.F., McCarley R.W. Longitudinal loss of gray matter volume in patients with first-episode schizophrenia: DARTEL automated analysis and ROI validation. Neuroimage 2011, 59(2):986-996.
2. Benjamini Y., Krieger A.M., Yekutieli D. Adaptive linear step-up procedures that control the false discovery rate. Biometrika 2006, 93:491-507.
3. Bernal-Rusiel J.L., Atienza M., Cantero J.L. Determining the optimal level of smoothing in cortical thickness analysis: a hierarchical approach based on sequential statistical thresholding. Neuroimage 2010, 52:158-171.
4. Bernal-Rusiel J.L., Greve D.N., Reuter M., Fischl B., Sabuncu M.R. Statistical analysis of longitudinal neuroimage data with Linear Mixed Effects models. Neuroimage 2012, 249-260.
5. Blockx I., Van Camp N., Verhoye M., Boisgard R., Dubois A., Jego B., Jonckers E., Raber K., Siquier K., Kuhnast B., Dolle F., Nguyen H.P., Von Horsten S., Tavitian B., Van der Linden A. Genotype specific age related changes in a transgenic rat model of Huntington's disease. Neuroimage 2011, 58:1006-1016.
6. Bowman F.D. Spatiotemporal models for region of interest analyses of functional neuroimaging data. J. Am. Stat. Assoc. 2007, 102:442-453.
7. Bowman F.D., Kilts C. Modeling intra-subject correlation among repeated scans in positron emission tomography (PET) neuroimaging data. Hum. Brain Mapp. 2003, 20:59-70.
8. Bowman F.D., Caffo B.S., Spear Bassett S., Kilts C. A Bayesian hierarchical framework for spatial modeling of fMRI data 2008.
9. Chetelat G., Landeau B., Eustache F., Mezenge F., Viader F., de La Sayette V., Desgranges B., Baron J.C. Using voxel-based morphometry to map the structural changes associated with rapid conversion in MCI: a longitudinal MRI study. Neuroimage 2005, 27:934-946.
10. Cox R.W. AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput. Biomed. Res. 1996, 29:162-173.
11. Dale A.M., Fischl B., Sereno M.I. Cortical Surface-Based Analysis I: Segmentation and Surface Reconstruction. NeuroImage 1999, 9(2):179-194.
12. Davatzikos C., Resnick S.M. Degenerative age changes in white matter connectivity visualized in vivo using magnetic resonance imaging. Cereb. Cortex 2002, 12:767-771.
13. Delaloye C., Moy G., de Bilbao F., Weber K., Baudois S., Haller S., Xekardaki A., Canuto A., Giardini U., Lövblad K.O. Longitudinal analysis of cognitive performances and structural brain changes in late life bipolar disorder. Int. J. Geriatr. Psychiatry 2011, 26:1309-1318.
14. Derado G., Bowman F.D., Zhang L. Predicting brain activity using a Bayesian spatial model. Stat. Methods Med. Res. 2012, 10.1177/0962280212448972.
15. Desikan R.S., McEvoy L.K., Thompson W.K., Holland D., Roddey J.C., Blennow K., Aisen P.S., Brewer J.B., Hyman B.T., Dale A.M. Amyloid-β associated volume loss occurs only in the presence of phospho-tau. Ann. Neurol. 2011, 70(4):657-661.
16. Dickerson B.C., Bakkour A., Salat D.H., Feczko E., Pacheco J., Greve D.N., Grodstein F., Wright C.I., Blacker D., Rosas H.D. The cortical signature of Alzheimer's disease: regionally specific cortical thinning relates to symptom severity in very mild to mild AD dementia and is detectable in asymptomatic amyloid-positive individuals. Cereb. Cortex 2009, 19:497-510.
17. Draganski B., Gaser C., Busch V., Schuierer G., Bogdahn U., May A. Neuroplasticity: changes in grey matter induced by training. Nature 2004, 427:311-312.
18. Driscoll I., Beydoun M.A., An Y., Davatzikos C., Ferrucci L., Zonderman A.B., Resnick S.M. Midlife obesity and trajectories of brain volume changes in older adults. Hum. Brain Mapp. 2011, 33:2204-2210.
19. Fischl B. Freesurfer. Neuroimage 2012, 62(2):774-781.
20. Fischl B., Dale A.M. Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc. Natl. Acad. Sci. 2000, 97:11050.
21. Fischl B., Sereno M.I., Dale A.M. Cortical surface-based analysis* 1: II: Inflation, flattening, and a surface-based coordinate system. Neuroimage 1999, 9:195-207.
22. Fischl B., Sereno M.I., Tootell R.B.H., Dale A.M. High-resolution intersubject averaging and a coordinate system for the cortical surface. Hum. Brain Mapp. 1999, 8:272-284.
23. Fitzmaurice G.M., Laird N.M., Ware J.H. Applied Longitudinal Analysis 2011, Wiley.
24. Fjell A.M., Walhovd K.B., Fennema-Notestine C., McEvoy L.K., Hagler D.J., Holland D., Brewer J.B., Dale A.M. One-year brain atrophy evident in healthy aging. J. Neurosci. 2009, 29:15223-15231.
25. Fotenos A.F., Snyder A., Girton L., Morris J., Buckner R. Normative estimates of cross-sectional and longitudinal brain volume decline in aging and AD. Neurology 2005, 64:1032-1039.
26. Fouquet M., Desgranges B., Landeau B., Duchesnay E., Mézenge F., De La Sayette V., Viader F., Baron J.C., Eustache F., Chételat G. Longitudinal brain metabolic changes from amnestic mild cognitive impairment to Alzheimer's disease. Brain 2009, 132:2058-2067.
27. Frings L., Mader I., Landwehrmeyer B.G., Weiller C., Hüll M., Huppertz H.J. Quantifying change in individual subjects affected by frontotemporal lobar degeneration using automated longitudinal MRI volumetry. Hum. Brain Mapp. 2011, 33(7):1526-1535.
28. Friston K.J. Statistical Parametric Mapping: the Analysis of Functional Brain Images 2007, Academic Press.
29. Friston K.J., Glaser D.E., Henson R.N., Kiebel S., Phillips C., Ashburner J. Classical and Bayesian inference in neuroimaging: applications. Neuroimage 2002, 16:484-512.
30. Friston K.J., Penny W., Phillips C., Kiebel S., Hinton G., Ashburner J. Classical and Bayesian inference in neuroimaging: theory. Neuroimage 2002, 16:465-483.
31. Friston K., Stephan K., Lund T., Morcom A., Kiebel S. Mixed-effects and fMRI studies. Neuroimage 2005, 24:244-252.
32. Giedd J.N., Blumenthal J., Jeffries N.O., Castellanos F.X., Liu H., Zijdenbos A., Paus T., Evans A.C., Rapoport J.L. Brain development during childhood and adolescence: a longitudinal MRI study. Nat. Neurosci. 1999, 2:861-862.
33. Gonzales R., Woods R.E., Eddins S. Digital Image Processing 2002, Prentice Hall, New Jersey.
34. Gossl C., Auer D.P., Fahrmeir L. Bayesian spatiotemporal inference in functional magnetic resonance imaging. Biometrics 2004, 57:554-562.
35. Greven S., Crainiceanu C.M., K√»chenhoff H., Peters A. Restricted likelihood ratio testing for zero variance components in linear mixed models. J. Comput. Graph. Stat. 2008, 17.
36. Guo Y., DuBois Bowman F., Kilts C. Predicting the brain response to treatment using a Bayesian hierarchical model with application to a study of schizophrenia. Hum. Brain Mapp. 2008, 29:1092-1109.
37. Han X., Jovicich J., Salat D., van der Kouwe A., Quinn B., Czanner S., Busa E., Pacheco J., Albert M., Killiany R. Reliability of MRI-derived measurements of human cerebral cortical thickness: the effects of field strength, scanner upgrade and manufacturer. Neuroimage 2006, 32:180-194.
38. Hedman A.M., van Haren N.E.M., Schnack H.G., Kahn R.S., Hulshoff Pol H.E. Human brain changes across the life span: a review of 56 longitudinal magnetic resonance imaging studies. Hum. Brain Mapp. 2011, 33(8):1987-2002.
39. Ho B.C., Andreasen N.C., Nopoulos P., Arndt S., Magnotta V., Flaum M. Progressive structural brain abnormalities and their relationship to clinical outcome: a longitudinal magnetic resonance imaging study early in schizophrenia. Arch. Gen. Psychiatry 2003, 60:585.
40. Holland D., Brewer J.B., Hagler D.J., Fennema-Notestine C., Dale A.M., Weiner M., Thal L., Petersen R., Jack C.R., Jagust W. Subregional neuroanatomical change as a biomarker for Alzheimer's disease. Proc. Natl. Acad. Sci. 2009, 106:20954-20959.
41. Holland D., McEvoy L.K., Dale A.M. Unbiased comparison of sample size estimates from longitudinal structural measures in ADNI. Hum. Brain Mapp. 2011, 33(11):2586-2602.
42. Hua X., Leow A.D., Levitt J.G., Caplan R., Thompson P.M., Toga A.W. Detecting brain growth patterns in normal children using tensor-based morphometry. Hum. Brain Mapp. 2009, 30:209-219.
43. Hua X., Hibar D.P., Lee S., Toga A.W., Jack C.R., Weiner M.W., Thompson P.M. Sex and age differences in atrophic rates: an ADNI study with n=1368 MRI scans. Neurobiol. Aging 2010, 31:1463-1480.
44. Jack C.R., Weigand S.D., Shiung M.M., Przybelski S.A., O'Brien P.C., Gunter J.L., Knopman D.S., Boeve B.F., Smith G.E., Petersen R.C. Atrophy rates accelerate in amnestic mild cognitive impairment. Neurology 2008, 70:1740-1752.
45. Jack C.R., Lowe V.J., Weigand S.D., Wiste H.J., Senjem M.L., Knopman D.S., Shiung M.M., Gunter J.L., Boeve B.F., Kemp B.J. Serial PIB and MRI in normal, mild cognitive impairment and Alzheimer's disease: implications for sequence of pathological events in Alzheimer's disease. Brain 2009, 132:1355-1365.
46. Josephs K.A., Whitwell J.L., Ahmed Z., Shiung M.M., Weigand S.D., Knopman D.S., Boeve B.F., Parisi J.E., Petersen R.C., Dickson D.W. Β-amyloid burden is not associated with rates of brain atrophy. Ann. Neurol. 2008, 63:204-212.
47. Kaladjian A., Jeanningros R., Azorin J.M., Nazarian B., Roth M., Anton J.L., Mazzola-Pomietto P. Remission from mania is associated with a decrease in amygdala activation during motor response inhibition. Bipolar Disord. 2009, 11:530-538.
48. Kalkers N.F., Ameziane N., Bot J.C.J., Minneboo A., Polman C.H., Barkhof F. Longitudinal brain volume measurement in multiple sclerosis: rate of brain atrophy is independent of the disease subtype. Arch. Neurol. 2002, 59:1572.
49. Kasai K., Shenton M.E., Salisbury D.F., Hirayasu Y., Onitsuka T., Spencer M.H., Yurgelun-Todd D.A., Kikinis R., Jolesz F.A., McCarley R.W. Progressive decrease of left Heschl gyrus and planum temporale gray matter volume in first-episode schizophrenia: a longitudinal magnetic resonance imaging study. Arch. Gen. Psychiatry 2003, 60:766.
50. Kenward M.G., Roger J.H. Small sample inference for fixed effects from restricted maximum likelihood. Biometrics 1997, 983-997.
51. Laird N., Lange N., Stram D. Maximum likelihood computations with repeated measures: application of the EM algorithm. J. Am. Stat. Assoc. 1987, 97-105.
52. Lau J.C., Lerch J.P., Sled J.G., Henkelman R.M., Evans A.C., Bedell B.J. Longitudinal neuroanatomical changes determined by deformation-based morphometry in a mouse model of Alzheimer's disease. Neuroimage 2008, 42:19-27.
53. Lerch J.P., Pruessner J.C., Zijdenbos A., Hampel H., Teipel S.J., Evans A.C. Focal decline of cortical thickness in Alzheimer's disease identified by computational neuroanatomy. Cereb. Cortex 2005, 15:995-1001.
54. Li Y., Zhu H., Shen D., Lin W., Gilmore J.H., Ibrahim J.G. Multiscale adaptive regression models for neuroimaging data. J. R. Stat. Soc. Ser. B (Stat. Methodol.) 2011, 73:559-578.
55. Li Y., Gilmore J.H., Shen D., Styner M., Lin W., Zhu H. Multiscale adaptive generalized estimating equations for longitudinal neuroimaging data. Neuroimage 2013, 72:91-105.
56. Marcus D.S., Wang T.H., Parker J., Csernansky J.G., Morris J.C., Buckner R.L. Open Access Series of Imaging Studies (OASIS): cross-sectional MRI data in young, middle aged, nondemented, and demented older adults. J. Cogn. Neurosci. 2007, 19:1498-1507.
57. Marcus D.S., Fotenos A.F., Csernansky J.G., Morris J.C., Buckner R.L. Open access series of imaging studies: longitudinal MRI data in nondemented and demented older adults. J. Cogn. Neurosci. 2010, 22:2677-2684.
58. Martensson J., Eriksson J., Bodammer N.C., Lindgren M., Johansson M., Nyberg L., Lovden M. Growth of language-related brain areas after foreign language learning. Neuroimage 2012, 63(1):240-244.
59. Ment L.R., Kesler S., Vohr B., Katz K.H., Baumgartner H., Schneider K.C., Delancy S., Silbereis J., Duncan C.C., Constable R.T. Longitudinal brain volume changes in preterm and term control subjects during late childhood and adolescence. Pediatrics 2009, 123:503-511.
60. Misra C., Fan Y., Davatzikos C. Baseline and longitudinal patterns of brain atrophy in MCI patients, and their use in prediction of short-term conversion to AD: results from ADNI. Neuroimage 2009, 44:1415.
61. Pantelis C., Velakoulis D., McGorry P.D., Wood S.J., Suckling J., Phillips L.J., Yung A.R., Bullmore E.T., Brewer W., Soulsby B. Neuroanatomical abnormalities before and after onset of psychosis: a cross-sectional and longitudinal MRI comparison. Lancet 2003, 361:281-288.
62. Paviour D.C., Price S.L., Jahanshahi M., Lees A.J., Fox N.C. Longitudinal MRI in progressive supranuclear palsy and multiple system atrophy: rates and regions of atrophy. Brain 2006, 129:1040-1049.
63. Resnick S., Sojkova J., Zhou Y., An Y., Ye W., Holt D., Dannals R., Mathis C., Klunk W., Ferrucci L. Longitudinal cognitive decline is associated with fibrillar amyloid-beta measured by [11C] PiB. Neurology 2010, 74:807-815.
64. Reuter M., Fischl B. Avoiding asymmetry-induced bias in longitudinal image processing. Neuroimage 2011, 57:19-21.
65. Reuter M., Rosas H.D., Fischl B. Highly accurate inverse consistent registration: a robust approach. Neuroimage 2010, 53:1181-1196.
66. Reuter M., Schmansky N.J., Rosas H.D., Fischl B. Within-subject template estimation for unbiased longitudinal image analysis. Neuroimage 2012, 10.1016/j.neuroimage.2012.02.084.
67. Rosas H.D., Reuter M., Doros G., Lee S.Y., Triggs T., Malarick K., Fischl B., Salat D.H., Hersch S.M. A tale of two factors: what determines the rate of progression in Huntington's disease? A longitudinal MRI study. Mov. Disord. 2011, 26:1691-1697.
68. Sabuncu M.R., Desikan R.S., Sepulcre J., Yeo B.T.T., Liu H., Schmansky N.J., Reuter M., Weiner M.W., Buckner R.L., Sperling R.A. The dynamics of cortical and hippocampal atrophy in Alzheimer disease. Arch. Neurol. 2011, 68:1040.
69. Schuff N., Tosun D., Insel P.S., Chiang G.C., Truran D., Aisen P.S., Jack C.R., Weiner M.W. Nonlinear time course of brain volume loss in cognitively normal and impaired elders. Neurobiol. Aging 2010, 33(5):845-855.
70. Schumann C.M., Bloss C.S., Barnes C.C., Wideman G.M., Carper R.A., Akshoomoff N., Pierce K., Hagler D., Schork N., Lord C. Longitudinal magnetic resonance imaging study of cortical development through early childhood in autism. J. Neurosci. 2010, 30:4419-4427.
71. Shaw P., Kabani N.J., Lerch J.P., Eckstrand K., Lenroot R., Gogtay N., Greenstein D., Clasen L., Evans A., Rapoport J.L. Neurodevelopmental trajectories of the human cerebral cortex. J. Neurosci. 2008, 28:3586-3594.
72. Shinohara R.T., Crainiceanu C.M., Caffo B.S., Reich D.S. Longitudinal analysis of spatiotemporal processes: a case study of dynamic contrast-enhanced magnetic resonance imaging in multiple sclerosis 2011.
73. Sidtis J.J., Strother S.C., Naoum A., Rottenberg D.A., Gomez C. Longitudinal cerebral blood flow changes during speech in hereditary ataxia. Brain Lang. 2010, 114:43-51.
74. Singh V., Chertkow H., Lerch J.P., Evans A.C., Dorr A.E., Kabani N.J. Spatial patterns of cortical thinning in mild cognitive impairment and Alzheimer's disease. Brain 2006, 129:2885-2893.
75. Skup M., Zhu H., Zhang H. Multiscale adaptive marginal analysis of longitudinal neuroimaging data with time-varying covariates. Biometrics 2012, 68:1083-1092.
76. Sluimer J.D., Van Der Flier W.M., Karas G.B., Fox N.C., Scheltens P., Barkhof F., Vrenken H. Whole-brain atrophy rate and cognitive decline: longitudinal MR study of memory clinic patients1. Radiology 2008, 248:590-598.
77. Sluimer J.D., Van Der Flier W.M., Karas G.B., Van Schijndel R., Barnes J., Boyes R.G., Cover K.S., Olabarriaga S.D., Fox N.C., Scheltens P. Accelerating regional atrophy rates in the progression from normal aging to Alzheimer's disease. Eur. Radiol. 2009, 19:2826-2833.
78. Smith S.M., Jenkinson M., Woolrich M.W., Beckmann C.F., Behrens T.E.J., Johansen-Berg H., Bannister P.R., De Luca M., Drobnjak I., Flitney D.E. Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 2004, 23:S208-S219.
79. SPM http://www.fil.ion.ucl.ac.uk/spm/.
80. Sullivan E.V., Pfefferbaum A., Rohlfing T., Baker F.C., Padilla M.L., Colrain I.M. Developmental change in regional brain structure over 7months in early adolescence: comparison of approaches for longitudinal atlas-based parcellation. Neuroimage 2011, 57(1):214-224.
81. Thambisetty M., Wan J., Carass A., An Y., Prince J.L., Resnick S.M. Longitudinal changes in cortical thickness associated with normal aging. Neuroimage 2010, 52:1215-1223.
82. Thambisetty M., An Y., Kinsey A., Koka D., Saleem M., Kraut M., Ferrucci L. Plasma clusterin concentration is associated with longitudinal brain atrophy in mild cognitive impairment. Neuroimage 2011, 59(1):212-217.
83. Thirion B., Pinel P., Mériaux S., Roche A., Dehaene S., Poline J.B. Analysis of a large fMRI cohort: statistical and methodological issues for group analyses. Neuroimage 2007, 35:105-120.
84. Verbeke G., Molenberghs G. Linear Mixed Models for Longitudinal Data 2000, Springer, N.Y.
85. Wenger E., Schaefer S., Noack H., K√»hn S., M√•rtensson J., Heinze H.J., D√»zel E., B√§ckman L., Lindenberger U., L√∂vd√©n M. Cortical thickness changes following spatial navigation training in adulthood and aging. Neuroimage 2011, 59(4):3389-3397.
86. Whitwell J.L., Jack C.R., Parisi J.E., Knopman D.S., Boeve B.F., Petersen R.C., Ferman T.J., Dickson D.W., Josephs K.A. Rates of cerebral atrophy differ in different degenerative pathologies. Brain 2007, 130:1148-1158.
87. Whitwell J., Weigand S., Gunter J., Boeve B., Rademakers R., Baker M., Knopman D., Wszolek Z., Petersen R., Jack C. Trajectories of brain and hippocampal atrophy in FTD with mutations in MAPT or GRN. Neurology 2011, 77:393-398.
88. Wilde E.A., Merkley T.L., Bigler E.D., Max J.E., Schmidt A.T., Ayoub K.W., McCauley S.R., Hunter J.V., Hanten G., Li X. Longitudinal changes in cortical thickness in children after traumatic brain injury and their relation to behavioral regulation and emotional control. Int. J. Dev. Neurosci. 2012, 30(3):267-276.
89. Woolrich M.W., Jenkinson M., Brady J.M., Smith S.M. Fully Bayesian spatio-temporal modeling of fMRI data. IEEE Trans. Med. Imaging 2004, 23:213-231.
90. Zhang X., Johnson T., Little R., Cao Y. Longitudinal image analysis of tumor/brain change in contrast uptake induced by radiation. The University of Michigan Department of Biostatistics Working Paper Series 2009.
91. Zipunnikov V., Greven S., Caffo B., Reich D.S., Crainiceanu C. Longitudinal high-dimensional data analysis 2011.