Statistical analysis of longitudinal neuroimage data with Linear Mixed Effects models
Longitudinal neuroimaging (LNI) studies are rapidly becoming more prevalent and growing in size. Today, no standardized computational tools exist for the analysis of LNI data and widely used methods are sub-optimal for the types of data encountered in real-life studies. Linear Mixed Effects (LME) mo...
Saved in:
| Published in | NeuroImage (Orlando, Fla.) Vol. 66; pp. 249 - 260 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Amsterdam
Elsevier Inc
01.02.2013
Elsevier Elsevier Limited |
| Subjects | |
| Online Access | Get full text |
Cover
Loading…
| Abstract | Longitudinal neuroimaging (LNI) studies are rapidly becoming more prevalent and growing in size. Today, no standardized computational tools exist for the analysis of LNI data and widely used methods are sub-optimal for the types of data encountered in real-life studies. Linear Mixed Effects (LME) modeling, a mature approach well known in the statistics community, offers a powerful and versatile framework for analyzing real-life LNI data. This article presents the theory behind LME models, contrasts it with other popular approaches in the context of LNI, and is accompanied with an array of computational tools that will be made freely available through FreeSurfer — a popular Magnetic Resonance Image (MRI) analysis software package.
Our core contribution is to provide a quantitative empirical evaluation of the performance of LME and competing alternatives popularly used in prior longitudinal structural MRI studies, namely repeated measures ANOVA and the analysis of annualized longitudinal change measures (e.g. atrophy rate). In our experiments, we analyzed MRI-derived longitudinal hippocampal volume and entorhinal cortex thickness measurements from a public dataset consisting of Alzheimer's patients, subjects with mild cognitive impairment and healthy controls. Our results suggest that the LME approach offers superior statistical power in detecting longitudinal group differences.
► We discuss Linear Mixed Effects (LME) models in the context of longitudinal imaging. ► We contrast LME with widely used methods in longitudinal imaging. ► We illustrate, validate and benchmark LME-based computational tools. ► These tools will be freely available in FreeSurfer. |
|---|---|
| AbstractList | Longitudinal neuroimaging (LNI) studies are rapidly becoming more prevalent and growing in size. Today, no standardized computational tools exist for the analysis of LNI data and widely used methods are sub-optimal for the types of data encountered in real-life studies. Linear Mixed Effects (LME) modeling, a mature approach well known in the statistics community, offers a powerful and versatile framework for analyzing real-life LNI data. This article presents the theory behind LME models, contrasts it with other popular approaches in the context of LNI, and is accompanied with an array of computational tools that will be made freely available through FreeSurfer - a popular Magnetic Resonance Image (MRI) analysis software package. Our core contribution is to provide a quantitative empirical evaluation of the performance of LME and competing alternatives popularly used in prior longitudinal structural MRI studies, namely repeated measures ANOVA and the analysis of annualized longitudinal change measures (e.g. atrophy rate). In our experiments, we analyzed MRI-derived longitudinal hippocampal volume and entorhinal cortex thickness measurements from a public dataset consisting of Alzheimer's patients, subjects with mild cognitive impairment and healthy controls. Our results suggest that the LME approach offers superior statistical power in detecting longitudinal group differences.Longitudinal neuroimaging (LNI) studies are rapidly becoming more prevalent and growing in size. Today, no standardized computational tools exist for the analysis of LNI data and widely used methods are sub-optimal for the types of data encountered in real-life studies. Linear Mixed Effects (LME) modeling, a mature approach well known in the statistics community, offers a powerful and versatile framework for analyzing real-life LNI data. This article presents the theory behind LME models, contrasts it with other popular approaches in the context of LNI, and is accompanied with an array of computational tools that will be made freely available through FreeSurfer - a popular Magnetic Resonance Image (MRI) analysis software package. Our core contribution is to provide a quantitative empirical evaluation of the performance of LME and competing alternatives popularly used in prior longitudinal structural MRI studies, namely repeated measures ANOVA and the analysis of annualized longitudinal change measures (e.g. atrophy rate). In our experiments, we analyzed MRI-derived longitudinal hippocampal volume and entorhinal cortex thickness measurements from a public dataset consisting of Alzheimer's patients, subjects with mild cognitive impairment and healthy controls. Our results suggest that the LME approach offers superior statistical power in detecting longitudinal group differences. Longitudinal neuroimaging (LNI) studies are rapidly becoming more prevalent and growing in size. Today, no standardized computational tools exist for the analysis of LNI data and widely used methods are sub-optimal for the types of data encountered in real-life studies. Linear Mixed Effects (LME) modeling, a mature approach well known in the statistics community, offers a powerful and versatile framework for analyzing real-life LNI data. This article presents the theory behind LME models, contrasts it with other popular approaches in the context of LNI, and is accompanied with an array of computational tools that will be made freely available through FreeSurfer a a popular Magnetic Resonance Image (MRI) analysis software package. Longitudinal neuroimaging (LNI) studies are rapidly becoming more prevalent and growing in size. Today, no standardized computational tools exist for the analysis of LNI data and widely used methods are sub-optimal for the types of data encountered in real-life studies. Linear Mixed Effects (LME) modeling, a mature approach well known in the statistics community, offers a powerful and versatile framework for analyzing real-life LNI data. This article presents the theory behind LME models, contrasts it with other popular approaches in the context of LNI, and is accompanied with an array of computational tools that will be made freely available through FreeSurfer – a popular Magnetic Resonance Image (MRI) analysis software package. Our core contribution is to provide a quantitative empirical evaluation of the performance of LME and competing alternatives popularly used in prior longitudinal structural MRI studies, namely repeated measures ANOVA and the analysis of annualized longitudinal change measures (e.g. atrophy rate). In our experiments, we analyzed MRI-derived longitudinal hippocampal volume and entorhinal cortex thickness measurements from a public dataset consisting of Alzheimer’s patients, subjects with mild cognitive impairment and healthy controls. Our results suggest that the LME approach offers superior statistical power in detecting longitudinal group differences. Longitudinal neuroimaging (LNI) studies are rapidly becoming more prevalent and growing in size. Today, no standardized computational tools exist for the analysis of LNI data and widely used methods are sub-optimal for the types of data encountered in real-life studies. Linear Mixed Effects (LME) modeling, a mature approach well known in the statistics community, offers a powerful and versatile framework for analyzing real-life LNI data. This article presents the theory behind LME models, contrasts it with other popular approaches in the context of LNI, and is accompanied with an array of computational tools that will be made freely available through FreeSurfer -- a popular Magnetic Resonance Image (MRI) analysis software package. Our core contribution is to provide a quantitativeempiricalevaluation of the performance of LME and competing alternatives popularly used in prior longitudinal structural MRI studies, namely repeated measures ANOVA and the analysis of annualized longitudinal change measures (e.g. atrophy rate). In our experiments, we analyzed MRI-derived longitudinal hippocampal volume and entorhinal cortex thickness measurements from a public dataset consisting of Alzheimer's patients, subjects with mild cognitive impairment and healthy controls. Our results suggest that the LME approach offers superior statistical power in detecting longitudinal group differences. Longitudinal neuroimaging (LNI) studies are rapidly becoming more prevalent and growing in size. Today, no standardized computational tools exist for the analysis of LNI data and widely used methods are sub-optimal for the types of data encountered in real-life studies. Linear Mixed Effects (LME) modeling, a mature approach well known in the statistics community, offers a powerful and versatile framework for analyzing real-life LNI data. This article presents the theory behind LME models, contrasts it with other popular approaches in the context of LNI, and is accompanied with an array of computational tools that will be made freely available through FreeSurfer — a popular Magnetic Resonance Image (MRI) analysis software package. Our core contribution is to provide a quantitative empirical evaluation of the performance of LME and competing alternatives popularly used in prior longitudinal structural MRI studies, namely repeated measures ANOVA and the analysis of annualized longitudinal change measures (e.g. atrophy rate). In our experiments, we analyzed MRI-derived longitudinal hippocampal volume and entorhinal cortex thickness measurements from a public dataset consisting of Alzheimer's patients, subjects with mild cognitive impairment and healthy controls. Our results suggest that the LME approach offers superior statistical power in detecting longitudinal group differences. ► We discuss Linear Mixed Effects (LME) models in the context of longitudinal imaging. ► We contrast LME with widely used methods in longitudinal imaging. ► We illustrate, validate and benchmark LME-based computational tools. ► These tools will be freely available in FreeSurfer. Longitudinal neuroimaging (LNI) studies are rapidly becoming more prevalent and growing in size. Today, no standardized computational tools exist for the analysis of LNI data and widely used methods are sub-optimal for the types of data encountered in real-life studies. Linear Mixed Effects (LME) modeling, a mature approach well known in the statistics community, offers a powerful and versatile framework for analyzing real-life LNI data. This article presents the theory behind LME models, contrasts it with other popular approaches in the context of LNI, and is accompanied with an array of computational tools that will be made freely available through FreeSurfer - a popular Magnetic Resonance Image (MRI) analysis software package. Our core contribution is to provide a quantitative empirical evaluation of the performance of LME and competing alternatives popularly used in prior longitudinal structural MRI studies, namely repeated measures ANOVA and the analysis of annualized longitudinal change measures (e.g. atrophy rate). In our experiments, we analyzed MRI-derived longitudinal hippocampal volume and entorhinal cortex thickness measurements from a public dataset consisting of Alzheimer's patients, subjects with mild cognitive impairment and healthy controls. Our results suggest that the LME approach offers superior statistical power in detecting longitudinal group differences. |
| Author | Fischl, Bruce Greve, Douglas N. Reuter, Martin Bernal-Rusiel, Jorge L. Sabuncu, Mert R. |
| AuthorAffiliation | 1 Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School/Massachusetts General Hospital, Charlestown, MA 2 Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 3 Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA |
| AuthorAffiliation_xml | – name: 2 Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA – name: 3 Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA – name: 1 Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School/Massachusetts General Hospital, Charlestown, MA |
| Author_xml | – sequence: 1 givenname: Jorge L. surname: Bernal-Rusiel fullname: Bernal-Rusiel, Jorge L. organization: Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School/Massachusetts General Hospital, Charlestown, MA, USA – sequence: 2 givenname: Douglas N. surname: Greve fullname: Greve, Douglas N. organization: Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School/Massachusetts General Hospital, Charlestown, MA, USA – sequence: 3 givenname: Martin surname: Reuter fullname: Reuter, Martin organization: Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School/Massachusetts General Hospital, Charlestown, MA, USA – sequence: 4 givenname: Bruce surname: Fischl fullname: Fischl, Bruce organization: Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School/Massachusetts General Hospital, Charlestown, MA, USA – sequence: 5 givenname: Mert R. surname: Sabuncu fullname: Sabuncu, Mert R. email: msabuncu@nmr.mgh.harvard.edu organization: Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School/Massachusetts General Hospital, Charlestown, MA, USA |
| BackLink | http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=27110929$$DView record in Pascal Francis https://www.ncbi.nlm.nih.gov/pubmed/23123680$$D View this record in MEDLINE/PubMed |
| BookMark | eNqNkktvEzEUhS1URB_wF5AlhMQmwfaMH7NBlKoFpCAW0LXlse-kDhO72DOF_Pt61JRANmRly_f4u9c-5xQdhRgAIUzJnBIq3q7mAcYU_dosYc4IZeV4TgR_gk4oafis4ZIdTXtezRSlzTE6zXlFCGlorZ6hY1ZRVglFTtD1t8EMPg_emh6bYPpN9hnHDvcxLP0wOl_O8K4bdmYw-JcfbvDCBzAJf_G_weHLrgM7ZLyODvr8HD3tTJ_hxXY9Q9dXl98vPs0WXz9-vjhfzKxgcpjxtmlV2xlTcWehbp3oHFRVAw0VwhrHayuJMko5qohgpHU1cCI7yghQZ2l1ht49cG_Hdg2FEYZken2byqxpo6Px-t9K8Dd6Ge90xZWQtSyAN1tAij9HyINe-2yh702AOGZNBa2aoiP1_6WcECmooqpIX-1JV3FM5SMnFWeEMSlFUb38e_g_Uz-aUwSvtwKTiz1dMsH6vNNJWsxmze4XbIo5J-i09ZOrcXqz7zUlekqNXumdj3pKzVQpqSkAtQd47HHA1Q8PV4vrcOch6Ww9BAvOpxII7aI_BPJ-D2J7H6ZI_oDNYYh7DnH5ug |
| CitedBy_id | crossref_primary_10_1186_s13034_016_0093_8 crossref_primary_10_1093_cercor_bhac053 crossref_primary_10_3233_JAD_170055 crossref_primary_10_1093_cercor_bhab081 crossref_primary_10_3389_fnagi_2022_869387 crossref_primary_10_1002_hbm_24463 crossref_primary_10_1016_j_jneumeth_2016_12_020 crossref_primary_10_1016_j_bandc_2018_09_004 crossref_primary_10_1186_s40035_023_00336_2 crossref_primary_10_1021_acs_est_8b01295 crossref_primary_10_1371_journal_pone_0277099 crossref_primary_10_1109_ACCESS_2017_2773359 crossref_primary_10_1016_S1474_4422_18_30028_0 crossref_primary_10_1038_ncomms11934 crossref_primary_10_1007_s12021_024_09657_7 crossref_primary_10_1016_j_neuroimage_2020_117581 crossref_primary_10_1016_j_neuroimage_2016_04_023 crossref_primary_10_1136_bmjopen_2016_012174 crossref_primary_10_1136_bjsports_2020_102002 crossref_primary_10_1007_s00415_023_12172_5 crossref_primary_10_1016_j_neuroimage_2014_04_015 crossref_primary_10_18632_aging_103110 crossref_primary_10_1038_jcbfm_2015_101 crossref_primary_10_1016_j_nicl_2023_103529 crossref_primary_10_1016_j_ijrobp_2023_06_013 crossref_primary_10_1016_j_nicl_2023_103523 crossref_primary_10_1016_j_dcn_2024_101470 crossref_primary_10_1093_jnci_djx285 crossref_primary_10_1002_hbm_25414 crossref_primary_10_1002_pst_2357 crossref_primary_10_3389_fpsyt_2020_00574 crossref_primary_10_1038_ijo_2017_254 crossref_primary_10_1002_hbm_24245 crossref_primary_10_1212_WNL_0000000000207768 crossref_primary_10_1212_WNL_0000000000009498 crossref_primary_10_1016_j_exger_2016_01_007 crossref_primary_10_1016_j_nicl_2018_10_026 crossref_primary_10_1007_s11682_020_00366_8 crossref_primary_10_1016_j_neuroimage_2016_07_020 crossref_primary_10_1007_s10548_016_0509_z crossref_primary_10_1016_j_jaac_2022_03_026 crossref_primary_10_1016_j_nicl_2020_102374 crossref_primary_10_1186_s12936_019_2885_9 crossref_primary_10_1162_imag_a_00500 crossref_primary_10_1016_j_neuroimage_2016_04_001 crossref_primary_10_1371_journal_pone_0182182 crossref_primary_10_1186_s12887_017_0793_0 crossref_primary_10_3389_fneur_2019_00450 crossref_primary_10_1016_j_neuroimage_2014_12_006 crossref_primary_10_1093_cercor_bhaa332 crossref_primary_10_3390_toxics10110663 crossref_primary_10_1073_pnas_1611073113 crossref_primary_10_1038_s41380_024_02592_8 crossref_primary_10_2174_0115672050295317240223162312 crossref_primary_10_1002_nbm_3453 crossref_primary_10_3389_fneur_2023_1161527 crossref_primary_10_1016_j_molmet_2019_08_014 crossref_primary_10_3174_ajnr_A4508 crossref_primary_10_1017_S003329171800212X crossref_primary_10_1073_pnas_2411492122 crossref_primary_10_1016_j_neuropsychologia_2019_04_005 crossref_primary_10_1016_j_dcn_2025_101518 crossref_primary_10_1016_j_biopsych_2018_05_008 crossref_primary_10_1109_TMI_2023_3325380 crossref_primary_10_1038_s41593_023_01513_2 crossref_primary_10_3389_fnins_2016_00108 crossref_primary_10_3389_fpsyt_2021_686967 crossref_primary_10_1001_jamaneurol_2022_1025 crossref_primary_10_3920_JIFF2021_0076 crossref_primary_10_3389_fnins_2015_00375 crossref_primary_10_1016_j_neuroimage_2018_09_058 crossref_primary_10_3389_fnagi_2015_00081 crossref_primary_10_1016_j_ecoenv_2022_114013 crossref_primary_10_1016_j_scitotenv_2022_157469 crossref_primary_10_1080_02699052_2020_1858345 crossref_primary_10_1021_acs_est_1c03754 crossref_primary_10_1007_s11154_021_09701_w crossref_primary_10_1038_s41380_022_01870_7 crossref_primary_10_1093_cercor_bhac137 crossref_primary_10_1016_j_neurobiolaging_2021_10_003 crossref_primary_10_1038_s41598_019_56404_z crossref_primary_10_1002_hbm_24771 crossref_primary_10_1002_hbm_26271 crossref_primary_10_1016_j_tranon_2023_101769 crossref_primary_10_1016_j_nicl_2017_01_024 crossref_primary_10_1016_j_compmedimag_2021_101910 crossref_primary_10_1016_j_nicl_2020_102182 crossref_primary_10_1007_s10548_017_0544_4 crossref_primary_10_5665_sleep_5768 crossref_primary_10_1001_jamaoto_2020_2497 crossref_primary_10_1002_hbm_23435 crossref_primary_10_3389_fonc_2022_1021615 crossref_primary_10_1016_j_jad_2025_01_066 crossref_primary_10_1016_j_neuroimage_2019_116441 crossref_primary_10_1002_hbm_23317 crossref_primary_10_1038_s41398_019_0395_8 crossref_primary_10_1007_s00401_024_02750_w crossref_primary_10_1016_j_cmpb_2020_105348 crossref_primary_10_1002_hbm_24682 crossref_primary_10_1002_hbm_23590 crossref_primary_10_1007_s12021_018_9380_2 crossref_primary_10_1002_hbm_25412 crossref_primary_10_1016_j_trci_2017_06_004 crossref_primary_10_1109_TMI_2024_3435855 crossref_primary_10_1038_s41386_024_01836_z crossref_primary_10_1044_2019_JSLHR_S_CSMC7_18_0356 crossref_primary_10_3389_fphys_2015_00351 crossref_primary_10_1118_1_4871040 crossref_primary_10_1016_j_neuroimage_2016_08_029 crossref_primary_10_1016_j_nicl_2015_06_009 crossref_primary_10_1093_brain_aww243 crossref_primary_10_1212_NXI_0000000000200125 crossref_primary_10_1016_j_preteyeres_2021_100972 crossref_primary_10_1007_s00259_019_04519_w crossref_primary_10_1159_000445481 crossref_primary_10_1212_WNL_0000000000002492 crossref_primary_10_1002_hbm_23580 crossref_primary_10_1016_j_neurobiolaging_2016_09_015 crossref_primary_10_1159_000539467 crossref_primary_10_1016_j_neuroimage_2015_10_090 crossref_primary_10_1186_s12868_023_00783_7 crossref_primary_10_1016_j_neuroimage_2022_119729 crossref_primary_10_1002_sim_8568 crossref_primary_10_1093_brain_awv387 crossref_primary_10_3390_nu14245300 crossref_primary_10_1109_TCBB_2021_3106939 crossref_primary_10_1212_WNL_0000000000001045 crossref_primary_10_1038_s41598_020_65767_7 crossref_primary_10_1016_j_ajp_2025_104445 crossref_primary_10_3233_JAD_201162 crossref_primary_10_1016_j_biopsych_2019_08_015 crossref_primary_10_1016_j_cortex_2015_12_001 crossref_primary_10_1016_j_neuroimage_2023_119888 crossref_primary_10_1016_j_neuroimage_2017_01_052 crossref_primary_10_1088_1755_1315_303_1_012003 crossref_primary_10_1016_j_bpsc_2018_09_006 crossref_primary_10_1016_j_pnpbp_2020_110037 crossref_primary_10_1016_j_dcn_2017_11_007 crossref_primary_10_1016_j_neuroimage_2021_118312 crossref_primary_10_1177_25424823241306097 crossref_primary_10_7554_eLife_83660 crossref_primary_10_3389_fnagi_2023_1158579 crossref_primary_10_3389_fnins_2022_1025108 crossref_primary_10_3233_JAD_210308 crossref_primary_10_1002_hbm_24052 crossref_primary_10_1080_24709360_2017_1342186 crossref_primary_10_1177_1352458520940548 crossref_primary_10_1016_j_jneumeth_2020_108698 crossref_primary_10_1016_j_neuroimage_2013_01_047 crossref_primary_10_1089_neu_2017_5124 crossref_primary_10_1016_j_schres_2017_10_013 crossref_primary_10_1038_s41398_020_0809_7 crossref_primary_10_1016_j_neurobiolaging_2018_10_002 crossref_primary_10_1038_s41398_020_01090_z crossref_primary_10_1093_schbul_sbad040 crossref_primary_10_1080_07347332_2020_1855497 crossref_primary_10_1016_j_nicl_2023_103374 crossref_primary_10_1162_nol_a_00122 crossref_primary_10_1016_j_nicl_2018_11_016 crossref_primary_10_3389_fneur_2020_00673 crossref_primary_10_1016_j_cct_2021_106488 crossref_primary_10_1016_j_ijrobp_2021_05_134 crossref_primary_10_1002_hbm_24884 crossref_primary_10_1007_s11682_018_9904_2 crossref_primary_10_1016_j_atherosclerosis_2025_119159 crossref_primary_10_1016_j_neurobiolaging_2015_12_009 crossref_primary_10_1016_j_neurobiolaging_2014_03_044 crossref_primary_10_1007_s11682_018_9980_3 crossref_primary_10_1016_j_jneumeth_2022_109581 crossref_primary_10_1016_j_bbr_2016_05_047 crossref_primary_10_1002_nbm_4839 crossref_primary_10_1117_1_JMI_9_5_052404 crossref_primary_10_1371_journal_pone_0147774 crossref_primary_10_1177_1545968319868710 crossref_primary_10_1080_23737484_2021_1959468 crossref_primary_10_1002_dad2_12258 crossref_primary_10_1177_1352458515615224 crossref_primary_10_7554_eLife_34354 crossref_primary_10_1002_hbm_23301 crossref_primary_10_1016_j_schres_2020_02_005 crossref_primary_10_1016_j_chemosphere_2021_129906 crossref_primary_10_1016_S1474_4422_16_30125_9 crossref_primary_10_1016_j_neuroimage_2016_03_032 crossref_primary_10_1002_ana_25145 crossref_primary_10_1016_j_neuropsychologia_2017_03_014 crossref_primary_10_1038_s41598_022_18129_4 crossref_primary_10_1038_s42003_024_07414_9 crossref_primary_10_1007_s00234_020_02611_9 crossref_primary_10_1016_j_nicl_2018_03_015 crossref_primary_10_1093_cercor_bhz240 crossref_primary_10_1186_s13195_024_01450_7 crossref_primary_10_1109_JBHI_2020_3042447 crossref_primary_10_3389_fneur_2017_00340 crossref_primary_10_1002_alz_12323 crossref_primary_10_1016_j_media_2024_103436 crossref_primary_10_1016_j_neuroimage_2016_02_003 crossref_primary_10_1016_j_intell_2019_101401 crossref_primary_10_1016_j_neuroimage_2015_01_029 crossref_primary_10_1038_s42003_024_05873_8 crossref_primary_10_3233_JAD_190283 crossref_primary_10_1212_WNL_0000000000003094 crossref_primary_10_1093_biostatistics_kxw031 crossref_primary_10_1097_RLI_0000000000000564 crossref_primary_10_1017_S0033291723000387 crossref_primary_10_1002_hipo_23039 crossref_primary_10_1073_pnas_1604378113 crossref_primary_10_1016_j_media_2021_102051 crossref_primary_10_1016_j_neuroimage_2014_03_029 crossref_primary_10_1016_j_nicl_2018_01_030 crossref_primary_10_1016_j_envint_2018_06_027 crossref_primary_10_1016_j_media_2022_102571 crossref_primary_10_1002_hbm_22758 crossref_primary_10_3233_JAD_170261 crossref_primary_10_1016_j_aaf_2020_06_010 crossref_primary_10_1016_j_cam_2019_112378 crossref_primary_10_1038_s41539_020_00081_5 crossref_primary_10_1016_j_nicl_2021_102757 crossref_primary_10_1073_pnas_1508831112 crossref_primary_10_1093_braincomms_fcab205 crossref_primary_10_1002_mds_28228 crossref_primary_10_3390_e23040384 crossref_primary_10_1038_s41598_020_67398_4 crossref_primary_10_1016_j_ecoenv_2022_114423 crossref_primary_10_1016_j_biopsych_2024_03_012 crossref_primary_10_1038_s41467_025_55830_0 crossref_primary_10_1002_brb3_687 crossref_primary_10_1016_j_neuroimage_2013_01_034 crossref_primary_10_3389_fnimg_2024_1355402 crossref_primary_10_1186_s12916_024_03449_1 crossref_primary_10_3389_fnins_2021_682812 crossref_primary_10_1016_j_jaac_2018_02_010 crossref_primary_10_1016_j_pscychresns_2021_111311 crossref_primary_10_1002_sim_9244 crossref_primary_10_1002_bimj_202200333 crossref_primary_10_1038_s41598_018_33530_8 crossref_primary_10_1002_hbm_26579 crossref_primary_10_1212_WNL_0000000000005258 crossref_primary_10_1016_j_dcn_2021_100997 crossref_primary_10_3233_JAD_215553 crossref_primary_10_1016_j_fertnstert_2021_09_013 crossref_primary_10_1038_s41598_022_17727_6 crossref_primary_10_1002_hbm_26692 crossref_primary_10_1093_braincomms_fcac072 crossref_primary_10_1016_j_neurobiolaging_2018_12_013 crossref_primary_10_1109_TPAMI_2016_2578317 crossref_primary_10_1016_j_media_2016_06_014 crossref_primary_10_1109_TMI_2022_3166131 crossref_primary_10_1161_STROKEAHA_117_017526 crossref_primary_10_1016_j_dadm_2018_02_003 crossref_primary_10_1016_j_bandl_2019_104661 crossref_primary_10_1016_j_nicl_2019_101827 crossref_primary_10_1111_acer_14446 crossref_primary_10_1002_hbm_26205 crossref_primary_10_1016_j_trci_2019_07_001 crossref_primary_10_1016_j_neuroimage_2018_06_065 |
| Cites_doi | 10.1093/cercor/12.7.767 10.1016/j.neurobiolaging.2010.04.033 10.2307/2533558 10.1016/j.neuroimage.2012.01.021 10.1016/S1474-4422(09)70299-6 10.1001/archpsyc.58.2.148 10.1016/j.neuroimage.2011.02.076 10.1093/brain/awp062 10.1212/01.WNL.0000154530.72969.11 10.1093/cercor/bhh200 10.1016/j.bandl.2010.03.007 10.1002/hbm.21386 10.1212/01.wnl.0000281688.77598.35 10.1016/j.neuroimage.2008.04.252 10.1001/archpsyc.60.8.766 10.1002/hbm.21353 10.1016/j.neuroimage.2011.04.003 10.1016/S0197-4580(01)00271-8 10.1016/S0140-6736(06)68542-5 10.1002/sim.4780111411 10.1016/j.neuroimage.2010.04.258 10.1006/nimg.1998.0395 10.1001/archneurol.2011.3405 10.1007/s00330-009-1512-5 10.1002/hbm.1058 10.1002/(SICI)1097-0193(1999)8:4<272::AID-HBM10>3.0.CO;2-4 10.1016/j.neuroimage.2010.07.020 10.1080/01621459.1979.10481038 10.1523/JNEUROSCI.5714-09.2010 10.1001/archpsyc.60.6.585 10.1212/WNL.0b013e3181d3e3e9 10.1002/hbm.21304 10.1016/j.neuroimage.2011.07.056 10.1038/13158 10.1523/JNEUROSCI.5309-07.2008 10.1016/j.neurobiolaging.2010.04.030 10.1016/j.neuroimage.2011.07.007 10.2307/3002019 10.1080/01621459.1987.10478395 10.1016/j.neuroimage.2004.07.051 10.1006/nimg.1998.0396 10.1002/hbm.21334 10.1016/j.neuroimage.2011.08.066 10.1002/hbm.20498 10.1073/pnas.0906053106 10.1016/j.neuroimage.2006.11.054 10.1602/neurorx.2.2.348 10.1093/brain/awl021 10.1016/S0140-6736(03)12323-9 10.1212/WNL.49.3.786 10.1016/j.schres.2005.05.009 10.1212/WNL.54.4.813 10.1001/archneur.59.10.1572 10.1002/ana.22509 10.1016/S0896-6273(02)00569-X 10.1111/j.1399-5618.2009.00722.x 10.1542/peds.2008-0025 10.1001/archneurol.2011.167 10.1016/j.neuroimage.2012.02.084 10.1093/brain/awp132 10.1176/appi.ajp.2011.10111690 10.1093/brain/awm021 10.1212/WNL.0b013e318227047f 10.1016/j.neuroimage.2005.05.015 10.1523/JNEUROSCI.3252-09.2009 10.1176/appi.ajp.158.8.1248 10.1016/j.neuroimage.2004.06.018 10.1002/ana.21223 10.1148/radiol.2482070938 |
| ContentType | Journal Article |
| Copyright | 2012 Elsevier Inc. 2014 INIST-CNRS Copyright © 2012 Elsevier Inc. All rights reserved. Copyright Elsevier Limited Feb 1, 2013 2012 Elsevier Inc. All rights reserved. 2012 |
| Copyright_xml | – notice: 2012 Elsevier Inc. – notice: 2014 INIST-CNRS – notice: Copyright © 2012 Elsevier Inc. All rights reserved. – notice: Copyright Elsevier Limited Feb 1, 2013 – notice: 2012 Elsevier Inc. All rights reserved. 2012 |
| CorporateAuthor | for the Alzheimer's Disease Neuroimaging Initiative Alzheimer's Disease Neuroimaging Initiative |
| CorporateAuthor_xml | – name: for the Alzheimer's Disease Neuroimaging Initiative – name: Alzheimer's Disease Neuroimaging Initiative |
| DBID | AAYXX CITATION IQODW CGR CUY CVF ECM EIF NPM 3V. 7TK 7X7 7XB 88E 88G 8AO 8FD 8FE 8FH 8FI 8FJ 8FK ABUWG AFKRA AZQEC BBNVY BENPR BHPHI CCPQU DWQXO FR3 FYUFA GHDGH GNUQQ HCIFZ K9. LK8 M0S M1P M2M M7P P64 PHGZM PHGZT PJZUB PKEHL PPXIY PQEST PQGLB PQQKQ PQUKI PRINS PSYQQ Q9U RC3 7QO 7X8 5PM |
| DOI | 10.1016/j.neuroimage.2012.10.065 |
| DatabaseName | CrossRef Pascal-Francis Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed ProQuest Central (Corporate) Neurosciences Abstracts Health & Medical Collection ProQuest Central (purchase pre-March 2016) Medical Database (Alumni Edition) Psychology Database (Alumni) ProQuest Pharma Collection Technology Research Database ProQuest SciTech Collection ProQuest Natural Science Collection Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni) ProQuest Central UK/Ireland ProQuest Central Essentials Biological Science Collection ProQuest Central Natural Science Collection ProQuest One ProQuest Central Korea Engineering Research Database Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Central Student ProQuest SciTech Premium Collection ProQuest Health & Medical Complete (Alumni) Biological Sciences ProQuest Health & Medical Collection Medical Database Psychology Database Biological Science Database Biotechnology and BioEngineering Abstracts ProQuest Central Premium ProQuest One Academic (New) ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic ProQuest One Academic UKI Edition ProQuest Central China ProQuest One Psychology ProQuest Central Basic Genetics Abstracts Biotechnology Research Abstracts MEDLINE - Academic PubMed Central (Full Participant titles) |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) ProQuest One Psychology ProQuest Central Student Technology Research Database ProQuest One Academic Middle East (New) ProQuest Central Essentials ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest One Health & Nursing ProQuest Natural Science Collection ProQuest Pharma Collection ProQuest Central China ProQuest Central ProQuest One Applied & Life Sciences ProQuest Health & Medical Research Collection Genetics Abstracts Health Research Premium Collection Health and Medicine Complete (Alumni Edition) Natural Science Collection ProQuest Central Korea Health & Medical Research Collection Biological Science Collection ProQuest Central (New) ProQuest Medical Library (Alumni) ProQuest Biological Science Collection ProQuest Central Basic ProQuest One Academic Eastern Edition ProQuest Hospital Collection Health Research Premium Collection (Alumni) ProQuest Psychology Journals (Alumni) Biological Science Database ProQuest SciTech Collection Neurosciences Abstracts ProQuest Hospital Collection (Alumni) Biotechnology and BioEngineering Abstracts ProQuest Health & Medical Complete ProQuest Medical Library ProQuest Psychology Journals ProQuest One Academic UKI Edition Engineering Research Database ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni) Biotechnology Research Abstracts MEDLINE - Academic |
| DatabaseTitleList | MEDLINE - Academic Engineering Research Database ProQuest One Psychology MEDLINE |
| Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database – sequence: 3 dbid: BENPR name: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Medicine |
| EISSN | 1095-9572 |
| EndPage | 260 |
| ExternalDocumentID | PMC3586747 3396571481 23123680 27110929 10_1016_j_neuroimage_2012_10_065 S1053811912010683 |
| Genre | Research Support, Non-U.S. Gov't Journal Article Research Support, N.I.H., Extramural |
| GrantInformation_xml | – fundername: NIA NIH HHS grantid: AG022381 – fundername: NINDS NIH HHS grantid: 1R21NS072652-01 – fundername: NCCIH NIH HHS grantid: RC1 AT005728 – fundername: NIA NIH HHS grantid: R01 AG022381 – fundername: NINDS NIH HHS grantid: 2R01NS042861-06A1 – fundername: NIA NIH HHS grantid: 5R01AG008122-22 – fundername: NIA NIH HHS grantid: U01 AG024904 – fundername: NIMH NIH HHS grantid: U01 MH093765 – fundername: NCRR NIH HHS grantid: 1S10RR023043 – fundername: NICHD NIH HHS grantid: R01-HD071664 |
| GroupedDBID | --- --K --M .1- .FO .~1 0R~ 123 1B1 1RT 1~. 1~5 4.4 457 4G. 5RE 5VS 7-5 71M 7X7 88E 8AO 8FE 8FH 8FI 8FJ 8P~ 9JM AABNK AAEDT AAEDW AAIKJ AAKOC AALRI AAOAW AAQFI AATTM AAXKI AAXLA AAXUO AAYWO ABBQC ABCQJ ABFNM ABFRF ABIVO ABJNI ABMAC ABMZM ABUWG ABXDB ACDAQ ACGFO ACGFS ACIEU ACPRK ACRLP ACVFH ADBBV ADCNI ADEZE ADFRT AEBSH AEFWE AEIPS AEKER AENEX AEUPX AFJKZ AFKRA AFPUW AFRHN AFTJW AFXIZ AGCQF AGUBO AGWIK AGYEJ AHHHB AHMBA AIEXJ AIIUN AIKHN AITUG AJRQY AJUYK AKBMS AKRWK AKYEP ALMA_UNASSIGNED_HOLDINGS AMRAJ ANKPU ANZVX AXJTR AZQEC BBNVY BENPR BHPHI BKOJK BLXMC BNPGV BPHCQ BVXVI CCPQU CS3 DM4 DU5 DWQXO EBS EFBJH EFKBS EJD EO8 EO9 EP2 EP3 F5P FDB FIRID FNPLU FYGXN FYUFA G-Q GBLVA GNUQQ GROUPED_DOAJ HCIFZ HMCUK IHE J1W KOM LG5 LK8 LX8 M1P M29 M2M M2V M41 M7P MO0 MOBAO N9A O-L O9- OAUVE OVD OZT P-8 P-9 P2P PC. PHGZM PHGZT PJZUB PPXIY PQGLB PQQKQ PROAC PSQYO PSYQQ PUEGO Q38 ROL RPZ SAE SCC SDF SDG SDP SES SSH SSN SSZ T5K TEORI UKHRP UV1 YK3 Z5R ZU3 ~G- 3V. AACTN AADPK AAIAV ABLVK ABYKQ AFKWA AJBFU AJOXV AMFUW C45 EFLBG HMQ LCYCR RIG SNS ZA5 29N 53G AAFWJ AAQXK AAYXX ACRPL ADFGL ADMUD ADNMO ADVLN ADXHL AFPKN AGHFR AGQPQ AGRNS AIGII AKRLJ ALIPV APXCP ASPBG AVWKF AZFZN CAG CITATION COF FEDTE FGOYB G-2 HDW HEI HMK HMO HVGLF HZ~ OK1 R2- SEW WUQ XPP ZMT IQODW CGR CUY CVF ECM EIF NPM 7TK 7XB 8FD 8FK FR3 K9. P64 PKEHL PQEST PQUKI PRINS Q9U RC3 7QO 7X8 5PM |
| ID | FETCH-LOGICAL-c627t-5b9b8bfaa35dce4bd6fde339e9166cad54c708a88d180620bd4e507f120e1dc13 |
| IEDL.DBID | 7X7 |
| ISSN | 1053-8119 1095-9572 |
| IngestDate | Thu Aug 21 14:39:38 EDT 2025 Mon Jul 21 10:38:27 EDT 2025 Fri Jul 11 11:22:03 EDT 2025 Wed Aug 13 04:54:58 EDT 2025 Thu Apr 03 06:55:58 EDT 2025 Wed Apr 02 07:25:23 EDT 2025 Tue Jul 01 02:14:49 EDT 2025 Thu Apr 24 23:10:54 EDT 2025 Fri Feb 23 02:36:05 EST 2024 Tue Aug 26 16:31:45 EDT 2025 |
| IsDoiOpenAccess | false |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Linear Mixed Effects models Longitudinal studies Statistical analysis Models |
| Language | English |
| License | CC BY 4.0 Copyright © 2012 Elsevier Inc. All rights reserved. |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c627t-5b9b8bfaa35dce4bd6fde339e9166cad54c708a88d180620bd4e507f120e1dc13 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Data used in the preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators is available at http://tinyurl.com/ADNI-main. |
| OpenAccessLink | http://doi.org/10.1016/j.neuroimage.2012.10.065 |
| PMID | 23123680 |
| PQID | 1552022776 |
| PQPubID | 2031077 |
| PageCount | 12 |
| ParticipantIDs | pubmedcentral_primary_oai_pubmedcentral_nih_gov_3586747 proquest_miscellaneous_1613947304 proquest_miscellaneous_1500761818 proquest_journals_1552022776 pubmed_primary_23123680 pascalfrancis_primary_27110929 crossref_citationtrail_10_1016_j_neuroimage_2012_10_065 crossref_primary_10_1016_j_neuroimage_2012_10_065 elsevier_sciencedirect_doi_10_1016_j_neuroimage_2012_10_065 elsevier_clinicalkey_doi_10_1016_j_neuroimage_2012_10_065 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2013-02-01 |
| PublicationDateYYYYMMDD | 2013-02-01 |
| PublicationDate_xml | – month: 02 year: 2013 text: 2013-02-01 day: 01 |
| PublicationDecade | 2010 |
| PublicationPlace | Amsterdam |
| PublicationPlace_xml | – name: Amsterdam – name: United States |
| PublicationTitle | NeuroImage (Orlando, Fla.) |
| PublicationTitleAlternate | Neuroimage |
| PublicationYear | 2013 |
| Publisher | Elsevier Inc Elsevier Elsevier Limited |
| Publisher_xml | – name: Elsevier Inc – name: Elsevier – name: Elsevier Limited |
| References | Jack, Vemuri, Wiste, Weigand, Lesnick, Lowe, Kantarci, Bernstein, Senjem, Gunter (bb0200) 2012; 69 Nichols, Holmes (bb0265) 2002; 15 Resnick, Sojkova, Zhou, An, Ye, Holt, Dannals, Mathis, Klunk, Ferrucci (bb0280) 2010; 74 Ge, Grossman, Udupa, Fulton, Constantinescu, Gonzales, ÄìScarano, Babb, Mannon, Kolson, Cohen (bb0125) 2000; 54 Friston (bb0115) 2007 Fotenos, Snyder, Girton, Morris, Buckner (bb0100) 2005; 64 Lerch, Pruessner, Zijdenbos, Hampel, Teipel, Evans (bb0240) 2005; 15 Davatzikos, Resnick (bb0040) 2002; 12 Sluimer, Van Der Flier, Karas, Fox, Scheltens, Barkhof, Vrenken (bb0325) 2008; 248 SPM (bb0340) Mathalon, Sullivan, Lim, Pfefferbaum (bb0250) 2001; 58 Cleveland (bb0030) 1979 Jack, Lowe, Weigand, Wiste, Senjem, Knopman, Shiung, Gunter, Boeve, Kemp (bb0190) 2009; 132 Blockx, Van Camp, Verhoye, Boisgard, Dubois, Jego, Jonckers, Raber, Siquier, Kuhnast, Dolle, Nguyen, Von Horsten, Tavitian, Van der Linden (bb0010) 2011; 58 Davis, Jeste, Eyler (bb0045) 2005; 78 Gauthier, Reisberg, Zaudig, Petersen, Ritchie, Broich, Belleville, Brodaty, Bennett, Chertkow (bb0120) 2006; 367 Fjell, Walhovd, Fennema-Notestine, McEvoy, Hagler, Holland, Brewer, Dale (bb0095) 2009; 29 Hedman, van Haren, Schnack, Kahn, Hulshoff Pol (bb0145) 2012; 33 Montgomery, Peck, Vining (bb0260) 2007 Kasai, Shenton, Salisbury, Hirayasu, Onitsuka, Spencer, Yurgelun-Todd, Kikinis, Jolesz, McCarley (bb0220) 2003; 60 Lau, Lerch, Sled, Henkelman, Evans, Bedell (bb0235) 2008; 42 Reuter, Rosas, Fischl (bb0290) 2010; 53 Sidtis, Strother, Naoum, Rottenberg, Gomez (bb0320) 2010; 114 Shaw, Kabani, Lerch, Eckstrand, Lenroot, Gogtay, Greenstein, Clasen, Evans, Rapoport (bb0315) 2008; 28 Thambisetty, An, Kinsey, Koka, Saleem, Kraut, Ferrucci (bb0355) 2012; 59 Verbeke, Molenberghs (bb0375) 2000 Smith, Jenkinson, Woolrich, Beckmann, Behrens, Johansen-Berg, Bannister, De Luca, Drobnjak, Flitney (bb0335) 2004; 23 Bonne, Brandes, Gilboa, Gomori, Shenton, Pitman, Shalev (bb0015) 2001; 158 Sluimer, Van Der Flier, Karas, Van Schijndel, Barnes, Boyes, Cover, Olabarriaga, Fox, Scheltens (bb0330) 2009; 19 Kaladjian, Jeanningros, Azorin, Nazarian, Roth, Anton, Mazzola-Pomietto (bb0210) 2009; 11 Jack, Knopman, Jagust, Shaw, Aisen, Weiner, Petersen, Trojanowski (bb0195) 2010; 9 Holland, McEvoy, Dale (bb0165) 2012; 33 Reuter, Schmansky, Rosas, Fischl (bb0295) 2012; 61 Holland, Brewer, Hagler, Fennema-Notestine, Dale, Weiner, Thal, Petersen, Jack, Jagust (bb0160) 2009; 106 Asami, Bouix, Whitford, Shenton, Salisbury, McCarley (bb0005) 2012; 59 Jack, Petersen, Xu, Waring, O'Brien, Tangalos, Smith, Ivnik, Kokmen (bb0180) 1997; 49 Dale, Fischl, Sereno (bb0035) 1999; 9 Frings, Mader, Landwehrmeyer, Weiller, Hüll, Huppertz (bb0110) 2012; 33 Fitzmaurice, Laird, Ware (bb0090) 2011 Josephs, Whitwell, Ahmed, Shiung, Weigand, Knopman, Boeve, Parisi, Petersen, Dickson (bb0205) 2008; 63 Laird, Lange, Stram (bb0230) 1987 Hua, Hibar, Lee, Toga, Jack, Weiner, Thompson (bb0175) 2010; 31 Dickerson, Sperling (bb0055) 2005; 2 Dickerson, Goncharova, Sullivan, Forchetti, Wilson, Bennett, Beckett, deToledo-Morrell (bb0060) 2001; 22 Lindstrom, Bates (bb0245) 1988 Fischl (bb0070) 2012; 62 Fischl, Sereno, Dale (bb0075) 1999; 9 Fouquet, Desgranges, Landeau, Duchesnay, Mézenge, De La Sayette, Viader, Baron, Eustache, Chételat (bb0105) 2009; 132 Hua, Leow, Levitt, Caplan, Thompson, Toga (bb0170) 2009; 30 Tosun, Schuff, Truran-Sacrey, Shaw, Trojanowski, Aisen, Peterson, Weiner (bb0370) 2010; 31 Kenward, Roger (bb0225) 1997 Helms (bb0150) 1992; 11 Schumann, Bloss, Barnes, Wideman, Carper, Akshoomoff, Pierce, Hagler, Schork, Lord (bb0310) 2010; 30 Paviour, Price, Jahanshahi, Lees, Fox (bb0275) 2006; 129 Sabuncu, Desikan, Sepulcre, Yeo, Liu, Schmansky, Reuter, Weiner, Buckner, Sperling (bb0300) 2011; 68 Good (bb0140) 2000 Whitwell, Weigand, Gunter, Boeve, Rademakers, Baker, Knopman, Wszolek, Petersen, Jack (bb0385) 2011; 77 Jack, Weigand, Shiung, Przybelski, O'Brien, Gunter, Knopman, Boeve, Smith, Petersen (bb0185) 2008; 70 Fischl, Sereno, Tootell, Dale (bb0080) 1999; 8 Giedd, Blumenthal, Jeffries, Castellanos, Liu, Zijdenbos, Paus, Evans, Rapoport (bb0130) 1999; 2 Ho, Andreasen, Nopoulos, Arndt, Magnotta, Flaum (bb0155) 2003; 60 Thambisetty, Wan, Carass, An, Prince, Resnick (bb0350) 2010; 52 Pantelis, Velakoulis, McGorry, Wood, Suckling, Phillips, Yung, Bullmore, Brewer, Soulsby (bb0270) 2003; 361 Ment, Kesler, Vohr, Katz, Baumgartner, Schneider, Delancy, Silbereis, Duncan, Constable (bb0255) 2009; 123 Driscoll, Beydoun, An, Davatzikos, Ferrucci, Zonderman, Resnick (bb0065) 2012; 33 Buckner, Head, Parker, Fotenos, Marcus, Morris, Snyder (bb0020) 2004; 23 Thompson, Hallmayer, O'Hara, Alzheimer's Disease Neuroimaging (bb0365) 2011; 168 Reuter, Fischl (bb0285) 2011; 57 Satterthwaite (bb0305) 1946; 2 Chetelat, Landeau, Eustache, Mezenge, Viader, de La Sayette, Desgranges, Baron (bb0025) 2005; 27 Whitwell, Jack, Parisi, Knopman, Boeve, Petersen, Ferman, Dickson, Josephs (bb0380) 2007; 130 Desikan, McEvoy, Thompson, Holland, Roddey, Blennow, Aisen, Brewer, Hyman, Dale (bb0050) 2011; 70 Fischl, Salat, Busa, Albert, Dieterich, Haselgrove, Van Der Kouwe, Killiany, Kennedy, Klaveness (bb0085) 2002; 33 Sullivan, Pfefferbaum, Rohlfing, Baker, Padilla, Colrain (bb0345) 2011; 57 Kalkers, Ameziane, Bot, Minneboo, Polman, Barkhof (bb0215) 2002; 59 Thirion, Pinel, Meriaux, Roche, Dehaene, Poline (bb0360) 2007; 35 Girden (bb0135) 1992 Sidtis (10.1016/j.neuroimage.2012.10.065_bb0320) 2010; 114 Whitwell (10.1016/j.neuroimage.2012.10.065_bb0380) 2007; 130 Thambisetty (10.1016/j.neuroimage.2012.10.065_bb0350) 2010; 52 Thirion (10.1016/j.neuroimage.2012.10.065_bb0360) 2007; 35 Sabuncu (10.1016/j.neuroimage.2012.10.065_bb0300) 2011; 68 Davis (10.1016/j.neuroimage.2012.10.065_bb0045) 2005; 78 Resnick (10.1016/j.neuroimage.2012.10.065_bb0280) 2010; 74 Montgomery (10.1016/j.neuroimage.2012.10.065_bb0260) 2007 Mathalon (10.1016/j.neuroimage.2012.10.065_bb0250) 2001; 58 Lindstrom (10.1016/j.neuroimage.2012.10.065_bb0245) 1988 Reuter (10.1016/j.neuroimage.2012.10.065_bb0290) 2010; 53 Giedd (10.1016/j.neuroimage.2012.10.065_bb0130) 1999; 2 Whitwell (10.1016/j.neuroimage.2012.10.065_bb0385) 2011; 77 Holland (10.1016/j.neuroimage.2012.10.065_bb0165) 2012; 33 Lau (10.1016/j.neuroimage.2012.10.065_bb0235) 2008; 42 Fotenos (10.1016/j.neuroimage.2012.10.065_bb0100) 2005; 64 Reuter (10.1016/j.neuroimage.2012.10.065_bb0285) 2011; 57 Dickerson (10.1016/j.neuroimage.2012.10.065_bb0055) 2005; 2 Frings (10.1016/j.neuroimage.2012.10.065_bb0110) 2012; 33 Ment (10.1016/j.neuroimage.2012.10.065_bb0255) 2009; 123 Davatzikos (10.1016/j.neuroimage.2012.10.065_bb0040) 2002; 12 Buckner (10.1016/j.neuroimage.2012.10.065_bb0020) 2004; 23 Sluimer (10.1016/j.neuroimage.2012.10.065_bb0330) 2009; 19 Fjell (10.1016/j.neuroimage.2012.10.065_bb0095) 2009; 29 Fischl (10.1016/j.neuroimage.2012.10.065_bb0080) 1999; 8 Kaladjian (10.1016/j.neuroimage.2012.10.065_bb0210) 2009; 11 Ho (10.1016/j.neuroimage.2012.10.065_bb0155) 2003; 60 Ge (10.1016/j.neuroimage.2012.10.065_bb0125) 2000; 54 Sluimer (10.1016/j.neuroimage.2012.10.065_bb0325) 2008; 248 Jack (10.1016/j.neuroimage.2012.10.065_bb0195) 2010; 9 Desikan (10.1016/j.neuroimage.2012.10.065_bb0050) 2011; 70 Driscoll (10.1016/j.neuroimage.2012.10.065_bb0065) 2012; 33 Fitzmaurice (10.1016/j.neuroimage.2012.10.065_bb0090) 2011 Friston (10.1016/j.neuroimage.2012.10.065_bb0115) 2007 Jack (10.1016/j.neuroimage.2012.10.065_bb0200) 2012; 69 Blockx (10.1016/j.neuroimage.2012.10.065_bb0010) 2011; 58 Tosun (10.1016/j.neuroimage.2012.10.065_bb0370) 2010; 31 Good (10.1016/j.neuroimage.2012.10.065_bb0140) 2000 Fischl (10.1016/j.neuroimage.2012.10.065_bb0075) 1999; 9 Josephs (10.1016/j.neuroimage.2012.10.065_bb0205) 2008; 63 Hedman (10.1016/j.neuroimage.2012.10.065_bb0145) 2012; 33 Laird (10.1016/j.neuroimage.2012.10.065_bb0230) 1987 Smith (10.1016/j.neuroimage.2012.10.065_bb0335) 2004; 23 Reuter (10.1016/j.neuroimage.2012.10.065_bb0295) 2012; 61 Kenward (10.1016/j.neuroimage.2012.10.065_bb0225) 1997 Dale (10.1016/j.neuroimage.2012.10.065_bb0035) 1999; 9 Dickerson (10.1016/j.neuroimage.2012.10.065_bb0060) 2001; 22 Satterthwaite (10.1016/j.neuroimage.2012.10.065_bb0305) 1946; 2 Thompson (10.1016/j.neuroimage.2012.10.065_bb0365) 2011; 168 Gauthier (10.1016/j.neuroimage.2012.10.065_bb0120) 2006; 367 Paviour (10.1016/j.neuroimage.2012.10.065_bb0275) 2006; 129 Jack (10.1016/j.neuroimage.2012.10.065_bb0185) 2008; 70 Bonne (10.1016/j.neuroimage.2012.10.065_bb0015) 2001; 158 Schumann (10.1016/j.neuroimage.2012.10.065_bb0310) 2010; 30 Chetelat (10.1016/j.neuroimage.2012.10.065_bb0025) 2005; 27 Holland (10.1016/j.neuroimage.2012.10.065_bb0160) 2009; 106 Cleveland (10.1016/j.neuroimage.2012.10.065_bb0030) 1979 Fischl (10.1016/j.neuroimage.2012.10.065_bb0070) 2012; 62 Verbeke (10.1016/j.neuroimage.2012.10.065_bb0375) 2000 Shaw (10.1016/j.neuroimage.2012.10.065_bb0315) 2008; 28 Girden (10.1016/j.neuroimage.2012.10.065_bb0135) 1992 Jack (10.1016/j.neuroimage.2012.10.065_bb0180) 1997; 49 Fouquet (10.1016/j.neuroimage.2012.10.065_bb0105) 2009; 132 Hua (10.1016/j.neuroimage.2012.10.065_bb0175) 2010; 31 Pantelis (10.1016/j.neuroimage.2012.10.065_bb0270) 2003; 361 Kasai (10.1016/j.neuroimage.2012.10.065_bb0220) 2003; 60 Asami (10.1016/j.neuroimage.2012.10.065_bb0005) 2012; 59 Sullivan (10.1016/j.neuroimage.2012.10.065_bb0345) 2011; 57 Jack (10.1016/j.neuroimage.2012.10.065_bb0190) 2009; 132 Lerch (10.1016/j.neuroimage.2012.10.065_bb0240) 2005; 15 Helms (10.1016/j.neuroimage.2012.10.065_bb0150) 1992; 11 Kalkers (10.1016/j.neuroimage.2012.10.065_bb0215) 2002; 59 Thambisetty (10.1016/j.neuroimage.2012.10.065_bb0355) 2012; 59 SPM (10.1016/j.neuroimage.2012.10.065_bb0340) Fischl (10.1016/j.neuroimage.2012.10.065_bb0085) 2002; 33 Hua (10.1016/j.neuroimage.2012.10.065_bb0170) 2009; 30 Nichols (10.1016/j.neuroimage.2012.10.065_bb0265) 2002; 15 19477964 - Brain. 2009 Aug;132(Pt 8):2058-67 21376812 - Neuroimage. 2011 Jul 1;57(1):19-21 1480880 - Stat Med. 1992 Oct-Nov;11(14-15):1889-913 21824521 - Neuroimage. 2012 Jan 2;59(1):212-7 10690968 - Neurology. 2000 Feb 22;54(4):813-7 22887828 - Hum Brain Mapp. 2012 Sep;33(9):2204-10 12796222 - Arch Gen Psychiatry. 2003 Jun;60(6):585-94 15537673 - Cereb Cortex. 2005 Jul;15(7):995-1001 21915942 - Hum Brain Mapp. 2012 Aug;33(8):1987-2002 22002658 - Ann Neurol. 2011 Oct;70(4):657-61 15501092 - Neuroimage. 2004;23 Suppl 1:S208-19 18385317 - J Neurosci. 2008 Apr 2;28(14):3586-94 22409939 - Arch Neurol. 2012 Jul;69(7):856-67 9931268 - Neuroimage. 1999 Feb;9(2):179-94 9931269 - Neuroimage. 1999 Feb;9(2):195-207 21830259 - Hum Brain Mapp. 2012 Nov;33(11):2586-602 12912760 - Arch Gen Psychiatry. 2003 Aug;60(8):766-75 12559861 - Lancet. 2003 Jan 25;361(9354):281-8 20637289 - Neuroimage. 2010 Dec;53(4):1181-96 17239619 - Neuroimage. 2007 Mar;35(1):105-20 17894374 - Ann Neurol. 2008 Feb;63(2):204-12 19624392 - Bipolar Disord. 2009 Aug;11(5):530-8 15897955 - NeuroRx. 2005 Apr;2(2):348-60 18032747 - Neurology. 2008 May 6;70(19 Pt 2):1740-52 18064588 - Hum Brain Mapp. 2009 Jan;30(1):209-19 10491603 - Nat Neurosci. 1999 Oct;2(10):861-3 21618662 - Hum Brain Mapp. 2012 Jul;33(7):1526-35 11747097 - Hum Brain Mapp. 2002 Jan;15(1):1-25 20570401 - Neurobiol Aging. 2010 Aug;31(8):1340-54 21511039 - Neuroimage. 2011 Jul 1;57(1):214-24 18574133 - Radiology. 2008 Aug;248(2):590-8 12050088 - Cereb Cortex. 2002 Jul;12(7):767-71 20417959 - Brain Lang. 2010 Jul;114(1):43-51 15979287 - Schizophr Res. 2005 Oct 1;78(1):45-60 19996185 - Proc Natl Acad Sci U S A. 2009 Dec 8;106(49):20954-9 19171615 - Pediatrics. 2009 Feb;123(2):503-11 20287815 - Biometrics. 1946 Dec;2(6):110-4 11177116 - Arch Gen Psychiatry. 2001 Feb;58(2):148-57 21825241 - Arch Neurol. 2011 Aug;68(8):1040-8 22248573 - Neuroimage. 2012 Aug 15;62(2):774-81 20620666 - Neurobiol Aging. 2010 Aug;31(8):1463-80 21767653 - Neuroimage. 2011 Oct 15;58(4):1006-16 11705634 - Neurobiol Aging. 2001 Sep-Oct;22(5):747-54 11481158 - Am J Psychiatry. 2001 Aug;158(8):1248-51 12374494 - Arch Neurol. 2002 Oct;59(10):1572-6 21924364 - Neuroimage. 2012 Jan 16;59(2):986-96 15979341 - Neuroimage. 2005 Oct 1;27(4):934-46 22430496 - Neuroimage. 2012 Jul 16;61(4):1402-18 20083042 - Lancet Neurol. 2010 Jan;9(1):119-28 19955375 - J Neurosci. 2009 Dec 2;29(48):15223-31 11832223 - Neuron. 2002 Jan 31;33(3):341-55 16631882 - Lancet. 2006 Apr 15;367(9518):1262-70 15781822 - Neurology. 2005 Mar 22;64(6):1032-9 21753165 - Neurology. 2011 Jul 26;77(4):393-8 21724665 - Am J Psychiatry. 2011 Sep;168(9):894-903 17347250 - Brain. 2007 Apr;130(Pt 4):1148-58 Neuroimage. 2015 Mar;108:110 19618189 - Eur Radiol. 2009 Dec;19(12):2826-33 9333350 - Biometrics. 1997 Sep;53(3):983-97 18547819 - Neuroimage. 2008 Aug 1;42(1):19-27 9305341 - Neurology. 1997 Sep;49(3):786-94 20335478 - J Neurosci. 2010 Mar 24;30(12):4419-27 19339253 - Brain. 2009 May;132(Pt 5):1355-65 20147655 - Neurology. 2010 Mar 9;74(10):807-15 16455792 - Brain. 2006 Apr;129(Pt 4):1040-9 15488422 - Neuroimage. 2004 Oct;23(2):724-38 10619420 - Hum Brain Mapp. 1999;8(4):272-84 20441796 - Neuroimage. 2010 Oct 1;52(4):1215-23 |
| References_xml | – volume: 123 start-page: 503 year: 2009 end-page: 511 ident: bb0255 article-title: Longitudinal brain volume changes in preterm and term control subjects during late childhood and adolescence publication-title: Pediatrics – volume: 58 start-page: 1006 year: 2011 end-page: 1016 ident: bb0010 article-title: Genotype specific age related changes in a transgenic rat model of Huntington's disease publication-title: NeuroImage – volume: 19 start-page: 2826 year: 2009 end-page: 2833 ident: bb0330 article-title: Accelerating regional atrophy rates in the progression from normal aging to Alzheimer's disease publication-title: Eur. Radiol. – volume: 60 start-page: 585 year: 2003 ident: bb0155 article-title: Progressive structural brain abnormalities and their relationship to clinical outcome: a longitudinal magnetic resonance imaging study early in schizophrenia publication-title: Arch. Gen. Psychiatry – volume: 31 start-page: 1463 year: 2010 end-page: 1480 ident: bb0175 article-title: Sex and age differences in atrophic rates: an ADNI study with n publication-title: Neurobiol. Aging – volume: 78 start-page: 45 year: 2005 end-page: 60 ident: bb0045 article-title: Review of longitudinal functional neuroimaging studies of drug treatments in patients with schizophrenia publication-title: Schizophr. Res. – volume: 367 start-page: 1262 year: 2006 end-page: 1270 ident: bb0120 article-title: Mild cognitive impairment publication-title: Lancet – volume: 59 start-page: 986 year: 2012 end-page: 996 ident: bb0005 article-title: Longitudinal loss of gray matter volume in patients with first-episode schizophrenia: DARTEL automated analysis and ROI validation publication-title: Neuroimage – year: 2007 ident: bb0115 article-title: Statistical parametric mapping: the analysis of functional brain images – year: 2011 ident: bb0090 article-title: Applied longitudinal analysis – volume: 23 start-page: S208 year: 2004 end-page: S219 ident: bb0335 article-title: Advances in functional and structural MR image analysis and implementation as FSL publication-title: NeuroImage – volume: 54 start-page: 813 year: 2000 end-page: 817 ident: bb0125 article-title: Glatiramer acetate (Copaxone) treatment in relapsing–remitting MS publication-title: Neurology – volume: 2 start-page: 861 year: 1999 end-page: 862 ident: bb0130 article-title: Brain development during childhood and adolescence: a longitudinal MRI study publication-title: Nat. Neurosci. – volume: 11 start-page: 530 year: 2009 end-page: 538 ident: bb0210 article-title: Remission from mania is associated with a decrease in amygdala activation during motor response inhibition publication-title: Bipolar Disord. – volume: 70 start-page: 657 year: 2011 end-page: 661 ident: bb0050 article-title: Amyloid-β associated volume loss occurs only in the presence of phospho-tau publication-title: Ann. Neurol. – volume: 30 start-page: 4419 year: 2010 end-page: 4427 ident: bb0310 article-title: Longitudinal magnetic resonance imaging study of cortical development through early childhood in autism publication-title: J. Neurosci. – volume: 33 start-page: 1526 year: 2012 end-page: 1535 ident: bb0110 article-title: Quantifying change in individual subjects affected by frontotemporal lobar degeneration using automated longitudinal MRI volumetry publication-title: Hum. Brain Mapp. – volume: 74 start-page: 807 year: 2010 end-page: 815 ident: bb0280 article-title: Longitudinal cognitive decline is associated with fibrillar amyloid-beta measured by [11C] PiB publication-title: Neurology – volume: 9 start-page: 179 year: 1999 end-page: 194 ident: bb0035 article-title: Cortical surface-based analysis* 1: I. Segmentation and surface reconstruction publication-title: NeuroImage – volume: 12 start-page: 767 year: 2002 end-page: 771 ident: bb0040 article-title: Degenerative age changes in white matter connectivity visualized in vivo using magnetic resonance imaging publication-title: Cereb. Cortex – volume: 158 start-page: 1248 year: 2001 ident: bb0015 article-title: Longitudinal MRI study of hippocampal volume in trauma survivors with PTSD publication-title: Am. J. Psychiatry – start-page: 1014 year: 1988 end-page: 1022 ident: bb0245 article-title: Newton–Raphson and EM algorithms for linear mixed-effects models for repeated-measures data publication-title: J. Am. Stat. Assoc. – volume: 77 start-page: 393 year: 2011 end-page: 398 ident: bb0385 article-title: Trajectories of brain and hippocampal atrophy in FTD with mutations in MAPT or GRN publication-title: Neurology – year: 1992 ident: bb0135 article-title: ANOVA: Repeated measures – volume: 33 start-page: 1987 year: 2012 end-page: 2002 ident: bb0145 article-title: Human brain changes across the life span: A review of 56 longitudinal magnetic resonance imaging studies publication-title: Hum. Brain Mapp. – volume: 59 start-page: 1572 year: 2002 ident: bb0215 article-title: Longitudinal brain volume measurement in multiple sclerosis: rate of brain atrophy is independent of the disease subtype publication-title: Arch. Neurol. – volume: 52 start-page: 1215 year: 2010 end-page: 1223 ident: bb0350 article-title: Longitudinal changes in cortical thickness associated with normal aging publication-title: NeuroImage – volume: 61 start-page: 1402 year: 2012 end-page: 1418 ident: bb0295 article-title: Within-subject template estimation for unbiased longitudinal image analysis publication-title: NeuroImage – year: 2007 ident: bb0260 article-title: Introduction to Linear Regression Analysis – volume: 114 start-page: 43 year: 2010 end-page: 51 ident: bb0320 article-title: Longitudinal cerebral blood flow changes during speech in hereditary ataxia publication-title: Brain Lang. – volume: 106 start-page: 20954 year: 2009 end-page: 20959 ident: bb0160 article-title: Subregional neuroanatomical change as a biomarker for Alzheimer's disease publication-title: Proc. Natl. Acad. Sci. – start-page: 97 year: 1987 end-page: 105 ident: bb0230 article-title: Maximum likelihood computations with repeated measures: application of the EM algorithm publication-title: J. Am. Stat. Assoc. – volume: 33 start-page: 2204 year: 2012 end-page: 2210 ident: bb0065 article-title: Midlife obesity and trajectories of brain volume changes in older adults publication-title: Hum. Brain. Mapp. – volume: 64 start-page: 1032 year: 2005 end-page: 1039 ident: bb0100 article-title: Normative estimates of cross-sectional and longitudinal brain volume decline in aging and AD publication-title: Neurology – volume: 49 start-page: 786 year: 1997 end-page: 794 ident: bb0180 article-title: Medial temporal atrophy on MRI in normal aging and very mild Alzheimer's disease publication-title: Neurology – volume: 15 start-page: 995 year: 2005 end-page: 1001 ident: bb0240 article-title: Focal decline of cortical thickness in Alzheimer's disease identified by computational neuroanatomy publication-title: Cereb. Cortex – ident: bb0340 – volume: 168 start-page: 894 year: 2011 end-page: 903 ident: bb0365 article-title: Design considerations for characterizing psychiatric trajectories across the lifespan: application to effects of APOE-epsilon4 on cerebral cortical thickness in Alzheimer's disease publication-title: Am. J. Psychiatry – volume: 58 start-page: 148 year: 2001 ident: bb0250 article-title: Progressive brain volume changes and the clinical course of schizophrenia in men: a longitudinal magnetic resonance imaging study publication-title: Arch. Gen. Psychiatry – volume: 129 start-page: 1040 year: 2006 end-page: 1049 ident: bb0275 article-title: Longitudinal MRI in progressive supranuclear palsy and multiple system atrophy: rates and regions of atrophy publication-title: Brain – volume: 361 start-page: 281 year: 2003 end-page: 288 ident: bb0270 article-title: Neuroanatomical abnormalities before and after onset of psychosis: a cross-sectional and longitudinal MRI comparison publication-title: Lancet – volume: 60 start-page: 766 year: 2003 ident: bb0220 article-title: Progressive decrease of left Heschl gyrus and planum temporale gray matter volume in first-episode schizophrenia: a longitudinal magnetic resonance imaging study publication-title: Arch. Gen. Psychiatry – volume: 132 start-page: 1355 year: 2009 end-page: 1365 ident: bb0190 article-title: Serial PIB and MRI in normal, mild cognitive impairment and Alzheimer's disease: implications for sequence of pathological events in Alzheimer's disease publication-title: Brain – volume: 53 start-page: 1181 year: 2010 end-page: 1196 ident: bb0290 article-title: Highly accurate inverse consistent registration: a robust approach publication-title: NeuroImage – start-page: 983 year: 1997 end-page: 997 ident: bb0225 article-title: Small sample inference for fixed effects from restricted maximum likelihood publication-title: Biometrics – volume: 33 start-page: 341 year: 2002 end-page: 355 ident: bb0085 article-title: Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain publication-title: Neuron – volume: 22 start-page: 747 year: 2001 end-page: 754 ident: bb0060 article-title: MRI-derived entorhinal and hippocampal atrophy in incipient and very mild Alzheimer's disease publication-title: Neurobiol. Aging – volume: 68 start-page: 1040 year: 2011 ident: bb0300 article-title: The dynamics of cortical and hippocampal atrophy in Alzheimer disease publication-title: Arch. Neurol. – volume: 23 start-page: 724 year: 2004 end-page: 738 ident: bb0020 article-title: 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 publication-title: NeuroImage – volume: 30 start-page: 209 year: 2009 end-page: 219 ident: bb0170 article-title: Detecting brain growth patterns in normal children using tensor-based morphometry publication-title: Hum. Brain Mapp. – volume: 57 start-page: 19 year: 2011 end-page: 21 ident: bb0285 article-title: Avoiding asymmetry-induced bias in longitudinal image processing publication-title: NeuroImage – volume: 9 start-page: 119 year: 2010 end-page: 128 ident: bb0195 article-title: Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade publication-title: Lancet Neurol. – start-page: 829 year: 1979 end-page: 836 ident: bb0030 article-title: Robust locally weighted regression and smoothing scatterplots publication-title: J. Am. Stat. Assoc. – volume: 2 start-page: 110 year: 1946 end-page: 114 ident: bb0305 article-title: An approximate distribution of estimates of variance components publication-title: Biom. Bull. – volume: 15 start-page: 1 year: 2002 end-page: 25 ident: bb0265 article-title: Nonparametric permutation tests for functional neuroimaging: a primer with examples publication-title: Hum. Brain Mapp. – volume: 57 start-page: 214 year: 2011 end-page: 224 ident: bb0345 article-title: Developmental change in regional brain structure over 7 months in early adolescence: Comparison of approaches for longitudinal atlas-based parcellation publication-title: Neuroimage – volume: 9 start-page: 195 year: 1999 end-page: 207 ident: bb0075 article-title: Cortical surface-based analysis* 1: II: Inflation, flattening, and a surface-based coordinate system publication-title: NeuroImage – volume: 8 start-page: 272 year: 1999 end-page: 284 ident: bb0080 article-title: High-resolution intersubject averaging and a coordinate system for the cortical surface publication-title: Hum. Brain Mapp. – volume: 63 start-page: 204 year: 2008 end-page: 212 ident: bb0205 article-title: β-amyloid burden is not associated with rates of brain atrophy publication-title: Ann. Neurol. – volume: 35 start-page: 105 year: 2007 end-page: 120 ident: bb0360 article-title: Analysis of a large fMRI cohort: statistical and methodological issues for group analyses publication-title: NeuroImage – volume: 29 start-page: 15223 year: 2009 end-page: 15231 ident: bb0095 article-title: One-year brain atrophy evident in healthy aging publication-title: J. Neurosci. – volume: 62 start-page: 774 year: 2012 end-page: 781 ident: bb0070 article-title: Freesurfer publication-title: NeuroImage – volume: 132 start-page: 2058 year: 2009 end-page: 2067 ident: bb0105 article-title: Longitudinal brain metabolic changes from amnestic mild cognitive impairment to Alzheimer's disease publication-title: Brain – volume: 11 start-page: 1889 year: 1992 end-page: 1913 ident: bb0150 article-title: Intentionally incomplete longitudinal designs: I. Methodology and comparison of some full span designs publication-title: Stat. Med. – volume: 2 start-page: 348 year: 2005 end-page: 360 ident: bb0055 article-title: Neuroimaging biomarkers for clinical trials of disease-modifying therapies in Alzheimer's disease publication-title: NeuroRx – volume: 28 start-page: 3586 year: 2008 end-page: 3594 ident: bb0315 article-title: Neurodevelopmental trajectories of the human cerebral cortex publication-title: J. Neurosci. – volume: 27 start-page: 934 year: 2005 end-page: 946 ident: bb0025 article-title: Using voxel-based morphometry to map the structural changes associated with rapid conversion in MCI: a longitudinal MRI study publication-title: NeuroImage – volume: 42 start-page: 19 year: 2008 end-page: 27 ident: bb0235 article-title: Longitudinal neuroanatomical changes determined by deformation-based morphometry in a mouse model of Alzheimer's disease publication-title: NeuroImage – volume: 31 start-page: 1340 year: 2010 end-page: 1354 ident: bb0370 article-title: Relations between brain tissue loss, CSF biomarkers, and the ApoE genetic profile: a longitudinal MRI study publication-title: Neurobiol. Aging – year: 2000 ident: bb0140 article-title: Permutation tests – volume: 248 start-page: 590 year: 2008 end-page: 598 ident: bb0325 article-title: Whole-brain atrophy rate and cognitive decline: longitudinal MR study of memory clinic patients 1 publication-title: Radiology – volume: 130 start-page: 1148 year: 2007 end-page: 1158 ident: bb0380 article-title: Rates of cerebral atrophy differ in different degenerative pathologies publication-title: Brain – volume: 33 start-page: 2586 year: 2012 end-page: 2602 ident: bb0165 article-title: Unbiased comparison of sample size estimates from longitudinal structural measures in ADNI publication-title: Hum. Brain Mapp. – volume: 70 start-page: 1740 year: 2008 end-page: 1752 ident: bb0185 article-title: Atrophy rates accelerate in amnestic mild cognitive impairment publication-title: Neurology – volume: 69 start-page: 856 year: 2012 end-page: 867 ident: bb0200 article-title: Shapes of the Trajectories of 5 Major Biomarkers of Alzheimer Disease publication-title: Arch. Neurol. – volume: 59 start-page: 212 year: 2012 end-page: 217 ident: bb0355 article-title: Plasma clusterin concentration is associated with longitudinal brain atrophy in mild cognitive impairment publication-title: Neuroimage – year: 2000 ident: bb0375 article-title: Linear mixed models for longitudinal data – volume: 12 start-page: 767 year: 2002 ident: 10.1016/j.neuroimage.2012.10.065_bb0040 article-title: Degenerative age changes in white matter connectivity visualized in vivo using magnetic resonance imaging publication-title: Cereb. Cortex doi: 10.1093/cercor/12.7.767 – year: 2000 ident: 10.1016/j.neuroimage.2012.10.065_bb0140 – volume: 31 start-page: 1463 year: 2010 ident: 10.1016/j.neuroimage.2012.10.065_bb0175 article-title: Sex and age differences in atrophic rates: an ADNI study with n=1368 MRI scans publication-title: Neurobiol. Aging doi: 10.1016/j.neurobiolaging.2010.04.033 – start-page: 983 year: 1997 ident: 10.1016/j.neuroimage.2012.10.065_bb0225 article-title: Small sample inference for fixed effects from restricted maximum likelihood publication-title: Biometrics doi: 10.2307/2533558 – volume: 62 start-page: 774 issue: 2 year: 2012 ident: 10.1016/j.neuroimage.2012.10.065_bb0070 article-title: Freesurfer publication-title: NeuroImage doi: 10.1016/j.neuroimage.2012.01.021 – volume: 9 start-page: 119 year: 2010 ident: 10.1016/j.neuroimage.2012.10.065_bb0195 article-title: Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade publication-title: Lancet Neurol. doi: 10.1016/S1474-4422(09)70299-6 – volume: 58 start-page: 148 year: 2001 ident: 10.1016/j.neuroimage.2012.10.065_bb0250 article-title: Progressive brain volume changes and the clinical course of schizophrenia in men: a longitudinal magnetic resonance imaging study publication-title: Arch. Gen. Psychiatry doi: 10.1001/archpsyc.58.2.148 – volume: 57 start-page: 19 year: 2011 ident: 10.1016/j.neuroimage.2012.10.065_bb0285 article-title: Avoiding asymmetry-induced bias in longitudinal image processing publication-title: NeuroImage doi: 10.1016/j.neuroimage.2011.02.076 – volume: 132 start-page: 1355 year: 2009 ident: 10.1016/j.neuroimage.2012.10.065_bb0190 article-title: Serial PIB and MRI in normal, mild cognitive impairment and Alzheimer's disease: implications for sequence of pathological events in Alzheimer's disease publication-title: Brain doi: 10.1093/brain/awp062 – year: 2000 ident: 10.1016/j.neuroimage.2012.10.065_bb0375 – volume: 64 start-page: 1032 year: 2005 ident: 10.1016/j.neuroimage.2012.10.065_bb0100 article-title: Normative estimates of cross-sectional and longitudinal brain volume decline in aging and AD publication-title: Neurology doi: 10.1212/01.WNL.0000154530.72969.11 – volume: 15 start-page: 995 year: 2005 ident: 10.1016/j.neuroimage.2012.10.065_bb0240 article-title: Focal decline of cortical thickness in Alzheimer's disease identified by computational neuroanatomy publication-title: Cereb. Cortex doi: 10.1093/cercor/bhh200 – volume: 114 start-page: 43 year: 2010 ident: 10.1016/j.neuroimage.2012.10.065_bb0320 article-title: Longitudinal cerebral blood flow changes during speech in hereditary ataxia publication-title: Brain Lang. doi: 10.1016/j.bandl.2010.03.007 – volume: 33 start-page: 2586 issue: 11 year: 2012 ident: 10.1016/j.neuroimage.2012.10.065_bb0165 article-title: Unbiased comparison of sample size estimates from longitudinal structural measures in ADNI publication-title: Hum. Brain Mapp. doi: 10.1002/hbm.21386 – volume: 70 start-page: 1740 year: 2008 ident: 10.1016/j.neuroimage.2012.10.065_bb0185 article-title: Atrophy rates accelerate in amnestic mild cognitive impairment publication-title: Neurology doi: 10.1212/01.wnl.0000281688.77598.35 – volume: 42 start-page: 19 year: 2008 ident: 10.1016/j.neuroimage.2012.10.065_bb0235 article-title: Longitudinal neuroanatomical changes determined by deformation-based morphometry in a mouse model of Alzheimer's disease publication-title: NeuroImage doi: 10.1016/j.neuroimage.2008.04.252 – volume: 60 start-page: 766 year: 2003 ident: 10.1016/j.neuroimage.2012.10.065_bb0220 article-title: Progressive decrease of left Heschl gyrus and planum temporale gray matter volume in first-episode schizophrenia: a longitudinal magnetic resonance imaging study publication-title: Arch. Gen. Psychiatry doi: 10.1001/archpsyc.60.8.766 – volume: 33 start-page: 2204 issue: 9 year: 2012 ident: 10.1016/j.neuroimage.2012.10.065_bb0065 article-title: Midlife obesity and trajectories of brain volume changes in older adults publication-title: Hum. Brain. Mapp. doi: 10.1002/hbm.21353 – volume: 57 start-page: 214 issue: 1 year: 2011 ident: 10.1016/j.neuroimage.2012.10.065_bb0345 article-title: Developmental change in regional brain structure over 7 months in early adolescence: Comparison of approaches for longitudinal atlas-based parcellation publication-title: Neuroimage doi: 10.1016/j.neuroimage.2011.04.003 – volume: 22 start-page: 747 year: 2001 ident: 10.1016/j.neuroimage.2012.10.065_bb0060 article-title: MRI-derived entorhinal and hippocampal atrophy in incipient and very mild Alzheimer's disease publication-title: Neurobiol. Aging doi: 10.1016/S0197-4580(01)00271-8 – volume: 367 start-page: 1262 year: 2006 ident: 10.1016/j.neuroimage.2012.10.065_bb0120 article-title: Mild cognitive impairment publication-title: Lancet doi: 10.1016/S0140-6736(06)68542-5 – volume: 11 start-page: 1889 year: 1992 ident: 10.1016/j.neuroimage.2012.10.065_bb0150 article-title: Intentionally incomplete longitudinal designs: I. Methodology and comparison of some full span designs publication-title: Stat. Med. doi: 10.1002/sim.4780111411 – volume: 52 start-page: 1215 year: 2010 ident: 10.1016/j.neuroimage.2012.10.065_bb0350 article-title: Longitudinal changes in cortical thickness associated with normal aging publication-title: NeuroImage doi: 10.1016/j.neuroimage.2010.04.258 – volume: 9 start-page: 179 year: 1999 ident: 10.1016/j.neuroimage.2012.10.065_bb0035 article-title: Cortical surface-based analysis* 1: I. Segmentation and surface reconstruction publication-title: NeuroImage doi: 10.1006/nimg.1998.0395 – volume: 69 start-page: 856 issue: 7 year: 2012 ident: 10.1016/j.neuroimage.2012.10.065_bb0200 article-title: Shapes of the Trajectories of 5 Major Biomarkers of Alzheimer Disease publication-title: Arch. Neurol. doi: 10.1001/archneurol.2011.3405 – year: 2007 ident: 10.1016/j.neuroimage.2012.10.065_bb0260 – volume: 19 start-page: 2826 year: 2009 ident: 10.1016/j.neuroimage.2012.10.065_bb0330 article-title: Accelerating regional atrophy rates in the progression from normal aging to Alzheimer's disease publication-title: Eur. Radiol. doi: 10.1007/s00330-009-1512-5 – year: 2011 ident: 10.1016/j.neuroimage.2012.10.065_bb0090 – volume: 15 start-page: 1 year: 2002 ident: 10.1016/j.neuroimage.2012.10.065_bb0265 article-title: Nonparametric permutation tests for functional neuroimaging: a primer with examples publication-title: Hum. Brain Mapp. doi: 10.1002/hbm.1058 – volume: 8 start-page: 272 year: 1999 ident: 10.1016/j.neuroimage.2012.10.065_bb0080 article-title: High-resolution intersubject averaging and a coordinate system for the cortical surface publication-title: Hum. Brain Mapp. doi: 10.1002/(SICI)1097-0193(1999)8:4<272::AID-HBM10>3.0.CO;2-4 – volume: 53 start-page: 1181 year: 2010 ident: 10.1016/j.neuroimage.2012.10.065_bb0290 article-title: Highly accurate inverse consistent registration: a robust approach publication-title: NeuroImage doi: 10.1016/j.neuroimage.2010.07.020 – start-page: 829 year: 1979 ident: 10.1016/j.neuroimage.2012.10.065_bb0030 article-title: Robust locally weighted regression and smoothing scatterplots publication-title: J. Am. Stat. Assoc. doi: 10.1080/01621459.1979.10481038 – volume: 30 start-page: 4419 year: 2010 ident: 10.1016/j.neuroimage.2012.10.065_bb0310 article-title: Longitudinal magnetic resonance imaging study of cortical development through early childhood in autism publication-title: J. Neurosci. doi: 10.1523/JNEUROSCI.5714-09.2010 – volume: 60 start-page: 585 year: 2003 ident: 10.1016/j.neuroimage.2012.10.065_bb0155 article-title: Progressive structural brain abnormalities and their relationship to clinical outcome: a longitudinal magnetic resonance imaging study early in schizophrenia publication-title: Arch. Gen. Psychiatry doi: 10.1001/archpsyc.60.6.585 – volume: 74 start-page: 807 year: 2010 ident: 10.1016/j.neuroimage.2012.10.065_bb0280 article-title: Longitudinal cognitive decline is associated with fibrillar amyloid-beta measured by [11C] PiB publication-title: Neurology doi: 10.1212/WNL.0b013e3181d3e3e9 – volume: 33 start-page: 1526 issue: 7 year: 2012 ident: 10.1016/j.neuroimage.2012.10.065_bb0110 article-title: Quantifying change in individual subjects affected by frontotemporal lobar degeneration using automated longitudinal MRI volumetry publication-title: Hum. Brain Mapp. doi: 10.1002/hbm.21304 – year: 2007 ident: 10.1016/j.neuroimage.2012.10.065_bb0115 – volume: 59 start-page: 212 issue: 1 year: 2012 ident: 10.1016/j.neuroimage.2012.10.065_bb0355 article-title: Plasma clusterin concentration is associated with longitudinal brain atrophy in mild cognitive impairment publication-title: Neuroimage doi: 10.1016/j.neuroimage.2011.07.056 – volume: 2 start-page: 861 year: 1999 ident: 10.1016/j.neuroimage.2012.10.065_bb0130 article-title: Brain development during childhood and adolescence: a longitudinal MRI study publication-title: Nat. Neurosci. doi: 10.1038/13158 – volume: 28 start-page: 3586 year: 2008 ident: 10.1016/j.neuroimage.2012.10.065_bb0315 article-title: Neurodevelopmental trajectories of the human cerebral cortex publication-title: J. Neurosci. doi: 10.1523/JNEUROSCI.5309-07.2008 – volume: 31 start-page: 1340 year: 2010 ident: 10.1016/j.neuroimage.2012.10.065_bb0370 article-title: Relations between brain tissue loss, CSF biomarkers, and the ApoE genetic profile: a longitudinal MRI study publication-title: Neurobiol. Aging doi: 10.1016/j.neurobiolaging.2010.04.030 – volume: 58 start-page: 1006 year: 2011 ident: 10.1016/j.neuroimage.2012.10.065_bb0010 article-title: Genotype specific age related changes in a transgenic rat model of Huntington's disease publication-title: NeuroImage doi: 10.1016/j.neuroimage.2011.07.007 – volume: 2 start-page: 110 year: 1946 ident: 10.1016/j.neuroimage.2012.10.065_bb0305 article-title: An approximate distribution of estimates of variance components publication-title: Biom. Bull. doi: 10.2307/3002019 – start-page: 97 year: 1987 ident: 10.1016/j.neuroimage.2012.10.065_bb0230 article-title: Maximum likelihood computations with repeated measures: application of the EM algorithm publication-title: J. Am. Stat. Assoc. doi: 10.1080/01621459.1987.10478395 – volume: 23 start-page: S208 year: 2004 ident: 10.1016/j.neuroimage.2012.10.065_bb0335 article-title: Advances in functional and structural MR image analysis and implementation as FSL publication-title: NeuroImage doi: 10.1016/j.neuroimage.2004.07.051 – volume: 9 start-page: 195 year: 1999 ident: 10.1016/j.neuroimage.2012.10.065_bb0075 article-title: Cortical surface-based analysis* 1: II: Inflation, flattening, and a surface-based coordinate system publication-title: NeuroImage doi: 10.1006/nimg.1998.0396 – volume: 33 start-page: 1987 issue: 8 year: 2012 ident: 10.1016/j.neuroimage.2012.10.065_bb0145 article-title: Human brain changes across the life span: A review of 56 longitudinal magnetic resonance imaging studies publication-title: Hum. Brain Mapp. doi: 10.1002/hbm.21334 – volume: 59 start-page: 986 issue: 2 year: 2012 ident: 10.1016/j.neuroimage.2012.10.065_bb0005 article-title: Longitudinal loss of gray matter volume in patients with first-episode schizophrenia: DARTEL automated analysis and ROI validation publication-title: Neuroimage doi: 10.1016/j.neuroimage.2011.08.066 – volume: 30 start-page: 209 year: 2009 ident: 10.1016/j.neuroimage.2012.10.065_bb0170 article-title: Detecting brain growth patterns in normal children using tensor-based morphometry publication-title: Hum. Brain Mapp. doi: 10.1002/hbm.20498 – volume: 106 start-page: 20954 year: 2009 ident: 10.1016/j.neuroimage.2012.10.065_bb0160 article-title: Subregional neuroanatomical change as a biomarker for Alzheimer's disease publication-title: Proc. Natl. Acad. Sci. doi: 10.1073/pnas.0906053106 – year: 1992 ident: 10.1016/j.neuroimage.2012.10.065_bb0135 – volume: 35 start-page: 105 year: 2007 ident: 10.1016/j.neuroimage.2012.10.065_bb0360 article-title: Analysis of a large fMRI cohort: statistical and methodological issues for group analyses publication-title: NeuroImage doi: 10.1016/j.neuroimage.2006.11.054 – volume: 2 start-page: 348 year: 2005 ident: 10.1016/j.neuroimage.2012.10.065_bb0055 article-title: Neuroimaging biomarkers for clinical trials of disease-modifying therapies in Alzheimer's disease publication-title: NeuroRx doi: 10.1602/neurorx.2.2.348 – volume: 129 start-page: 1040 year: 2006 ident: 10.1016/j.neuroimage.2012.10.065_bb0275 article-title: Longitudinal MRI in progressive supranuclear palsy and multiple system atrophy: rates and regions of atrophy publication-title: Brain doi: 10.1093/brain/awl021 – volume: 361 start-page: 281 year: 2003 ident: 10.1016/j.neuroimage.2012.10.065_bb0270 article-title: Neuroanatomical abnormalities before and after onset of psychosis: a cross-sectional and longitudinal MRI comparison publication-title: Lancet doi: 10.1016/S0140-6736(03)12323-9 – volume: 49 start-page: 786 year: 1997 ident: 10.1016/j.neuroimage.2012.10.065_bb0180 article-title: Medial temporal atrophy on MRI in normal aging and very mild Alzheimer's disease publication-title: Neurology doi: 10.1212/WNL.49.3.786 – volume: 78 start-page: 45 year: 2005 ident: 10.1016/j.neuroimage.2012.10.065_bb0045 article-title: Review of longitudinal functional neuroimaging studies of drug treatments in patients with schizophrenia publication-title: Schizophr. Res. doi: 10.1016/j.schres.2005.05.009 – volume: 54 start-page: 813 year: 2000 ident: 10.1016/j.neuroimage.2012.10.065_bb0125 article-title: Glatiramer acetate (Copaxone) treatment in relapsing–remitting MS publication-title: Neurology doi: 10.1212/WNL.54.4.813 – volume: 59 start-page: 1572 year: 2002 ident: 10.1016/j.neuroimage.2012.10.065_bb0215 article-title: Longitudinal brain volume measurement in multiple sclerosis: rate of brain atrophy is independent of the disease subtype publication-title: Arch. Neurol. doi: 10.1001/archneur.59.10.1572 – volume: 70 start-page: 657 issue: 4 year: 2011 ident: 10.1016/j.neuroimage.2012.10.065_bb0050 article-title: Amyloid-β associated volume loss occurs only in the presence of phospho-tau publication-title: Ann. Neurol. doi: 10.1002/ana.22509 – volume: 33 start-page: 341 year: 2002 ident: 10.1016/j.neuroimage.2012.10.065_bb0085 article-title: Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain publication-title: Neuron doi: 10.1016/S0896-6273(02)00569-X – volume: 11 start-page: 530 year: 2009 ident: 10.1016/j.neuroimage.2012.10.065_bb0210 article-title: Remission from mania is associated with a decrease in amygdala activation during motor response inhibition publication-title: Bipolar Disord. doi: 10.1111/j.1399-5618.2009.00722.x – volume: 123 start-page: 503 year: 2009 ident: 10.1016/j.neuroimage.2012.10.065_bb0255 article-title: Longitudinal brain volume changes in preterm and term control subjects during late childhood and adolescence publication-title: Pediatrics doi: 10.1542/peds.2008-0025 – volume: 68 start-page: 1040 year: 2011 ident: 10.1016/j.neuroimage.2012.10.065_bb0300 article-title: The dynamics of cortical and hippocampal atrophy in Alzheimer disease publication-title: Arch. Neurol. doi: 10.1001/archneurol.2011.167 – volume: 61 start-page: 1402 year: 2012 ident: 10.1016/j.neuroimage.2012.10.065_bb0295 article-title: Within-subject template estimation for unbiased longitudinal image analysis publication-title: NeuroImage doi: 10.1016/j.neuroimage.2012.02.084 – volume: 132 start-page: 2058 year: 2009 ident: 10.1016/j.neuroimage.2012.10.065_bb0105 article-title: Longitudinal brain metabolic changes from amnestic mild cognitive impairment to Alzheimer's disease publication-title: Brain doi: 10.1093/brain/awp132 – volume: 168 start-page: 894 year: 2011 ident: 10.1016/j.neuroimage.2012.10.065_bb0365 article-title: Design considerations for characterizing psychiatric trajectories across the lifespan: application to effects of APOE-epsilon4 on cerebral cortical thickness in Alzheimer's disease publication-title: Am. J. Psychiatry doi: 10.1176/appi.ajp.2011.10111690 – volume: 130 start-page: 1148 year: 2007 ident: 10.1016/j.neuroimage.2012.10.065_bb0380 article-title: Rates of cerebral atrophy differ in different degenerative pathologies publication-title: Brain doi: 10.1093/brain/awm021 – volume: 77 start-page: 393 year: 2011 ident: 10.1016/j.neuroimage.2012.10.065_bb0385 article-title: Trajectories of brain and hippocampal atrophy in FTD with mutations in MAPT or GRN publication-title: Neurology doi: 10.1212/WNL.0b013e318227047f – volume: 27 start-page: 934 year: 2005 ident: 10.1016/j.neuroimage.2012.10.065_bb0025 article-title: Using voxel-based morphometry to map the structural changes associated with rapid conversion in MCI: a longitudinal MRI study publication-title: NeuroImage doi: 10.1016/j.neuroimage.2005.05.015 – ident: 10.1016/j.neuroimage.2012.10.065_bb0340 – volume: 29 start-page: 15223 year: 2009 ident: 10.1016/j.neuroimage.2012.10.065_bb0095 article-title: One-year brain atrophy evident in healthy aging publication-title: J. Neurosci. doi: 10.1523/JNEUROSCI.3252-09.2009 – volume: 158 start-page: 1248 year: 2001 ident: 10.1016/j.neuroimage.2012.10.065_bb0015 article-title: Longitudinal MRI study of hippocampal volume in trauma survivors with PTSD publication-title: Am. J. Psychiatry doi: 10.1176/appi.ajp.158.8.1248 – start-page: 1014 year: 1988 ident: 10.1016/j.neuroimage.2012.10.065_bb0245 article-title: Newton–Raphson and EM algorithms for linear mixed-effects models for repeated-measures data publication-title: J. Am. Stat. Assoc. – volume: 23 start-page: 724 year: 2004 ident: 10.1016/j.neuroimage.2012.10.065_bb0020 article-title: 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 publication-title: NeuroImage doi: 10.1016/j.neuroimage.2004.06.018 – volume: 63 start-page: 204 year: 2008 ident: 10.1016/j.neuroimage.2012.10.065_bb0205 article-title: β-amyloid burden is not associated with rates of brain atrophy publication-title: Ann. Neurol. doi: 10.1002/ana.21223 – volume: 248 start-page: 590 year: 2008 ident: 10.1016/j.neuroimage.2012.10.065_bb0325 article-title: Whole-brain atrophy rate and cognitive decline: longitudinal MR study of memory clinic patients 1 publication-title: Radiology doi: 10.1148/radiol.2482070938 – reference: 18064588 - Hum Brain Mapp. 2009 Jan;30(1):209-19 – reference: 18547819 - Neuroimage. 2008 Aug 1;42(1):19-27 – reference: 11747097 - Hum Brain Mapp. 2002 Jan;15(1):1-25 – reference: 11705634 - Neurobiol Aging. 2001 Sep-Oct;22(5):747-54 – reference: 20335478 - J Neurosci. 2010 Mar 24;30(12):4419-27 – reference: 20083042 - Lancet Neurol. 2010 Jan;9(1):119-28 – reference: 10619420 - Hum Brain Mapp. 1999;8(4):272-84 – reference: 15979341 - Neuroimage. 2005 Oct 1;27(4):934-46 – reference: 11481158 - Am J Psychiatry. 2001 Aug;158(8):1248-51 – reference: 17347250 - Brain. 2007 Apr;130(Pt 4):1148-58 – reference: 11832223 - Neuron. 2002 Jan 31;33(3):341-55 – reference: 18385317 - J Neurosci. 2008 Apr 2;28(14):3586-94 – reference: 20441796 - Neuroimage. 2010 Oct 1;52(4):1215-23 – reference: 21767653 - Neuroimage. 2011 Oct 15;58(4):1006-16 – reference: 21753165 - Neurology. 2011 Jul 26;77(4):393-8 – reference: 19618189 - Eur Radiol. 2009 Dec;19(12):2826-33 – reference: 21825241 - Arch Neurol. 2011 Aug;68(8):1040-8 – reference: 19339253 - Brain. 2009 May;132(Pt 5):1355-65 – reference: 15488422 - Neuroimage. 2004 Oct;23(2):724-38 – reference: 9305341 - Neurology. 1997 Sep;49(3):786-94 – reference: 17894374 - Ann Neurol. 2008 Feb;63(2):204-12 – reference: 1480880 - Stat Med. 1992 Oct-Nov;11(14-15):1889-913 – reference: 22887828 - Hum Brain Mapp. 2012 Sep;33(9):2204-10 – reference: 19996185 - Proc Natl Acad Sci U S A. 2009 Dec 8;106(49):20954-9 – reference: 9333350 - Biometrics. 1997 Sep;53(3):983-97 – reference: 20417959 - Brain Lang. 2010 Jul;114(1):43-51 – reference: 20287815 - Biometrics. 1946 Dec;2(6):110-4 – reference: 22002658 - Ann Neurol. 2011 Oct;70(4):657-61 – reference: 22430496 - Neuroimage. 2012 Jul 16;61(4):1402-18 – reference: - Neuroimage. 2015 Mar;108:110 – reference: 15501092 - Neuroimage. 2004;23 Suppl 1:S208-19 – reference: 22248573 - Neuroimage. 2012 Aug 15;62(2):774-81 – reference: 12559861 - Lancet. 2003 Jan 25;361(9354):281-8 – reference: 19477964 - Brain. 2009 Aug;132(Pt 8):2058-67 – reference: 21915942 - Hum Brain Mapp. 2012 Aug;33(8):1987-2002 – reference: 10690968 - Neurology. 2000 Feb 22;54(4):813-7 – reference: 15979287 - Schizophr Res. 2005 Oct 1;78(1):45-60 – reference: 22409939 - Arch Neurol. 2012 Jul;69(7):856-67 – reference: 21511039 - Neuroimage. 2011 Jul 1;57(1):214-24 – reference: 18032747 - Neurology. 2008 May 6;70(19 Pt 2):1740-52 – reference: 18574133 - Radiology. 2008 Aug;248(2):590-8 – reference: 21724665 - Am J Psychiatry. 2011 Sep;168(9):894-903 – reference: 21618662 - Hum Brain Mapp. 2012 Jul;33(7):1526-35 – reference: 20637289 - Neuroimage. 2010 Dec;53(4):1181-96 – reference: 12050088 - Cereb Cortex. 2002 Jul;12(7):767-71 – reference: 19624392 - Bipolar Disord. 2009 Aug;11(5):530-8 – reference: 15897955 - NeuroRx. 2005 Apr;2(2):348-60 – reference: 16631882 - Lancet. 2006 Apr 15;367(9518):1262-70 – reference: 15781822 - Neurology. 2005 Mar 22;64(6):1032-9 – reference: 20620666 - Neurobiol Aging. 2010 Aug;31(8):1463-80 – reference: 21824521 - Neuroimage. 2012 Jan 2;59(1):212-7 – reference: 11177116 - Arch Gen Psychiatry. 2001 Feb;58(2):148-57 – reference: 17239619 - Neuroimage. 2007 Mar;35(1):105-20 – reference: 12912760 - Arch Gen Psychiatry. 2003 Aug;60(8):766-75 – reference: 21830259 - Hum Brain Mapp. 2012 Nov;33(11):2586-602 – reference: 10491603 - Nat Neurosci. 1999 Oct;2(10):861-3 – reference: 20570401 - Neurobiol Aging. 2010 Aug;31(8):1340-54 – reference: 19171615 - Pediatrics. 2009 Feb;123(2):503-11 – reference: 12374494 - Arch Neurol. 2002 Oct;59(10):1572-6 – reference: 9931268 - Neuroimage. 1999 Feb;9(2):179-94 – reference: 9931269 - Neuroimage. 1999 Feb;9(2):195-207 – reference: 20147655 - Neurology. 2010 Mar 9;74(10):807-15 – reference: 19955375 - J Neurosci. 2009 Dec 2;29(48):15223-31 – reference: 12796222 - Arch Gen Psychiatry. 2003 Jun;60(6):585-94 – reference: 21924364 - Neuroimage. 2012 Jan 16;59(2):986-96 – reference: 15537673 - Cereb Cortex. 2005 Jul;15(7):995-1001 – reference: 21376812 - Neuroimage. 2011 Jul 1;57(1):19-21 – reference: 16455792 - Brain. 2006 Apr;129(Pt 4):1040-9 |
| SSID | ssj0009148 |
| Score | 2.5531487 |
| Snippet | Longitudinal neuroimaging (LNI) studies are rapidly becoming more prevalent and growing in size. Today, no standardized computational tools exist for the... |
| SourceID | pubmedcentral proquest pubmed pascalfrancis crossref elsevier |
| SourceType | Open Access Repository Aggregation Database Index Database Enrichment Source Publisher |
| StartPage | 249 |
| SubjectTerms | Aged Aged, 80 and over Algorithms Alzheimer Disease - pathology Biological and medical sciences Brain - pathology Cognitive Dysfunction - pathology Female Fundamental and applied biological sciences. Psychology Humans Hypothesis testing Image Processing, Computer-Assisted - methods Linear Mixed Effects models Linear Models Longitudinal Studies Magnetic Resonance Imaging Male Medical imaging Middle Aged Parameter estimation Software Standard deviation Statistical analysis Statistical methods Studies Variance analysis Vertebrates: nervous system and sense organs |
| SummonAdditionalLinks | – databaseName: Elsevier SD Freedom Collection dbid: .~1 link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3da9swEBelD2MwxtZ9eeuKBnt1E1myPuhTKSulkL5sgb4ZyZKYR-eEJoE97W_fnS07yygj0NfoDuTT6e4U_fQ7Qj47yFqOFTaPyHYrLLe5CZrlwcdahjqqEPFx8uxGXs3F9W15e0AuhrcwCKtMsb-P6V20Tr9MkjUny6aZfIXKANINnDfwQldqZPwUQqGXn_7ewjwME_1zuJLnKJ3QPD3Gq-OMbH7CzkWQV3GKOC9MMw-nqGdLuwLDxb7jxUMl6b_Iyr9S1eUL8jzVmPS8_4yX5CC0R-TJLN2ivyJzrDA7gmaQsomVhC4ivVtg96KNx05ZdDtrijBSiv_YUji6wtags-ZX8LRnPl7RrpvO6jWZX375dnGVp_YKeS0Ltc5LZ5x20VpewnyF8zL6wLkJUDHK2vpS1Gqqrdae6aksps6LANVjBHsH5mvG35DDdtGGd4TKoDl3vLSF8sIZZoUS2grPTB1KaXhG1GDRqk7c49gC464aQGY_qu1XVbgWOAJrkRE2ai57_o09dMywaNXwvhQiYgVJYg_ds1F3xw_31D7Z8ZFxyoVCZtfCZOR4cJoqBYtVhSx4yOSoZEY-jcOwzfHuxrZhsUEZvDOFckz_RwZKMyMgZIuMvO39cDsBjjQ7egorseOhowDSjO-OtM33jm6cl1rCofP9oyzzgTwtukYiCAQ6Jofr-034COXc2p10-_UPdCJNOQ priority: 102 providerName: Elsevier |
| Title | Statistical analysis of longitudinal neuroimage data with Linear Mixed Effects models |
| URI | https://www.clinicalkey.com/#!/content/1-s2.0-S1053811912010683 https://dx.doi.org/10.1016/j.neuroimage.2012.10.065 https://www.ncbi.nlm.nih.gov/pubmed/23123680 https://www.proquest.com/docview/1552022776 https://www.proquest.com/docview/1500761818 https://www.proquest.com/docview/1613947304 https://pubmed.ncbi.nlm.nih.gov/PMC3586747 |
| Volume | 66 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3fi9QwEA7eHYhwiL-tnksEX3s2TZqm-CCn3LEqu4i4sG8laVJu5Wz37C745N_uTJu2rhzHPvUhMzBtJjNfk8k3hLwxkLUMi3VYItut0FyHmVMsdLYspCvK1JV4OXk2l9OF-LxMln7DrfFllX1MbAO1rQvcI3-LVGFId5fK9-vrELtG4emqb6FxQI6QugxLutJlOpLuMtFdhUt4qEDAV_J09V0tX-TqJ6xaLPCKT7HGC1PMzenpeK0b-Ghl1-3iJjj6f1XlP2nq4gG57_ElPesc4iG546pH5O7Mn6A_JgtEly05M0hpz0hC65Je1di5aGuxSxYdraZYQkpxt5bCbyssCzpb_XaWdqzHDW076TRPyOLi_PvHaehbK4SFjNNNmJjMKFNqzROwVxgrS-s4zxygRVlom4gijZRWyjIVyTgyVjhAjiWLI8dswfhTcljVlXtOqHSKc8MTHadWmIxpkQqlhWVZ4RKZ8YCk_RfNC887ju0vrvK-wOxHPr5VjnOBIzAXAWGD5rrj3thDJ-snLe_vlkI0zCFB7KH7btD1-KPDFXtqT3Z8ZDA5TpHVNc4CctI7Te4DRZOPbh2Q18MwLHE8t9GVq7cog-elAMXULTIAyzIB4VoE5Fnnh6MBHCl2VAQzseOhgwBSjO-OVKvLlmqcJ0rCD-eL201_Se7FbZcQrPI5IYebX1v3CrDaxkzIwekfNmmX5YQcnX36Mp3D88P5_Ou3v853Rf8 |
| linkProvider | ProQuest |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1tb9MwED6NTgIkhHinMIaR4GMgfkniCCHEy6aOrRVCq7RvwbEdUTTSQlsBf4rfyF3eStE09cs-2xc5vvPdY_v8HMDTHKNWzoUJCmK7VUaaIPWaB94VNva2SHxBj5OHo3gwVh9OopMt-NO-haG0ytYnVo7aTS2dkb8gqjCiu0vi17PvAVWNotvVtoRGbRaH_vdP3LLNXx28R_0-E2J_7_jdIGiqCgQ2FskiiPI013lhjIyc9Sp3ceG8lKlHoBRb4yJlk1AbrR3XYSzC3CmPoKngIvTcWS7xu5dgW0ncyvRg--3e6OOnFc0vV_Xju0gGmvO0yR2qM8oqhsrJN_QTlFImnlNWGQW1swPitZmZo5qKur7GWQD4_zzOfwLj_g243iBa9qY2wZuw5ctbcHnY3NnfhjHh2YoOGnuZhgOFTQt2OqVaSUtHdbnYatSMklYZnQ8z3CjjjLPh5Jd3rOZZnrOqds_8DowvZNrvQq-clv4-sNhrKXMZGZE4lafcqERpoxxPrY_iVPYhaWc0sw3TORXcOM3alLav2eqvMtIFtaAu-sA7yVnN9rGBTNoqLWtfs6L_zTAkbSD7spNtEE-NZDaU3l2zkW7IIiEeWZH2Yac1mqxxTfNstZD68KRrRqdCN0Wm9NMl9aEbWgR_-pw-CARThQFC9eFebYerAUgi9dEhamLNQrsORGq-3lJOvlTk5jLSMW5xH5w_9MdwZXA8PMqODkaHD-GqqGqUUI7RDvQWP5b-ESLFRb7bLE8Gny_aI_wFJ3CBUg |
| linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1bb9MwFLbGkCakCXEnMIaR4DEsviR2hBBCjGpjdOKBSn0LTmyLoi0ppBXw1_h1nJNLQ9E09WXPtivX5_icz_Hn7xDyPIeslTNuQo9qt9IIE6ZOs9BZXySu8Mp5fJw8Pk2OJvLDNJ5ukT_9WxikVfYxsQnUtirwG_kBSoWh3J1KDnxHi_h0OHoz_x5iBSm8ae3LabQucuJ-_4TjW_36-BBs_YLz0fvP747CrsJAWCRcLcI4T3Ode2NEbAsnc5t464RIHYCmpDA2loWKtNHaMh0lPMqtdACgPOORY7ZgAn73GrmuRMxwj6mpGgR_mWyf4cUi1IylHYuo5ZY1WpWzc4gYSC7jL5Ffhunt4tS4Ozc1GMy3lTYugsL_Mzr_SZGjW-Rmh23p29YZb5MtV94hO-Pu9v4umSCybYShoZfp1FBo5elZhVWTlhYrdNFh1hTpqxS_FFM4MsN60_Hsl7O0VVyuaVPFp75HJley6PfJdlmV7iGhidNC5CI2XFmZp8xIJbWRlqWFi5NUBET1K5oVneY5lt44y3py27ds-FcZ2gJbwBYBYauR81b3Y4MxaW-0rH_XCpE4g-S0wdhXq7Ed9mkxzYaj99d8ZDVlrlBRlqcB2eudJuuCVJ0NWyogz1bNEF7wzsiUrlpiH7yrBRioL-kDkDCVkCpkQB60fjhMQKC8j47AEmseuuqA8ubrLeXsayNzLmKdwGH30eVTf0p2IA5kH49PTx6TG7wpVoJkoz2yvfixdE8AMi7y_WZvUvLlqoPBX32uhCI |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Statistical+analysis+of+longitudinal+neuroimage+data+with+Linear+Mixed+Effects+models&rft.jtitle=NeuroImage+%28Orlando%2C+Fla.%29&rft.au=Anon.%2C+Anon&rft.date=2013-02-01&rft.issn=1053-8119&rft.volume=66&rft.spage=249&rft.epage=260&rft_id=info:doi/10.1016%2Fj.neuroimage.2012.10.065&rft.externalDBID=NO_FULL_TEXT |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1053-8119&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1053-8119&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1053-8119&client=summon |