Linear mixed-effects modeling approach to FMRI group analysis

Aguirre, 1998, The variability of human, BOLD hemodynamic responses, Neuroimage, 8, 360, 10.1006/nimg.1998.0369 Allison, 2001 Alvarez, 2011, Phasic and sustained fear in humans elicit distinct activity in the extended amygdala, Neuroimage, 55, 389, 10.1016/j.neuroimage.2010.11.057 Baayen Bates Beauchamp, 2003, FMRI responses to video and point-light displays of moving humans and manipulable objects, J. Cogn. Neurosci., 15, 991, 10.1162/089892903770007380 Bernal-Rusiel, 2012, Statistical analysis of longitudinal neuroimage data with linear mixed effects models, Neuroimage, 66, 249, 10.1016/j.neuroimage.2012.10.065 Britton, J.C., Grillon, C., Lissek, S., Norcross, M.A., Szuhany, K.L., Chen, G., Ernst, M., Nelson, E.E., Leibenluft, E., Shechner, T., Pine, D.S., under review. Response to learned threat: an fMRI study in adolescent and adult anxiety. Chen, 2012, FMRI group analysis combining effect estimates and their variances, Neuroimage, 60, 747, 10.1016/j.neuroimage.2011.12.060 Cohen, 1997, Parametric analysis of fMRI data using linear systems methods, Neuroimage, 6, 93, 10.1006/nimg.1997.0278 Conner, 2011, Variability of the relationship between electrophysiology and BOLD-fMRI across cortical regions in humans, J. Neurosci., 31, 12855, 10.1523/JNEUROSCI.1457-11.2011 Cox, 1996, AFNI: software for analysis and visualization of functional magnetic resonance neuroimages, Comput. Biomed. Res., 29, 162, 10.1006/cbmr.1996.0014 Crowder, 1990 Demidenko, 2004 Falconer, 1996 Geier, 2007, Circuitry underlying temporally extended spatial working memory, Neuroimage, 35, 904, 10.1016/j.neuroimage.2006.12.022 Gelman, 2005, Analysis of variance — why it is more important than ever, Ann. Stat., 33, 1, 10.1214/009053604000001048 Glaser, 2007, Covariance components. Statistical Parametric Mapping Halekoh, U., Højsgaard, S., in press. A Kenward-Roger approximation and parametric bootstrap methods for tests in linear mixed models — the R package pbkrtest. J. Stat. Softw. Handwerker, 2004, Variation of BOLD hemodynamic responses across subjects and brain regions and their effects on statistical analyses, Neuroimage, 21, 1639, 10.1016/j.neuroimage.2003.11.029 Henson, 2007, Convolution models for fMRI Henson, 2002, Detecting latency differences in event-related BOLD responses: application to words versus nonwords and initial versus repeated face presentations, Neuroimage, 15, 83, 10.1006/nimg.2001.0940 Kenward, 1997, Small sample inference for fixed effects from restricted maximum likelihood, Biometrics, 53, 983, 10.2307/2533558 Keselman, 2001, The analysis of repeated measures designs: a review, Br. J. Math. Stat. Psychol., 54, 1, 10.1348/000711001159357 Kuhn, M. with contributions from Steve Weston, Jed Wing and James Forester, 2011. Contrast: a collection of contrast methods. R package version 0.14. http://CRAN.R-project.org/package=contrast. Lazar, 2002, Combining brains: a survey of methods for statistical pooling of information, Neuroimage, 16, 538, 10.1006/nimg.2002.1107 Li, 2012, Twinmarm: two-stage spatial adaptive analysis of twin neuroimaging data, IEEE Trans. Med. Imaging, 31, 1100, 10.1109/TMI.2012.2185830 Little, 2002 McLaren, 2011, Repeated-measures designs overestimate between-subject effects in fMRI packages using one error term Min, 2012, Coexpression network analysis in abdominal and gluteal adipose tissue reveals regulatory genetic loci for metabolic syndrome and related phenotypes, PLoS Genet., 8, e1002505, 10.1371/journal.pgen.1002505 Neale, 1989, Fitting genetic models with LISREL: hypothesis testing, Behav. Genet., 19, 37, 10.1007/BF01065882 Nichols, 2005, Valid conjunction inference with the minimum statistic, Neuroimage, 25, 653, 10.1016/j.neuroimage.2004.12.005 Nicholson, 2011, Human metabolic profiles are stably controlled by genetic and environmental variation, Mol. Syst. Biol., 7, 525, 10.1038/msb.2011.57 Penny, 2007, Random effects analysis Pinheiro, 2000 Pinheiro, 2011, nlme: Linear and nonlinear mixed effects models 2012 2011 Rutherford, 2001 Saad, 2006, Functional imaging analysis contest (FIAC) analysis according to AFNI and SUMA, Hum. Brain Mapp., 27, 417, 10.1002/hbm.20247 Satterthwaite, 1946, An approximate distribution of estimates of variance components, Biometrics, 2, 110, 10.2307/3002019 Schafer, 1997 Shrout, 1979, Intraclass correlations: uses in assessing rater reliability, Psychol. Bull., 86, 420, 10.1037/0033-2909.86.2.420 Skaug, 2012, glmmADMB: generalized linear mixed models using AD model builder Skup, 2012, Multiscale adaptive marginal analysis of longitudinal neuroimaging data with time-varying covariates, Biometrics, 68, 1083, 10.1111/j.1541-0420.2012.01767.x Stoffers, 2012, Resting-state cognition is associated with resting-state network activation Tierney Vaden, 2012, Multiple imputation of missing fMRI data in whole brain analysis, Neuroimage, 60, 1843, 10.1016/j.neuroimage.2012.01.123 Venables Viechtbauer, 2007, Hypothesis tests for population heterogeneity in meta-analysis, Br. J. Math. Stat. Psychol., 60, 29, 10.1348/000711005X64042 Wang, 2011, Statistical inference in mixed models and analysis of twin and family data, Biometrics, 67, 987, 10.1111/j.1541-0420.2010.01548.x Weissman, 2006, The neural bases of momentary lapses in attention, Nat. Neurosci., 9, 971, 10.1038/nn1727 Woolrich, 2004, Multilevel linear modelling for FMRI group analysis using Bayesian inference, NeuroImage, 21, 1732, 10.1016/j.neuroimage.2003.12.023 Worsley, 2002, A general statistical analysis for fMRI data, NeuroImage, 15, 1, 10.1006/nimg.2001.0933 Yu, 2006, A unified mixed-model method for association mapping that accounts for multiple levels of relatedness, Nat. Genet., 38, 203, 10.1038/ng1702