An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data
Tài liệu tham khảo
Akaike, 1974, A new look at the statistical model identification, IEEE Trans. Autom. Control, 19, 716, 10.1109/TAC.1974.1100705
Auer, 2008, Spontaneous low-frequency blood oxygenation level-dependent fluctuations and functional connectivity analysis of the 'resting' brain, Magn. Reson. Imaging, 26, 1055, 10.1016/j.mri.2008.05.008
Behzadi, 2007, A component based noise correction method (CompCor) for BOLD and perfusion based fMRI, Neuroimage, 37, 90, 10.1016/j.neuroimage.2007.04.042
Birn, 2006, Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI, Neuroimage, 31, 1536, 10.1016/j.neuroimage.2006.02.048
Biswal, 1995, Functional connectivity in the motor cortex of resting human brain using echo-planar MRI, Magn. Reson. Med., 34, 537, 10.1002/mrm.1910340409
Biswal, 2010, Toward discovery science of human brain function, Proc. Natl. Acad. Sci. U. S. A., 107, 4734, 10.1073/pnas.0911855107
Bullmore, 1999, Methods for diagnosis and treatment of stimulus-correlated motion in generic brain activation studies using fMRI, Hum. Brain Mapp., 7, 38, 10.1002/(SICI)1097-0193(1999)7:1<38::AID-HBM4>3.0.CO;2-Q
Carp, 2011, Optimizing the order of operations for movement scrubbing: comment on Power et al., Neuroimage
Chai, 2011, Abnormal medial prefrontal cortex resting-state connectivity in bipolar disorder and schizophrenia, Neuropsychopharmacology, 36, 2009, 10.1038/npp.2011.88
Chang, 2009, Effects of model-based physiological noise correction on default mode network anti-correlations and correlations, Neuroimage, 47, 1448, 10.1016/j.neuroimage.2009.05.012
Church, 2010, The “Task B problem” and other considerations in developmental functional neuroimaging, Hum. Brain Mapp., 31, 852, 10.1002/hbm.21036
Churchill, 2012, Optimizing preprocessing and analysis pipelines for single-subject fMRI. I. Standard temporal motion and physiological noise correction methods, Hum. Brain Mapp., 33, 609, 10.1002/hbm.21238
Churchill, 2012, Optimizing preprocessing and analysis pipelines for single-subject fMRI: 2. Interactions with ICA, PCA, task contrast and inter-subject heterogeneity, PLoS One, 7, e31147, 10.1371/journal.pone.0031147
Cordes, 2001, Frequencies contributing to functional connectivity in the cerebral cortex in “resting-state” data, AJNR Am. J. Neuroradiol., 22, 1326
D'Angelo, 2011, A generalized estimating equations approach for resting-state functional MRI group analysis, Conf. Proc. IEEE Eng. Med. Biol. Soc., 2011, 5064
Diedrichsen, 2005, Detecting and adjusting for artifacts in fMRI time series data, Neuroimage, 27, 624, 10.1016/j.neuroimage.2005.04.039
Dosenbach, 2010, Prediction of individual brain maturity using fMRI, Science, 329, 1358, 10.1126/science.1194144
Feinberg, 2010, Multiplexed echo planar imaging for sub-second whole brain FMRI and fast diffusion imaging, PLoS One, 5, e15710, 10.1371/journal.pone.0015710
Fox, 2010, Clinical applications of resting state functional connectivity, Front. Syst. Neurosci., 4, 19
Fox, 2007, Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging, Nat. Rev. Neurosci., 8, 700, 10.1038/nrn2201
Fox, 2005, The human brain is intrinsically organized into dynamic, anticorrelated functional networks, Proc. Natl. Acad. Sci. U. S. A., 102, 9673, 10.1073/pnas.0504136102
Fox, 2009, The global signal and observed anticorrelated resting state brain networks, J. Neurophysiol., 101, 3270, 10.1152/jn.90777.2008
Friston, 1996, Movement-related effects in fMRI time-series, Magn. Reson. Med., 35, 346, 10.1002/mrm.1910350312
Glahn, 2010, Genetic control over the resting brain, Proc. Natl. Acad. Sci. U. S. A., 107, 1223, 10.1073/pnas.0909969107
Glover, 2000, Image-based method for retrospective correction of physiological motion effects in fMRI: RETROICOR, Magn. Reson. Med., 44, 162, 10.1002/1522-2594(200007)44:1<162::AID-MRM23>3.0.CO;2-E
Guo, 2012, One-year test-retest reliability of intrinsic connectivity network fMRI in older adults, NeuroImage, 61, 1471, 10.1016/j.neuroimage.2012.03.027
Gur, 2012, Age group and sex differences in performance on a computerized neurocognitive battery in children age 8–21, Neuropsychology, 26, 251, 10.1037/a0026712
Jenkinson, 2002, Improved optimization for the robust and accurate linear registration and motion correction of brain images, Neuroimage, 17, 825, 10.1006/nimg.2002.1132
Johnstone, 2006, Motion correction and the use of motion covariates in multiple-subject fMRI analysis, Hum. Brain Mapp., 27, 779, 10.1002/hbm.20219
Jones, 2008, Integration of motion correction and physiological noise regression in fMRI, Neuroimage, 42, 582, 10.1016/j.neuroimage.2008.05.019
Lemieux, 2007, Modelling large motion events in fMRI studies of patients with epilepsy, Magn. Reson. Imaging, 25, 894, 10.1016/j.mri.2007.03.009
Luna, 2010, Methodological approaches in developmental neuroimaging studies, Hum. Brain Mapp., 31, 863, 10.1002/hbm.21073
Murphy, 2009, The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?, Neuroimage, 44, 893, 10.1016/j.neuroimage.2008.09.036
Niazy, 2011, Spectral characteristics of resting state networks, Prog. Brain Res., 193, 259, 10.1016/B978-0-444-53839-0.00017-X
Ollinger, 2009, The secret life of motion covariates, Neuroimage, 47, 122
Power, 2011, Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion, Neuroimage, 59, 2142, 10.1016/j.neuroimage.2011.10.018
Power, 2011, Functional network organization of the human brain, Neuron, 72, 665, 10.1016/j.neuron.2011.09.006
Power, 2012
Rubinov, 2011, Weight-conserving characterization of complex functional brain networks, Neuroimage, 56, 2068, 10.1016/j.neuroimage.2011.03.069
Satterthwaite, 2012, Impact of in-scanner head motion on multiple measures of functional connectivity: relevance for studies of neurodevelopment in youth, Neuroimage, 60, 623, 10.1016/j.neuroimage.2011.12.063
Satterthwaite, 2012, Being right is its own reward: load and performance related ventral striatum activation to correct responses during a working memory task in youth, Neuroimage, 61, 723, 10.1016/j.neuroimage.2012.03.060
Schöpf, 2010, Fully exploratory network ICA (FENICA) on resting-state fMRI data, J. Neurosci. Methods, 192, 207, 10.1016/j.jneumeth.2010.07.028
Schöpf, 2011, Model-free fMRI group analysis using FENICA, Neuroimage, 55, 185, 10.1016/j.neuroimage.2010.11.010
Seeley, 2009, Neurodegenerative diseases target large-scale human brain networks, Neuron, 62, 42, 10.1016/j.neuron.2009.03.024
Shmueli, 2007, Low-frequency fluctuations in the cardiac rate as a source of variance in the resting-state fMRI BOLD signal, Neuroimage, 38, 306, 10.1016/j.neuroimage.2007.07.037
Smith, 2002, Fast robust automated brain extraction, Hum. Brain Mapp., 17, 143, 10.1002/hbm.10062
Strother, 2002, The quantitative evaluation of functional neuroimaging experiments: the NPAIRS data analysis framework, Neuroimage, 15, 747, 10.1006/nimg.2001.1034
Tohka, 2008, Automatic independent component labeling for artifact removal in fMRI, Neuroimage, 39, 1227, 10.1016/j.neuroimage.2007.10.013
Tremblay, 2005, Retrospective coregistration of functional magnetic resonance imaging data using external monitoring, Magn. Reson. Med., 53, 141, 10.1002/mrm.20319
Van Dijk, 2010, Intrinsic functional connectivity as a tool for human connectomics: theory, properties, and optimization, J. Neurophysiol., 103, 297, 10.1152/jn.00783.2009
Van Dijk, 2011, The influence of head motion on intrinsic functional connectivity MRI, Neuroimage, 59, 431, 10.1016/j.neuroimage.2011.07.044
Van Essen, 2001, An integrated software suite for surface-based analyses of cerebral cortex, J. Am. Med. Inform. Assoc., 8, 443, 10.1136/jamia.2001.0080443
Weissenbacher, 2009, Correlations and anticorrelations in resting-state functional connectivity MRI: a quantitative comparison of preprocessing strategies, Neuroimage, 47, 1408, 10.1016/j.neuroimage.2009.05.005
Woolrich, 2009, Bayesian analysis of neuroimaging data in FSL, Neuroimage, 45, S173, 10.1016/j.neuroimage.2008.10.055
Yeo, 2011, The organization of the human cerebral cortex estimated by intrinsic functional connectivity, J. Neurophysiol., 106, 1125, 10.1152/jn.00338.2011
Zhang, 2001, Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm, IEEE Trans. Med. Imaging, 20, 45, 10.1109/42.906424
Zhang, 2009, Evaluation and optimization of fMRI single-subject processing pipelines with NPAIRS and second-level CVA, Magn. Reson. Imaging, 27, 264, 10.1016/j.mri.2008.05.021
Zhou, 2010, Divergent network connectivity changes in behavioural variant frontotemporal dementia and Alzheimer's disease, Brain, 133, 1352, 10.1093/brain/awq075
Zou, 2008, An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: fractional ALFF, J. Neurosci. Methods, 172, 137, 10.1016/j.jneumeth.2008.04.012
Zu Eulenburg, 2012, Meta-analytical definition and functional connectivity of the human vestibular cortex, Neuroimage, 60, 162, 10.1016/j.neuroimage.2011.12.032