Extending the Human Connectome Project across ages: Imaging protocols for the Lifespan Development and Aging projects
暂无分享,去创建一个
Thomas E. Nichols | Timothy S. Coalson | Stephen M. Smith | D. Marcus | D. V. Essen | R. Buckner | R. Woods | D. Barch | D. Greve | D. Salat | B. Fischl | G. Douaud | K. Uğurbil | A. Kouwe | E. Yacoub | J. Andersson | S. Jbabdi | G. C. Burgess | M. Harms | M. Glasser | Lilla Zöllei | S. Moeller | S. Bookheimer | Timothy Brown | E. Robinson | L. Somerville | B. Ances | M. Bastiani | M. Chappell | M. Dapretto | Cynthia Hodge | K. Jamison | S. Kandala | Xiufeng Li | R. Mair | S. Mangia | D. Mascali | S. Sotiropoulos | M. Terpstra | K. Thomas | M. Tisdall | Stephen M. Smith | D. C. Essen | Daniele Mascali
[1] Hui Zhang,et al. Imaging brain microstructure with diffusion MRI: practicality and applications , 2019, NMR in biomedicine.
[2] Essa Yacoub,et al. The Lifespan Human Connectome Project in Development: A large-scale study of brain connectivity development in 5–21 year olds , 2018, NeuroImage.
[3] J. Whitwell,et al. Alzheimer's disease neuroimaging , 2018, Current opinion in neurology.
[4] Thomas E. Nichols,et al. Statistical Challenges in “Big Data” Human Neuroimaging , 2018, Neuron.
[5] Stephen M. Smith,et al. Using temporal ICA to selectively remove global noise while preserving global signal in functional MRI data , 2017, NeuroImage.
[6] Hui Zhang,et al. Susceptibility-induced distortion that varies due to motion: Correction in diffusion MR without acquiring additional data , 2017, NeuroImage.
[7] Daniel Rueckert,et al. Multimodal surface matching with higher-order smoothness constraints , 2017, NeuroImage.
[8] Dustin Scheinost,et al. Influences on the Test–Retest Reliability of Functional Connectivity MRI and its Relationship with Behavioral Utility , 2017, Cerebral cortex.
[9] Abraham Z. Snyder,et al. Real-time motion analytics during brain MRI improve data quality and reduce costs , 2017, NeuroImage.
[10] B Fischl,et al. High-resolution magnetic resonance imaging reveals nuclei of the human amygdala: manual segmentation to automatic atlas , 2017, NeuroImage.
[11] R. Henson,et al. Challenges in measuring individual differences in functional connectivity using fMRI: The case of healthy aging , 2017, Human brain mapping.
[12] Hui Zhang,et al. Towards a comprehensive framework for movement and distortion correction of diffusion MR images: Within volume movement , 2017, NeuroImage.
[13] T. Paus,et al. Studying neuroanatomy using MRI , 2017, Nature Neuroscience.
[14] Timothy O. Laumann,et al. Sources and implications of whole-brain fMRI signals in humans , 2017, NeuroImage.
[15] Markus H. Sneve,et al. Relationship between structural and functional connectivity change across the adult lifespan: A longitudinal investigation , 2017 .
[16] Mario Pannunzi,et al. Resting-state fMRI correlations: From link-wise unreliability to whole brain stability , 2016, NeuroImage.
[17] Satrajit S. Ghosh,et al. BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods , 2016, bioRxiv.
[18] Evan M. Gordon,et al. On the Stability of BOLD fMRI Correlations , 2016, Cerebral cortex.
[19] T. Goldberg,et al. Cerebral blood flow measured by arterial spin labeling MRI at resting state in normal aging and Alzheimer’s disease , 2017, Neuroscience & Biobehavioral Reviews.
[20] P. Matthews,et al. Multimodal population brain imaging in the UK Biobank prospective epidemiological study , 2016, Nature Neuroscience.
[21] Steen Moeller,et al. The Human Connectome Project's neuroimaging approach , 2016, Nature Neuroscience.
[22] Jesper Andersson,et al. A multi-modal parcellation of human cerebral cortex , 2016, Nature.
[23] Satrajit S. Ghosh,et al. The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments , 2016, Scientific Data.
[24] Simon B Eickhoff,et al. Going Beyond Finding the "Lesion": A Path for Maturation of Neuroimaging. , 2016, The American journal of psychiatry.
[25] Bruce Fischl,et al. Joint reconstruction of white-matter pathways from longitudinal diffusion MRI data with anatomical priors , 2016, NeuroImage.
[26] M. Dylan Tisdall,et al. Prospective motion correction with volumetric navigators (vNavs) reduces the bias and variance in brain morphometry induced by subject motion , 2016, NeuroImage.
[27] Stamatios N. Sotiropoulos,et al. An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging , 2016, NeuroImage.
[28] Bruce R. Rosen,et al. MGH–USC Human Connectome Project datasets with ultra-high b-value diffusion MRI , 2016, NeuroImage.
[29] Jesper Andersson,et al. Changes in white matter microstructure in the developing brain—A longitudinal diffusion tensor imaging study of children from 4 to 11 years of age , 2016, NeuroImage.
[30] Robert Oostenveld,et al. ConnectomeDB—Sharing human brain connectivity data , 2016, NeuroImage.
[31] Daniel R Weinberger,et al. Finding the Elusive Psychiatric "Lesion" With 21st-Century Neuroanatomy: A Note of Caution. , 2015, The American journal of psychiatry.
[32] Chelsea C. Hays,et al. The Utility of Cerebral Blood Flow as a Biomarker of Preclinical Alzheimer’s Disease , 2016, Cellular and Molecular Neurobiology.
[33] Timothy E. J. Behrens,et al. Measuring macroscopic brain connections in vivo , 2015, Nature Neuroscience.
[34] Evan M. Gordon,et al. Functional System and Areal Organization of a Highly Sampled Individual Human Brain , 2015, Neuron.
[35] S. Nagarajan,et al. White Matter Changes of Neurite Density and Fiber Orientation Dispersion during Human Brain Maturation , 2015, PloS one.
[36] Yi Wang,et al. Multi-vendor reliability of arterial spin labeling perfusion MRI using a near-identical sequence: Implications for multi-center studies , 2015, NeuroImage.
[37] Koenraad Van Leemput,et al. A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI , 2015, NeuroImage.
[38] M. Dylan Tisdall,et al. Head motion during MRI acquisition reduces gray matter volume and thickness estimates , 2015, NeuroImage.
[39] Steen Moeller,et al. Theoretical and experimental evaluation of multi-band EPI for high-resolution whole brain pCASL Imaging , 2015, NeuroImage.
[40] M. Chakravarty,et al. Functional Consequences of Neurite Orientation Dispersion and Density in Humans across the Adult Lifespan , 2015, The Journal of Neuroscience.
[41] Bruce Fischl,et al. Gray matter myelination of 1555 human brains using partial volume corrected MRI images , 2015, NeuroImage.
[42] G. Zaharchuk,et al. Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: A consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia. , 2015, Magnetic resonance in medicine.
[43] Mark Jenkinson,et al. MSM: A new flexible framework for Multimodal Surface Matching , 2014, NeuroImage.
[44] Steen Moeller,et al. ICA-based artefact removal and accelerated fMRI acquisition for improved resting state network imaging , 2014, NeuroImage.
[45] Kawin Setsompop,et al. Interslice leakage artifact reduction technique for simultaneous multislice acquisitions , 2014, Magnetic resonance in medicine.
[46] Efstathios D. Gennatas,et al. Impact of puberty on the evolution of cerebral perfusion during adolescence , 2014, Proceedings of the National Academy of Sciences.
[47] Aart J. Nederveen,et al. Accuracy and precision of pseudo-continuous arterial spin labeling perfusion during baseline and hypercapnia: A head-to-head comparison with 15O H2O positron emission tomography , 2014, NeuroImage.
[48] H. Laufs,et al. Decoding Wakefulness Levels from Typical fMRI Resting-State Data Reveals Reliable Drifts between Wakefulness and Sleep , 2014, Neuron.
[49] Ludovica Griffanti,et al. Automatic denoising of functional MRI data: Combining independent component analysis and hierarchical fusion of classifiers , 2014, NeuroImage.
[50] Steen Moeller,et al. Evaluation of slice accelerations using multiband echo planar imaging at 3T , 2013, NeuroImage.
[51] Thomas E. Nichols,et al. Functional connectomics from resting-state fMRI , 2013, Trends in Cognitive Sciences.
[52] Steen Moeller,et al. Pushing spatial and temporal resolution for functional and diffusion MRI in the Human Connectome Project , 2013, NeuroImage.
[53] Steen Moeller,et al. Advances in diffusion MRI acquisition and processing in the Human Connectome Project , 2013, NeuroImage.
[54] Mark W. Woolrich,et al. Resting-state fMRI in the Human Connectome Project , 2013, NeuroImage.
[55] Julien Cohen-Adad,et al. Pushing the limits of in vivo diffusion MRI for the Human Connectome Project , 2013, NeuroImage.
[56] Abraham Z. Snyder,et al. Human Connectome Project informatics: Quality control, database services, and data visualization , 2013, NeuroImage.
[57] Essa Yacoub,et al. The WU-Minn Human Connectome Project: An overview , 2013, NeuroImage.
[58] Mark Jenkinson,et al. The minimal preprocessing pipelines for the Human Connectome Project , 2013, NeuroImage.
[59] Noah D. Brenowitz,et al. Integrated strategy for improving functional connectivity mapping using multiecho fMRI , 2013, Proceedings of the National Academy of Sciences.
[60] Whitney B. Pope,et al. Multi-delay multi-parametric arterial spin-labeled perfusion MRI in acute ischemic stroke — Comparison with dynamic susceptibility contrast enhanced perfusion imaging☆ , 2013, NeuroImage: Clinical.
[61] David H. Salat,et al. The Relationship between Cortical Blood Flow and Sub-Cortical White-Matter Health across the Adult Age Span , 2013, PloS one.
[62] Manuel Graña,et al. Model‐based analysis of multishell diffusion MR data for tractography: How to get over fitting problems , 2012, Magnetic resonance in medicine.
[63] Lars T. Westlye,et al. Network-specific effects of age and in-scanner subject motion: A resting-state fMRI study of 238 healthy adults , 2012, NeuroImage.
[64] Bruce Fischl,et al. Volumetric navigators for prospective motion correction and selective reacquisition in neuroanatomical MRI , 2012, Magnetic resonance in medicine.
[65] Bruce Fischl,et al. Within-subject template estimation for unbiased longitudinal image analysis , 2012, NeuroImage.
[66] Weiying Dai,et al. Reduced resolution transit delay prescan for quantitative continuous arterial spin labeling perfusion imaging , 2012, Magnetic resonance in medicine.
[67] B. Avants,et al. Longitudinal reproducibility and accuracy of pseudo-continuous arterial spin-labeled perfusion MR imaging in typically developing children. , 2012, Radiology.
[68] Wen-Ming Luh,et al. Differentiating BOLD and non-BOLD signals in fMRI time series using multi-echo EPI , 2012, NeuroImage.
[69] C. Lebel,et al. Diffusion tensor imaging of white matter tract evolution over the lifespan , 2012, NeuroImage.
[70] Mark A. Elliott,et al. Impact of in-scanner head motion on multiple measures of functional connectivity: Relevance for studies of neurodevelopment in youth , 2012, NeuroImage.
[71] D. V. van Essen,et al. Mapping Human Cortical Areas In Vivo Based on Myelin Content as Revealed by T1- and T2-Weighted MRI , 2011, The Journal of Neuroscience.
[72] R. Kraft,et al. 3D GRASE PROPELLER: Improved image acquisition technique for arterial spin labeling perfusion imaging , 2011, Magnetic resonance in medicine.
[73] Bruce Fischl,et al. Avoiding asymmetry-induced bias in longitudinal image processing , 2011, NeuroImage.
[74] Timothy O. Laumann,et al. Informatics and Data Mining Tools and Strategies for the Human Connectome Project , 2011, Front. Neuroinform..
[75] David H. Salat,et al. Age-associated reductions in cerebral blood flow are independent from regional atrophy , 2011, NeuroImage.
[76] D. Selkoe. Alzheimer's disease. , 2011, Cold Spring Harbor perspectives in biology.
[77] Stephen M. Smith,et al. Multiplexed Echo Planar Imaging for Sub-Second Whole Brain FMRI and Fast Diffusion Imaging , 2010, PloS one.
[78] Bruce Fischl,et al. Highly accurate inverse consistent registration: A robust approach , 2010, NeuroImage.
[79] A. Dale,et al. Life-span changes of the human brain white matter: diffusion tensor imaging (DTI) and volumetry. , 2010, Cerebral cortex.
[80] Matthias Günther,et al. Separation of macrovascular signal in multi‐inversion time arterial spin labelling MRI , 2010, Magnetic resonance in medicine.
[81] Mark W. Woolrich,et al. Variational Bayesian Inference for a Nonlinear Forward Model , 2020, IEEE Transactions on Signal Processing.
[82] Martin Blaimer,et al. General formulation for quantitative G‐factor calculation in GRAPPA reconstructions , 2009, Magnetic resonance in medicine.
[83] Catie Chang,et al. Influence of heart rate on the BOLD signal: The cardiac response function , 2009, NeuroImage.
[84] Jonathan Westley Peirce,et al. Neuroinformatics Original Research Article Generating Stimuli for Neuroscience Using Psychopy , 2022 .
[85] D. Alsop,et al. Continuous flow‐driven inversion for arterial spin labeling using pulsed radio frequency and gradient fields , 2008, Magnetic resonance in medicine.
[86] André J. W. van der Kouwe,et al. Brain morphometry with multiecho MPRAGE , 2008, NeuroImage.
[87] Lynne M Connelly,et al. Accuracy and precision. , 2008, Medsurg nursing : official journal of the Academy of Medical-Surgical Nurses.
[88] J. Detre,et al. A theoretical and experimental investigation of the tagging efficiency of pseudocontinuous arterial spin labeling , 2007, Magnetic resonance in medicine.
[89] Jonathan W. Peirce,et al. PsychoPy—Psychophysics software in Python , 2007, Journal of Neuroscience Methods.
[90] M. Tosetti,et al. Age dependence of cerebral perfusion assessed by magnetic resonance continuous arterial spin labeling , 2007, Journal of magnetic resonance imaging : JMRI.
[91] Mark W. Woolrich,et al. Probabilistic diffusion tractography with multiple fibre orientations: What can we gain? , 2007, NeuroImage.
[92] Daniel S. Marcus,et al. The extensible neuroimaging archive toolkit , 2007, Neuroinformatics.
[93] Timothy R. Olsen,et al. The Extensible Neuroimaging Archive Toolkit: an informatics platform for managing, exploring, and sharing neuroimaging data. , 2007, Neuroinformatics.
[94] Peter A. Bandettini,et al. Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI , 2006, NeuroImage.
[95] Oliver Speck,et al. Magnetic resonance imaging of freely moving objects: prospective real-time motion correction using an external optical motion tracking system , 2006, NeuroImage.
[96] D. Feinberg,et al. Single‐shot 3D imaging techniques improve arterial spin labeling perfusion measurements , 2005, Magnetic resonance in medicine.
[97] P. Tofts,et al. Normal cerebral perfusion measurements using arterial spin labeling: Reproducibility, stability, and age and gender effects , 2004, Magnetic resonance in medicine.
[98] F A Jolesz,et al. Optimized single-slab three-dimensional spin-echo MR imaging of the brain. , 2000, Radiology.
[99] S Thesen,et al. Prospective acquisition correction for head motion with image‐based tracking for real‐time fMRI , 2000, Magnetic resonance in medicine.
[100] G H Glover,et al. Image‐based method for retrospective correction of physiological motion effects in fMRI: RETROICOR , 2000, Magnetic resonance in medicine.
[101] S. Posse,et al. Enhancement of BOLD‐contrast sensitivity by single‐shot multi‐echo functional MR imaging , 1999, Magnetic resonance in medicine.
[102] Hitoshi Shinotoh,et al. Human cerebral acetylcholinesterase activity measured with positron emission tomography: procedure, normal values and effect of age , 1999, European Journal of Nuclear Medicine.
[103] P. Hutchins,et al. The microcirculation in experimental hypertension and aging. , 1996, Cardiovascular research.
[104] J. Hogg. Magnetic resonance imaging. , 1994, Journal of the Royal Naval Medical Service.
[105] On the Stability of , 1994 .
[106] Donald S. Williams,et al. Perfusion imaging , 1992, Magnetic resonance in medicine.
[107] J. Mugler,et al. Three‐dimensional magnetization‐prepared rapid gradient‐echo imaging (3D MP RAGE) , 1990, Magnetic resonance in medicine.
[108] Richard S. J. Frackowiak,et al. Cerebral blood flow, blood volume and oxygen utilization. Normal values and effect of age. , 1990, Brain : a journal of neurology.