Tau and atrophy: domain-specific relationships with cognition
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Emilie T. Reas | A. Dale | J. Brewer | E. Reas | S. Banks | L. Digma | John R. Madsen | J. Madsen | Leonardino A. Digma
[1] M M Mesulam,et al. Large‐scale neurocognitive networks and distributed processing for attention, language, and memory , 1990, Annals of neurology.
[2] Xiao-Li Meng,et al. Comparing correlated correlation coefficients , 1992 .
[3] A. Evans,et al. Correction for partial volume effects in PET: principle and validation. , 1998, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.
[4] Alan C. Evans,et al. A nonparametric method for automatic correction of intensity nonuniformity in MRI data , 1998, IEEE Transactions on Medical Imaging.
[5] A. Dale,et al. High‐resolution intersubject averaging and a coordinate system for the cortical surface , 1999, Human brain mapping.
[6] Anders M. Dale,et al. Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction , 1999, NeuroImage.
[7] A. Dale,et al. Cortical Surface-Based Analysis II: Inflation, Flattening, and a Surface-Based Coordinate System , 1999, NeuroImage.
[8] J. Aharon-Peretz,et al. Posterior Cortical Atrophy Variants of Alzheimer’s Disease , 1999, Dementia and Geriatric Cognitive Disorders.
[9] J. Kril,et al. Specific temporoparietal gyral atrophy reflects the pattern of language dissolution in Alzheimer's disease. , 1999, Brain : a journal of neurology.
[10] J. Grafman,et al. The calculating brain: an fMRI study , 2000, Neuropsychologia.
[11] Ivanei E. Bramati,et al. The cerebral correlates of set-shifting: an fMRI study of the trail making test. , 2002, Arquivos de neuro-psiquiatria.
[12] Hilde van der Togt,et al. Publisher's Note , 2003, J. Netw. Comput. Appl..
[13] D. Stuss,et al. California Verbal Learning Test: performance by patients with focal frontal and non-frontal lesions. , 2003, Brain : a journal of neurology.
[14] M. Mesulam,et al. Neurofibrillary tangles, amyloid, and memory in aging and mild cognitive impairment. , 2003, Archives of neurology.
[15] J. Morrison,et al. Tangle and neuron numbers, but not amyloid load, predict cognitive status in Alzheimer’s disease , 2003, Neurology.
[16] H. Braak,et al. Neuropathological stageing of Alzheimer-related changes , 2004, Acta Neuropathologica.
[17] Anders M. Dale,et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest , 2006, NeuroImage.
[18] Anders M. Dale,et al. Reliability in multi-site structural MRI studies: Effects of gradient non-linearity correction on phantom and human data , 2006, NeuroImage.
[19] Ayse Pinar Saygin,et al. Smoothing and cluster thresholding for cortical surface-based group analysis of fMRI data , 2006, NeuroImage.
[20] J B Poline,et al. Direct voxel-based comparison between grey matter hypometabolism and atrophy in Alzheimer's disease. , 2007, Brain : a journal of neurology.
[21] B. Miller,et al. Neurodegenerative Diseases Target Large-Scale Human Brain Networks , 2009, Neuron.
[22] J. Morris,et al. The Cortical Signature of Alzheimer's Disease: Regionally Specific Cortical Thinning Relates to Symptom Severity in Very Mild to Mild AD Dementia and is Detectable in Asymptomatic Amyloid-Positive Individuals , 2008, Cerebral cortex.
[23] Jeffrey A. Fessler,et al. Reducing between scanner differences in multi-center PET studies , 2009, NeuroImage.
[24] J. Morris,et al. Clinical core of the Alzheimer's disease neuroimaging initiative: Progress and plans , 2010, Alzheimer's & Dementia.
[25] C. Jack,et al. Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade , 2010, The Lancet Neurology.
[26] Cindee M. Madison,et al. Associations between cognitive, functional, and FDG-PET measures of decline in AD and MCI , 2011, Neurobiology of Aging.
[27] L. McEvoy,et al. Predicting MCI outcome with clinically available MRI and CSF biomarkers , 2011, Neurology.
[28] A. Dale,et al. Mild cognitive impairment: baseline and longitudinal structural MR imaging measures improve predictive prognosis. , 2011, Radiology.
[29] D. Salmon,et al. The neuropsychological profile of Alzheimer disease. , 2012, Cold Spring Harbor perspectives in medicine.
[30] W. Jagust,et al. Physical Activity and AD-Related Pathology-Reply. , 2012, Archives of neurology.
[31] K. Jellinger,et al. Correlation of Alzheimer Disease Neuropathologic Changes With Cognitive Status: A Review of the Literature , 2012, Journal of neuropathology and experimental neurology.
[32] W. Jagust,et al. Association of lifetime cognitive engagement and low β-amyloid deposition. , 2012, Archives of neurology.
[33] G. Chételat,et al. Region-Specific Hierarchy between Atrophy, Hypometabolism, and β-Amyloid (Aβ) Load in Alzheimer's Disease Dementia , 2012, The Journal of Neuroscience.
[34] C. Jack,et al. Tracking pathophysiological processes in Alzheimer's disease: an updated hypothetical model of dynamic biomarkers , 2013, The Lancet Neurology.
[35] H. Kolb,et al. [18F]T807, a novel tau positron emission tomography imaging agent for Alzheimer's disease , 2013, Alzheimer's & Dementia.
[36] Cindee M. Madison,et al. Diverging patterns of amyloid deposition and hypometabolism in clinical variants of probable Alzheimer's disease. , 2013, Brain : a journal of neurology.
[37] T. Hedden,et al. Meta-analysis of amyloid-cognition relations in cognitively normal older adults , 2013, Neurology.
[38] Cindee M. Madison,et al. Intrinsic connectivity networks in healthy subjects explain clinical variability in Alzheimer’s disease , 2013, Proceedings of the National Academy of Sciences.
[39] D. Fair,et al. Hemispheric lateralization of verbal and spatial working memory during adolescence , 2013, Brain and Cognition.
[40] C. Jack,et al. Update on hypothetical model of Alzheimer's disease biomarkers , 2013, Alzheimer's & Dementia.
[41] M. Mintun,et al. Amyloid-β Imaging with Pittsburgh Compound B and Florbetapir: Comparing Radiotracers and Quantification Methods , 2013, The Journal of Nuclear Medicine.
[42] Bruce R. Rosen,et al. Cortical surface-based analysis reduces bias and variance in kinetic modeling of brain PET data , 2014, NeuroImage.
[43] Keith A. Johnson,et al. Validating novel tau positron emission tomography tracer [F‐18]‐AV‐1451 (T807) on postmortem brain tissue , 2015, Annals of neurology.
[44] R. Sperling,et al. Bayesian model reveals latent atrophy factors with dissociable cognitive trajectories in Alzheimer’s disease , 2016, Proceedings of the National Academy of Sciences.
[45] A. Joshi,et al. Regional profiles of the candidate tau PET ligand 18F-AV-1451 recapitulate key features of Braak histopathological stages. , 2016, Brain : a journal of neurology.
[46] D. Spencer,et al. Imaging synaptic density in the living human brain , 2016, Science Translational Medicine.
[47] Steen Moeller,et al. The Human Connectome Project's neuroimaging approach , 2016, Nature Neuroscience.
[48] Daniel R. Schonhaut,et al. PET Imaging of Tau Deposition in the Aging Human Brain , 2016, Neuron.
[49] Talakad G. Lohith,et al. Preclinical Characterization of 18F-MK-6240, a Promising PET Tracer for In Vivo Quantification of Human Neurofibrillary Tangles , 2016, The Journal of Nuclear Medicine.
[50] Keith A. Johnson,et al. A/T/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers , 2016, Neurology.
[51] Hanna Cho,et al. Tau PET in Alzheimer disease and mild cognitive impairment , 2016, Neurology.
[52] Daniel R. Schonhaut,et al. Tau PET patterns mirror clinical and neuroanatomical variability in Alzheimer's disease. , 2016, Brain : a journal of neurology.
[53] W. Jagust,et al. Considerations and code for partial volume correcting [18F]-AV-1451 tau PET data , 2017, Data in brief.
[54] Daniel R. Schonhaut,et al. Tau pathology and neurodegeneration contribute to cognitive impairment in Alzheimer’s disease , 2017, Brain : a journal of neurology.
[55] M. Weiner,et al. Association Between Elevated Brain Amyloid and Subsequent Cognitive Decline Among Cognitively Normal Persons , 2017, JAMA.
[56] O. Hansson,et al. Tau Pathology Distribution in Alzheimer's disease Corresponds Differentially to Cognition-Relevant Functional Brain Networks , 2017, Frontiers in Neuroscience.
[57] J. Cummings,et al. Alzheimer's disease drug development pipeline: 2017 , 2017, Alzheimer's & dementia.
[58] Keith A. Johnson,et al. Lessons learned about [F-18]-AV-1451 off-target binding from an autopsy-confirmed Parkinson’s case , 2017, Acta Neuropathologica Communications.
[59] J. Morris,et al. The Alzheimer's Disease Neuroimaging Initiative 3: Continued innovation for clinical trial improvement , 2017, Alzheimer's & Dementia.
[60] Alexander Kmentt. 2017 , 2018, The Treaty Prohibiting Nuclear Weapons.
[61] J. Phillips,et al. Tau PET imaging predicts cognition in atypical variants of Alzheimer's disease , 2018, Human brain mapping.
[62] M. Citron,et al. The tau positron‐emission tomography tracer AV‐1451 binds with similar affinities to tau fibrils and monoamine oxidases , 2018, Movement disorders : official journal of the Movement Disorder Society.
[63] O. Hansson,et al. ASSOCIATIONS BETWEEN TAU, Aβ AND CORTICAL THICKNESS WITH COGNITION IN ALZHEIMER’S DISEASE , 2018, Alzheimer's & Dementia.
[64] D. Y. Lee,et al. Association of Cerebral Amyloid-&bgr; Aggregation With Cognitive Functioning in Persons Without Dementia , 2018, JAMA psychiatry.
[65] C. Jack,et al. NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease , 2018, Alzheimer's & Dementia.
[66] J. Brewer,et al. Combined Biomarker Prognosis of Mild Cognitive Impairment: An 11-Year Follow-Up Study in the Alzheimer's Disease Neuroimaging Initiative. , 2019, Journal of Alzheimer's disease : JAD.
[67] Patrick J. Lao,et al. Letter and Category Fluency Performance Correlates with Distinct Patterns of Cortical Thickness in Older Adults. , 2019, Cerebral cortex.
[68] Philip S. Insel,et al. Associations between tau, Aβ, and cortical thickness with cognition in Alzheimer disease , 2019, Neurology.
[69] J. Cummings,et al. Repurposed agents in the Alzheimer’s disease drug development pipeline , 2020, Alzheimer's Research & Therapy.