Tau and atrophy: domain-specific relationships with cognition

[1]  J. Cummings,et al.  Repurposed agents in the Alzheimer’s disease drug development pipeline , 2020, Alzheimer's Research & Therapy.

[2]  Patrick J. Lao,et al.  Letter and Category Fluency Performance Correlates with Distinct Patterns of Cortical Thickness in Older Adults. , 2019, Cerebral cortex.

[3]  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.

[4]  Philip S. Insel,et al.  Associations between tau, Aβ, and cortical thickness with cognition in Alzheimer disease , 2019, Neurology.

[5]  C. Jack,et al.  NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease , 2018, Alzheimer's & Dementia.

[6]  J. Phillips,et al.  Tau PET imaging predicts cognition in atypical variants of Alzheimer's disease , 2018, Human brain mapping.

[7]  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.

[8]  D. Y. Lee,et al.  Association of Cerebral Amyloid-&bgr; Aggregation With Cognitive Functioning in Persons Without Dementia , 2018, JAMA psychiatry.

[9]  Daniel R. Schonhaut,et al.  Tau pathology and neurodegeneration contribute to cognitive impairment in Alzheimer’s disease , 2017, Brain : a journal of neurology.

[10]  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.

[11]  W. Jagust,et al.  Considerations and code for partial volume correcting [18F]-AV-1451 tau PET data , 2017, Data in brief.

[12]  M. Weiner,et al.  Association Between Elevated Brain Amyloid and Subsequent Cognitive Decline Among Cognitively Normal Persons , 2017, JAMA.

[13]  J. Cummings,et al.  Alzheimer's disease drug development pipeline: 2017 , 2017, Alzheimer's & dementia.

[14]  J. Morris,et al.  The Alzheimer's Disease Neuroimaging Initiative 3: Continued innovation for clinical trial improvement , 2017, Alzheimer's & Dementia.

[15]  O. Hansson,et al.  Tau Pathology Distribution in Alzheimer's disease Corresponds Differentially to Cognition-Relevant Functional Brain Networks , 2017, Frontiers in Neuroscience.

[16]  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.

[17]  Steen Moeller,et al.  The Human Connectome Project's neuroimaging approach , 2016, Nature Neuroscience.

[18]  Keith A. Johnson,et al.  A/T/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers , 2016, Neurology.

[19]  Hanna Cho,et al.  Tau PET in Alzheimer disease and mild cognitive impairment , 2016, Neurology.

[20]  D. Spencer,et al.  Imaging synaptic density in the living human brain , 2016, Science Translational Medicine.

[21]  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.

[22]  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.

[23]  Daniel R. Schonhaut,et al.  Tau PET patterns mirror clinical and neuroanatomical variability in Alzheimer's disease. , 2016, Brain : a journal of neurology.

[24]  Daniel R. Schonhaut,et al.  PET Imaging of Tau Deposition in the Aging Human Brain , 2016, Neuron.

[25]  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.

[26]  Bruce R. Rosen,et al.  Cortical surface-based analysis reduces bias and variance in kinetic modeling of brain PET data , 2014, NeuroImage.

[27]  H. Kolb,et al.  [18F]T807, a novel tau positron emission tomography imaging agent for Alzheimer's disease , 2013, Alzheimer's & Dementia.

[28]  C. Jack,et al.  Update on hypothetical model of Alzheimer's disease biomarkers , 2013, Alzheimer's & Dementia.

[29]  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.

[30]  D. Fair,et al.  Hemispheric lateralization of verbal and spatial working memory during adolescence , 2013, Brain and Cognition.

[31]  T. Hedden,et al.  Meta-analysis of amyloid-cognition relations in cognitively normal older adults , 2013, Neurology.

[32]  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.

[33]  C. Jack,et al.  Tracking pathophysiological processes in Alzheimer's disease: an updated hypothetical model of dynamic biomarkers , 2013, The Lancet Neurology.

[34]  M. Mintun,et al.  Amyloid-β Imaging with Pittsburgh Compound B and Florbetapir: Comparing Radiotracers and Quantification Methods , 2013, The Journal of Nuclear Medicine.

[35]  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.

[36]  W. Jagust,et al.  Physical Activity and AD-Related Pathology-Reply. , 2012, Archives of neurology.

[37]  W. Jagust,et al.  Association of lifetime cognitive engagement and low β-amyloid deposition. , 2012, Archives of neurology.

[38]  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.

[39]  D. Salmon,et al.  The neuropsychological profile of Alzheimer disease. , 2012, Cold Spring Harbor perspectives in medicine.

[40]  L. McEvoy,et al.  Predicting MCI outcome with clinically available MRI and CSF biomarkers , 2011, Neurology.

[41]  Cindee M. Madison,et al.  Associations between cognitive, functional, and FDG-PET measures of decline in AD and MCI , 2011, Neurobiology of Aging.

[42]  A. Dale,et al.  Mild cognitive impairment: baseline and longitudinal structural MR imaging measures improve predictive prognosis. , 2011, Radiology.

[43]  J. Morris,et al.  Clinical core of the Alzheimer's disease neuroimaging initiative: Progress and plans , 2010, Alzheimer's & Dementia.

[44]  C. Jack,et al.  Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade , 2010, The Lancet Neurology.

[45]  Jeffrey A. Fessler,et al.  Reducing between scanner differences in multi-center PET studies , 2009, NeuroImage.

[46]  B. Miller,et al.  Neurodegenerative Diseases Target Large-Scale Human Brain Networks , 2009, Neuron.

[47]  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.

[48]  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.

[49]  Ayse Pinar Saygin,et al.  Smoothing and cluster thresholding for cortical surface-based group analysis of fMRI data , 2006, NeuroImage.

[50]  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.

[51]  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.

[52]  H. Braak,et al.  Neuropathological stageing of Alzheimer-related changes , 2004, Acta Neuropathologica.

[53]  D. Stuss,et al.  California Verbal Learning Test: performance by patients with focal frontal and non-frontal lesions. , 2003, Brain : a journal of neurology.

[54]  J. Morrison,et al.  Tangle and neuron numbers, but not amyloid load, predict cognitive status in Alzheimer’s disease , 2003, Neurology.

[55]  M. Mesulam,et al.  Neurofibrillary tangles, amyloid, and memory in aging and mild cognitive impairment. , 2003, Archives of neurology.

[56]  Hilde van der Togt,et al.  Publisher's Note , 2003, J. Netw. Comput. Appl..

[57]  Ivanei E. Bramati,et al.  The cerebral correlates of set-shifting: an fMRI study of the trail making test. , 2002, Arquivos de neuro-psiquiatria.

[58]  J. Grafman,et al.  The calculating brain: an fMRI study , 2000, Neuropsychologia.

[59]  J. Aharon-Peretz,et al.  Posterior Cortical Atrophy Variants of Alzheimer’s Disease , 1999, Dementia and Geriatric Cognitive Disorders.

[60]  J. Kril,et al.  Specific temporoparietal gyral atrophy reflects the pattern of language dissolution in Alzheimer's disease. , 1999, Brain : a journal of neurology.

[61]  A. Dale,et al.  Cortical Surface-Based Analysis II: Inflation, Flattening, and a Surface-Based Coordinate System , 1999, NeuroImage.

[62]  Anders M. Dale,et al.  Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction , 1999, NeuroImage.

[63]  A. Dale,et al.  High‐resolution intersubject averaging and a coordinate system for the cortical surface , 1999, Human brain mapping.

[64]  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.

[65]  Alan C. Evans,et al.  A nonparametric method for automatic correction of intensity nonuniformity in MRI data , 1998, IEEE Transactions on Medical Imaging.

[66]  Xiao-Li Meng,et al.  Comparing correlated correlation coefficients , 1992 .

[67]  M M Mesulam,et al.  Large‐scale neurocognitive networks and distributed processing for attention, language, and memory , 1990, Annals of neurology.