Altered network stability in progressive supranuclear palsy

[1]  Luke J. Chang,et al.  Movie viewing elicits rich and reliable brain state dynamics , 2020, Nature Communications.

[2]  John L. Robinson,et al.  Distribution patterns of tau pathology in progressive supranuclear palsy , 2020, Acta Neuropathologica.

[3]  T. Robbins,et al.  Locus coeruleus pathology in progressive supranuclear palsy, and its relation to disease severity , 2020, Acta Neuropathologica Communications.

[4]  J. Klein,et al.  Diagnosis Across the Spectrum of Progressive Supranuclear Palsy and Corticobasal Syndrome , 2019, JAMA neurology.

[5]  D. Vidaurre,et al.  Behavioural relevance of spontaneous, transient brain network interactions in fMRI , 2019, NeuroImage.

[6]  M. Murray,et al.  Neuropathologic basis of frontotemporal dementia in progressive supranuclear palsy , 2019, Movement disorders : official journal of the Movement Disorder Society.

[7]  J. Shine Neuromodulatory Influences on Integration and Segregation in the Brain , 2019, Trends in Cognitive Sciences.

[8]  Oluwasanmi Koyejo,et al.  Human cognition involves the dynamic integration of neural activity and neuromodulatory systems , 2019, Nature Neuroscience.

[9]  Russell A. Poldrack,et al.  Catecholaminergic manipulation alters dynamic network topology across cognitive states , 2018, Network Neuroscience.

[10]  C. Peng,et al.  A Strategy to Reduce Bias of Entropy Estimates in Resting-State fMRI Signals , 2018, Front. Neurosci..

[11]  Yihong Yang,et al.  Neurophysiological Basis of Multi-Scale Entropy of Brain Complexity and Its Relationship With Functional Connectivity , 2018, Front. Neurosci..

[12]  Ilya E. Monosov,et al.  The Basal Forebrain Regulates Global Resting-State fMRI Fluctuations , 2018, Neuron.

[13]  J. Rowe,et al.  Neurotransmitter deficits from frontotemporal lobar degeneration , 2018, Brain : a journal of neurology.

[14]  Yoed N. Kenett,et al.  Robust prediction of individual creative ability from brain functional connectivity , 2018, Proceedings of the National Academy of Sciences.

[15]  Stephen M. Smith,et al.  Brain network dynamics are hierarchically organized in time , 2017, Proceedings of the National Academy of Sciences.

[16]  Jesse A. Brown,et al.  Advancing functional dysconnectivity and atrophy in progressive supranuclear palsy , 2017, NeuroImage: Clinical.

[17]  Mark W. Woolrich,et al.  Discovering dynamic brain networks from big data in rest and task , 2017, NeuroImage.

[18]  Murray Grossman,et al.  Clinical diagnosis of progressive supranuclear palsy: The movement disorder society criteria , 2017, Movement disorders : official journal of the Movement Disorder Society.

[19]  D. Lulé,et al.  Intrinsic functional connectivity alterations in progressive supranuclear palsy: Differential effects in frontal cortex, motor, and midbrain networks , 2017, Movement disorders : official journal of the Movement Disorder Society.

[20]  C. Beckmann,et al.  Using Dual Regression to Investigate Network Shape and Amplitude in Functional Connectivity Analyses , 2017, Front. Neurosci..

[21]  Vince D. Calhoun,et al.  Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls , 2017, NeuroImage.

[22]  Gustavo Deco,et al.  The dynamics of resting fluctuations in the brain: metastability and its dynamical cortical core , 2016, bioRxiv.

[23]  Thomas E. Nichols,et al.  Scanning the horizon: towards transparent and reproducible neuroimaging research , 2016, Nature Reviews Neuroscience.

[24]  Evan M. Gordon,et al.  On the Stability of BOLD fMRI Correlations , 2016, Cerebral cortex.

[25]  Edward T. Bullmore,et al.  Small-World Brain Networks Revisited , 2016, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[26]  Yu Zhang,et al.  The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture , 2016, Cerebral cortex.

[27]  A. Investigators Predicting disease progression in progressive supranuclear palsy in multicenter clinical trials , 2016 .

[28]  Markus Werkle-Bergner,et al.  On the estimation of brain signal entropy from sparse neuroimaging data , 2016, Scientific Reports.

[29]  Gustavo Deco,et al.  Can sliding-window correlations reveal dynamic functional connectivity in resting-state fMRI? , 2016, NeuroImage.

[30]  M. Chun,et al.  A neuromarker of sustained attention from whole-brain functional connectivity , 2015, Nature Neuroscience.

[31]  Federico E. Turkheimer,et al.  The brain's code and its canonical computational motifs. From sensory cortex to the default mode network: A multi-scale model of brain function in health and disease , 2015, Neuroscience & Biobehavioral Reviews.

[32]  Norbert Schuff,et al.  Bayesian segmentation of brainstem structures in MRI , 2015, NeuroImage.

[33]  Yasser Ghanbari,et al.  Joint Analysis of Band-Specific Functional Connectivity and Signal Complexity in Autism , 2015, Journal of autism and developmental disorders.

[34]  V. Calhoun,et al.  The Chronnectome: Time-Varying Connectivity Networks as the Next Frontier in fMRI Data Discovery , 2014, Neuron.

[35]  John Suckling,et al.  A wavelet method for modeling and despiking motion artifacts from resting-state fMRI time series , 2014, NeuroImage.

[36]  Jonathan D. Power,et al.  Intrinsic and Task-Evoked Network Architectures of the Human Brain , 2014, Neuron.

[37]  Jean M. Vettel,et al.  Controllability of structural brain networks , 2014, Nature Communications.

[38]  Danny J. J. Wang,et al.  Multiple time scale complexity analysis of resting state FMRI , 2013, Brain Imaging and Behavior.

[39]  Stephen M. Smith,et al.  Permutation inference for the general linear model , 2014, NeuroImage.

[40]  J. Hodges,et al.  Cognition in corticobasal syndrome and progressive supranuclear palsy: A review , 2014, Movement disorders : official journal of the Movement Disorder Society.

[41]  Ian M. McDonough,et al.  Network complexity as a measure of information processing across resting-state networks: evidence from the Human Connectome Project , 2014, Front. Hum. Neurosci..

[42]  J. Olszewski,et al.  Progressive Supranuclear Palsy: A Heterogeneous Degeneration Involving the Brain Stem, Basal Ganglia and Cerebellum With Vertical Gaze and Pseudobulbar Palsy, Nuchal Dystonia and Dementia , 2014, Seminars in Neurology.

[43]  Zeshan Ahmed,et al.  A novel in vivo model of tau propagation with rapid and progressive neurofibrillary tangle pathology: the pattern of spread is determined by connectivity, not proximity , 2014, Acta Neuropathologica.

[44]  A. Lees,et al.  Characteristics of progressive supranuclear palsy presenting with corticobasal syndrome: a cortical variant , 2014, Neuropathology and applied neurobiology.

[45]  J. Kelso,et al.  The Metastable Brain , 2014, Neuron.

[46]  Angela R. Laird,et al.  ICA model order selection of task co-activation networks , 2013, Front. Neurosci..

[47]  John R. Hodges,et al.  Validation of the Addenbrooke's Cognitive Examination III in Frontotemporal Dementia and Alzheimer's Disease , 2013, Dementia and Geriatric Cognitive Disorders.

[48]  Jonathan D. Cohen,et al.  The effects of neural gain on attention and learning , 2013, Nature Neuroscience.

[49]  Andrew Trujillo,et al.  Intrinsic connectivity network disruption in progressive supranuclear palsy , 2013, Annals of neurology.

[50]  Vasily A. Vakorin,et al.  Spatiotemporal Dependency of Age-Related Changes in Brain Signal Variability , 2013, Cerebral cortex.

[51]  P. Tu,et al.  Complexity of spontaneous BOLD activity in default mode network is correlated with cognitive function in normal male elderly: a multiscale entropy analysis , 2013, Neurobiology of Aging.

[52]  Karl J. Friston,et al.  Perception and self-organized instability , 2012, Front. Comput. Neurosci..

[53]  Abraham Z. Snyder,et al.  Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion , 2012, NeuroImage.

[54]  Clifford R. Jack,et al.  Disrupted thalamocortical connectivity in PSP: a resting-state fMRI, DTI, and VBM study. , 2011, Parkinsonism & related disorders.

[55]  A. Snyder,et al.  Longitudinal analysis of neural network development in preterm infants. , 2010, Cerebral cortex.

[56]  Stephen M Smith,et al.  Correspondence of the brain's functional architecture during activation and rest , 2009, Proceedings of the National Academy of Sciences.

[57]  Martin Beibel,et al.  Transmission and spreading of tauopathy in transgenic mouse brain , 2009, Nature Cell Biology.

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

[59]  Olaf Sporns,et al.  Network structure of cerebral cortex shapes functional connectivity on multiple time scales , 2007, Proceedings of the National Academy of Sciences.

[60]  L. Golbe,et al.  A clinical rating scale for progressive supranuclear palsy. , 2007, Brain : a journal of neurology.

[61]  Edward T. Bullmore,et al.  Efficiency and Cost of Economical Brain Functional Networks , 2007, PLoS Comput. Biol..

[62]  John R Hodges,et al.  The Addenbrooke's Cognitive Examination Revised (ACE‐R): a brief cognitive test battery for dementia screening , 2006, International journal of geriatric psychiatry.

[63]  B. Boeve,et al.  Increased tau burden in the cortices of progressive supranuclear palsy presenting with corticobasal syndrome , 2005, Movement disorders : official journal of the Movement Disorder Society.

[64]  Madalena Costa,et al.  Multiscale entropy analysis of biological signals. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[65]  J. Richman,et al.  Physiological time-series analysis using approximate entropy and sample entropy. , 2000, American journal of physiology. Heart and circulatory physiology.

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

[67]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[68]  A L Goldberger,et al.  Physiological time-series analysis: what does regularity quantify? , 1994, The American journal of physiology.

[69]  Bruce H. Morimoto,et al.  Predicting disease progression in progressive supranuclear palsy in multicenter clinical trials. , 2016, Parkinsonism & related disorders.

[70]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[71]  Aric Hagberg,et al.  Exploring Network Structure, Dynamics, and Function using NetworkX , 2008 .

[72]  Ronald C. Duncan,et al.  A robust prediction , 1997 .