Subcortical-cortical dynamical states of the human brain and their breakdown in stroke

[1]  M. Corbetta,et al.  The secret life of predictive brains: what’s spontaneous activity for? , 2021, Trends in Cognitive Sciences.

[2]  S. Ganguli,et al.  Coupling of activity, metabolism and behaviour across the Drosophila brain , 2021, Nature.

[3]  Lorenzo Pini,et al.  A low-dimensional structure of neurological impairment in stroke , 2021, Brain communications.

[4]  O. Wu,et al.  Abnormal dynamic functional connectivity is linked to recovery after acute ischemic stroke , 2021, Human brain mapping.

[5]  Jingliang Cheng,et al.  An imbalance between functional segregation and integration in patients with pontine stroke: A dynamic functional network connectivity study , 2020, NeuroImage: Clinical.

[6]  Farnaz Zamani Esfahlani,et al.  Edge-centric functional network representations of human cerebral cortex reveal overlapping system-level architecture , 2020, Nature Neuroscience.

[7]  Olaf Sporns,et al.  Dynamic expression of brain functional systems disclosed by fine-scale analysis of edge time series , 2020, bioRxiv.

[8]  Maurizio Corbetta,et al.  Post-stroke deficit prediction from lesion and indirect structural and functional disconnection. , 2020, Brain : a journal of neurology.

[9]  V. Calhoun,et al.  Acute ischaemic stroke alters the brain’s preference for distinct dynamic connectivity states , 2020, Brain : a journal of neurology.

[10]  Maureen Le Danseur.  Stroke Rehabilitation. , 2020, Critical care nursing clinics of North America.

[11]  P. Nachev,et al.  Brain disconnections link structural connectivity with function and behaviour , 2020, Nature Communications.

[12]  Maurizio Corbetta,et al.  Damage to the shortest structural paths between brain regions is associated with disruptions of resting-state functional connectivity after stroke , 2020, NeuroImage.

[13]  W. Byblow,et al.  Advances and challenges in stroke rehabilitation , 2020, The Lancet Neurology.

[14]  Daniel S. Margulies,et al.  Topographic organization of the human subcortex unveiled with functional connectivity gradients , 2020, Nature Neuroscience.

[15]  Evan M. Gordon,et al.  Integrative and Network-Specific Connectivity of the Basal Ganglia and Thalamus Defined in Individuals , 2019, Neuron.

[16]  Michael Breakspear,et al.  The Low-Dimensional Neural Architecture of Cognitive Complexity Is Related to Activity in Medial Thalamic Nuclei , 2019, Neuron.

[17]  Olaf Sporns,et al.  Edge-centric functional network representations of human cerebral cortex reveal overlapping system-level architecture , 2019, Nature Neuroscience.

[18]  Morten L. Kringelbach,et al.  Dynamical exploration of the repertoire of brain networks at rest is modulated by psilocybin , 2019, NeuroImage.

[19]  Morten L. Kringelbach,et al.  Awakening: Predicting external stimulation to force transitions between different brain states , 2019, Proceedings of the National Academy of Sciences.

[20]  Massimo Filippi,et al.  Characterizing Rapid Fluctuations of Resting State Functional Connectivity in Demyelinating, Neurodegenerative, and Psychiatric Conditions: From Static to Time-Varying Analysis , 2019, Front. Neurosci..

[21]  Massimo Filippi,et al.  Resting State Dynamic Functional Connectivity in Neurodegenerative Conditions: A Review of Magnetic Resonance Imaging Findings , 2019, Front. Neurosci..

[22]  T. Ge,et al.  Resting brain dynamics at different timescales capture distinct aspects of human behavior , 2019, Nature Communications.

[23]  G. Buzsáki.  The Brain from Inside Out , 2019 .

[24]  Gustavo Deco,et al.  Altered ability to access a clinically relevant control network in patients remitted from major depressive disorder , 2019, Human brain mapping.

[25]  Joseph C. Griffis,et al.  Structural disconnections explain brain network dysfunction after stroke , 2019, bioRxiv.

[26]  Q. Xi,et al.  Alterations of static functional connectivity and dynamic functional connectivity in motor execution regions after stroke , 2018, Neuroscience Letters.

[27]  S. Small,et al.  Changes in dynamic resting state network connectivity following aphasia therapy , 2018, Brain Imaging and Behavior.

[28]  Nicholas A. Steinmetz,et al.  Spontaneous behaviors drive multidimensional, brainwide activity , 2019, Science.

[29]  Andrew W. Kraft,et al.  Spontaneous Infra-slow Brain Activity Has Unique Spatiotemporal Dynamics and Laminar Structure , 2018, Neuron.

[30]  Zhiqiang Zhang,et al.  Dynamic Network Analysis Reveals Altered Temporal Variability in Brain Regions after Stroke: A Longitudinal Resting-State fMRI Study , 2018, Neural plasticity.

[31]  Evan M. Gordon,et al.  Re-emergence of modular brain networks in stroke recovery , 2018, Cortex.

[32]  A. Lozano,et al.  Deep brain stimulation for stroke: Current uses and future directions , 2018, Brain Stimulation.

[33]  Timothy D. Verstynen,et al.  Population-averaged atlas of the macroscale human structural connectome and its network topology , 2018, NeuroImage.

[34]  Maurizio Corbetta,et al.  On the low dimensionality of behavioral deficits and alterations of brain network connectivity after focal injury , 2018, Cortex.

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

[36]  Morten L. Kringelbach,et al.  Functional connectivity dynamically evolves on multiple time-scales over a static structural connectome: Models and mechanisms , 2017, NeuroImage.

[37]  Dimitri Van De Ville,et al.  The dynamic functional connectome: State-of-the-art and perspectives , 2017, NeuroImage.

[38]  Celia M. Dong,et al.  Low-frequency hippocampal–cortical activity drives brain-wide resting-state functional MRI connectivity , 2017, Proceedings of the National Academy of Sciences.

[39]  Gustavo Deco,et al.  Cognitive performance in healthy older adults relates to spontaneous switching between states of functional connectivity during rest , 2017, Scientific Reports.

[40]  E. Ray,et al.  Efficient transport of tropospheric aerosol into the stratosphere via the Asian summer monsoon anticyclone , 2017, Proceedings of the National Academy of Sciences.

[41]  B. T. Thomas Yeo,et al.  Interpreting temporal fluctuations in resting-state functional connectivity MRI , 2017, NeuroImage.

[42]  W. Song,et al.  Application of noninvasive brain stimulation for post‐stroke dysphagia rehabilitation , 2017, The Kaohsiung journal of medical sciences.

[43]  M Corbetta,et al.  Behavioural clusters and predictors of performance during recovery from stroke , 2016, Nature Human Behaviour.

[44]  James M. Shine,et al.  Subcortical contributions to large-scale network communication , 2016, Neuroscience & Biobehavioral Reviews.

[45]  M. Corbetta,et al.  The effects of hemodynamic lag on functional connectivity and behavior after stroke , 2016, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[46]  M. Siket,et al.  Treatment of Acute Ischemic Stroke. , 2016, Emergency medicine clinics of North America.

[47]  Elizabeth Jefferies,et al.  Situating the default-mode network along a principal gradient of macroscale cortical organization , 2016, Proceedings of the National Academy of Sciences.

[48]  M. Raichle,et al.  Human cortical–hippocampal dialogue in wake and slow-wave sleep , 2016, Proceedings of the National Academy of Sciences.

[49]  Antonello Baldassarre,et al.  Disruptions of network connectivity predict impairment in multiple behavioral domains after stroke , 2016, Proceedings of the National Academy of Sciences.

[50]  Antonello Baldassarre,et al.  Normalization of network connectivity in hemispatial neglect recovery , 2016, Annals of neurology.

[51]  Laurent Thoraval,et al.  Product Hidden Markov Models for subject-based dynamic functional connectivity analysis of the resting state brain , 2016, 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI).

[52]  S. Petersen,et al.  Brain Networks and Cognitive Architectures , 2015, Neuron.

[53]  Adeel Razi,et al.  Selective vulnerability of Rich Club brain regions is an organizational principle of structural connectivity loss in Huntington’s disease , 2015, Brain : a journal of neurology.

[54]  Tianming Liu,et al.  Characterizing and Differentiating Brain State Dynamics via Hidden Markov Models , 2014, Brain Topography.

[55]  Dimitri Van De Ville,et al.  Transient brain activity disentangles fMRI resting-state dynamics in terms of spatially and temporally overlapping networks , 2015, Nature Communications.

[56]  Jonathan W. Pillow,et al.  Single-trial spike trains in parietal cortex reveal discrete steps during decision-making , 2015, Science.

[57]  Julia P. Owen,et al.  Edge density imaging: Mapping the anatomic embedding of the structural connectome within the white matter of the human brain , 2015, NeuroImage.

[58]  Carl D. Hacker,et al.  Common Behavioral Clusters and Subcortical Anatomy in Stroke , 2015, Neuron.

[59]  David Attwell,et al.  Non-signalling energy use in the brain , 2015, The Journal of physiology.

[60]  T. Murphy,et al.  Optogenetic Mapping after Stroke Reveals Network-Wide Scaling of Functional Connections and Heterogeneous Recovery of the Peri-Infarct , 2014, The Journal of Neuroscience.

[61]  Joaquín Goñi,et al.  A Network Convergence Zone in the Hippocampus , 2014, PLoS Comput. Biol..

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

[63]  J. Wardlaw,et al.  Imaging of acute stroke prior to treatment: current practice and evolving techniques. , 2014, The British journal of radiology.

[64]  Leonardo L. Gollo,et al.  Time-resolved resting-state brain networks , 2014, Proceedings of the National Academy of Sciences.

[65]  L. Pessoa.  Understanding brain networks and brain organization. , 2014, Physics of life reviews.

[66]  Eswar Damaraju,et al.  Tracking whole-brain connectivity dynamics in the resting state. , 2014, Cerebral cortex.

[67]  O. Sporns,et al.  Network hubs in the human brain , 2013, Trends in Cognitive Sciences.

[68]  Carl D. Hacker,et al.  Resting state network estimation in individual subjects , 2013, NeuroImage.

[69]  Jing Zhang,et al.  Modeling brain functional dynamics via hidden Markov models , 2013, 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER).

[70]  David A. Leopold,et al.  Dynamic functional connectivity: Promise, issues, and interpretations , 2013, NeuroImage.

[71]  Ravi S. Menon,et al.  Resting‐state networks show dynamic functional connectivity in awake humans and anesthetized macaques , 2013, Human brain mapping.

[72]  J. Duyn,et al.  Time-varying functional network information extracted from brief instances of spontaneous brain activity , 2013, Proceedings of the National Academy of Sciences.

[73]  Enzo Tagliazucchi,et al.  Dynamic BOLD functional connectivity in humans and its electrophysiological correlates , 2012, Front. Hum. Neurosci..

[74]  J. Matias Palva,et al.  Infra-slow fluctuations in electrophysiological recordings, blood-oxygenation-level-dependent signals, and psychophysical time series , 2012, NeuroImage.

[75]  D. Attwell,et al.  Synaptic Energy Use and Supply , 2012, Neuron.

[76]  Bruce Fischl,et al.  FreeSurfer , 2012, NeuroImage.

[77]  D. Attwell,et al.  Updated Energy Budgets for Neural Computation in the Neocortex and Cerebellum , 2012, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[78]  O. Sporns,et al.  High-cost, high-capacity backbone for global brain communication , 2012, Proceedings of the National Academy of Sciences.

[79]  Mark D'Esposito,et al.  Focal Brain Lesions to Critical Locations Cause Widespread Disruption of the Modular Organization of the Brain , 2012, Journal of Cognitive Neuroscience.

[80]  Stephen M. Smith,et al.  Temporally-independent functional modes of spontaneous brain activity , 2012, Proceedings of the National Academy of Sciences.

[81]  Timothy O. Laumann,et al.  Functional Network Organization of the Human Brain , 2011, Neuron.

[82]  O. Sporns,et al.  Rich-Club Organization of the Human Connectome , 2011, The Journal of Neuroscience.

[83]  Olaf Sporns,et al.  Complex network measures of brain connectivity: Uses and interpretations , 2010, NeuroImage.

[84]  M. Viergever,et al.  Recovery of Sensorimotor Function after Experimental Stroke Correlates with Restoration of Resting-State Interhemispheric Functional Connectivity , 2010, The Journal of Neuroscience.

[85]  Catie Chang,et al.  Time–frequency dynamics of resting-state brain connectivity measured with fMRI , 2010, NeuroImage.

[86]  Kent A. Kiehl,et al.  A method for evaluating dynamic functional network connectivity and task-modulation: application to schizophrenia , 2010, Magnetic Resonance Materials in Physics, Biology and Medicine.

[87]  Walter Schneider,et al.  Identifying the brain's most globally connected regions , 2010, NeuroImage.

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

[89]  Gorka Zamora-López,et al.  Cortical Hubs Form a Module for Multisensory Integration on Top of the Hierarchy of Cortical Networks , 2009, Front. Neuroinform..

[90]  Alan C. Evans,et al.  Small-world anatomical networks in the human brain revealed by cortical thickness from MRI. , 2007, Cerebral cortex.

[91]  Maurizio Corbetta,et al.  The human brain is intrinsically organized into dynamic, anticorrelated functional networks. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[92]  G. Buzsáki.  Large-scale recording of neuronal ensembles , 2004, Nature Neuroscience.

[93]  M. Shadlen,et al.  Response of Neurons in the Lateral Intraparietal Area during a Combined Visual Discrimination Reaction Time Task , 2002, The Journal of Neuroscience.

[94]  Eric R. Ziegel,et al.  Generalized Linear Models , 2002, Technometrics.

[95]  N. Tzourio-Mazoyer,et al.  Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain , 2002, NeuroImage.

[96]  Arthur E. Hoerl,et al.  Ridge Regression: Biased Estimation for Nonorthogonal Problems , 2000, Technometrics.

[97]  R A Robb,et al.  A software system for interactive and quantitative visualization of multidimensional biomedical images. , 1991, Australasian physical & engineering sciences in medicine.

[98]  Julia M. Huntenburg,et al.  Large-Scale Gradients in Human Cortical Organization , 2018, Trends in Cognitive Sciences.

[99]  Timothy O. Laumann,et al.  Generation and Evaluation of a Cortical Area Parcellation from Resting-State Correlations. , 2016, Cerebral cortex.

[100]  R. Llinás.  I of the Vortex , 2000 .

[101]  P. Celnik,et al.  Stroke Rehabilitation. , 2015, Physical medicine and rehabilitation clinics of North America.

[102]  J. MacQueen.  Some methods for classification and analysis of multivariate observations , 1967 .

[103]  E. S. Pearson,et al.  On the Problem of the Most Efficient Tests of Statistical Hypotheses , 1933 .