Microstates and power envelope hidden Markov modeling probe bursting brain activity at different timescales

[1]  M. Woolrich,et al.  Replay bursts in humans coincide with activation of the default mode and parietal alpha networks , 2020, Neuron.

[2]  J. Triesch,et al.  EEG microstate periodicity explained by rotating phase patterns of resting-state alpha oscillations , 2020, NeuroImage.

[3]  Catie Chang,et al.  Evidence for modulation of EEG microstate sequence by vigilance level , 2020, NeuroImage.

[4]  M. Woolrich,et al.  Brain dysconnectivity relates to disability and cognitive impairment in multiple sclerosis , 2020, Human brain mapping.

[5]  M. Herzog,et al.  EEG microstates are a candidate endophenotype for schizophrenia , 2020, Nature Communications.

[6]  P. Peigneux,et al.  Alterations in resting-state network dynamics along the Alzheimer’s disease continuum , 2020, Scientific Reports.

[7]  M. Woolrich,et al.  Changes in electrophysiological static and dynamic human brain functional architecture from childhood to late adulthood , 2020, Scientific Reports.

[8]  Tatiana Sitnikova,et al.  Spontaneous activity changes in large-scale cortical networks in older adults couple to distinct hemodynamic morphology , 2020, bioRxiv.

[9]  Deepti R. Bathula,et al.  Investigating the temporal dynamics of electroencephalogram (EEG) microstates using recurrent neural networks , 2020, Human brain mapping.

[10]  Mathieu Bourguignon,et al.  Comparing MEG and high-density EEG for intrinsic functional connectivity mapping , 2020, NeuroImage.

[11]  Mark W. Woolrich,et al.  The role of transient spectral ‘bursts’ in functional connectivity: A magnetoencephalography study , 2020, NeuroImage.

[12]  Vincent Wens,et al.  Age of onset determines intrinsic functional brain architecture in Friedreich ataxia , 2019, Annals of clinical and translational neurology.

[13]  Michael X. Cohen,et al.  EEG microstates as a continuous phenomenon , 2019, NeuroImage.

[14]  Maurizio Corbetta,et al.  The Impact of the Geometric Correction Scheme on MEG Functional Topology at Rest , 2019, Front. Neurosci..

[15]  Mark W. Woolrich,et al.  Do the posterior midline cortices belong to the electrophysiological default-mode network? , 2019, NeuroImage.

[16]  Mathieu Bourguignon,et al.  Synchrony, metastability, dynamic integration, and competition in the spontaneous functional connectivity of the human brain , 2019, NeuroImage.

[17]  Mark Woolrich,et al.  Altered transient brain dynamics in multiple sclerosis: Treatment or pathology? , 2019, Human brain mapping.

[18]  Christoph M. Michel,et al.  EEG Microstates Analysis in Young Adults With Autism Spectrum Disorder During Resting-State , 2019, Front. Hum. Neurosci..

[19]  Christoph M. Michel,et al.  EEG Source Imaging: A Practical Review of the Analysis Steps , 2019, Front. Neurol..

[20]  M. De Vos,et al.  A dynamic system of brain networks revealed by fast transient EEG fluctuations and their fMRI correlates , 2019, NeuroImage.

[21]  Mark W. Woolrich,et al.  Task-Evoked Dynamic Network Analysis Through Hidden Markov Modeling , 2018, Front. Neurosci..

[22]  Benjamin A. E. Hunt,et al.  Spontaneous cortical activity transiently organises into frequency specific phase-coupling networks , 2018, Nature Communications.

[23]  A. Nobre,et al.  Neural Oscillations: Sustained Rhythms or Transient Burst-Events? , 2018, Trends in Neurosciences.

[24]  Mark W. Woolrich,et al.  Altered temporal stability in dynamic neural networks underlies connectivity changes in neurodevelopment , 2018, NeuroImage.

[25]  Mark W. Woolrich,et al.  Short timescale abnormalities in the states of spontaneous synchrony in the functional neural networks in Alzheimer's disease , 2018, NeuroImage: Clinical.

[26]  Nicola Molinaro,et al.  Contrasting functional imaging parametric maps: The mislocation problem and alternative solutions , 2018, NeuroImage.

[27]  Mark W. Woolrich,et al.  Dynamics of large-scale electrophysiological networks: A technical review , 2017, NeuroImage.

[28]  Dimitri Van De Ville,et al.  Electroencephalographic Resting-State Networks: Source Localization of Microstates , 2017, Brain Connect..

[29]  Fernando Maestú,et al.  Choice of Magnetometers and Gradiometers after Signal Space Separation , 2017, Sensors.

[30]  Thomas Koenig,et al.  EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: A review , 2017, NeuroImage.

[31]  N. Wenderoth,et al.  Detecting large‐scale networks in the human brain using high‐density electroencephalography , 2017, Human brain mapping.

[32]  Diego Vidaurre,et al.  Spontaneous cortical activity transiently organises into frequency specific phase-coupling networks , 2017, bioRxiv.

[33]  Sylvain Baillet,et al.  Magnetoencephalography for brain electrophysiology and imaging , 2017, Nature Neuroscience.

[34]  Janet Scheel,et al.  Spatiotemporal Dynamics , 2017, Encyclopedia of GIS.

[35]  Dezhong Yao,et al.  Is the Surface Potential Integral of a Dipole in a Volume Conductor Always Zero? A Cloud Over the Average Reference of EEG and ERP , 2017, Brain Topography.

[36]  M Corbetta,et al.  A Dynamic Core Network and Global Efficiency in the Resting Human Brain. , 2016, Cerebral cortex.

[37]  Joerg F. Hipp,et al.  Measuring the cortical correlation structure of spontaneous oscillatory activity with EEG and MEG , 2016, NeuroImage.

[38]  Christoph M. Michel,et al.  Fluctuations of spontaneous EEG topographies predict disease state in relapsing-remitting multiple sclerosis , 2016, NeuroImage: Clinical.

[39]  Andrea Bergmann,et al.  Statistical Parametric Mapping The Analysis Of Functional Brain Images , 2016 .

[40]  Mathieu Bourguignon,et al.  A geometric correction scheme for spatial leakage effects in MEG/EEG seed‐based functional connectivity mapping , 2015, Human brain mapping.

[41]  Christoph M. Michel,et al.  Schizophrenia patients and 22q11.2 deletion syndrome adolescents at risk express the same deviant patterns of resting state EEG microstates: A candidate endophenotype of schizophrenia , 2015, Schizophrenia Research: Cognition.

[42]  Á. Pascual-Leone,et al.  Microstates in resting-state EEG: Current status and future directions , 2015, Neuroscience & Biobehavioral Reviews.

[43]  Vincent Wens,et al.  Investigating complex networks with inverse models: analytical aspects of spatial leakage and connectivity estimation. , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

[44]  Mathieu Bourguignon,et al.  About the electrophysiological basis of resting state networks , 2014, Clinical Neurophysiology.

[45]  Stephen M Smith,et al.  Fast transient networks in spontaneous human brain activity , 2014, eLife.

[46]  Martin Luessi,et al.  MNE software for processing MEG and EEG data , 2014, NeuroImage.

[47]  Scott Makeig,et al.  BCILAB: a platform for brain–computer interface development , 2013, Journal of neural engineering.

[48]  Hamid Reza Mohseni,et al.  Dynamic state allocation for MEG source reconstruction , 2013, NeuroImage.

[49]  W. Klimesch.  Alpha-band oscillations, attention, and controlled access to stored information , 2012, Trends in Cognitive Sciences.

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

[51]  M. Corbetta,et al.  A Cortical Core for Dynamic Integration of Functional Networks in the Resting Human Brain , 2012, Neuron.

[52]  C. Koch,et al.  The origin of extracellular fields and currents — EEG, ECoG, LFP and spikes , 2012, Nature Reviews Neuroscience.

[53]  M. Corbetta,et al.  Large-scale cortical correlation structure of spontaneous oscillatory activity , 2012, Nature Neuroscience.

[54]  Han Yuan,et al.  Spatiotemporal dynamics of the brain at rest — Exploring EEG microstates as electrophysiological signatures of BOLD resting state networks , 2012, NeuroImage.

[55]  A. Engel,et al.  Spectral fingerprints of large-scale neuronal interactions , 2012, Nature Reviews Neuroscience.

[56]  Pablo Balenzuela,et al.  Criticality in Large-Scale Brain fMRI Dynamics Unveiled by a Novel Point Process Analysis , 2012, Front. Physio..

[57]  Darren Price,et al.  Investigating the electrophysiological basis of resting state networks using magnetoencephalography , 2011, Proceedings of the National Academy of Sciences.

[58]  Christoph M. Michel,et al.  Spatiotemporal Analysis of Multichannel EEG: CARTOOL , 2011, Comput. Intell. Neurosci..

[59]  Tracy Warbrick,et al.  Spontaneous brain activity and EEG microstates. A novel EEG/fMRI analysis approach to explore resting-state networks , 2010, NeuroImage.

[60]  Dimitri Van De Ville,et al.  BOLD correlates of EEG topography reveal rapid resting-state network dynamics , 2010, NeuroImage.

[61]  S. Luck,et al.  The effects of electrode impedance on data quality and statistical significance in ERP recordings. , 2010, Psychophysiology.

[62]  W. Klimesch,et al.  Oscillatory mechanisms of process binding in memory , 2010, Neuroscience & Biobehavioral Reviews.

[63]  J. Schoffelen,et al.  Source connectivity analysis with MEG and EEG , 2009, Human brain mapping.

[64]  Thomas Koenig,et al.  Electrical Neuroimaging in the time domain , 2009 .

[65]  Lauri Parkkonen,et al.  Recording epileptic activity with MEG in a light-weight magnetic shield , 2008, Epilepsy Research.

[66]  Denis Brunet,et al.  Topographic ERP Analyses: A Step-by-Step Tutorial Review , 2008, Brain Topography.

[67]  S. Taulu,et al.  Applications of the signal space separation method , 2005, IEEE Transactions on Signal Processing.

[68]  Robert Tibshirani,et al.  Cluster Validation by Prediction Strength , 2005 .

[69]  T. Koenig,et al.  EEG microstate duration and syntax in acute, medication-naïve, first-episode schizophrenia: a multi-center study , 2005, Psychiatry Research: Neuroimaging.

[70]  Stephen J. Roberts,et al.  Ensemble Hidden Markov Models with Extended Observation Densities for Biosignal Analysis , 2005 .

[71]  Wolfgang Skrandies,et al.  Global field power and topographic similarity , 2005, Brain Topography.

[72]  Arnaud Delorme,et al.  EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis , 2004, Journal of Neuroscience Methods.

[73]  D. Tucker,et al.  Scalp electrode impedance, infection risk, and EEG data quality , 2001, Clinical Neurophysiology.

[74]  Erkki Oja,et al.  Independent component approach to the analysis of EEG and MEG recordings , 2000, IEEE Transactions on Biomedical Engineering.

[75]  F. L. D. Silva,et al.  Event-related EEG/MEG synchronization and desynchronization: basic principles , 1999, Clinical Neurophysiology.

[76]  Dietrich Lehmann,et al.  A deviant EEG brain microstate in acute, neuroleptic-naive schizophrenics at rest , 1999, European Archives of Psychiatry and Clinical Neuroscience.

[77]  T. Koenig,et al.  Brain electric microstates and momentary conscious mind states as building blocks of spontaneous thinking: I. Visual imagery and abstract thoughts. , 1998, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[78]  R. Hari,et al.  Human cortical oscillations: a neuromagnetic view through the skull , 1997, Trends in Neurosciences.

[79]  D. Lehmann,et al.  Segmentation of brain electrical activity into microstates: model estimation and validation , 1995, IEEE Transactions on Biomedical Engineering.

[80]  A. Dale,et al.  Improved Localizadon of Cortical Activity by Combining EEG and MEG with MRI Cortical Surface Reconstruction: A Linear Approach , 1993, Journal of Cognitive Neuroscience.

[81]  F. Perrin,et al.  Spherical splines for scalp potential and current density mapping. , 1989, Electroencephalography and clinical neurophysiology.

[82]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[83]  D Lehmann,et al.  EEG alpha map series: brain micro-states by space-oriented adaptive segmentation. , 1987, Electroencephalography and clinical neurophysiology.

[84]  O Bertrand,et al.  A theoretical justification of the average reference in topographic evoked potential studies. , 1985, Electroencephalography and clinical neurophysiology.

[85]  F. Takens.  Detecting strange attractors in turbulence , 1981 .

[86]  R. C. Oldfield.  The assessment and analysis of handedness: the Edinburgh inventory. , 1971, Neuropsychologia.

[87]  Josef BOKR,et al.  Dynamic System , 2022 .