Bayesian estimation of ERP components from multicondition and multichannel EEG

[1]  Matthew J. Beal.  Variational algorithms for approximate Bayesian inference , 2003 .

[2]  R. Oostenveld,et al.  Independent EEG Sources Are Dipolar , 2012, PloS one.

[3]  T. Baldeweg,et al.  Impaired auditory frequency discrimination in dyslexia detected with mismatch evoked potentials , 1999, Annals of neurology.

[4]  B. MCA. SAVERS,et al.  The Mechanism of Auditory Evoked EEG Responses , 1974, Nature.

[5]  T. Allison,et al.  Electrophysiological Studies of Face Perception in Humans , 1996, Journal of Cognitive Neuroscience.

[6]  Yuan Qi,et al.  Parameter Expanded Variational Bayesian Methods , 2006, NIPS.

[7]  Peter E. Clayson,et al.  How does noise affect amplitude and latency measurement of event-related potentials (ERPs)? A methodological critique and simulation study. , 2013, Psychophysiology.

[8]  R. Herbrich.  On Gaussian Expectation Propagation , 2005 .

[9]  Kevin P. Murphy,et al.  Machine learning - a probabilistic perspective , 2012, Adaptive computation and machine learning series.

[10]  Yuhong Yang,et al.  Information Theory, Inference, and Learning Algorithms , 2005 .

[11]  Karl J. Friston,et al.  A mesostate-space model for EEG and MEG , 2007, NeuroImage.

[12]  José Carlos Príncipe,et al.  A Spatiotemporal Filtering Methodology for Single-Trial ERP Component Estimation , 2009, IEEE Transactions on Biomedical Engineering.

[13]  José Carlos Príncipe,et al.  A New Spatiotemporal Filtering Method for Single-Trial Estimation of Correlated ERP Subcomponents , 2011, IEEE Transactions on Biomedical Engineering.

[14]  M. Tarr,et al.  Expertise Training with Novel Objects Leads to Left-Lateralized Facelike Electrophysiological Responses , 2002, Psychological science.

[15]  Yan Wang,et al.  Contrasting single-trial ERPs between experimental manipulations: Improving differentiability by blind source separation , 2006, NeuroImage.

[16]  R. Barry,et al.  Event-related potentials in the auditory oddball as a function of EEG alpha phase at stimulus onset , 2004, Clinical Neurophysiology.

[17]  Fumikazu Miwakeichi,et al.  Decomposing EEG data into space–time–frequency components using Parallel Factor Analysis , 2004, NeuroImage.

[18]  T. Sejnowski,et al.  Dynamic Brain Sources of Visual Evoked Responses , 2002, Science.

[19]  J. Movshon,et al.  The analysis of visual motion: a comparison of neuronal and psychophysical performance , 1992, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[20]  Fusheng Yang,et al.  BCI competition 2003-data set IIb: enhancing P300 wave detection using ICA-based subspace projections for BCI applications , 2004, IEEE Transactions on Biomedical Engineering.

[21]  Stefan Haufe,et al.  Single-trial analysis and classification of ERP components — A tutorial , 2011, NeuroImage.

[22]  E Donchin,et al.  A metric for thought: a comparison of P300 latency and reaction time. , 1981, Science.

[23]  S. Hillyard,et al.  Endogenous brain potentials associated with selective auditory attention. , 1980, Electroencephalography and clinical neurophysiology.

[24]  C. Woody.  Characterization of an adaptive filter for the analysis of variable latency neuroelectric signals , 1967, Medical and biological engineering.

[25]  E. Donchin,et al.  A multivariate approach to the analysis of average evoked potentials. , 1966, IEEE transactions on bio-medical engineering.

[26]  M. Woldorff,et al.  Distortion of ERP averages due to overlap from temporally adjacent ERPs: analysis and correction. , 2007, Psychophysiology.

[27]  C. Joyce,et al.  The face-sensitive N170 and VPP components manifest the same brain processes: The effect of reference electrode site , 2005, Clinical Neurophysiology.

[28]  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.

[29]  V. Goffaux,et al.  Spatio-temporal localization of the face inversion effect: an event-related potentials study , 1999, Biological Psychology.

[30]  R. Bro,et al.  A new efficient method for determining the number of components in PARAFAC models , 2003 .

[31]  W. Klimesch,et al.  Are event-related potential components generated by phase resetting of brain oscillations? A critical discussion , 2007, Neuroscience.

[32]  Jian Li,et al.  ASEO: A Method for the Simultaneous Estimation of Single-Trial Event-Related Potentials and Ongoing Brain Activities , 2009, IEEE Transactions on Biomedical Engineering.

[33]  Tamara G. Kolda,et al.  Tensor Decompositions and Applications , 2009, SIAM Rev..

[34]  Yehoshua Y. Zeevi,et al.  Extraction of a source from multichannel data using sparse decomposition , 2002, Neurocomputing.

[35]  Marina Schmid,et al.  An Introduction To The Event Related Potential Technique , 2016 .

[36]  E. Oja,et al.  BSS and ICA in Neuroinformatics: From Current Practices to Open Challenges , 2008, IEEE Reviews in Biomedical Engineering.

[37]  Daniel Graupe,et al.  Topographic component (Parallel Factor) analysis of multichannel evoked potentials: Practical issues in trilinear spatiotemporal decomposition , 2005, Brain Topography.

[38]  H. Flor,et al.  A spelling device for the paralysed , 1999, Nature.

[39]  Lars Kai Hansen,et al.  Shift-invariant multilinear decomposition of neuroimaging data , 2008, NeuroImage.

[40]  T. Sejnowski,et al.  Analysis and visualization of single‐trial event‐related potentials , 2001, Human brain mapping.

[41]  J. Fermaglich.  Electric Fields of the Brain: The Neurophysics of EEG , 1982 .

[42]  Wei Wu,et al.  Extraction of mismatch negativity using a resampling-based spatial filtering method , 2013, Journal of neural engineering.

[43]  W. Klimesch,et al.  Alpha phase synchronization predicts P1 and N1 latency and amplitude size. , 2005, Cerebral cortex.

[44]  J. Maunsell,et al.  Network Rhythms Influence the Relationship between Spike-Triggered Local Field Potential and Functional Connectivity , 2011, The Journal of Neuroscience.

[45]  Wei Wu,et al.  A hierarchical Bayesian approach for learning sparse spatio-temporal decompositions of multichannel EEG , 2011, NeuroImage.

[46]  George Eastman House,et al.  Sparse Bayesian Learning and the Relevance Vector Machine , 2001 .

[47]  Xingyu Wang,et al.  Spatial-Temporal Discriminant Analysis for ERP-Based Brain-Computer Interface , 2013, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[48]  Mingzhou Ding,et al.  Differentially variable component analysis: Identifying multiple evoked components using trial-to-trial variability. , 2006, Journal of neurophysiology.

[49]  Karl J. Friston,et al.  Modelling event-related responses in the brain , 2005, NeuroImage.

[50]  J. Eggermont,et al.  Maturation of human central auditory system activity: evidence from multi-channel evoked potentials , 2000, Clinical Neurophysiology.

[51]  E. Vogel,et al.  The visual N1 component as an index of a discrimination process. , 2000, Psychophysiology.

[52]  L. K. Hansen,et al.  Automatic relevance determination for multi‐way models , 2009 .

[53]  David J. C. MacKay,et al.  Information Theory, Inference, and Learning Algorithms , 2004, IEEE Transactions on Information Theory.

[54]  Andrzej Cichocki,et al.  A New Learning Algorithm for Blind Signal Separation , 1995, NIPS.

[55]  Lars Kai Hansen,et al.  Parallel Factor Analysis as an exploratory tool for wavelet transformed event-related EEG , 2006, NeuroImage.

[56]  Jeff Miller,et al.  Measurement of ERP latency differences: a comparison of single-participant and jackknife-based scoring methods. , 2008, Psychophysiology.