Symmetrical event-related EEG/fMRI information fusion in a variational Bayesian framework

[1]  J. C. Jimenez,et al.  Nonlinear local electrovascular coupling. I: A theoretical model , 2006, Human brain mapping.

[2]  Jean Gotman,et al.  Anatomically informed interpolation of fMRI data on the cortical surface , 2006, NeuroImage.

[3]  Karl J. Friston,et al.  MEG source localization under multiple constraints: An extended Bayesian framework , 2006, NeuroImage.

[4]  Jérémie Mattout,et al.  Data-driven parceling and entropic inference in MEG , 2006, NeuroImage.

[5]  Diego Clonda,et al.  Bayesian spatio-temporal approach for EEG source reconstruction: conciliating ECD and distributed models , 2006, IEEE Transactions on Biomedical Engineering.

[6]  Nathalie Chang,et al.  Dipole localization using simulated intracerebral EEG , 2005, Clinical Neurophysiology.

[7]  Jean Gotman,et al.  Hemodynamic and metabolic responses to activation, deactivation and epileptic discharges , 2005, NeuroImage.

[8]  J.-M. Lina,et al.  Assessing the relevance of fMRI-based prior in the EEG inverse problem: a bayesian model comparison approach , 2005, IEEE Transactions on Signal Processing.

[9]  I. Fried,et al.  Coupling Between Neuronal Firing, Field Potentials, and fMRI in Human Auditory Cortex , 2005, Science.

[10]  Karl J. Friston,et al.  A theory of cortical responses , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[11]  Karl J. Friston.  Models of brain function in neuroimaging. , 2005, Annual review of psychology.

[12]  U. von Toussaint,et al.  Bayesian inference and maximum entropy methods in science and engineering , 2004 .

[13]  Jean-Francois Mangin,et al.  Automatized clustering and functional geometry of human parietofrontal networks for language, space, and number , 2004, NeuroImage.

[14]  Karl J. Friston,et al.  Biophysical models of fMRI responses , 2004, Current Opinion in Neurobiology.

[15]  Habib Benali,et al.  Estimation of the hemodynamic response in event-related functional MRI: Bayesian networks as a framework for efficient Bayesian modeling and inference , 2004, IEEE Transactions on Medical Imaging.

[16]  J. Gotman,et al.  Combining EEG and fMRI in Epilepsy: Methodological Challenges and Clinical Results , 2004, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[17]  Seppo P. Ahlfors,et al.  Geometrical interpretation of fMRI-guided MEG/EEG inverse estimates , 2004, NeuroImage.

[18]  Jérémie Mattout,et al.  Data-driven cortex parcelling: a regularization tool for the EEG/MEG inverse problem , 2004, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).

[19]  Olaf Hauk,et al.  Keep it simple: a case for using classical minimum norm estimation in the analysis of EEG and MEG data , 2004, NeuroImage.

[20]  Nikos K Logothetis,et al.  Interpreting the BOLD signal. , 2004, Annual review of physiology.

[21]  P. Nunez,et al.  On the Relationship of Synaptic Activity to Macroscopic Measurements: Does Co-Registration of EEG with fMRI Make Sense? , 2004, Brain Topography.

[22]  Habib Benali,et al.  Estimation of the Hemodynamic Response Function in Event-Related Functional MRI: Directed Acyclic Graphs for a General Bayesian Inference Framework , 2003, IPMI.

[23]  O. Arthurs,et al.  What aspect of the fMRI BOLD signal best reflects the underlying electrophysiology in human somatosensory cortex? , 2003, Clinical Neurophysiology.

[24]  H. Benali,et al.  Robust Bayesian estimation of the hemodynamic response function in event‐related BOLD fMRI using basic physiological information , 2003, Human brain mapping.

[25]  Ying Zheng,et al.  The Hemodynamic Impulse Response to a Single Neural Event , 2003, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[26]  Febo Cincotti,et al.  Multimodal integration of high-resolution EEG and functional magnetic resonance imaging data: a simulation study , 2003, NeuroImage.

[27]  Nicholas Ayache,et al.  Parcellation of brain images with anatomical and functional constraints for fMRI data analysis , 2002, Proceedings IEEE International Symposium on Biomedical Imaging.

[28]  Jean-Baptiste Poline,et al.  Bayesian estimation of the hemodynamic response function in functional MRI , 2002 .

[29]  Richard M. Leahy,et al.  Electromagnetic brain mapping , 2001, IEEE Signal Process. Mag..

[30]  N. Logothetis,et al.  Neurophysiological investigation of the basis of the fMRI signal , 2001, Nature.

[31]  N. Trujillo-Barreto,et al.  Bayesian model for EEG/MEG and fMRI data fusion , 2001, NeuroImage.

[32]  C Gössl,et al.  Bayesian Spatiotemporal Inference in Functional Magnetic Resonance Imaging , 2001, Biometrics.

[33]  G L Shulman,et al.  INAUGURAL ARTICLE by a Recently Elected Academy Member:A default mode of brain function , 2001 .

[34]  O. Blanke,et al.  The use of functional constraints for the neuroelectromagnetic inverse problem: alternatives and caveats. , 2001 .

[35]  Nelson J. Trujillo-Barreto,et al.  A symmetrical Bayesian model for fMRI and EEG/MEG neuroimage fusion , 2001 .

[36]  Greenblatt Ijbem,et al.  Nonlinear Analysis of Multimodal Dynamic Brain Imaging Data , 2001 .

[37]  Alan C. Evans,et al.  A general statistical analysis for fMRI data , 2000, NeuroImage.

[38]  J.C. Mosher,et al.  Recursive MUSIC: A framework for EEG and MEG source localization , 1998, IEEE Transactions on Biomedical Engineering.

[39]  C. Mathiesen,et al.  Modification of activity‐dependent increases of cerebral blood flow by excitatory synaptic activity and spikes in rat cerebellar cortex , 1998, The Journal of physiology.

[40]  A K Liu,et al.  Spatiotemporal imaging of human brain activity using functional MRI constrained magnetoencephalography data: Monte Carlo simulations. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[41]  T. Allison,et al.  Comparison of cortical activation evoked by faces measured by intracranial field potentials and functional MRI: Two case studies , 1997, Human brain mapping.

[42]  T. L. Davis,et al.  Characterization of Cerebral Blood Oxygenation and Flow Changes during Prolonged Brain Activation , 2022 .

[43]  L. Wasserman,et al.  The Selection of Prior Distributions by Formal Rules , 1996 .

[44]  David B. Dunson,et al.  Bayesian Data Analysis , 2010 .

[45]  Karl J. Friston,et al.  Analysis of fMRI Time-Series Revisited , 1995, NeuroImage.

[46]  D. Lehmann,et al.  Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain. , 1994, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[47]  C. N. Guy,et al.  Intracerebral propagation of interictal activity in partial epilepsy: implications for source localisation. , 1994, Journal of neurology, neurosurgery, and psychiatry.

[48]  Zoubin Ghahramani,et al.  Factorial Learning and the EM Algorithm , 1994, NIPS.

[49]  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.

[50]  J. D. Munck.  The potential distribution in a layered anisotropic spheroidal volume conductor , 1988 .

[51]  P. Nunez,et al.  Electric fields of the brain , 1981 .

[52]  H. P. Bowditch.  The Physiological Laboratory at Leipzig , 1870, Nature.