A parametric empirical Bayesian framework for fMRI-constrained MEG/EEG source reconstruction.
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A multi-subject, multi-modal human neuroimaging dataset.Incorporating priors for EEG source imaging and connectivity analysisHow to use fMRI functional localizers to improve EEG/MEG source estimation.Dynamic causal models and physiological inference: a validation study using isoflurane anaesthesia in rodentsNew levels of language processing complexity and organization revealed by granger causation.Performance evaluation of the Champagne source reconstruction algorithm on simulated and real M/EEG dataSpatiotemporal neural network dynamics for the processing of dynamic facial expressions.Source localization with MEG data: A beamforming approach based on covariance thresholding.Bayesian Models for fMRI Data Analysis.Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness.A Review of Issues Related to Data Acquisition and Analysis in EEG/MEG Studies.EEG and MEG data analysis in SPM8.A Parametric Empirical Bayesian Framework for the EEG/MEG Inverse Problem: Generative Models for Multi-Subject and Multi-Modal Integration.A review of multivariate methods for multimodal fusion of brain imaging dataA selective review of multimodal fusion methods in schizophrenia.EEG/fMRI fusion based on independent component analysis: integration of data-driven and model-driven methods.Bayesian symmetrical EEG/fMRI fusion with spatially adaptive priors.MEG source localization of spatially extended generators of epileptic activity: comparing entropic and hierarchical bayesian approaches.In vivo imaging of epileptic foci in rats using a miniature probe integrating diffuse optical tomography and electroencephalographic source localization.Unfolding the spatial and temporal neural processing of lying about face familiarityUnfolding the Spatial and Temporal Neural Processing of Making Dishonest Choices.Contribution of substantia nigra glutamate to prediction error signals in schizophrenia: a combined magnetic resonance spectroscopy/functional imaging study.A review of EEG and MEG for brainnetome research.Comparing variational Bayes with Markov chain Monte Carlo for Bayesian computation in neuroimaging.Asymmetric Weighting to Optimize Regional Sensitivity in Combined fMRI-MEG Maps.Good practice for conducting and reporting MEG research.Algorithmic procedures for Bayesian MEG/EEG source reconstruction in SPM.A variational Bayes spatiotemporal model for electromagnetic brain mapping.Incorporating FMRI functional networks in EEG source imaging: a Bayesian model comparison approach.EEG/MEG source imaging using fMRI informed time-variant constraints.Combining multi-modality data for searching biomarkers in schizophrenia.Non-invasive Investigation of Human Hippocampal Rhythms Using Magnetoencephalography: A Review.
P2860
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P2860
A parametric empirical Bayesian framework for fMRI-constrained MEG/EEG source reconstruction.
description
2010 nî lūn-bûn
@nan
2010年の論文
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
2010年论文
@zh
2010年论文
@zh-cn
name
A parametric empirical Bayesia ...... MEG/EEG source reconstruction.
@en
A parametric empirical Bayesia ...... MEG/EEG source reconstruction.
@nl
type
label
A parametric empirical Bayesia ...... MEG/EEG source reconstruction.
@en
A parametric empirical Bayesia ...... MEG/EEG source reconstruction.
@nl
prefLabel
A parametric empirical Bayesia ...... MEG/EEG source reconstruction.
@en
A parametric empirical Bayesia ...... MEG/EEG source reconstruction.
@nl
P2860
P356
P1433
P1476
A parametric empirical Bayesia ...... MEG/EEG source reconstruction.
@en
P2093
Jérémie Mattout
Richard N Henson
P2860
P304
P356
10.1002/HBM.20956
P577
2010-10-01T00:00:00Z