A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Filters
Bayesian brain source imaging based on combined MEG/EEG and fMRI using MCMC
2008
NeuroImage
Preserved Fulltext
We formulate Bayesian integration of magnetoencephalography (MEG) data and functional magnetic resonance imaging (fMRI) data by incorporating fMRI data into a spatial prior. ...
In this paper we introduce methods of Bayesian inference as a way to integrate different forms of brain imaging data in a probabilistic framework. ...
We propose a combined spatiotemporal MEG/fMRI dipole analysis based on Bayesian inference. ...
doi:10.1016/j.neuroimage.2007.12.029
pmid:18314351
pmcid:PMC2929566
fatcat:pusjqwqdhbfe5edcoogrziod3e
Variational Bayesian MultimodalEncephaloGraphy (VBMEG): Its Theory and Applications
階層変分ベイズ推定法(VBMEG)の原理と応用
2011
The Brain & Neural Networks
階層変分ベイズ推定法(VBMEG)の原理と応用
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Vol.39, No.2, pp.728-741 8) Jun, S.C., George, J.S., Par-Blagoev, J., Plis, S.M., Ranken, D.M., Schmidt, D.M., Wood, C.C. (2005): Spatiotemporal Bayesian inference dipole analysis for MEG neuroimaging ...
, Neuroimage, Vol.17, No.1, pp.324-343 7) Kiebel, S.J., Daunizeau, J., Phillips, C., Friston, K.J. (2008): Variational Bayesian inversion of the equivalent current dipole model in EEG/MEG, Neuroimage, ...
doi:10.3902/jnns.18.214
fatcat:r2doqfzxgneavm6ux3aprpvemm
Spatiotemporal noise covariance estimation from limited empirical magnetoencephalographic data
2006
Physics in Medicine and Biology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2016; you can also visit the original URL.
The file type is application/pdf.
To verify its capability we used Bayesian inference dipole analysis and a number of simulated and empirical datasets. ...
For such cases, a diagonal spatiotemporal noise covariance model consisting of sensor variances with no spatial or temporal correlation has been the common choice for spatiotemporal analysis. ...
Some figures showing the results of the Bayesian dipole analysis were generated using MRIVIEW (Ranken et al 2002) . ...
doi:10.1088/0031-9155/51/21/011
pmid:17047269
fatcat:bg44r65pv5etvkmv5foqvob6za
Electrophysiological Source Imaging: A Noninvasive Window to Brain Dynamics
2018
Annual Review of Biomedical Engineering
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
We review methodological developments in electrophysiological source imaging over the past three decades and envision its future advancement into a powerful functional neuroimaging technology for basic ...
Electrophysiological source imaging estimates the underlying brain electrical sources from EEG and MEG measurements. ...
Bayesian Methods Bayesian inference provides a general framework in which many source imaging algorithms can be derived and interpreted. ...
doi:10.1146/annurev-bioeng-062117-120853
pmid:29494213
pmcid:PMC7941524
fatcat:xypqgl7snbbnnidrn5ddepj6tu
Neuro-current response functions: A unified approach to MEG source analysis under the continuous stimuli paradigm
2020
NeuroImage
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
The analysis of experimentally-recorded MEG data without MR scans corroborates existing findings, but also delineates the distinct cortical distribution of the underlying neural processes at high spatiotemporal ...
In summary, we provide a principled modeling and estimation paradigm for MEG source analysis tailored to extracting the cortical origin of electrophysiological responses to continuous stimuli. ...
To this end, we developed a fast inverse solution under a Bayesian estimation setting, the Champ-Lasso algorithm, for inferring the Neuro-Current Response Functions (as spatiotemporal models of cortical ...
doi:10.1016/j.neuroimage.2020.116528
pmid:31945510
pmcid:PMC7717175
fatcat:ywygvlg3dfa5dfm3ol6pbagpzq
Multimodal Functional Neuroimaging: Integrating Functional MRI and EEG/MEG
2008
IEEE Reviews in Biomedical Engineering
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Combining fMRI and EEG/MEG data allows us to study brain function from different perspectives. ...
in the understanding and modeling of neurovascular coupling and in the methodologies for the fMRI-EEG/MEG simultaneous recording. ...
Such inference is classic in terms of statistics, as opposed to more recent methods based on the Bayesian inference which provides the posterior probability that the voxel is activated given the data ...
doi:10.1109/rbme.2008.2008233
pmid:20634915
pmcid:PMC2903760
fatcat:6hogffiwvrbonmxn2swkyqstde
A spatiotemporal dynamic distributed solution to the MEG inverse problem
2012
NeuroImage
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
MEG/EEG are non-invasive imaging techniques that record brain activity with high temporal resolution. ...
In this article, we present a model for cortical activity based on nearest-neighbor autoregression that incorporates local spatiotemporal interactions between distributed sources in a manner consistent ...
Analysis of experimental data from human subjects We also applied the MNE, FIS, sMAP-EM, and dMAP-EM algorithms to mu-rhythm MEG data from a human subject. ...
doi:10.1016/j.neuroimage.2011.11.020
pmid:22155043
pmcid:PMC3432302
fatcat:lz7wamgjuzhc5jp7obsbcvmyga
Spatiotemporal neural network dynamics for the processing of dynamic facial expressions
2015
Scientific Reports
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
This contrasts with an MEG study, which reported that the current dipole of posterior activity for dynamic facial stimuli during this time period was located in the V5 region 13 . ...
Consistent with these behavioral data, neuroimaging studies using functional magnetic resonance imaging (fMRI) and positron-emission tomography have shown that several cortical and subcortical regions ...
Masaki for advice and the ATR Brain Activity Imaging Center for support in data acquisition. ...
doi:10.1038/srep12432
pmid:26206708
pmcid:PMC4513292
fatcat:ohx6ar6aszhrdax7xux5udjxgi
Bayesian models for functional magnetic resonance imaging data analysis
2014
Wiley Interdisciplinary Reviews: Computational Statistics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
We divide methods according to the objective of the analysis. We start from spatiotemporal models for fMRI data that detect task-related activation patterns. ...
A remarkable feature of fully Bayesian approaches is that they allow a flexible modeling of spatial and temporal correlations in the data. ...
ACKNOWLEDGMENTS We wish to thank the Editor and the three referees for their constructive comments. ...
doi:10.1002/wics.1339
pmid:25750690
pmcid:PMC4346370
fatcat:jqt3gog5f5h7hcceqnbve2mtye
Neuro-Current Response Functions: A Unified Approach to MEG Source Analysis under the Continuous Stimuli Paradigm
[article]
2019
bioRxiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
cortex via source localization, or the neuroimaging data are first mapped to the cortex followed by estimating TRFs for each of the resulting cortical sources. ...
In summary, we provide a principled modeling and estimation paradigm for MEG source analysis tailored to extracting the cortical origin of electrophysiological responses to continuous stimuli. ...
To this end, we developed a fast inverse solution under a Bayesian estimation setting, the Champ-Lasso algorithm, for inferring the Neuro-Current Response Functions (as spatiotemporal models of cortical ...
doi:10.1101/761999
fatcat:izvlv7aslvannb6yl7pidoo3zi
Hierarchical multiscale Bayesian algorithm for robust MEG/EEG source reconstruction
2018
NeuroImage
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
We then derive a novel Bayesian algorithm for probabilistic inference with this graphical model. ...
In this paper, we present a novel hierarchical multiscale Bayesian algorithm for electromagnetic brain imaging using magnetoencephalography (MEG) and electroencephalography (EEG). ...
We would also like to thank Julia Owen for the support of MEG data simulation and evaluation, Hagai Attias for inspiration and early discussions, and Inez Raharjo for editing. ...
doi:10.1016/j.neuroimage.2018.07.056
pmid:30059734
pmcid:PMC6214686
fatcat:sm4x7k7ri5fzrp3yiirjzsbeea
Automatic fMRI-guided MEG multidipole localization for visual responses
2009
Human Brain Mapping
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Previously, we introduced the use of individual cortical location and orientation constraints in the spatiotemporal Bayesian dipole analysis setting proposed by Jun et al. ([2005]; Neuroimage 28:84-98) ...
On this account, the algorithm acts perhaps more as a stochastic optimizer than enables a full Bayesian posterior analysis. ...
Marja Balk for assistance in gathering the functional magnetic resonance imaging data. ...
doi:10.1002/hbm.20570
pmid:18465749
fatcat:3o72hithqnaqvcboxy3x6kykce
Bayesian inverse analysis of neuromagnetic data using cortically constrained multiple dipoles
2007
Human Brain Mapping
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
A recently introduced Bayesian model for magnetoencephalographic (MEG) data consistently localized multiple simulated dipoles with the help of marginalization of spatiotemporal background noise covariance ...
structure in the analysis : Neuroimage 28:84-98]. ...
Recently, Jun et al. [2005] proposed a Bayesian inference technique for multiple dipole analysis of MEG data having a full spatiotemporal sensor space noise covariance structure. ...
doi:10.1002/hbm.20334
pmid:17370346
fatcat:grquxtfpmrgntkwwrvsgkfbhyi
Population-level inferences for distributed MEG source localization under multiple constraints: Application to face-evoked fields
2007
NeuroImage
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
We address some key issues entailed by population inference about responses evoked in distributed brain systems using magnetoencephalography (MEG). ...
At the within-subject level, we focused on the use of multiple constraints, or priors, for inverting distributed source models. ...
Introduction This paper is about the analysis of multi-subject MEG data using distributed source estimates. ...
doi:10.1016/j.neuroimage.2007.07.026
pmid:17888687
fatcat:zl4nioeoxrey7comjgx7qgbyd4
Proceedings: ISBET 200 – 14th World Congress of the International Society for Brain Electromagnetic Topography, November 19-23, 2003
2003
Brain Topography
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Signal-space separation (SSS) is applied for head movement correction and noise compensation. For method developers, MATLAB interface exists for MEG/EEG, MRI, MCE and dipole data. ...
The BESA (Brain Electrical Source Analysis) program provides a large variety of tools for the complete analysis of EEG and MEG recordings. ...
We use a dipole based spatiotemporal Bayesian inference analysis to demonstrate the use of this noise model [3] . ...
doi:10.1023/b:brat.0000019284.29068.8d
fatcat:tpvp3dcojrczjkuzcu3xefyizy
« Previous
Showing results 1 — 15 out of 208 results