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84
Dynamic causal modelling of evoked responses
 in EEG and MEG. NeuroImage
"... EEG/MEG with lead field parameterization ..."
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MEG source localization under multiple constraints: an extended Bayesian framework
 NeuroImage
, 2006
"... To use Electroencephalography (EEG) and Magnetoencephalography (MEG) as functional brain 3D imaging techniques, identifiable distributed source models are required. The reconstruction of EEG/ MEG sources rests on inverting these models and is illposed because the solution does not depend continuous ..."
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Cited by 28 (4 self)
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To use Electroencephalography (EEG) and Magnetoencephalography (MEG) as functional brain 3D imaging techniques, identifiable distributed source models are required. The reconstruction of EEG/ MEG sources rests on inverting these models and is illposed because the solution does not depend continuously on the data and there is no unique solution in the absence of prior information or constraints. We have described a general framework that can account for several priors in a common inverse solution. An empirical Bayesian framework based on hierarchical linear models was proposed for the analysis of
Dynamic causal modelling of evoked responses in eeg/meg with leadfield parameterization. Under revision
, 2005
"... Neuronally plausible, generative or forward models are essential for understanding how eventrelated fields (ERFs) and potentials (ERPs) are generated. In this paper, we present a new approach to modeling eventrelated responses measured with EEG or MEG. This approach uses a biologically informed mo ..."
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Cited by 28 (16 self)
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Neuronally plausible, generative or forward models are essential for understanding how eventrelated fields (ERFs) and potentials (ERPs) are generated. In this paper, we present a new approach to modeling eventrelated responses measured with EEG or MEG. This approach uses a biologically informed model to make inferences about the underlying neuronal networks generating responses. The approach can be regarded as a neurobiologically constrained source reconstruction scheme, in which the parameters of the reconstruction have an explicit neuronal interpretation. Specifically, these parameters encode, among other things, the coupling among sources and how that coupling depends upon stimulus attributes or experimental context. The basic idea is to supplement conventional electromagnetic forward models, of how sources are expressed in measurement space, with a model of how source activity is generated by neuronal dynamics. A single inversion of this extended forward model enables inference about both the spatial deployment of sources and the underlying neuronal architecture generating them. Critically, this inference covers longrange connections among welldefined neuronal subpopulations. In a previous paper, we simulated ERPs using a hierarchical neuralmass model that embodied bottomup, topdown and lateral connections among remote regions. In this paper, we describe a Bayesian procedure to estimate the parameters of this model using empirical data. We demonstrate this procedure by characterizing the role of changes in corticocortical coupling, in the genesis of ERPs. In the first experiment, ERPs recorded during the perception of faces and houses were modeled as distinct cortical sources in the ventral visual pathway. Categoryselectivity, as indexed by the faceAbbreviations: DCM, dynamic causal Model(ing); EEG, electroencephalography; ERF, eventrelated field; ERP, eventrelated potential;
Mapping human brain function with MEG and EEG: methods and validation
 NeuroImage
, 2004
"... We survey the field of magnetoencephalography (MEG) and electroencephalography (EEG) source estimation. These modalities offer the potential for functional brain mapping with temporal resolution in the millisecond range. However, the limited number of spatial measurements and the illposedness of th ..."
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Cited by 20 (0 self)
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We survey the field of magnetoencephalography (MEG) and electroencephalography (EEG) source estimation. These modalities offer the potential for functional brain mapping with temporal resolution in the millisecond range. However, the limited number of spatial measurements and the illposedness of the inverse problem present significant limits to our ability to produce accurate spatial maps from these data without imposing major restrictions on the form of the inverse solution. Here we describe approaches to solving the forward problem of computing the mapping from putative inverse solutions into the data space. We then describe the inverse problem in terms of low dimensional solutions, based on the equivalent current dipole (ECD), and high dimensional solutions, in which images of neural activation are constrained to the cerebral cortex. We also address the issue of objective assessment of the relative performance of inverse procedures by the freeresponse receiver operating characteristic (FROC) curve. We conclude with a discussion of methods for assessing statistical significance of experimental results through use of the bootstrap for determining confidence regions in dipolefitting methods, and random field (RF) and permutation methods for detecting significant activation in cortically constrained imaging studies.
Leadfield Bases for Electroencephalography Source Imaging
, 2000
"... In recent years, significant progress has been made in the area of electroencephalography (EEG) source imaging. Source localization on simple spherical models has become increasingly efficient, with consistently reported accuracy of within 5 mm. In contrast, source localization on realistic head mod ..."
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Cited by 12 (1 self)
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In recent years, significant progress has been made in the area of electroencephalography (EEG) source imaging. Source localization on simple spherical models has become increasingly efficient, with consistently reported accuracy of within 5 mm. In contrast, source localization on realistic head models remains slow, with subcentimeter accuracy being the exception rather than the norm. A primary reason for this discrepancy is that most source imaging techniques are based on lead fields. While the lead field for simplied geometries can be easily computed analytically, an efficient method for computing realistic domain lead fields has, until now, remained elusive. In this paper, we propose two efficient methods for computing realistic EEG leadfield bases: the first is element oriented, and the second is node oriented. We compare these two bases, discuss how they can be used to apply recent source imaging methods to realistic models, and report timings for constructing the bases.
The Fast Multipole Method for the Direct E/MEG Problem
 in Proceedings of ISBI
, 2002
"... Reconstructing neuronal activity from MEG and EEG measurements requires the accurate calculation of the electromagnetic field inside the head. The boundary element formulation of this problem leads to a dense linear system which is too large to be solved directly. We propose to accelerate the comput ..."
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Cited by 8 (5 self)
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Reconstructing neuronal activity from MEG and EEG measurements requires the accurate calculation of the electromagnetic field inside the head. The boundary element formulation of this problem leads to a dense linear system which is too large to be solved directly. We propose to accelerate the computations via the fast multipole method. This method approximates the electromagnetic interaction between surface elements by performing multipole expansions at a coarse resolution. It significantly reduces the computational complexity of the matrixvector products needed for the iterative solution of the linear system, and avoids the storage of its matrix. We describe the singlelevel fast multipole method and present several experiments demonstrating its accuracy and performance.
Symmetric BEM formulation for the M/EEG forward problem
 Information Processing in Medical Imaging, volume 2732 of LNCS
, 2003
"... Abstract. The forward M/EEG problem consists in simulating the electric potential and the magnetic field produced outside the head by currents in the brain related to neural activity. All previously proposed solutions using the Boundary Element Method (BEM) were based on a doublelayer integral form ..."
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Cited by 7 (5 self)
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Abstract. The forward M/EEG problem consists in simulating the electric potential and the magnetic field produced outside the head by currents in the brain related to neural activity. All previously proposed solutions using the Boundary Element Method (BEM) were based on a doublelayer integral formulation. We have developed an alternative symmetric BEM formulation, achieving a significantly higher accuracy for sources close to tissue interfaces, namely in the cortex. Numerical experiments using a spherical semirealistic multilayer head model with a known analytical solution are presented, showing that the new BEM performs better than the formulations used in our earlier comparisons, and in most cases outperforms the Finite Element Method (FEM) as far as accuracy is concerned, thus making the BEM a viable choice. 1
Volume currents in forward and inverse magnetoencephalographic simulations using realistic head models
 Annals of Biomedical Engineering
, 2003
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Biologicallydriven Musical Instrument
"... Abstract — This project proposes to use the analysis of physiological signals (electroencephalogram (EEG), electromyogram (EMG), heart beats) to control sound synthesis algorithms in order to build a biologically driven musical instrument. This project took place during the eNTERFACE’05 summer works ..."
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Cited by 4 (0 self)
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Abstract — This project proposes to use the analysis of physiological signals (electroencephalogram (EEG), electromyogram (EMG), heart beats) to control sound synthesis algorithms in order to build a biologically driven musical instrument. This project took place during the eNTERFACE’05 summer workshop in Mons, Belgium. Over four weeks specialists from the fields of brain computer interfaces and sound synthesis worked together to produce playable biologically controlled musical instruments. Indeed, a ”bio orchestra”, with three new digital musical instruments controlled by physiological signals of two biomusicians on stage, was offered to a live audience.
On the Weak Solutions of the Forward Problem in EEG
 Journal of Applied Mathematics
"... The process underlying the generation of the EEG signals can be described as a set of current sources within the brain. The potential distribution produced by these sources can be measured on the scalp and inside the brain by means of an EEG recorder. There is a wellknown mathematical model that ..."
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Cited by 3 (2 self)
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The process underlying the generation of the EEG signals can be described as a set of current sources within the brain. The potential distribution produced by these sources can be measured on the scalp and inside the brain by means of an EEG recorder. There is a wellknown mathematical model that relates the electric potential in the head with the intracerebral sources. In this paper, we study and prove some properties of the solutions of the model for known sources. In particular, we study the error in the potential, introduced by considering an approximated shape of the head. 1.