Dealing with mismatched fMRI activations in fMRI constrained EEG cortical source imaging: a simulation study assuming various mismatch types

Although fMRI constrained EEG source imaging could be a promising approach to enhancing both spatial and temporal resolutions of independent fMRI and EEG analyses, it has been frequently reported that a hard fMRI constraint may cause severe distortion or elimination of significant EEG sources when there are distinct mismatches between fMRI activations and EEG sources. If estimating actual EEG source locations is important and fMRI prior information is used as an auxiliary tool to enhance the concentration of widespread EEG source distributions, it is reasonable to weaken the fMRI constraint when significantly mismatched sources exist. The present study demonstrates that the mismatch problem may be partially solved by extending the prior fMRI activation regions based on the conventional source imaging results. A hard fMRI constraint is then applied when there is no distinct mismatch, while a weakened fMRI constraint is applied when there are significant mismatches. A preliminary simulation study assuming different types of mismatches such as fMRI invisible, extra, and discrepancy sources demonstrated that this approach can be a promising option to treat mismatched fMRI activations in fMRI constrained EEG source imaging.     

Anatomically constrained dipole adjustment (ANACONDA) for accurate MEG/EEG focal source localizations

This paper proposes an alternative approach to enhance localization accuracy of MEG and EEG focal sources. The proposed approach assumes anatomically constrained spatio-temporal dipoles, initial positions of which are estimated from local peak positions of distributed sources obtained from a pre-execution of distributed source reconstruction. The positions of the dipoles are then adjusted on the cortical surface using a novel updating scheme named cortical surface scanning. The proposed approach has many advantages over the conventional ones: (1) as the cortical surface scanning algorithm uses spatio-temporal dipoles, it is robust with respect to noise; (2) it requires no a priori information on the numbers and initial locations of the activations; (3) as the locations of dipoles are restricted only on a tessellated cortical surface, it is physiologically more plausible than the conventional ECD model. To verify the proposed approach, it was applied to several realistic MEG/EEG simulations and practical experiments. From the several case studies, it is concluded that the anatomically constrained dipole adjustment (ANACONDA) approach will be a very promising technique to enhance accuracy of focal source localization which is essential in many clinical and neurological applications of MEG and EEG.     

Simultaneous MEG and EEG source analysis

A method is described to derive source and conductivity estimates in a simultaneous MEG and EEG source analysis. In addition the covariance matrix of the estimates is derived. Simulation studies with a concentric spheres model and a more realistic boundary element model indicate that this method has several advantages, even if only a few EEG sensors are added to a MEG configuration. First, a simultaneous analysis profits from the 'preferred' location directions of MEG and EEG. Second, deep sources can be estimated quite accurately, which is an advantage compared to MEG. Third, superficial sources profit from accurate MEG location and from accurate EEG moment. Fourth, the radial source component can be estimated, which is an advantage compared to MEG. Fifth, the conductivities can be estimated. It is shown that conductivity estimation gives a substantial increase in precision, even if the conductivities are not identified appropriately. An illustrative analysis of empirical data supports these findings.     

Role of neuronal synchrony in the generation of evoked EEG/MEG responses

Evoked EEG/MEG responses are a primary real-time measure of perceptual and cognitive activity in the human brain, but their neuronal generator mechanisms are not yet fully understood. Arguments have been put forward in favor of either "phase-reset" of ongoing oscillations or "added-energy" models. Instead of advocating for one or the other model, here we show theoretically that the differentiation between these two generation mechanisms might not be possible if based solely on macroscopic EEG/MEG recordings. Using mathematical modeling, we show that a simultaneous phase reset of multiple oscillating neuronal (microscopic) sources contributing to EEG/MEG can produce evoked responses in agreement with both, the "added-energy" and the "phase-reset" model. We observe a smooth transition between the two models by just varying the strength of synchronization between the multiple microscopic sources. Consequently, because precise knowledge about the strength of microscopic ensemble synchronization is commonly not available in noninvasive EEG/MEG studies, they cannot, in principle, differentiate between the two mechanisms for macroscopic-evoked responses.     

Localization of coherent sources by simultaneous MEG and EEG beamformer

Simultaneous magnetoencephalography (MEG) and electroencephalography (EEG) analysis is known generally to yield better localization performance than a single modality only. For simultaneous analysis, MEG and EEG data should be combined to maximize synergistic effects. Recently, beamformer for simultaneous MEG/EEG analysis was proposed to localize both radial and tangential components well, while single modality analyses could not detect them, or had relatively higher location bias. In practice, most interesting brain sources are likely to be activated coherently; however, conventional beamformer may not work properly for such coherent sources. To overcome this difficulty, a linearly constrained minimum variance (LCMV) beamformer may be used with a source suppression strategy. In this work, simultaneous MEG/EEG LCMV beamformer using source suppression was formulated firstly to investigate its capability over various suppression strategies. The localization performance of our proposed approach was examined mainly for coherent sources and compared thoroughly with the conventional simultaneous and single modality approaches, over various suppression strategies. For this purpose, we used numerous simulated data, as well as empirical auditory stimulation data. In addition, some strategic issues of simultaneous MEG/EEG analysis were discussed. Overall, we found that our simultaneous MEG/EEG LCMV beamformer using a source suppression strategy is greatly beneficial in localizing coherent sources.     

Sensitivity of MEG and EEG to Source Orientation

An important difference between magnetoencephalography (MEG) and electroencephalography (EEG) is that MEG is insensitive to radially oriented sources. We quantified computationally the dependency of MEG and EEG on the source orientation using a forward model with realistic tissue boundaries. Similar to the simpler case of a spherical head model, in which MEG cannot see radial sources at all, for most cortical locations there was a source orientation to which MEG was insensitive. The median value for the ratio of the signal magnitude for the source orientation of the lowest and the highest sensitivity was 0.06 for MEG and 0.63 for EEG. The difference in the sensitivity to the source orientation is expected to contribute to systematic differences in the signal-to-noise ratio between MEG and EEG.     

Assessment criteria for MEG/EEG cortical patch tests

To validate newly developed methods or implemented software for magnetoencephalography/electroencephalography (MEG/EEG) source localization problems, many researchers have used human skull phantom experiments or artificially constructed forward data sets. Between the two methods, the use of an artificial data set constructed with forward calculation attains superiority over the use of a human skull phantom in that it is simple to implement, adjust and control various conditions. Nowadays, for the forward calculation, especially for the cortically distributed source models, generating artificial activation patches on a brain cortical surface has been popularized instead of activating some point dipole sources. However, no well-established assessment criterion to validate the reconstructed results quantitatively has yet been introduced. In this paper, we suggest some assessment criteria to compare and validate the various MEG/EEG source localization techniques or implemented software applied to the cortically distributed source model. Four different criteria can be used to measure accuracy, degrees of focalization, noise-robustness, existence of spurious sources and so on. To verify the usefulness of the proposed criteria, four different results from two different noise conditions and two different reconstruction techniques were compared for several patches. The simulated results show that the new criteria can provide us with a reliable index to validate the MEG/EEG source localization techniques.     

Integrated Analysis of EEG and fMRI Using Sparsity of Spatial Maps

Integration of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is an open problem, which has motivated many researches. The most important challenge in EEG-fMRI integration is the unknown relationship between these two modalities. In this paper, we extract the same features (spatial map of neural activity) from both modality. Therefore, the proposed integration method does not need any assumption about the relationship of EEG and fMRI. We present a source localization method from scalp EEG signal using jointly fMRI analysis results as prior spatial information and source separation for providing temporal courses of sources of interest. The performance of the proposed method is evaluated quantitatively along with multiple sparse priors method and sparse Bayesian learning with the fMRI results as prior information. Localization bias and source distribution index are used to measure the performance of different localization approaches with or without a variety of fMRI-EEG mismatches on simulated realistic data. The method is also applied to experimental data of face perception of 16 subjects. Simulation results show that the proposed method is significantly stable against the noise with low localization bias. Although the existence of an extra region in the fMRI data enlarges localization bias, the proposed method outperforms the other methods. Conversely, a missed region in the fMRI data does not affect the localization bias of the common sources in the EEG-fMRI data. Results on experimental data are congruent with previous studies and produce clusters in the fusiform and occipital face areas (FFA and OFA, respectively). Moreover, it shows high stability in source localization against variations in different subjects.     

On the EEG/MEG forward problem solution for distributed cortical sources

In studies of EEG/MEG problems involving cortical sources, the cortex may be modeled by a 2-D manifold inside the brain. In such cases the primary or impressed current density over this manifold is usually approximated by a set of dipolar sources located at the vertices of the cortical surface tessellation. In this study, we analyze the different errors induced by this approximation on the EEG/MEG forward problem. Our results show that in order to obtain more accurate solutions of the forward problems with the multiple dipoles approximation, the moments of the dipoles should be weighted by the area of the surrounding triangles, or using an alternative approximation of the primary current as a constant or linearly varying current density over plane triangular elements of the cortical surface tessellation. This should be taken into account when computing the lead field matrix for solving the EEG/MEG inverse problem in brain imaging methods.     

A method for combining MEG and EEG to determine the sources

A three-step method is presented which combines an MEG and EEG map over the head to solve the inverse problem (to determine the sources). This method uses the feature that the MEG does not see a radial source, but only a tangential source, while the EEG sees both. A first test is also made of the method, using computer simulation, and the results presented. The purpose of the test is to see if the method is valid with noisy MEG and EEG data, and when some modelling errors are present; a single dipole source was used in a spherical head. It was found that the method works well when the RMS noise at each map location is 5% of the maximum MEG and EEG (readily attained in practice), but breaks down when the noise is 10% (quite noisy data). The modelling errors involved grid size, head radius and distance to the MEG coil, and were studied only through the first step of the method; with errors in a reasonable range, this limited test again worked well.     

EEG versus MEG localization accuracy: Theory and experiment

Summary We first review the theoretical and computer modelling studies concerning localization accuracy of EEG and MEG, both separately and together; the source is here a dipole. The results show that, of the three causes of localization errors, noise and head modelling errors have about the same effect on EEG and MEG localization accuracies, while the results for measurement placement errors are inconclusive. Thus, these results to date show no significant superiority of MEG over EEG localization accuracy. Secondly, we review the experimental findings, where there are again localization accuracy studies of EEG and MEG both separately and together. The most significant EEG-only study was due to dipoles implanted in the heads of patients, and produced an average localization error of 20 mm. Various MEG-only studies gave an average error of 2–3 mm in saline spheres and 4–8 mm in saline-filled skulls. In the one study where EEG and MEG localization were directly compared in the same actual head, again using dipoles implanted in patients, the average EEG and MEG errors of localization were 10 and 8 mm respectively. The MEG error was later confirmed by a similar (but MEG-only) experiment in another study, using a more elaborate MEG system. In summary, both theory and experiment suggests that the MEG offers no significant advantage over the EEG in the task of localizing a dipole source. The main use of the MEG, therefore, should be based on the proven feature that the MEG signal from a radial source is highly suppressed, allowing it to complement the EEG in selecting between competing source configurations. A secondary useful feature is that it handles source modelling errors differently than does the EEG, allowing it to help clarify non-dipolar extended sources.This work was supported by grants RO1NS26433, RO1NS19558 and RO1NS22703 from the National Institutes of Health.     

Spatio-temporal Regularization in Linear Distributed Source Reconstruction from EEG/MEG: A Critical Evaluation

The high temporal resolution of EEG/MEG data offers a way to improve source reconstruction estimates which provide insight into the spatio-temporal involvement of neuronal sources in the human brain. In this work, we investigated the performance of spatio-temporal regularization (STR) in a current density approach using a systematic comparison to simple ad hoc or post hoc filtering of the data or of the reconstructed current density, respectively. For the used STR approach we implemented a frequency-specific constraint to penalize solutions outside a narrow frequency band of interest. The widely used sLORETA algorithm was adapted for STR and generally used for source reconstruction. STR and filtering approaches were evaluated with respect to spatial localization error and spatial dispersion, as well as to correlation of original and reconstructed source time courses in single source and two source scenarios with fixed source locations and oscillating source waveforms. We used extensive computer simulations and tested all algorithms with different parameter settings (noise levels and regularization parameters) for EEG data. To verify our results, we also used data from MEG phantom measurements. For the investigated scenarios, we did not find any evidence that STR-based methods outperform purely spatial algorithms applied to temporally filtered data. Furthermore, the results show very clearly that the performance of STR depends very much on the choice of regularization parameters.     

Source models of sleep spindles using MEG and EEG measurements

Summary MEG measurements can detect brain sources that are difficult to detect with EEG measurements. The purpose of this study was to investigate models of sleep spindles using both MEG and EEG activity that had been recorded simultaneously. The components of magnetic fields perpendicular to the surface of the head were measured using a DC-SQUID with a first-derivative gradiometer. We propose three models for sleep spindles. In the first model, the source slides into the superficial region of the head so as to be perpendicular to it's surface, and with this model, the power spectrum of the MEG is decreased. In the second model, the source slides into the deeper structures, so that it is perpendicular to the surface. Here, the power spectra of both the MEG and the EEG are decreased. The third model has the source perpendicular to the surface, leaning and sliding into the deeper structures. Here, the power spectrum of the EEG is decreased but that of the MEG is not.     

Interpreting abnormality: an EEG and MEG study of P50 and the auditory paired-stimulus paradigm

Interpretation of neurophysiological differences between control and patient groups on the basis of scalp-recorded event-related brain potentials (ERPs), although common and promising, is often complicated in the absence of information on the distinct neural generators contributing to the ERP, particularly information regarding individual differences in the generators. For example, while sensory gating differences frequently observed in patients with schizophrenia in the P50 paired-click gating paradigm are typically interpreted as reflecting group differences in generator source strength, differences in the latency and/or orientation of P50 generators may also account for observed group differences. The present study examined how variability in source strength, amplitude, or orientation affects the P50 component of the scalp-recorded ERP. In Experiment 1, simulations examined the effect of changes in source strength, orientation, or latency in superior temporal gyrus (STG) dipoles on P50 recorded at Cz. In Experiment 2, within- and between-subject variability in left and right M50 STG dipole source strength, latency, and orientation was examined in 19 subjects. Given the frequently reported differences in left and right STG anatomy and function, substantial inter-subject and inter-hemispheric variability in these parameters were expected, with important consequences for how P50 at Cz reflects brain activity from relevant generators. In Experiment 1, simulated P50 responses were computed from hypothetical left- and right-hemisphere STG generators, with latency, amplitude, and orientation of the generators varied systematically. In Experiment 2, electroencephalographic (EEG) and magnetoencephalographic (MEG) data were collected from 19 subjects. Generators were modeled from the MEG data to assess and illustrate the generator variability evaluated parametrically in Experiment 1. In Experiment 1, realistic amounts of variability in generator latency, amplitude, and orientation produced ERPs in which P50 scoring was compromised and interpretation complicated. In Experiment 2, significant within and between subject variability was observed in the left and right hemisphere STG M50 sources. Given the variability in M50 source strength, orientation, and amplitude observed here in nonpatient subjects, future studies should examine whether group differences in P50 gating ratios typically observed for patient vs. control groups are specific to a particular hemisphere, as well as whether the group differences are due to differences in dipole source strength, latency, orientation, or a combination of these parameters. Present analyses focused on P50/M50 merely as an example of the broader need to evaluate scalp phenomena in light of underlying generators. The development and widespread use of EEG/MEG source localization methods will greatly enhance the interpretation and value of EEG/MEG data.     

The Existence of Two Sources in Rolandic Epilepsy: Confirmation with High Resolution EEG, MEG and fMRI

In benign rolandic epilepsy seizure semiology suggests that the epileptic focus resides in the lower sensorimotor cortex. Previous studies involving dipole modeling based on 32 channel EEG have confirmed this localization. These studies have also suggested that two distinct dipole sources are required to adequately describe the typical interictal spikes. Since in benign epilepsy invasive validation is prohibited, this study tries to further establish these results using a multi-modal approach, involving 32 channel EEG, high resolution 84 channel EEG, 151 channel MEG and fMRI. From one patient interictal spikes were recorded and analyzed using the MUSIC algorithm in a realistic volume conductor model. In an fMRI experiment the same patient performed voluntary tongue movements, thus mimicking a typical seizure. Results show that EEG, MEG and fMRI localization converge on the same area in the lower part of the sensorimotor cortex, and that high resolution EEG clearly reveals two distinct sources, one in the post- and one in the pre-central cortex.     

MEG and EEG Sensitivity in a Case of Medial Occipital Epilepsy

Interictal or ictal events in partial epilepsies may project on scalp EEG contralaterally to the side of the epileptogenic lesion. Such paradoxical lateralization can be observed in case of para-sagittal generators, and is likely due to the spatial orientation of the generator, presenting an oblique projection towards the midline. We present here a case of medial occipital epilepsy investigated using EEG, MEG and stereoelectroencephalography (SEEG). MRI displayed a focal cortical dysplasia in the superior margin of the right calcarine fissure. SEEG demonstrated bilateral medial occipital interictal spikes, with an inversion of polarity at the level of the lesion and a contralateral propagation occurring in 10 ms. Interictal iterative EEG cartographies showed a large posterior field, with a maximum contralateral to the initial generator (EEG paradoxical lateralization). With the same number of channels, interictal iterative MEG cartographies were more precise and more complex than EEG ones, indicating an onset accurately lateralized. A few milliseconds later, MEG cartographies were quadripolar, thus indicating two homotopic active generators. These MEG and EEG cartographies have been reproduced using BESA dipole simulator. Relative merits of MEG and EEG are still debated. With 151 channels, MEG source localizations indicated the right medial occipital area, as demonstrated by SEEG. An investigation with a corresponding number of EEG channels was not performed. After a down sampling to 64 sensors, this precision was lost. MEG and EEG source localization results, both with 64 channels, were quite comparable, indicating both medial occipital areas. However, a careful analysis of MEG/EEG iterative cartographies, performed with the same number of channels in both modalities, demonstrated that, in this configuration, MEG sensitivity was superior to the EEG one, allowing separating two medial occipital sources, characterized in SEEG by a time delay of 10 ms.     

Integrated MEG/fMRI Model Validated Using Real Auditory Data

The main objective of this paper is to present methods and results for the estimation of parameters of our proposed integrated magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) model. We use real auditory MEG and fMRI datasets from 7 normal subjects to estimate the parameters of the model. The MEG and fMRI data were acquired at different times, but the stimulus profile was the same for both techniques. We use independent component analysis (ICA) to extract activation-related signal from the MEG data. The stimulus-correlated ICA component is used to estimate MEG parameters of the model. The temporal and spatial information of the fMRI datasets are used to estimate fMRI parameters of the model. The estimated parameters have reasonable means and standard deviations for all subjects. Goodness of fit of the real data to our model shows the possibility of using the proposed model to simulate realistic datasets for evaluation of integrated MEG/fMRI analysis methods.     

Modeling and source localization of MEG activities

Summary During the past decade, substantial advances in the understanding of the functional organization of the human brain have been made through the technique of MEG topographic mapping. Most of these investigations were concerned with the estimation and localization of sources which were modeled as single current dipoles positioned in a semi-infinite volume conductor with homogeneous conductivity. However, the sources in the brain are complex, and the head as a volume conductor consists of different materials with different electrical conductivities. The influence of these inhomogeneities on the MEG topography is studied by a computer simulation, modeling the sources as single or multiple dipoles located in inhomogeneous volume conductors. The computer simulation suggests some important aspects in estimation of source localization. The sources of MEG activities in human subject during sleep are also studied. A comparison of simulated MEG topographic patterns with measured data suggests that the sources of K-complexes can be modeled by two current dipoles. Sources for delta waves are analyzed by the FFT technique. The results show that the frequency distributions are different for delta waves measured by MEG and EEG techniques, leading us to conclude that at least two different sources are present. The MEG measurements have an advantage to provide important information concerning brain function which cannot be obtained using the EEG measurements.This work was supported in part by grants 63850090 and 01790390 from the Ministry of Education Science and Culture, Japan, and by grants from Nakatani Electric Measuring Technology Association, and the Mitsubishi Foundation.     

MEG and EEG topography of frontal midline theta rhythm and source localization

Summary In this paper, we report on our study of frontal midline theta (Fm) activity in human subjects, recorded during mental processes such as arithmetic calculation. The Fm is a 6–7 Hz rhythmic wave with a duration of few seconds. The Fm activity is observed in the central region at the front of the head. EEGs and MEGs of Fm were measured simultaneously during mental calculation, and we analyzed these waveforms based on both topographic EEG maps and magnetic fields measurements. A single dipole simulated the EEG topography adequately, but there are many other dipole models which can generate a similar EEG pattern. It is difficult to estimate the source location of the Fm from the EEG topography alone because the EEG technique has a certain ambiguity associated with source estimation. Therefore, we considered the spatial relationships between the sources and the patterns of EEG and MEG that were simulated. Although it is not possible to obtain a unique solution for the source location of Fm from the EEG data alone, the simultaneous recording of MEGs from a large scalp area may result in an unambiguous solution. We therefore conclude that the simultaneous recording of both MEG and EEG data is more useful for accurate localization, than the EEG alone.