Jiri Vrba

Optimising experimental design for MEG beamformer imaging

In recent years, the use of beamformers for source localisation has significantly improved the spatial accuracy of magnetoencephalography. In this paper, we examine techniques by which to optimise experimental design, and ensure that the application of beamformers yields accurate results. We show that variation in the experimental duration, or variation in the bandwidth of a signal of interest, can significantly affect the accuracy of a beamformer reconstruction of source power. Specifically, power will usually be underestimated if covariance windows are made too short, or bandwidths too narrow. The accuracy of spatial localisation may also be reduced. We conclude that for optimum accuracy, experimenters should aim to collect as much data as possible, and use a bandwidth spanning the entire frequency distribution of the signal of interest. This minimises distortion to reconstructed source images, time courses and power estimation. In the case where experimental duration is short, and small covariance windows are therefore used, we show that accurate power estimation can be achieved by matrix regularisation. However, large amounts of regularisation cause a loss in the spatial resolution of the MEG beamformer, hence regularisation should be used carefully, particularly if multiple sources in close proximity are expected.

Magnetoencephalographic recordings of visual evoked brain activity in the human fetus

We investigated the feasibility of recording visual evoked brain activity in the human fetus by use of non-invasive magnetoencephalography (MEG). Each recording lasted 6 min and consisted of a sequence of 180 flashes with 33 ms duration delivered 2 s apart over the maternal abdomen. Four of ten fetuses included showed a response; the ranges of amplitude and latency of peak response were 15-30 x 10(-15) Tesla and 180-390 ms, respectively. Six fetuses showed no discernible response. With improvement, this method could aid in the testing of fetal neurological status throughout pregnancy.

Fetal MEG redistribution by projection operators

The fetal magnetoencephalogram (fMEG) is measured in the presence of large interference from the maternal and fetal magnetocardiograms. This interference can be efficiently attenuated by orthogonal projection of the corresponding spatial vectors. However, the projection operators redistribute the fMEG signal among sensors. Although redistribution can be readily accounted for in the forward solution, visual interpretation of the fMEG signal topography is made difficult. We have devised a general, model-independent method for correction of the redistribution effect that utilizes the assumption that we know in which channels the fMEG should be negligible (such channels are distant from the known fetal head position). In a simplified case where the fMEG can be explained by equivalent current dipoles, the correction can also be obtained from fitting the dipoles to the fMEG signal. The corrected fMEG signal topography then corresponds to the dipole forward solution, but without orthogonal projection. We illustrate the redistribution correction on an example of experimentally measured flash evoked fMEG.

Magnetoencephalography: the art of finding a needle in a haystack

Abstract The brains magnetic signals are much weaker than the magnetic disturbances inside the typical commercial magnetically-shielded room. Magnetic noise arises from far-field environmental sources (power lines, vehicles, etc.) and from near-field biological sources (electrically active tissues, such as muscle, heart, unwanted brain signals, etc.). Some form of inverse solution is generally used to solve for the sources that account for the MEG measurements. However, the inversion problem is non-unique and ill defined. Given the large amounts of noise and the non-uniqueness, how can MEG inversion succeed? One must provide methods for efficient attenuation of environmental noise, combined with MEG localization methods that are robust against the background clutter. Noise cancellation methods will be reviewed, and it will be shown that a combination of synthetic gradiometers, adaptive signal processing, and moderately shielded rooms can provide environmental noise attenuation in excess of 10 7 . Two types of MEG signal analysis techniques will be discussed: those depending solely on prior noise cancellation (e.g., equivalent current dipole fit and minimum norm), and those intrinsically providing additional cancellation of far and near field noise (e.g., beamformers). The principles and behavior of beamformers for variations in signal and noise will be explained. Several beamformer classes will be discussed, and the presentation will conclude with examples of their clinical applications.

Short-term serial magnetoencephalography recordings offetal auditory evoked responses.

The study objective was to determine whether short-term serial magnetoencephalographic (MEG) measurements would increase the odds in favor of obtaining fetal auditory evoked responses in normal fetuses. The recordings were performed in two phases using the newly developed 151-channel fetal MEG system, superconducting quantum interference device array for reproductive assessment. Ten pregnant subjects with gestational ages ranging from 30-35 weeks were recruited to participate. Daily recordings were performed over a minimum of 3 days during 1 week of gestation and repeated in the same subjects between 36 and 40 weeks gestation. In 80% of subjects, auditory evoked responses were detected at least once. In healthy fetuses, serial recordings over a short span of time increased the rate of detecting fetal evoked response.

SQUID sensor array configurations for magnetoencephalography applications

Electrophysiological activity in the human brain generates a small magnetic field from the spatial superposition of individual neuronal source currents. At a distance of about 15 mm from the scalp, the observed field is of the order of 10−13 to 10−12 T peak-to-peak. This measurement process is termed magnetoencephalography (MEG). In order to minimize instrumental noise, the MEG is usually detected using superconducting flux transformers, coupled to SQUID (superconducting quantum interference device) sensors. Since MEG signals are also measured in the presence of significant environmental magnetic noise, flux transformers must be designed to strongly attenuate environmental noise, maintain low instrumental noise and maximize signals from the brain. Furthermore, the flux transformers must adequately sample spatial field variations if the brain activity is to be imaged. The flux transformer optimization for maximum brain signal-to-noise ratio (SNR) requires analysis of the spatial and temporal properties of brain activity, the environmental noise and how these signals are coupled to the flux transformer. Flux transformers that maximize SNR can detect the smallest brain signals and have the best ability to spatially separate dipolar sources. An optimal flux transformer design is a synthetic higher-order gradiometer based on relatively short-baseline first-order radial gradiometer primary sensors.

Multichannel SQUID Biomagnetic Systems

The field of biomagnetism advanced considerably since the first recordings of magnetic fields of the human heart in 1963 and of the human brain in 1968. Since the introduction of whole-cortex magnetoencephalography (MEG) systems in 1992, the number of installed channels has dramatically increased, and the magnetic evaluation of the human brain has been gradually finding its place in clinical work. MEG is presently the most important biomagnetic application, and sophisticated MEG systems with large numbers of channels have been developed commercially. The MEG systems must meet certain specifications on noise, dynamic range, slew rate and linearity because they are exposed to environmental noise even when they are operated within shielded rooms. The systems are designed to meet these specifications through optimized design of SQUID flux transformers, SQUID control electronics and data acquisition, and development of various synthetic noise cancellation techniques. The interpretation of the resulting magnetic data is enhanced by combining the MEG results with information from electroencephalography (EEG) and other imaging modalities. In addition, an engineering effort is devoted to the development of various items of MEG peripheral equipment (stimulators, patient support, head positioning, etc.).

Human fetal brain imaging by magnetoencephalography: verification of fetal brain signals by comparison with fetal brain models.

Fetal magnetoencephalogram (fMEG) is measured in the presence of a large interference from maternal and fetal magnetocardiograms (mMCG and fMCG). This cardiac interference can be successfully removed by orthogonal projection of the corresponding spatial vectors. However, orthogonal projection redistributes the fMEG signal among channels. Such redistribution can be readily accounted for in the forward solution, and the signal topography can also be corrected. To assure that the correction has been done properly, and also to verify that the measured signal originates from within the fetal head, we have modeled the observed fMEG by two extreme models where the fetal head is assumed to be either electrically transparent or isolated from the abdominal tissue. Based on the measured spontaneous, sharp wave, and flash-evoked fMEG signals, we have concluded that the model of the electrically isolated fetal head is more appropriate for fMEG analysis. We show with the help of this model that the redistribution due to projection was properly corrected, and also, that the measured fMEG is consistent with the known position of the fetal head. The modeling provides additional confidence that the measured signals indeed originate from within the fetal head.

Optimal reduction of MCG in fetal MEG recordings

Recording fetal magnetoencephalographic (fMEG) signals in-utero is a demanding task due to biological interference, especially maternal and fetal magnetocardiographic (MCG) signals. A method based on orthogonal projection of MCG signal space vectors (OP) was evaluated and compared with independent component analysis (ICA). The evaluation was based on MCG amplitude reduction and signal-to-noise ratio of fetal brain signals using exemplary datasets recorded during ongoing studies related to auditory evoked fields. The results indicate that the OP method is the preferable approach for attenuation of MCG and for preserving the fetal brain signals in fMEG recordings

Investigating spatial specificity and data averaging in MEG

This study shows that the spatial specificity of MEG beamformer estimates of electrical activity can be affected significantly by the way in which covariance estimates are calculated. We define spatial specificity as the ability to extract independent timecourse estimates of electrical brain activity from two separate brain locations in close proximity. Previous analytical and simulated results have shown that beamformer estimates are affected by narrowing the time frequency window in which covariance estimates are made. Here we build on this by both experimental validation of previous results, and investigating the effect of data averaging prior to covariance estimation. In appropriate circumstances, we show that averaging has a marked effect on spatial specificity. However the averaging process results in ill-conditioned covariance matrices, thus necessitating a suitable matrix regularisation strategy, an example of which is described. We apply our findings to an MEG retinotopic mapping paradigm. A moving visual stimulus is used to elicit brain activation at different retinotopic locations in the visual cortex. This gives the impression of a moving electrical dipolar source in the brain. We show that if appropriate beamformer optimisation is applied, the moving source can be tracked in the cortex. In addition to spatial reconstruction of the moving source, we show that timecourse estimates can be extracted from neighbouring locations of interest in the visual cortex. If appropriate methodology is employed, the sequential activation of separate retinotopic locations can be observed. The retinotopic paradigm represents an ideal platform to test the spatial specificity of source localisation strategies. We suggest that future comparisons of MEG source localisation techniques (e.g. beamformer, minimum norm, Bayesian) could be made using this retinotopic mapping paradigm.