Synthetic Gradiometers Research Articles

Addressing magnetometer inconsistencies in drone-borne total field gradiometer surveys: case study from Rånbogen, Arctic Norway

SUMMARY Inconsistencies between (lightweight optical pumped) magnetometers in total field gradiometer surveys can introduce instrument-dependent responses, complicating geological interpretation. Here, we present an equivalent source-based processing method that combines equivalent sources with kernel regression to eliminate these instrument-dependent responses. We evaluate the method using a drone-borne triangular gradiometer survey from Rånbogen, Arctic Norway. The Rånbogen survey exhibits instrument-dependent responses in the measured total field differences, likely resulting from differences in the magnetometer’s heading error and the complexities from the induced field from the system itself. A synthetic gradiometer survey was generated to test the method, where different nonlinear synthetic heading errors were added to the synthetic magnetometer readings. The equivalent source-based processing method effectively removed these heading errors while constructing an equivalent source model that fits the actual underlying synthetic model. Furthermore, applying the method to the Rånbogen survey removes the data’s correlation to its orientation, thereby minimizing the effect of the instrument-dependent response. The method condenses the gradiometer data to a single equivalent source surface where the derivatives of the total field can be calculated to facilitate interpretation. The results suggest that the equivalent source-based method removes the inconsistencies between the magnetometers in a total field gradiometer survey, allowing for drone-borne gradiometer systems with multiple lightweight magnetometers.

Effects of system parameters on a single-beam synthetic gradiometer with a dual-cell structure.

We report a single-beam synthetic gradiometer operated in the spin-exchange-relaxation free (SERF) regime, using the structure of two separate atomic vapor cells spaced 2 cm apart. To improve the capability of the gradiometer in suppressing the common-mode magnetic field noise, we are aiming at investigating the effects of the system parameters on the gradiometer common-mode rejection ratio (CMRR). The mathematical expression for the relationship between the gradiometer CMRR and the two variables including the linewidth ratio and the pumping factor ratio is constructed for the first time, to our knowledge. This means that the CMRR can be optimized by controlling the linewidth and the pumping factor, which is easy to implement in the operation process. As a result, a CMRR of 246 is achieved and a gradiometer sensitivity of 4.5 fT/cm/Hz1/2 is also measured. This method provides a theoretical and experimental basis for the automated operation of gradiometers, and the gradiometer system performance can be tuned to a desired state by simply controlling the linewidth and the incident light intensity.

Improved Biomagnetic Signal-To-Noise Ratio and Source Localization Using Optically Pumped Magnetometers with Synthetic Gradiometers.

Optically pumped magnetometers (OPMs) can capture brain activity but are susceptible to magnetic noise. The objective of this study was to evaluate a novel methodology used to reduce magnetic noise in OPM measurements. A portable magnetoencephalography (MEG) prototype was developed with OPMs. The OPMs were divided into primary sensors and reference sensors. For each primary sensor, a synthetic gradiometer (SG) was constructed by computing a secondary sensor that simulated noise with signals from the reference sensors. MEG data from a phantom with known source signals and six human participants were used to assess the efficacy of the SGs. Magnetic noise in the OPM data appeared predominantly in a low frequency range (<4 Hz) and varied among OPMs. The SGs significantly reduced magnetic noise (p < 0.01), enhanced the signal-to-noise ratio (SNR) (p < 0.001) and improved the accuracy of source localization (p < 0.02). The SGs precisely revealed movement-evoked magnetic fields in MEG data recorded from human participants. SGs provided an effective method to enhance SNR and improve the accuracy of source localization by suppressing noise. Software-simulated SGs may provide new opportunities regarding the use of OPM measurements in various clinical and research applications, especially those in which movement is relevant.

A synthetic optically pumped gradiometer for magnetocardiography measurements**Project supported by the National Natural Science Foundation of China (Grant No. 61701486).

Magnetocardiography (MCG) measurement is important for investigating the cardiac biological activities. Traditionally, the extremely weak MCG signal was detected by using superconducting quantum interference devices (SQUIDs). As a room-temperature magnetic-field sensor, optically pumped magnetometer (OPM) has shown to have comparable sensitivity to that of SQUIDs, which is very suitable for biomagnetic measurements. In this paper, a synthetic gradiometer was constructed by using two OPMs under spin-exchange relaxation-free (SERF) conditions within a moderate magnetically shielded room (MSR). The magnetic noise of the OPM was measured to less than 70 fT/Hz1/2. Under a baseline of 100 mm, noise cancellation of about 30 dB was achieved. MCG was successfully measured with a signal to noise ratio (SNR) of about 37 dB. The synthetic gradiometer technique was very effective to suppress the residual environmental fields, demonstrating the OPM gradiometer technique for highly cost-effective biomagnetic measurements.

Noise cancellation for a whole-head magnetometer-based MEG system in hospital environment

We describe a strategy of removing magnetic field interference for a whole-head pediatric magnetoencephalography (MEG) system (‘babyMEG’) installed in a hospital. The 375-channel sensor array of babyMEG consists entirely of magnetometers in two layers to maximize the sensitivity for detecting MEG signals from infants, toddlers, and young children. It is equipped with a continuously operating closed-cycle helium recycler to reduce the operating costs. These two features pose special challenges for noise cancellation. Our strategy uses a combination of several methods. The system is installed in a light-weight, magnetically shielded room (MSR) equipped with an active external shielding. In addition we employ two software-based techniques—a signal space projection (SSP) technique and a synthetic gradiometer (SG) method—for removing the environmental magnetic noise in real time and displaying the output online. The shielding effects are: passive shielding–36 dB, active shielding–12 dB, SSP–40 dB and SG–40 dB, for a combined maximum shielding of about 90 dB at 0.1 Hz. We evaluated the performance of the babyMEG after applying the noise cancellation techniques. The dipole localization errors were <3 mm after averaging 50 epochs with empty room noise in a simulation study for dipoles >10 nAm, which is in the low range of empirically observed dipole moments. In a phantom study with realistic environmental noise, we could clearly recover an evoked cortical magnetic field produced by a 20 nAm dipole after averaging 50 epochs. The localization error was ∼6 mm after averaging 20 epochs. In infants, we could clearly detect a somatic evoked field after averaging ∼20 responses. The unique two-layer sensor design combined with the SSP or SG provides effective noise suppression for a magnetometer-based pediatric MEG system in hospital environment with the closed-cycle helium recycler operating continuously during MEG measurements.

BabyMEG: A whole-head pediatric magnetoencephalography system for human brain development research

We developed a 375-channel, whole-head magnetoencephalography (MEG) system ("BabyMEG") for studying the electrophysiological development of human brain during the first years of life. The helmet accommodates heads up to 95% of 36-month old boys in the USA. The unique two-layer sensor array consists of: (1) 270 magnetometers (10 mm diameter, ∼15 mm coil-to-coil spacing) in the inner layer, (2) thirty-five three-axis magnetometers (20 mm × 20 mm) in the outer layer 4 cm away from the inner layer. Additionally, there are three three-axis reference magnetometers. With the help of a remotely operated position adjustment mechanism, the sensor array can be positioned to provide a uniform short spacing (mean 8.5 mm) between the sensor array and room temperature surface of the dewar. The sensors are connected to superconducting quantum interference devices (SQUIDs) operating at 4.2 K with median sensitivity levels of 7.5 fT/√Hz for the inner and 4 fT/√Hz for the outer layer sensors. SQUID outputs are digitized by a 24-bit acquisition system. A closed-cycle helium recycler provides maintenance-free continuous operation, eliminating the need for helium, with no interruption needed during MEG measurements. BabyMEG with the recycler has been fully operational from March, 2015. Ongoing spontaneous brain activity can be monitored in real time without interference from external magnetic noise sources including the recycler, using a combination of a lightly shielded two-layer magnetically shielded room, an external active shielding, a signal-space projection method, and a synthetic gradiometer approach. Evoked responses in the cortex can be clearly detected without averaging. These new design features and capabilities represent several advances in MEG, increasing the utility of this technique in basic neuroscience as well as in clinical research and patient studies.

Accounting for linear transformations of EEG and MEG data in source analysis.

Analyses of electro- and magnetoencephalography (EEG, MEG) data often involve a linear modification of signals at the sensor level. Examples include re-referencing of the EEG, computation of synthetic gradiometer in MEG, or the removal of artifactual independent components to clean EEG and MEG data. A question of practical relevance is, if such modifications must be accounted for by adapting the physical forward model (leadfield) before subsequent source analysis. Here, we show that two scenarios need to be differentiated. In the first scenario, which corresponds to re-referencing the EEG and synthetic gradiometer computation in MEG, the leadfield must be adapted before source analysis. In the second scenario, which corresponds to removing artifactual components to ‘clean’ the data, the leadfield must not be changed. We demonstrate and discuss the consequences of wrongly modifying the leadfield in the latter case for an example. Future EEG and MEG studies employing source analyses should carefully consider whether and, if so, how the leadfield must be modified as explicated here.

Baseline optimization of SQUID gradiometer for magnetocardiography**Project supported by the “Strategic Priority Research Program (B)” of the Chinese Academy of Sciences (Grant No. XDB04020200) and the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No. KGCX2-EW-105).

SQUID gradiometer techniques are widely used in noise cancellation for biomagnetic measurements. An appropriate gradiometer baseline is very important for the biomagnetic detection with high performance. By placing several magnetometers at different heights along the vertical direction, we could simultaneously obtain the synthetic gradiometers with different baselines. By using the traditional signal-to-noise ratio (SNR) as a performance index, we successfully obtain an optimal baseline for the magnetocardiography (MCG) measurement in a magnetically shielded room (MSR). Finally, we obtain an optimal baseline of 7 cm and use it for the practical MCG measurement in our MSR. The SNR about 38 dB is obtained in the recorded MCG signal.

Quantitative evaluation of signal integrity for magnetocardiography

Magnetocardiography (MCG) is a non-invasive diagnostic tool used to investigate the activity of the heart. For applications in an unshielded environment, in order to extract the very weak signal of interest from the much higher background noise, dedicated hardware configuration and sophisticated signal processing techniques have been developed during the last decades. Being powerful in noise rejection, the signal processing may introduce signal distortions, if not properly designed and applied. However, there is a lack of an effective tool to quantitatively evaluate the signal integrity for MCG at present. In this paper, we have introduced a very simple method by using a small coil driven by a human ECG signal to generate a simulated MCG signal. Three key performance indexes were proposed, which are correlation in time domain, relative heights of different peaks and correlation in frequency domain, to evaluate the MCG system performance quantitatively. This evaluation method was applied to a synthetic gradiometer consisting of a second-order axial gradiometer and three orthogonal reference magnetometers. The evaluation turned out to be very effective in optimizing the parameters for signal processing. In addition, the method can serve as a useful tool for hardware improvement.

Effective electromagnetic noise cancellation with beamformers and synthetic gradiometry in shielded and partly shielded environments

The major challenge of MEG, the inverse problem, is to estimate the very weak primary neuronal currents from the measurements of extracranial magnetic fields. The non-uniqueness of this inverse solution is compounded by the fact that MEG signals contain large environmental and physiological noise that further complicates the problem. In this paper, we evaluate the effectiveness of magnetic noise cancellation by synthetic gradiometers and the beamformer analysis method of synthetic aperture magnetometry (SAM) for source localisation in the presence of large stimulus-generated noise. We demonstrate that activation of primary somatosensory cortex can be accurately identified using SAM despite the presence of significant stimulus-related magnetic interference. This interference was generated by a contact heat evoked potential stimulator (CHEPS), recently developed for thermal pain research, but which to date has not been used in a MEG environment. We also show that in a reduced shielding environment the use of higher order synthetic gradiometry is sufficient to obtain signal-to-noise ratios (SNRs) that allow for accurate localisation of cortical sensory function.

Experimental verification of a spatial deconvolution procedure for planar gradiometer configurations

By using a spatial filter model for planar gradiometers and a deconvolution procedure we were able to retrieve the magnetic field from flux measurements made by planar gradiometers configurations. Because the spatial filter model relies only on geometrical features of the gradiometer, such as baseline, coil area and shape, it does not depend on any particular field source. Synthetic gradiometers were implemented by numerically integrating the magnetic field measured by pointwise Hall-effect probes. We successfully tested the deconvolution procedure for different field sources and planar gradiometer designs, achieving excellent results.

Magnetoencephalography: the art of finding a needle in a haystack

The brain's 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.

Synthetic gradiometer systems for MEG

This paper will describe features and performance of low-T/sub c/ whole-cortex MEG systems which utilise synthetic gradiometers to achieve a high level of environmental noise cancellation. The near field MEG sensitivities achieved through use of synthetic gradiometers typically range from 3 to 7 fT//spl radic/Hz above 1 Hz in moderately shielded rooms and less than 10 fT//spl radic/Hz above a few Hz in open environments. This performance has been observed for fixed vertical and also adjustable MEG systems which can tilt between vertical and horizontal orientations.