Gastric slow waves propagate in the electrical syncytium of the healthy stomach, being generated at a rate of approximately three times per minute in a pacemaker region along the greater curvature of the antrum and propagating distally towards the pylorus. Disease states are known to alter the normal gastric slow wave. Recent studies have suggested the use of biomagnetic techniques for assessing parameters of the gastric slow wave that have potential diagnostic significance. We present a study in which the gastric syncytium was uncoupled by mechanical division as we recorded serosal electric potentials along with multichannel biomagnetic signals and cutaneous potentials. By computing the surface current density (SCD) from multichannel biomagnetic recordings, we were able to quantify gastric slow wave propagation as well as the frequency and amplitude of the slow wave and to show that these correlate well with similar parameters from serosal electrodes. We found the dominant slow wave frequency to be an unreliable indicator of gastric uncoupling as uncoupling results in the appearance of multiple slow wave sources at various frequencies in external recordings. The percentage of power distributed in specific frequency ranges exhibited significant postdivision changes. Propagation velocity determined from SCD maps was a weak indicator of uncoupling in this work; we believe that the relatively low spatial resolution of our 19-channel biomagnetometer confounds the characterization of spatial variations in slow wave propagation velocities. Nonetheless, the biomagnetic technique represents a non-invasive method for accurate determination of clinically significant parameters of the gastric slow wave.
electrogastrography; gastric slow wave; magnetogastrography; SQUID magnetometer
The magnetogastrogram records clinically relevant parameters of the electrical slow wave of the stomach noninvasively. Besides slow wave frequency, gastric slow wave propagation velocity is a potentially useful clinical indicator of the state of health of gastric tissue, but it is a difficult parameter to determine from noninvasive bioelectric or biomagnetic measurements. We present a method for computing the surface current density (SCD) from multichannel magnetogastrogram recordings that allows computation of the propagation velocity of the gastric slow wave. A moving dipole source model with hypothetical as well as realistic biomagnetometer parameters demonstrates that while a relatively sparse array of magnetometer sensors is sufficient to compute a single average propagation velocity, more detailed information about spatial variations in propagation velocity requires higher density magnetometer arrays. Finally, the method is validated with simultaneous MGG and serosal EMG measurements in a porcine subject.
biomagnetism; current dipole; electrogastrogram; magnetogastrogram; SQUID magnetometer
Biomagnetic techniques were used to measure motility in various parts of the gastrointestinal (GI) tract, particularly a new technique for detecting magnetic markers and tracers. A coil was used to enhance the signal from a magnetic tracer in the GI tract and the signal was detected using a fluxgate magnetometer or a magnetoresistor in an unshielded room. Estimates of esophageal transit time were affected by the position of the subject. The reproducibility of estimates derived using the new biomagnetic technique was greater than 85% and it yielded estimates similar to those obtained using scintigraphy. This technique is suitable for studying the effect of emotional state on GI physiology and for measuring GI transit time. The biomagnetic technique can be used to evaluate digesta transit time in the esophagus, stomach and colon, peristaltic frequency and gastric emptying and is easy to use in the hospital setting.
Biomagnetic techniques; Magnetogastrography; Gastric emptying; Scintigraphy; Peristaltic contractions
To elucidate the hemodynamics of the uterine artery myomas by use of Doppler ultrasound and biomagnetic measurements.
Twenty-four women were included in the study. Sixteen of them were characterised with large myomas whereas 8 of them with small ones. Biomagnetic signals of uterine arteries myomas were recorded and analyzed with Fourier analysis. The biomagnetic signals were distributed according to spectral amplitudes as high (140–300 ft/√Hz), low (50–110 ft/√Hz) and borderline (111–139 ft/√Hz). Uterine artery waveform measurements were evaluated by use of Pulsatility Index (PI) (normal value PI < 1.45).
There was a statistically significant difference between large and small myomas concerning the waveform amplitudes (P < 0.0005) and the PI index (P < 0.0005). Specifically, we noticed high biomagnetic amplitudes in most large myomas (93.75 %) and low biomagnetic amplitudes in most small ones (87.5 %).
It is suggested that the biomagnetic recordings of uterine artery myomas could be a valuable modality in the estimation of the circulation of blood cells justifying the findings of Doppler velocimetry examination.
To determine if there is any non-linearity in the biomagnetic recordings of uterine myomas and to find any differences that may be present in the mechanisms underlying their signal dynamics.
Twenty-four women were included in the study. Sixteen of them were characterised with large myomas and 8 with small ones. Uterine artery waveform measurements were evaluated by use of Pulsatility Index (PI) (normal value PI<1.45).
Applying nonlinear analysis to the biomagnetic signals of the uterine myomas, we observed a clear saturation value for the group of large ones (mean = 11.35 ± 1.49) and no saturation for the small ones.
The comparison of the saturation values in the biomagnetic recordings of large and small myomas may be a valuable tool in the evaluation of functional changes in their dynamic behavior.
Scanning tunneling spectroscopy (STS) enables the local, energy-resolved investigation of a samples surface density of states (DOS) by measuring the differential conductance (dI/dV) being approximately proportional to the DOS. It is popular to examine the electronic structure of elementary samples by acquiring dI/dV maps under constant current conditions. Here we demonstrate the intricacy of STS mapping of samples exhibiting a strong corrugation originating from electronic density and local work function changes. The confinement of the Ag(111) surface state by a porous organic network is studied with maps obtained under constant-current (CC) as well as open-feedback-loop (OFL) conditions. We show how the CC maps deviate markedly from the physically more meaningful OFL maps. By applying a renormalization procedure to the OFL data we can mimic the spurious effects of the CC mode and thereby rationalize the physical effects evoking the artefacts in the CC maps.
In the advent of next-generation sequencing (NGS) platforms, map-based sequencing strategy has been recently suppressed being too expensive and laborious. The detailed studies on NGS drafts alone indicated these assemblies remain far from gold standard reference quality, especially when applied on complex genomes. In this context the conventional BAC-based physical mapping has been identified as an important intermediate layer in current hybrid sequencing strategy. BAC-based physical map construction and its integration with high-density genetic maps have benefited from NGS and high-throughput array platforms. This paper addresses the current advancements of BAC-based physical mapping and high-throughput map integration strategies to obtain densely anchored well-ordered physical maps. The resulted maps are of immediate utility while providing a template to harness the maximum benefits of the current NGS platforms.
Biomagnetic nano and microparticles platforms have attracted considerable interest in the field of biological sensors due to their interesting physico-chemical properties, high specific surface area, good mechanical stability and opportunities for generating magneto-switchable devices. This review discusses recent advances in the development and characterization of active biomagnetic nanoassemblies, their interaction with biological molecules and their use in bioanalytical sensors.
Biomagnetic materials; composite magnetic materials; bio-immobilization; biological sensors
This paper presents a novel phase unwrapping architecture for accelerating the computational speed of digital holographic microscopy (DHM). A fast Fourier transform (FFT) based phase unwrapping algorithm providing a minimum squared error solution is adopted for hardware implementation because of its simplicity and robustness to noise. The proposed architecture is realized in a pipeline fashion to maximize throughput of the computation. Moreover, the number of hardware multipliers and dividers are minimized to reduce the hardware costs. The proposed architecture is used as a custom user logic in a system on programmable chip (SOPC) for physical performance measurement. Experimental results reveal that the proposed architecture is effective for expediting the computational speed while consuming low hardware resources for designing an embedded DHM system.
phase unwrapping; digital holographic microscopy; FPGA; reconfigurable computing; system on programmable chip
We have developed a MATLAB-based toolbox, eConnectome (electrophysiological connectome), for mapping and imaging functional connectivity at both the scalp and cortical levels from the electroencephalogram (EEG), as well as from the electrocorticogram (ECoG). Graphical user interfaces were designed for interactive and intuitive use of the toolbox. Major functions of eConnectome include EEG/ECoG preprocessing, scalp spatial mapping, cortical source estimation, connectivity analysis, and visualization. Granger causality measures such as Directed Transfer Function and adaptive Directed Transfer Function were implemented to estimate the directional interactions of brain functional networks, over the scalp and cortical sensor spaces. Cortical current density inverse imaging was implemented using a generic realistic geometry brain-head model from scalp EEGs. Granger causality could be further estimated over the cortical source domain from the inversely reconstructed cortical source signals as derived from the scalp EEG. Users may implement other connectivity estimators in the framework of eConnectome for various applications. The toolbox package is open-source and freely available at http://econnectome.umn.edu under the GNU general public license for noncommercial and academic uses.
EEG; ECoG; source imaging; functional connectivity; MATLAB; eConnectome
For simulations of neural networks, there is a trade-off between the size of the network that can be simulated and the complexity of the model used for individual neurons. In this study, we describe a generalization of the leaky integrate-and-fire model that produces a wide variety of spiking behaviors while still being analytically solvable between firings. For different parameter values, the model produces spiking or bursting, tonic, phasic or adapting responses, depolarizing or hyperpolarizing after potentials and so forth. The model consists of a diagonalizable set of linear differential equations describing the time evolution of membrane potential, a variable threshold, and an arbitrary number of firing-induced currents. Each of these variables is modified by an update rule when the potential reaches threshold. The variables used are intuitive and have biological significance. The model’s rich behavior does not come from the differential equations, which are linear, but rather from complex update rules. This single-neuron model can be implemented using algorithms similar to the standard integrate-and-fire model. It is a natural match with event-driven algorithms for which the firing times are obtained as a solution of a polynomial equation.
In the one and two beads Coarse Grained (CG) models for proteins, the two conformational dihedrals ϕ and ψ that describe the backbone geometry are no longer present as explicit internal coordinates, thus the information contained in the Ramachandran plot cannot be used directly. We derive an analytical mapping between these dihedrals and the internal variable describing the backbone conformation in the one(two) beads CG models, namely the pseudo-bond angle and pseudo-dihedral between subsequent Cαs. This is used to derive a new density plot that contains the same information as the Ramachandran plot and can be used with the one(two) beads CG models. The use of this mapping is then illustrated with a new one bead polypeptide model that accounts for transitions between α-helices and β-sheets.
Algorithms and geometrical properties are described for the automated building of nucleic acids in experimental electron density.
Medium- to high-resolution X-ray structures of DNA and RNA molecules were investigated to find geometric properties useful for automated model building in crystallographic electron-density maps. We describe a simple method, starting from a list of electron-density ‘blobs’, for identifying backbone phosphates and nucleic acid bases based on properties of the local electron-density distribution. This knowledge should be useful for the automated building of nucleic acid models into electron-density maps. We show that the distances and angles involving C1′ and the P atoms, using the pseudo-torsion angles and that describe the …P—C1′—P—C1′… chain, provide a promising basis for building the nucleic acid polymer. These quantities show reasonably narrow distributions with asymmetry that should allow the direction of the phosphate backbone to be established.
nucleic acids; autobuilding; geometric properties; electron-density distribution
The world’s first magnetoencephalography (MEG) system specifically designed for fetal and newborn assessment has been installed at the University of Arkansas for Medical Sciences. This non-invasive system called SARA (Squid Array for Reproductive Assessment) consists of 151 primary superconducting sensors which detect biomagnetic fields from the human body. Since the installation of SARA, significant progress has been made toward the ultimate goal of developing a clinical neurological assessment tool for the developing fetus. Using appropriate analysis techniques, cardiac and brain signals are recorded and studied to gain new understanding of fetal maturation. It is clear from our investigations that a combination of assessment protocols including both fetal heart and brain activity is necessary for the development of a comprehensive new method of fetal neurological testing. We plan to implement such a test protocol for fetuses at high-risk for neurological impairment due to certain maternal risk factors and/or fetal diagnostic findings.
fetal magnetoenecephalogram; fetal magnetocardiogram; HRV measures
To define the phenotype and elucidate the molecular basis for an autosomal recessively inherited optic atrophy and auditory neuropathy in a consanguineous family with two affected children.
Family members underwent detailed ophthalmologic, electrophysiological, and audiological assessments. An autozygosity mapping strategy using high-density single nucleotide polymorphism microarrays and microsatellite markers was used to detect regions of genome homozygosity that might contain the disease gene. Candidate genes were then screened for mutations by direct sequencing.
Both affected subjects had poor vision from birth and complained of progressive visual loss over time. Current visual acuity ranged from 6/60 to 6/120. Fundus examination revealed bilateral temporal optic nerve pallor in both patients with otherwise normal retinal findings. International-standard full-field electroretinograms were normal in both individuals, with no evidence of generalized retinal dysfunction. Pattern cortical visual evoked potentials were grossly abnormal bilaterally in both cases. The pattern electroretinogram N95:P50 ratio was subnormal, and the P50 was of shortened peak time bilaterally in both patients. The electrophysiological findings were consistent with bilateral retinal ganglion cell/optic nerve dysfunction. Audiological investigation in both siblings revealed abnormalities falling within the auditory neuropathy/dysynchrony spectrum. There were no auditory symptoms and good outer hair cell function (as demonstrated by transient evoked otoacoustic emissions) but impaired inner hair cell/neural function with abnormal stapedial reflex thresholds and abnormal or absent auditory brainstem-evoked responses. The single nucleotide polymorphism microarray data demonstrated a 24.17 Mb region of homozygosity at 11q14.1–11q22.3, which was confirmed by microsatellite marker analysis. The candidate target region contained the transmembrane protein 126A (TMEM126A) gene, and direct sequencing identified a previously described nonsense mutation (c.163C>T; p.Arg55X).
We describe the first detailed phenotyping of patients with autosomal recessive TMEM126A-associated optic atrophy and auditory neuropathy. These findings will facilitate the identification of individuals with this recently described disorder.
Pseudoknots have been recognized to be an important type of RNA secondary structures responsible for many biological functions. PseudoBase, a widely used database of pseudoknot secondary structures developed at Leiden University, contains over 250 records of pseudoknots obtained in the past 25 years through crystallography, NMR, mutational experiments and sequence comparisons. To promptly address the growing analysis requests of the researchers on RNA structures and bring together information from multiple sources across the Internet to a single platform, we designed and implemented PseudoBase++, an extension of PseudoBase for easy searching, formatting and visualization of pseudoknots. PseudoBase++ (http://pseudobaseplusplus.utep.edu) maps the PseudoBase dataset into a searchable relational database including additional functionalities such as pseudoknot type. PseudoBase++ links each pseudoknot in PseudoBase to the GenBank record of the corresponding nucleotide sequence and allows scientists to automatically visualize RNA secondary structures with PseudoViewer. It also includes the capabilities of fine-grained reference searching and collecting new pseudoknot information.
The damped-oscillator pseudo-wavelet is presented as a method of time-frequency analysis along with a new spectral density measure, the data power. An instantaneous phase can be defined for this pseudo-wavelet, and it is easily inverted. The data power measure is tested on both computer generated data and in vivo intrahippocampal electrophysiological recordings from a rat. The data power spectral density is found to give better time and frequency resolution than the more conventional total energy measure, and additionally shows intricate time-frequency structure in the rat that is altered in association with the emergence of epilepsy. With epileptogenesis, the baseline theta oscillation is severely degraded and is absorbed into a broader gamma band. There are also broad 600 Hz and 2000 Hz bands which localize to hippocampal layers that are distinct from those of the theta and gamma bands. The 600 Hz band decreases in prominence with epileptogenesis while the 2000 Hz band increases in prominence. The origins of these high frequency bands await further study. In general, we find that the damped-oscillator pseudo-wavelet is easy to use and is particularly suitable for problems where a wide range of oscillator frequencies is expected.
time-frequency analysis; wavelet analysis; high frequency oscillations; epileptogenesis
This paper presents a computationally efficient source estimation algorithm that localizes cortical oscillations and their phase relationships. The proposed method employs wavelet-transformed magnetoencephalography (MEG) data and uses anatomical MRI to constrain the current locations to the cortical mantle. In addition, the locations of the sources can be further confined with the help of functional MRI (fMRI) data. As a result, we obtain spatiotemporal maps of spectral power and phase relationships. As an example, we show how the phase locking value (PLV), that is, the trial-by-trial phase relationship between the stimulus and response, can be imaged on the cortex. We apply the method to spontaneous, evoked, and driven cortical oscillations measured with MEG. We test the method of combining MEG, structural MRI, and fMRI using simulated cortical oscillations along Heschl’s gyrus (HG). We also analyze sustained auditory gamma-band neuromagnetic fields from MEG and fMRI measurements. Our results show that combining the MEG recording with fMRI improves source localization for the non-noise-normalized wavelet power. In contrast, noise-normalized spectral power or PLV localization may not benefit from the fMRI constraint. We show that if the thresholds are not properly chosen, noise-normalized spectral power or PLV estimates may contain false (phantom) sources, independent of the inclusion of the fMRI prior information. The proposed algorithm can be used for evoked MEG/EEG and block-designed or event-related fMRI paradigms, or for spontaneous MEG data sets. Spectral spatiotemporal imaging of cortical oscillations and interactions in the human brain can provide further understanding of large-scale neural activity and communication between different brain regions.
Inverse; MEG; Evoked power; Phase locking; Oscillation; Brain; fMRI
This work develops a new current-mode mixed signal Complementary Metal-Oxide-Semiconductor (CMOS) imager, which can capture images and simultaneously produce vehicle lane maps. The adopted lane detection algorithm, which was modified to be compatible with hardware requirements, can achieve a high recognition rate of up to approximately 96% under various weather conditions. Instead of a Personal Computer (PC) based system or embedded platform system equipped with expensive high performance chip of Reduced Instruction Set Computer (RISC) or Digital Signal Processor (DSP), the proposed imager, without extra Analog to Digital Converter (ADC) circuits to transform signals, is a compact, lower cost key-component chip. It is also an innovative component device that can be integrated into intelligent automotive lane departure systems. The chip size is 2,191.4 × 2,389.8 μm, and the package uses 40 pin Dual-In-Package (DIP). The pixel cell size is 18.45 × 21.8 μm and the core size of photodiode is 12.45 × 9.6 μm; the resulting fill factor is 29.7%.
Image sensor; CMOS; photodiode; current-mode; lane detection; peak-finding algorithm; Gaussian filter; intelligent transportation systems
Dysfunction of the hippocampus has long been suspected to be a key component of the pathophysiology of major depressive disorder. Despite evidence of hippocampal structural abnormalities in depressed patients, abnormal hippocampal functioning has not been demonstrated. We aimed to link spatial navigation deficits previously documented in depressed patients to abnormal hippocampal functioning using a virtual reality navigation task.
Whole-head magnetoencephalography (MEG) recordings were collected while participants – 19 patients diagnosed with major depressive disorder and 19 healthy controls, matched by gender and age – navigated a virtual Morris water maze to find a hidden platform, and a visible one as a control condition. Behavioral measures were taken to assess navigation performance. Theta oscillatory activity (4-8 Hz) was mapped across the brain on a voxel-wise basis using a spatial-filtering MEG source analysis technique.
Depressed patients performed worse than controls in navigating to the hidden platform. Robust group differences in theta activity were observed in right medial temporal cortices during navigation, with patients exhibiting less engagement of the anterior hippocampus and parahippocampal cortices compared to controls. Left posterior hippocampal theta activity was positively correlated with individual performance within each group.
Consistent with previous findings, depressed patients showed impaired spatial navigation. Dysfunction of right anterior hippocampus and parahippocampal cortices may underlie this deficit and stem from structural abnormalities commonly found in depressed patients.
The recent development of large multielectrode recording arrays has made it affordable for an increasing number of laboratories to record from multiple brain regions simultaneously. The development of analytical tools for array data, however, lags behind these technological advances in hardware. In this paper, we present a method based on forward modeling for estimating current source density from electrophysiological signals recorded on a two-dimensional grid using multi-electrode rectangular arrays. This new method, which we call two-dimensional inverse Current Source Density (iCSD 2D), is based upon and extends our previous one- and three-dimensional techniques. We test several variants of our method, both on surrogate data generated from a collection of Gaussian sources, and on model data from a population of layer 5 neocortical pyramidal neurons. We also apply the method to experimental data from the rat subiculum. The main advantages of the proposed method are the explicit specification of its assumptions, the possibility to include system-specific information as it becomes available, the ability to estimate CSD at the grid boundaries, and lower reconstruction errors when compared to the traditional approach. These features make iCSD 2D a substantial improvement over the approaches used so far and a powerful new tool for the analysis of multielectrode array data. We also provide a free GUI-based MATLAB toolbox to analyze and visualize our test data as well as user datasets.
Electronic supplementary material
The online version of this article (doi:10.1007/s12021-011-9111-4) contains supplementary material, which is available to authorized users.
Current source density; Local field potentials; Evoked potentials; Inverse problems; Rat; Hippocampus; Subiculum; Cortical model
Fetal magnetoencephalography (fMEG) recordings are contaminated by maternal and fetal magnetocardiography (MCG) signals and by other biological and environmental interference. Currently, all methods for the attenuation of these signals are based on a time-domain approach. We have developed and tested a frequency dependent procedure for removal of MCG and other interference from the fMEG recordings. The method uses a set of reference channels and performs subtraction of interference in the frequency domain (SUBTR). The interference-free frequency domain signals are converted back to the time domain. We compare the performance of the frequency dependent approach with our present approach for MCG attenuation based on orthogonal projection (OP). SUBTR has an advantage over OP and similar template approaches because it removes not only the MCG but also other small amplitude biological interference, avoids the difficulties with inaccurate determination of the OP operator, provides more consistent and stable fMEG results, does not cause signal redistribution, and if references are selected judiciously, it does not reduce fMEG signal amplitude. SUBTR was found to perform well in simulations and on real fMEG recordings, and has a potential to improve the detection of fetal brain signals. The SUBTR removes interference without the need for a model of the individual interference sources. The method may be of interest for any sensor array noise reduction application where signal-free reference channels are available.
Magnetoencephalography; interference cancellation; frequency dependent subtraction; orthogonal projection; spontaneous fetal brain signals
The induction of “bystander effects” i.e. effects in cells which have not received an ionizing radiation track, is now accepted but the mechanisms are not completely clear. Bystander effects following high and low LET radiation exposure are accepted but mechanisms are still not understood. There is some evidence for a physical component to the signal. This paper tests the hypothesis that bioelectric or biomagnetic phenomena are involved. Human immortalized skin keratinocytes and primary explants of mouse bladder and fish skin, were exposed directly to ionizing radiation or treated in a variety of bystander protocols. Exposure of cells was conducted by shielding one group of flasks using lead, to reduce the dose below the threshold of 2mGy 60Cobalt gamma rays established for the bystander effect. The endpoint for the bystander effect in the reporter system used was reduction in cloning efficiency (RCE). The magnitude of the RCE was similar in shielded and unshielded flasks. When cells were placed in a Faraday cage the magnitude of the RCE was less but not eliminated. The results suggest that liquid media or cell-cell contact transmission of bystander factors may be only part of the bystander mechanism. Bioelectric or bio magnetic fields may have a role to play. To test this further, cells were placed in a Magnetic Resonance Imaging (MRI) machine for 10min using a typical head scan protocol. This treatment also induced a bystander response. Apart from the obvious clinical relevance, the MRI results further suggest that bystander effects may be produced by non-ionizing exposures. It is concluded that bioelectric or magnetic effects may be involved in producing bystander signaling cascades commonly seen following ionizing radiation exposure.
Radiation-induced bystander effect; bioelectric effects; explant cultures; fish cells; murine bladder
Automatic estimation of current dipoles from biomagnetic data is
still a problematic task. This is due not only to the ill-posedness of
the inverse problem but also to two intrinsic difficulties introduced by
the dipolar model: the unknown number of sources and the nonlinear
relationship between the source locations and the data. Recently, we
have developed a new Bayesian approach, particle filtering, based on
dynamical tracking of the dipole constellation. Contrary to many
dipole-based methods, particle filtering does not assume stationarity
of the source configuration: the number of dipoles and their positions
are estimated and updated dynamically during the course of the MEG
sequence. We have now developed a Matlab-based graphical user interface,
which allows nonexpert users to do automatic dipole estimation
from MEG data with particle filtering. In the present paper, we describe
the main features of the software and show the analysis of both
a synthetic data set and an experimental dataset.
The biomagnetic inverse problem has captured the interest of both mathematicians and physicists due to its important applications in the medical field. As a result of our experience in analyzing the electrical activity of the gastric smooth muscle, we present here a theoretical model of the magnetic field in the stomach and a computational implementation whereby we demonstrate its realism and usefulness. The computational algorithm developed for this purpose consists of dividing the magnetic field signal input surface into centroid-based grids that allow recursive least-squares approximations to be applied, followed by comparison tests in which the locations of the best-fitting current dipoles are determined. In the second part of the article, we develop a multiple-regression analysis of experimental gastric magnetic data collected using Superconducting QUantum Interference Device (SQUID) magnetometers and successfully processed using our algorithm. As a result of our analysis, we conclude on statistical grounds that it is sufficient to model the electrical activity of the GI tract using only two electric current dipoles in order to account for the magnetic data recorded non-invasively with SQUID magnetometers above the human abdomen.
gastrointestinal electrical activity; biomagnetic inverse problem; current dipole