An inverse method for designing loaded RF coils in MRI

Radio-frequency ( RF) coils are designed such that they induce homogeneous magnetic fields within some region of interest within a magnetic resonance imaging ( MRI) scanner. Loading the scanner with a patient disrupts the homogeneity of these fields and can lead to a considerable degradation of the quality of the acquired image. In this paper, an inverse method is presented for designing RF coils, in which the presence of a load ( patient) within the MRI scanner is accounted for in the model. To approximate the finite length of the coil, a Fourier series expansion is considered for the coil current density and for the induced fields. Regularization is used to solve this ill-conditioned inverse problem for the unknown Fourier coefficients. That is, the error between the induced and homogeneous target fields is minimized along with an additional constraint, chosen in this paper to represent the curvature of the coil windings. Smooth winding patterns are obtained for both unloaded and loaded coils. RF fields with a high level of homogeneity are obtained in the unloaded case and a limit to the level of homogeneity attainable is observed in the loaded case.

Dual-symmetric Lagrangians in quantum electrodynamics: I. Conservation laws and multi-polar coupling

By using a complex field with a symmetric combination of electric and magnetic fields, a first-order covariant Lagrangian for Maxwell's equations is obtained, similar to the Lagrangian for the Dirac equation. This leads to a dual-symmetric quantum electrodynamic theory with an infinite set of local conservation laws. The dual symmetry is shown to correspond to a helical phase, conjugate to the conserved helicity. There is also a scaling symmetry, conjugate to the conserved entanglement. The results include a novel form of the photonic wavefunction, with a well-defined helicity number operator conjugate to the chiral phase, related to the fundamental dual symmetry. Interactions with charged particles can also be included. Transformations from minimal coupling to multi-polar or more general forms of coupling are particularly straightforward using this technique. The dual-symmetric version of quantum electrodynamics derived here has potential applications to nonlinear quantum optics and cavity quantum electrodynamics.

Strong electronic correlations in superconducting organic charge transfer salts

We review the role of strong electronic correlations in quasi-two-dimensional organic charge transfer salts such as (BEDT-TTF)(2)X, (BETS)(2)Y, and beta'-[Pd(dmit)(2)](2)Z. We begin by defining minimal models for these materials. It is necessary to identify two classes of material: the first class is strongly dimerized and is described by a half-filled Hubbard model; the second class is not strongly dimerized and is described by a quarter-filled extended Hubbard model. We argue that these models capture the essential physics of these materials. We explore the phase diagram of the half-filled quasi-two-dimensional organic charge transfer salts, focusing on the metallic and superconducting phases. We review work showing that the metallic phase, which has both Fermi liquid and 'bad metal' regimes, is described both quantitatively and qualitatively by dynamical mean field theory (DMFT). The phenomenology of the superconducting state is still a matter of contention. We critically review the experimental situation, focusing on the key experimental results that may distinguish between rival theories of superconductivity, particularly probes of the pairing symmetry and measurements of the superfluid stiffness. We then discuss some strongly correlated theories of superconductivity, in particular the resonating valence bond (RVB) theory of superconductivity. We conclude by discussing some of the major challenges currently facing the field. These include parameterizing minimal models, the evidence for a pseudogap from nuclear magnetic resonance (NMR) experiments, superconductors with low critical temperatures and extremely small superfluid stiffnesses, the possible spin- liquid states in kappa-(ET)(2)Cu-2(CN)(3) and beta'-[Pd(dmit)(2)](2)Z, and the need for high quality large single crystals.

Real-time control of a Tokamak plasma using neural networks

This paper presents results from the first use of neural networks for the real-time feedback control of high temperature plasmas in a Tokamak fusion experiment. The Tokamak is currently the principal experimental device for research into the magnetic confinement approach to controlled fusion. In the Tokamak, hydrogen plasmas, at temperatures of up to 100 Million K, are confined by strong magnetic fields. Accurate control of the position and shape of the plasma boundary requires real-time feedback control of the magnetic field structure on a time-scale of a few tens of microseconds. Software simulations have demonstrated that a neural network approach can give significantly better performance than the linear technique currently used on most Tokamak experiments. The practical application of the neural network approach requires high-speed hardware, for which a fully parallel implementation of the multi-layer perceptron, using a hybrid of digital and analogue technology, has been developed.

Quantification of the relationship between, magnetoencephalographic (MEG) and blood oxygenation dependent (BOLD) images of brain function

Magnetoencephalography (MEG) is the measurement of the magnetic fields generated outside the head by the brain’s electrical activity. The technique offers the promise of high temporal and spatial resolution. There is however an ambiguity in the inversion process of estimating what goes on inside the head from what is measured outside. Other techniques, such as functional Magnetic Resonance Imaging (fMRI) have no such inversion problems yet suffer from poorer temporal resolution. In this study we examined metrics of mutual information and linear correlation between volumetric images from the two modalities. Measures of mutual information reveal a significant, non-linear, relationship between MEG and fMRI datasets across a number of frequency bands.

Biology of sensory systems

A comprehensive and highly illustrated text providing a broad and invaluable overview of sensory systems at the molecular, cellular and neurophysiological level of vertebrates, invertebrates and prokaryotes. It retains a strong focus on human systems, and takes an evolutionary and comparative approach to review the mechanosenses, chemosenses, photosenses, and other sensory systems including those for detecting pain, temperature electric and magnetic fields etc. It incorporates exciting and significant new insights provided by molecular biology which demonstrate how similar the molecular architecture and physiology of sensory cells are across species and across sensory modality, often indicationg a common ancestry dating back over half a billion years. Written by a renowned author, with extensive teaching experience in the biology of sensory systems, this book includes: - Over 400 illustrations - Self–assessment questions - Full bibliography preceded by short bibliographical essays - Boxes containing useful supplementary material. It will be invaluable for undergraduates and postgraduates studying biology, zoology, animal physiology, neuroscience, anatomy, molecular biology, physiological psychology and related courses.

Normative MEG data to flash and pattern reversal stimuli

We have attempted to establish normative values of components of the magnetic evoked field to flash and pattern reversal stimuli prior to clinical use of the MEG. Full visual field, binocular evoked magnetic fields were recorded from 100 subjects 16 to 86 years of age with a single channel dc Squid (BTI) second-order gradiometer at a point 5-6cm above the inion. The majority of subjects showed a large positive component (out going magnetic field) of mean latency 115 ms (SD range 2.5 -11.8 in different decades of life) to the pattern reversal stimulus. In many subjects, this P100M was preceeded and succeeded by negative deflections (in going field). About 6% of subjects showed an inverted response i.e. a PNP wave. Waveforms to flash were more variable in shape with several positive components; the most consistent having a mean latency of 110ms (SD range 6.4-23.2). Responses to both stimuli were consistent when measured on the same subject on six different occasions (SD range 4.8 to 7.3). The data suggest that norms can be established for evoked magnetic field components, in particular for the pattern reversal P100M, which could be used in the diagnosis of neuro-opthalmological disease.

Functional localisation of human sensory-motor cortex using magnetoencephalography

The 19 channel Neuromagnetometer system in the Clinical Neurophysiology Unit at Aston University is a multi-channel system, unique in the United Kingdom. A bite bar head localisation and MRI co-registration strategy which enabled accurate and reproducible localisation of MEG data into cortical space was developed. This afforded the opportunity to study magnetic fields of the human cortex generated by stimulation of peripheral nerve, by stimulation of visceral sensory receptors and by those evoked through voluntary finger movement. Initially, a study of sensory-motor evoked data was performed in a healthy control population. The techniques developed were then applied to patients who were to undergo neurosurgical intervention for the treatment of epilepsy and I or space occupying lesions. This enabled both validation of the effective accuracy of source localisation using MEG as well as to determine the clinical value of MEG in presurgical assessment of functional localisation in human cortex. The studies in this thesis have demonstrated that MEG can repeatedly and reliably locate sources contained within a single gyrus and thus potentially differentiate between disparate gyral activation. This ability is critical in the clinical application of any functional imaging technique; which is yet to be fully validated by any other 'non-invasive' functional imaging methodology. The technique was also applied to the study of visceral sensory representation in the cortex which yielded important data about the multiple cortical representation of visceral sensory function.

Neuro-electromagnetic imaging of the human visual cortex

Methods of solving the neuro-electromagnetic inverse problem are examined and developed, with specific reference to the human visual cortex. The anatomy, physiology and function of the human visual system are first reviewed. Mechanisms by which the visual cortex gives rise to external electric and magnetic fields are then discussed, and the forward problem is described mathematically for the case of an isotropic, piecewise homogeneous volume conductor, and then for an anisotropic, concentric, spherical volume conductor. Methods of solving the inverse problem are reviewed, before a new technique is presented. This technique combines prior anatomical information gained from stereotaxic studies, with a probabilistic distributed-source algorithm to yield accurate, realistic inverse solutions. The solution accuracy is enhanced by using both visual evoked electric and magnetic responses simultaneously. The numerical algorithm is then modified to perform equivalent current dipole fitting and minimum norm estimation, and these three techniques are implemented on a transputer array for fast computation. Due to the linear nature of the techniques, they can be executed on up to 22 transputers with close to linear speedup. The latter part of the thesis describes the application of the inverse methods to the analysis of visual evoked electric and magnetic responses. The CIIm peak of the pattern onset evoked magnetic response is deduced to be a product of current flowing away from the surface areas 17, 18 and 19, while the pattern reversal P100m response originates in the same areas, but from oppositely directed current. Cortical retinotopy is examined using sectorial stimuli, the CI and CIm ;peaks of the pattern onset electric and magnetic responses are found to originate from areas V1 and V2 simultaneously, and they therefore do not conform to a simple cruciform model of primary visual cortex.

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.

Transport properties of hot-pressed bulk carbon nanotubes compacted by spark plasma sintering

Electrical and thermal transport properties of the carbon nanotube bulk material compacted by spark plasma sintering have been investigated. The electrical conductivity of the as-prepared sample shows a lnT dependence from 4 to 50 K, after which the conductivity begins to increase approximately linearly with temperature. A magnetic field applied perpendicularly to the sample increases the electrical conductivity in the range of 0-8T at all testing temperatures, indicating that the sample possesses the two-dimensional weak localization at lower temperatures (?50 K), while behaviors like a semimetal at higher temperatures (?50 K). This material acts like a uniform compact consisting of randomly distributed two dimensional graphene layers. For the same material, the thermal conductivity is found to decrease almost linearly with decreasing temperature, similar to that of a single multi-walled carbon nanotube. Magnetic fields applied perpendicularly to the sample cause the thermal conductivity to decrease significantly, but the influence of the magnetic fields becomes weak when temperature increases.

Right hemisphere contributions to imitation tasks

Humans imitate biological movements faster than non-biological movements. The faster response has been attributed to an activation of the human mirror neuron system, which is thought to match observation and execution of actions. However, it is unclear which cortical areas are responsible for this behavioural advantage. Also, little is known about the timing of activations. Using whole-head magnetoencephalography we recorded neuronal responses to single biological finger movements and non-biological dot movements while the subjects were required to perform an imitation task or an observation task, respectively. Previous imaging studies on the human mirror neurone system suggested that activation in response to biological movements would be stronger in ventral premotor, parietal and superior temporal regions. In accordance with previous studies, reaction times to biological movements were faster than those to dot movements in all subjects. The analysis of evoked magnetic fields revealed that the reaction time benefit was paralleled by stronger and earlier activation of the left temporo-occipital cortex, right superior temporal area and right ventral motor/premotor area. The activity patterns suggest that the latter areas mediate the observed behavioural advantage of biological movements and indicate a predominant contribution of the right temporo-frontal hemisphere to action observation–execution matching processes in intransitive movements, which has not been reported previously.

Magneto-vibratory separation of glass and bronze granular mixtures immersed in a paramagnetic liquid

A fluid-immersed granular mixture may spontaneously separate when subjected to vertical vibration, separation occurring when the ratio of particle inertia to fluid drag is sufficiently different between the component species of the mixture. Here, we describe how fluid-driven separation is influenced by magneto-Archimedes buoyancy, the additional buoyancy force experienced by a body immersed in a paramagnetic fluid when a strong inhomogeneous magnetic field is applied. In our experiments glass and bronze mixtures immersed in paramagnetic aqueous solutions of MnCl2 have been subjected to sinusoidal vertical vibration. In the absence of a magnetic field the separation is similar to that observed when the interstitial fluid is water. However, at modest applied magnetic fields, magneto-Archimedes buoyancy may balance the inertia/fluid-drag separation mechanism, or it may dominate the separation process. We identify the vibratory and magnetic conditions for four granular configurations, each having distinctive granular convection. Abrupt transitions between these states occur at well-defined values of the magnetic and vibrational parameters. In order to gain insight into the dynamics of the separation process we use computer simulations based on solutions of the Navier-Stokes' equations. The simulations reproduce the experimental results revealing the important role of convection and gap formation in the stability of the different states.

Niedrigfeld Magnetowiderstand inhomogener Halbleiterschichten

The resistance of semiconductor superlattices under weak magnetic fields is modelled with a classical approach. It is shown, that this is sufficient to explain the experimental features of these systems and that a quantum-mechanical approach will only be needed for significantly smaller lattice structures.

Source localization methods

One of the most pressing demands on electrophysiology applied to the diagnosis of epilepsy is the non-invasive localization of the neuronal generators responsible for brain electrical and magnetic fields (the so-called inverse problem). These neuronal generators produce primary currents in the brain, which together with passive currents give rise to the EEG signal. Unfortunately, the signal we measure on the scalp surface doesn't directly indicate the location of the active neuronal assemblies. This is the expression of the ambiguity of the underlying static electromagnetic inverse problem, partly due to the relatively limited number of independent measures available. A given electric potential distribution recorded at the scalp can be explained by the activity of infinite different configurations of intracranial sources. In contrast, the forward problem, which consists of computing the potential field at the scalp from known source locations and strengths with known geometry and conductivity properties of the brain and its layers (CSF/meninges, skin and skull), i.e. the head model, has a unique solution. The head models vary from the computationally simpler spherical models (three or four concentric spheres) to the realistic models based on the segmentation of anatomical images obtained using magnetic resonance imaging (MRI). Realistic models – computationally intensive and difficult to implement – can separate different tissues of the head and account for the convoluted geometry of the brain and the significant inter-individual variability. In real-life applications, if the assumptions of the statistical, anatomical or functional properties of the signal and the volume in which it is generated are meaningful, a true three-dimensional tomographic representation of sources of brain electrical activity is possible in spite of the ‘ill-posed’ nature of the inverse problem (Michel et al., 2004). The techniques used to achieve this are now referred to as electrical source imaging (ESI) or magnetic source imaging (MSI). The first issue to influence reconstruction accuracy is spatial sampling, i.e. the number of EEG electrodes. It has been shown that this relationship is not linear, reaching a plateau at about 128 electrodes, provided spatial distribution is uniform. The second factor is related to the different properties of the source localization strategies used with respect to the hypothesized source configuration.