Volume conduction: Extracellular waveform generation in theory and practice.

The extracellular waveform manifestations of the intracellular action potential are the quintessential diagnostic foundation of electrodiagnostic medicine, and clinical neurophysiology in general. Volume conduction is the extracellular current flow and associated voltage distributions in an ionic conducting media, such as occurs in the human body. Both surface and intramuscular electrodes, in association with contemporary digital electromyographic systems, permit very sensitive detection and visualization of this extracellular spontaneous, voluntary, and evoked nerve/muscle electrical activity. Waveform configuration, with its associated discharge rate/rhythm, permits the identification of normal and abnormal waveforms, thereby assisting in the diagnosis of nerve and muscle pathology. This monograph utilizes a simple model to explain the various waveforms that may be encountered. There are a limited number of waveforms capable of being generated in excitable tissues which conform to well-known volume conductor concepts. Using these principles, such waveforms can be quickly identified in real time during clinical studies.

Artifact propagation in subdural cortical electrostimulation: Characterization and modeling.

Cortical stimulation via electrocorticography (ECoG) may be an effective method for inducing artificial sensation in bi-directional brain-computer interfaces (BD-BCIs). However, strong electrical artifacts caused by electrostimulation may significantly degrade or obscure neural information. A detailed understanding of stimulation artifact propagation through relevant tissues may improve existing artifact suppression techniques or inspire the development of novel artifact mitigation strategies. Our work thus seeks to comprehensively characterize and model the propagation of artifacts in subdural ECoG stimulation. To this end, we collected and analyzed data from eloquent cortex mapping procedures of four subjects with epilepsy who were implanted with subdural ECoG electrodes. From this data, we observed that artifacts exhibited phase-locking and ratcheting characteristics in the time domain across all subjects. In the frequency domain, stimulation caused broadband power increases, as well as power bursts at the fundamental stimulation frequency and its super-harmonics. The spatial distribution of artifacts followed the potential distribution of an electric dipole with a median goodness-of-fit of R 2 = 0.80 across all subjects and stimulation channels. Artifacts as large as ±1,100 µV appeared anywhere from 4.43 to 38.34 mm from the stimulation channel. These temporal, spectral and spatial characteristics can be utilized to improve existing artifact suppression techniques, inspire new strategies for artifact mitigation, and aid in the development of novel cortical stimulation protocols. Taken together, these findings deepen our understanding of cortical electrostimulation and provide critical design specifications for future BD-BCI systems.

A Review of Magnetic Flux Leakage Nondestructive Testing.

Magnetic flux leakage (MFL) testing is a widely used nondestructive testing (NDT) method for the inspection of ferromagnetic materials. This review paper presents the basic principles of MFL testing and summarizes the recent advances in MFL. An analytical expression for the leakage magnetic field based on the 3D magnetic dipole model is provided. Based on the model, the effects of defect size, defect orientation, and liftoff distance have been analyzed. Other influencing factors, such as magnetization strength, testing speed, surface roughness, and stress, have also been introduced. As the most important steps of MFL, the excitation method (a permanent magnet, DC, AC, pulsed) and sensing methods (Hall element, GMR, TMR, etc.), have been introduced in detail. Finally, the algorithms for the quantification of defects and the applications of MFL have been introduced.

Selected topics in diffraction with protons and nuclei: past, present, and future.

We review a broad range of phenomena in diffraction in the context of hadron-hadron, hadron-nucleus collisions and deep inelastic lepton-proton/nucleus scattering focusing on the interplay between the perturbative QCD and non-perturbative models. We discuss inclusive diffraction in DIS, phenomenology of dipole models, resummation and parton saturation at lowx, hard diffractive production of vector mesons, inelastic diffraction in hadron-hadron scattering, formalism of color fluctuations, inclusive coherent and incoherent diffraction as well as soft and hard diffraction phenomena in hadron-hadron/nucleus and photon-nucleus collisions. For each topic we review key results from the past and present experiments including HERA and the LHC. Finally, we identify the remaining open questions, which could be addressed in the continuing experiments, in particular in photon-induced reactions at the LHC and the future electron-ion collider in the US, large hadron electron collider and future circular collider at CERN.

Increasing efficiency and accuracy of magnetic interaction calculations in colloidal simulation through machine learning.

Calculating the magnetic interaction between magnetic particles that are positioned in close proximity to one another is a surprisingly challenging task. Exact solutions for this interaction exist either through numerical expansion of multipolar interactions or through solving Maxwell's equations with a finite element solver. These approaches can take hours for simple configurations of three particles. Meanwhile, across a range of scientific and engineering problems, machine learning approaches have been developed as fast computational platforms for solving complex systems of interest when large data sets are available. In this paper, we bring the touted benefits of recent advances in science-based machine learning algorithms to bear on the problem of modeling the magnetic interaction between three particles. We investigate this approach using diverse machine learning systems including physics informed neural networks. We find that once the training data has been collected and the model has been initiated, simulation times are reduced from hours to mere seconds while maintaining remarkable accuracy. Despite this promise, we also try to lay bare the current challenges of applying machine learning to these and more complex colloidal systems.

A Combined Experimental/Quantum-Chemical Study of Tetrel, Pnictogen, and Chalcogen Bonds of Linear Triatomic Molecules.

Linear triatomic molecules (CO2, N2O, and OCS) are scrutinized for their propensity to form perpendicular tetrel (CO2 and OCS) or pnictogen (N2O) bonds with Lewis bases (dimethyl ether and trimethyl amine) as compared with their tendency to form end-on chalcogen bonds. Comparison of the IR spectra of the complexes with the corresponding monomers in cryogenic solutions in liquid argon enables to determine the stoichiometry and the nature of the complexes. In the present cases, perpendicular tetrel and pnictogen 1:1 complexes are identified mainly on the basis of the lifting of the degenerate ν 2 bending mode with the appearance of both a blue and a red shift. Van 't Hoff plots of equilibrium constants as a function of temperature lead to complexation enthalpies that, when converted to complexation energies, form the first series of experimental complexation energies on sp1 tetrel bonds in the literature, directly comparable to quantum-chemically obtained values. Their order of magnitude corresponds with what can be expected on the basis of experimental work on halogen and chalcogen bonds and previous computational work on tetrel bonds. Both the order of magnitude and sequence are in fair agreement with both CCSD(T) and DFA calculations, certainly when taking into account the small differences in complexation energies of the different complexes (often not more than a few kJ mol-1) and the experimental error. It should, however, be noted that the OCS chalcogen complexes are not identified experimentally, most probably owing to entropic effects. For a given Lewis base, the stability sequence of the complexes is first successfully interpreted via a classical electrostatic quadrupole-dipole moment model, highlighting the importance of the magnitude and sign of the quadrupole moment of the Lewis acid. This approach is validated by a subsequent analysis of the molecular electrostatic potential, scrutinizing the σ and π holes, as well as the evolution in preference for chalcogen versus tetrel bonds when passing to "higher" chalcogens in agreement with the evolution of the quadrupole moment. The energy decomposition analysis gives further support to the importance/dominance of electrostatic effects, as it turns out to be the largest attractive term in all cases considered, followed by the orbital interaction and the dispersion term. The natural orbitals for chemical valence highlight the sequence of charge transfer in the orbital interaction term, which is dominated by an electron-donating effect of the N or O lone-pair(s) of the base to the central atom of the triatomics, with its value being lower than in the case of comparable halogen bonding situations. The effect is appreciably larger for TMA, in line with its much higher basicity than DME, explaining the comparable complexation energies for DME and TMA despite the much larger dipole moment for DME.

Investigation of the temporal and spatial dynamics of muscular action potentials through optically pumped magnetometers.

AIM: This study aims to simultaneously record the magnetic and electric components of the propagating muscular action potential. METHOD: A single-subject study of the monosynaptic stretch reflex of the musculus rectus femoris was performed; the magnetic field generated by the muscular activity was recorded in all three spatial directions by five optically pumped magnetometers. In addition, the electric field was recorded by four invasive fine-wire needle electrodes. The magnetic and electric fields were compared by modelling the muscular anatomy of the rectus femoris muscle and by simulating the corresponding magnetic field vectors. RESULTS: The magnetomyography (MMG) signal can reliably be recorded following the stimulation of the monosynaptic stretch reflex. The MMG signal shows several phases of activity inside the muscle, the first of which is the propagating muscular action potential. As predicted by the finite wire model, the magnetic field vectors of the propagating muscular action potential are generated by the current flowing along the muscle fiber. Based on the magnetic field vectors, it was possible to reconstruct the pinnation angle of the muscle fibers. The later magnetic field components are linked to the activation of the contractile apparatus. Interpretation MMG allows to analyze the muscle physiology from the propagating muscular action potential to the initiation of the contractile apparatus. At the same time, this methods reveals information about muscle fiber direction and extend. With the development of high-resolution magnetic cameras, that are based on OPM technology, it will be possible to image the function and structure of the biomagnetic field of any skeletal muscle with high precision. This method could be used both, in clinical medicine and also in sports science.

A Cascading Mean-Field Approach to the Calculation of Magnetization Fields in Magnetoactive Elastomers.

We consider magnetoactive elastomer samples based on the elastic matrix and magnetizable particle inclusions. The application of an external magnetic field to such composite samples causes the magnetization of particles, which start to interact with each other. This interaction is determined by the magnetization field, generated not only by the external magnetic field but also by the magnetic fields arising in the surroundings of interacting particles. Due to the scale invariance of magnetic interactions (O(r-3) in d=3 dimensions), a comprehensive description of the local as well as of the global effects requires a knowledge about the magnetization fields within individual particles and in mesoscopic portions of the composite material. Accordingly, any precise calculation becomes technically infeasible for a specimen comprising billions of particles arranged within macroscopic sample boundaries. Here, we show a way out of this problem by presenting a greatly simplified, but accurate approximation approach for the computation of magnetization fields in the composite samples. Based on the dipole model to magnetic interactions, we introduce the cascading mean-field description of the magnetization field by separating it into three contributions on the micro-, meso-, and macroscale. It is revealed that the contributions are nested into each other, as in the Matryoshka's toy. Such a description accompanied by an appropriate linearization scheme allows for an efficient and transparent analysis of magnetoactive elastomers under rather general conditions.

Optically pumped magnetometers disclose magnetic field components of the muscular action potential.

AIM: Aiming at analysing the signal conduction in muscular fibres, the spatio-temporal dynamics of the magnetic field generated by the propagating muscle action potential (MAP) is studied. METHOD: In this prospective, proof of principle study, the magnetic activity of the intrinsic foot muscle after electric stimulation of the tibial nerve was measured using optically pumped magnetometers (OPMs). A classical biophysical electric dipole model of the propagating MAP was implemented to model the source of the data. In order to account for radial currents of the muscular tubules system, a magnetic dipole oriented along the direction of the muscle was added. RESULTS: The signal profile generated by the activity of the intrinsic foot muscles was measured by four OPM devices. Three OPM sensors captured the spatio-temporal magnetic field pattern of the longitudinal intrinsic foot muscles. Changes of the activation pattern reflected the propagating muscular action potential along the muscle. A combined electric and magnetic dipole model could explain the recorded magnetic activity. INTERPRETATION: OPM devices allow for a new, non-invasive way to study MAP patterns. Since magnetic fields are less altered by the tissue surrounding the dipole source compared to electric activity, a precise analysis of the spatial characteristics and temporal dynamics of the MAP is possible. The classic electric dipole model explains major but not all aspects of the magnetic field. The field has longitudinal components generated by intrinsic structures of the muscle fibre. By understanding these magnetic components, new methods could be developed to analyse the muscular signal transduction pathway in greater detail. The approach has the potential to become a promising diagnostic tool in peripheral neurological motor impairments.

Physiological Artifacts and the Implications for Brain-Machine-Interface Design.

The accurate measurement of brain activity by Brain-Machine-Interfaces (BMI) and closed-loop Deep Brain Stimulators (DBS) is one of the most important steps in communicating between the brain and subsequent processing blocks. In conventional chest-mounted systems, frequently used in DBS, a significant amount of artifact can be induced in the sensing interface, often as a common-mode signal applied between the case and the sensing electrodes. Attenuating this common-mode signal can be a serious challenge in these systems due to finite common-mode-rejection-ratio (CMRR) capability in the interface. Emerging BMI and DBS devices are being developed which can mount on the skull. Mounting the system on the cranial region can potentially suppress these induced physiological signals by limiting the artifact amplitude. In this study, we model the effect of artifacts by focusing on cardiac activity, using a current- source dipole model in a torso-shaped volume conductor. Performing finite element simulation with the different DBS architectures, we estimate the ECG common mode artifacts for several device architectures. Using this model helps define the overall requirements for the total system CMRR to maintain resolution of brain activity. The results of the simulations estimate that the cardiac artifacts for skull-mounted systems will have a significantly lower effect than non-cranial systems that include the pectoral region. It is expected that with a pectoral mounted device, a minimum of 60-80 dB CMRR is required to suppress the ECG artifact, depending on device placement relative to the cardiac dipole, while in cranially mounted devices, a 0 dB CMRR is sufficient, in the worst-case scenario. In addition, the model suggests existing commercial devices could optimize performance with a right-hand side placement. The methods used for estimating cardiac artifacts can be extended to other sources such as motion/muscle sources. The susceptibility of the device to artifacts has significant implications for the practical translation of closed-loop DBS and BMI, including the choice of biomarkers, the system design requirements, and the surgical placement of the device relative to artifact sources.

Mental processing comparison between past and future employing a novel EEG analysis based on radiated EM field estimation.

BACKGROUND: The inverse problem solution in the field of ElectroEncephaloGraphy (EEG) analysis has been addressed in the scientific literature for many decades, utilizing either mathematical techniques for measurement fitting or pure ElectroMagnetic (EM) methods involving complex head models for the prediction of the near field. NEW METHOD: A novel radiated EM field estimation analysis scheme is proposed for EEG analysis, based on the determination of a grid of equivalent distributed EM sources with equal magnetic moments, in order to compute the extrapolated far field. A Pattern Search approach is adopted to minimize the Mean Absolute Relative Error between the EM near field created by the source grid and the EM field extracted by the measurements. RESULTS: The application of the method on a subject's brain activity recordings in the context of "Protagoras" mental-auditory experiment demonstrates the capability of the proposed scheme to compare the subject's concentration differences between the limit of present and past versus the limit of present and future. COMPARISON WITH EXISTING METHODS: The proposed method combines features from different existing methods, both in terms of mathematical and EM theory techniques, in order to extend their capabilities and transform the conventional analysis of EEG recordings to a far field radiation basis. CONCLUSIONS: The treatment of the brain as an equivalent far field radiator can be a useful and promising new perspective to the established analysis of EEG recordings arising from brain activity during mental processing.

Experimental Study on Residual Bending Strength of Corroded Reinforced Concrete Beam Based on Micromagnetic Sensor.

This paper presents a nondestructive test method to evaluate the residual bending strength of corroded reinforced concrete beam by analyzing the self-magnetic flux leakage (SMFL) signals. The automatic scanning device was equipped with a micromagnetic sensor and sensor-based experimental details were introduced. Next, the theoretical formula of the normal component HS(z) of the SMFL signal that originated from the corroded region was derived based on the magnetic dipole model and the experimental results were discussed. The results indicate that the experimental data of HS(z) are consistent with the theoretical calculations, both location and extent of the steel bars corrosion can be qualitatively determined by using HS(z). The gradient K of HS(z) is approximately linearly related to the loss rate, S, of the bending strength, which can be used to evaluate the residual bending strength of the corroded reinforced concrete beam. This work lays the foundation for evaluating the residual bending strength of corroded reinforced concrete beams using the SMFL signal; the micromagnetic sensor is further applied to the civil engineering.

Quantitative Study on Corrosion of Steel Strands Based on Self-Magnetic Flux Leakage.

This paper proposed a new computing method to quantitatively and non-destructively determine the corrosion of steel strands by analyzing the self-magnetic flux leakage (SMFL) signals from them. The magnetic dipole model and three growth models (Logistic model, Exponential model, and Linear model) were proposed to theoretically analyze the characteristic value of SMFL. Then, the experimental study on the corrosion detection by the magnetic sensor was carried out. The setup of the magnetic scanning device and signal collection method were also introduced. The results show that the Logistic Growth model is verified as the optimal model for calculating the magnetic field with good fitting effects. Combined with the experimental data analysis, the amplitudes of the calculated values (BxL(x,z) curves) agree with the measured values in general. This method provides significant application prospects for the evaluation of the corrosion and the residual bearing capacity of steel strand.

Neural Mechanisms of Attentional Switching Between Pain and a Visual Illusion Task: A Laser Evoked Potential Study.

Previous studies demonstrated that pain induced by a noxious stimulus during a distraction task is affected by both stimulus-driven and goal-directed processes which interact and change over time. The purpose of this exploratory study was to analyse associations of aspects of subjective pain experience and engagement with the distracting task with attention-sensitive components of noxious laser-evoked potentials (LEPs) on a single-trial basis. A laser heat stimulus was applied to the dorsum of the left hand while subjects either viewed the Rubin vase-face illusion (RVI), or focused on their pain and associated somatosensory sensations occurring on their stimulated hand. Pain-related sensations occurring with every laser stimulus were evaluated using a set of visual analogue scales. Factor analysis was used to identify the principal dimensions of pain experience. LEPs were correlated with subjective aspects of pain experience on a single-trial basis using a multiple linear regression model. A positive LEP component at the vertex electrodes in the interval 294-351 ms (P2) was smaller during focusing on RVI than during focusing on the stimulated hand. Single-trial amplitude variations of the P2 component correlated with changes in Factor 1, representing essential aspects of pain, and inversely with both Factor 2, accounting for anticipated pain, and the number of RVI figure reversals. A source dipole located in the posterior region of the cingulate cortex was the strongest contributor to the attention-related single-trial variations of the P2 component. Instantaneous amplitude variations of the P2 LEP component during switching attention towards pain in the presence of a distracting task are related to the strength of pain experience, engagement with the task, and the level of anticipated pain. Results provide neurophysiological underpinning for the use of distraction analgesia acute pain relief.

LSPR Coupling and Distribution of Interparticle Distances between Nanoparticles in Hydrogel on Optical Fiber End Face.

We report on a new localized surface plasmon resonance (LSPR)-based optical fiber (OF) architecture with a potential in sensor applications. The LSPR-OF system is fabricated by immobilizing gold nanoparticles (GNPs) in a hydrogel droplet polymerized on the fiber end face. This design has several advantages over earlier designs. It dramatically increase the number nanoparticles (NP) available for sensing, it offers precise control over the NP density, and the NPs are positioned in a true 3D aqueous environment. The OF-hydrogel design is also compatible with low-cost manufacturing. The LSPR-OF platform can measure volumetric changes in a stimuli-responsive hydrogel or measure binding to receptors on the NP surface. It can also be used as a two-parameter sensor by utilizing both effects. We present results from proof-of-concept experiments exploring the properties of LSPR and interparticle distances of the GNP-hydrogel OF design by characterizing the distribution of distances between NPs in the hydrogel, the refractive index of the hydrogel and the LSPR attributes of peak position, amplitude and linewidth for hydrogel deswelling controlled with pH solutions.

From evoked potentials to cortical currents: Resolving V1 and V2 components using retinotopy constrained source estimation without fMRI.

Despite evoked potentials' (EP) ubiquity in research and clinical medicine, insights are limited to gross brain dynamics as it remains challenging to map surface potentials to their sources in specific cortical regions. Multiple sources cancellation due to cortical folding and cross-talk obscures close sources, e.g. between visual areas V1 and V2. Recently retinotopic functional magnetic resonance imaging (fMRI) responses were used to constrain source locations to assist separating close sources and to determine cortical current generators. However, an fMRI is largely infeasible for routine EP investigation. We developed a novel method that replaces the fMRI derived retinotopic layout (RL) by an approach where the retinotopy and current estimates are generated from EEG or MEG signals and a standard clinical T1-weighted anatomical MRI. Using the EEG-RL, sources were localized to within 2 mm of the fMRI-RL constrained localized sources. The EEG-RL also produced V1 and V2 current waveforms that closely matched the fMRI-RL's (n = 2) r(1,198) = 0.99, P < 0.0001. Applying the method to subjects without fMRI (n = 4) demonstrates it generates waveforms that agree closely with the literature. Our advance allows investigators with their current EEG or MEG systems to create a library of brain models tuned to individual subjects' cortical folding in retinotopic maps, and should be applicable to auditory and somatosensory maps. The novel method developed expands EP's ability to study specific brain areas, revitalizing this well-worn technique. Hum Brain Mapp 37:1696-1709, 2016. © 2016 Wiley Periodicals, Inc.

Dipole analysis of the influence of linear arrays of points on visually perceived eye level (VPEL).

Previous research has shown that a visual field consisting of as little as one peripherally located luminous line that is pitched from vertical in a dark field induces large changes in an observer's visually perceived eye level (VPEL). The effects of this severely reduced inducing stimulus are surprisingly close to the effects of a highly structured pitched visual field. In the present report we describe two experiments with inducing stimuli that were still further reduced to one or two linear arrays of points of light. The results show that the array's effect on VPEL increases as a negatively accelerated increasing function of the amount of stimulus (i.e., the length of the array, the number of points, and the interpoint separation). We propose a multiscale dipole model (MDM), which quantifies the effect of the array of points on VPEL in terms of dipoles of various lengths that activate orientation and size specific neurons in visual cortex. For example, when the number of points increases in an array of fixed length, dipoles of progressively shorter length are created within the overall length of the stimulus. The shorter dipoles stimulate additional orientation-selective neurons with smaller receptive fields whose neural activity adds to the activity generated by the larger dipoles up to a saturation limit. The functional relation between the psychophysical response and the number of dipoles can be modeled as a rectangular hyperbola, formally similar to equations that have been used to model saturation binding and enzyme velocity in biochemistry and contrast response functions in neurophysiology and psychophysics.

Lead transformations and the dipole approximation: Practical applications.

The transformation of recorded electrocardiographic leads (source leads) into leads that are wanted but were not recorded (target leads) has many practical applications. In general, two transformation methods are put to use, a purely statistical one and a model-based one. They are briefly reviewed and compared. Lead transformations were first used in the early nineteen-sixties to transform the component leads of one vectorcardiographic lead system into those of another. Since then, the use of lead transformations has proliferated and they are currently applied for a variety of purposes. Lead transformations can be grouped according to the source and target leads that are involved. A few applications of lead transformations from the different groups are presented, with a focus on the practicality of the application. The validity and value of the dipole approximation in relation to lead transformations is discussed.

Fingers Crossed: Optical Activity of a Chiral Dimer of Plasmonic Nanorods.

We investigate theoretically the optical activity of a dimer of plasmonic nanoantennas, mimicking the geometry of a molecule with two isolated chromophores, a situation commonly described as exciton coupling in organic chemistry. As the scale of the system increases and approaches the wavelength of visible light, a rich variety of effects arise that are unique to the plasmonic case. Scattering of light by the particles, negligible in very small clusters, strongly perturbs, and eventually dominates, the optical activity. Additionally, retardation effects in dimers with an interparticle separation commensurate with the wavelength of the incident light affect the electromagnetic coupling between the particles and lead to an asymmetric circular dichroism spectrum. We identify conditions for efficient interaction and predict remarkably large anisotropy factors.

EEG spike source localization before and after surgery for temporal lobe epilepsy: a BOLD EEG-fMRI and independent component analysis study

Simultaneous measurements of EEG-functional magnetic resonance imaging (fMRI) combine the high temporal resolution of EEG with the distinctive spatial resolution of fMRI. The purpose of this EEG-fMRI study was to search for hemodynamic responses (blood oxygen level-dependent - BOLD responses) associated with interictal activity in a case of right mesial temporal lobe epilepsy before and after a successful selective amygdalohippocampectomy. Therefore, the study found the epileptogenic source by this noninvasive imaging technique and compared the results after removing the atrophied hippocampus. Additionally, the present study investigated the effectiveness of two different ways of localizing epileptiform spike sources, i.e., BOLD contrast and independent component analysis dipole model, by comparing their respective outcomes to the resected epileptogenic region. Our findings suggested a right hippocampus induction of the large interictal activity in the left hemisphere. Although almost a quarter of the dipoles were found near the right hippocampus region, dipole modeling resulted in a widespread distribution, making EEG analysis too weak to precisely determine by itself the source localization even by a sophisticated method of analysis such as independent component analysis. On the other hand, the combined EEG-fMRI technique made it possible to highlight the epileptogenic foci quite efficiently.