Kent R. Davey

Localizing the site of magnetic brain stimulation in humans

Magnetic stimulation of the human brain is performed in clinical and research settings, but the site of activation has not been clearly localized in humans or other species. We used a set of magnetic stimulus coils with different field profiles to isolate movement of single digits at motor threshold and to calculate corresponding electric field strengths at various distances beneath the scalp. Two coils could produce the same electric field intensity at only 1 point. Thus, we could estimate the depth of stimulation by finding the intersection of the electric field plots, which were then superimposed on MRIs of the underlying brain. In each of 3 subjects the field plots intersected at the crown of a gyrus, in the region of the central sulcus, and near the level of the gray-white junction. This position and the electric field orientation support localization to layer VI of cerebral cortex.

Magnetic stimulation coil and circuit design

A detailed analysis of the membrane voltage rise commensurate with the electrical charging circuit of a typical magnetic stimulator is presented. The analysis shows how the membrane voltage is linked to the energy, reluctance, and resonant frequency of the electrical charging circuit. There is an optimum resonant frequency for any nerve membrane depending on its capacitive time constant. The analysis also shows why a larger membrane voltage will be registered on the second phase of a biphasic pulse excitation. Typical constraints on three key quantities voltage, current, and silicone controlled rectifier (SCR) switching time dictate key components such as capacitance, inductance, and choice of turns.

Localization and characterization of speech arrest during transcranial magnetic stimulation

OBJECTIVE To determine the anatomic and physiologic localization of speech arrest induced by repetitive transcranial magnetic stimulation (rTMS), and to examine the relationship of speech arrest to language function. METHODS Ten normal, right-handed volunteers were tested in a battery of language tasks during rTMS. Four underwent mapping of speech arrest on a 1 cm grid over the left frontal region. Compound motor action potentials from the right face and hand were mapped onto the same grid. Mean positions for speech arrest and muscle activation were identified in two subjects on 3-dimensional MRI. RESULTS All subjects had lateralized arrest of spontaneous speech and reading aloud during rTMS over the left posterior-inferior frontal region. Writing, comprehension, repetition, naming, oral praxis, and singing were relatively spared (P < .05). Stimulation on the right during singing abolished melody in two subjects, but minimally affected speech production. The area of speech arrest overlay the caudal portion of the left precentral gyrus, congruous with the region where stimulation produced movement of the right face. CONCLUSIONS The site of magnetic speech arrest appears to be the facial motor cortex. Its characteristics differ from those of classic aphasias, and include a prominent dissociation among different types of speech output.

Iron-core coils for transcranial magnetic stimulation.

Summary Transcranial magnetic stimulation requires a great deal of power, which mandates bulky power supplies and produces rapid coil heating. The authors describe the construction, modeling, and testing of an iron-core TMS coil that reduces power requirements and heat generation substantially, while improving the penetration of the magnetic field. Experimental measurements and numeric boundary element analysis show that the iron-core stimulation coil induces much stronger electrical fields, allows greater charge recovery, and generates less heat than air-core counterparts when excited on a constant-energy basis. These advantages are magnified in constant-effect comparisons. Examples are given in which the iron-core coil allows more effective operation in research and clinical applications.

Suppressing the surface field during transcranial magnetic stimulation

Transcranial magnetic stimulation (TMS) is used commonly as both a diagnostic tool and as an alternative to electric shock therapy for the treatment of clinical depression. Among the clinical issues encountered in its use is the mitigation of accompanying pain. The objective becomes one of minimizing the induced surface field while still achieving the target field objective. Three techniques discussed for realizing this end are 1) placing a conducting shield over a portion of the central target region, 2) using supplementary coils of opposite polarity in tandem with the primary field, and 3) opening the core angle to distribute the field. Option (3) shows the greatest promise for reducing the ratio of the maximum surface field to the induced target field.

Modeling the effects of electrical conductivity of the head on the induced electric field in the brain during magnetic stimulation

OBJECTIVE The objective of this document is to quantify the effect of changing conductivity within the brain in transcranial magnetic stimulation. METHODS Extreme examples of white and grey matter distributions as well as cerebral spinal fluid are analyzed with numerical boundary element methods to show that the induced E fields for these various distributions vary little from the homogeneous case. RESULTS Models representative of the brain that demarcate regions of white matter and grey matter add an unnecessary level of complexity to the design and analysis of magnetic stimulators. The induced E field varies little between a precise model with exact placement of white and grey matter from that of its homogeneous counterpart. The E field will increase in white matter, and decrease in grey, but the variation is small. The contour integral of the E field around a closed path is dictated by the flux change through that contour. DISCUSSION The maximum value of the variation of the electric field between a fully homogeneous medium, and one filled with different conductivity media is 1/2 the conductivity ratio of the media involved. Neuronal stimulation is more likely at the interface between dissimilar mediums, the greatest being between white matter and cerebral spinal fluid. The interface location where no normal electric field exists will witness a localized electric field 51% greater than the homogeneous E field on the white matter side of that interface. White-grey matter interfaces will have a maximum localized increase in the E field 22.9% greater than the homogeneous case. CONCLUSIONS Variations in neural intracellular potential during a magnetic stimulation pulse will be small among patients. The most efficient modeling will follow by assuming the medium homogeneous, and noting that perturbations from this result will exist.

Designing transcranial magnetic stimulation systems

We explain the process of designing optimized transcranial magnetic stimulation systems and outline a method for identifying optimal system parameters such as the number of turns, the capacitor size, the working voltage, and the size of the stimulation coil. The method combines field analysis, linear and nonlinear circuit analysis, and neural strength-duration response parameters. The method uses boundary-element analysis to predict the electric field as a function of depth, frequency, current, and excitation coil size. It then uses the field analysis to determine the inductance as a function of size and, in general, current when a saturable core is used. Circuit analysis allows these electric field computations to be indexed against system parameters, and optimized for total system energy and stimulation coil size. System optimizations depend on desired stimulation depth. A distinguishing feature of the method is that it inherently treats excitation frequency as an unknown to be determined from optimization.

Latin Hypercube Sampling and Pattern Search in Magnetic Field Optimization Problems

Latin hypercube is a sampling technique for searching n dimensional space. Like Monte Carlo methods, it retains random qualities, and yet Latin hypercube is consistently more effective than Monte Carlo. Despite this fact, not a single paper has been published in IEEE Transactions on Magnetics on its use. Field analysis is a long way from delivering vectorized solutions where a vector of inputs can be processed. Stochastic algorithms are exceptionally inefficient compared to their deterministic counterparts. The best optimization tool would be a deterministic method which quickly and effectively interrogates the search space. Latin hypercube sampling, combined with pattern search solutions, comes close to achieving that objective. An improved solution for the magnetic TEAM Workshop problem 22 is presented using these tools.

Analytic analysis of single- and three-phase induction motors

The analysis of single and multiphase induction motors continues to represent a challenge to researchers in computational electromagnetics due to the presence of r/spl Omega//spl times/B electric fields. This contribution cannot be inserted into the Greens function for boundary element codes; finite difference and finite element approaches are forced to hard code these effects, compensating at high speeds with upwinding techniques. The direct computation of these affects using transfer relations in a linear environment offers an analytical backdrop both for benchmark testing numerical codes and for design assessment criteria. In addition to torque-speed predictions, the terminal relations and total power dissipation in the rotor are computed for an exposed winding three-phase and single-phase machine.

Predicting induction motor circuit parameters

Although boundary-element and finite-element-based numerical codes can now predict torque as a function of slip frequency with extremely high accuracy, most motor manufacturers and factory representatives still favor representing their induction motor as an equivalent circuit. This paper describes how to obtain an equivalent circuit based solely on three parameters: peak torque, frequency at peak torque, and induced stator voltage at peak torque.