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Background: Electromagnetic forces in transcranial magnetic stimulation (TMS) coils generate a loud clicking sound that produces confounding auditory activation and is potentially hazardous to hearing. To reduce this noise while maintaining stimulation efficiency similar to conventional TMS coils, we previously developed a quiet TMS double containment coil (qTMS-DCC). Objective: To compare the stimulation strength, perceived loudness, and EEG response between qTMS-DCC and a commercial TMS coil. Methods: Nine healthy volunteers participated in a within-subject study design. The resting motor thresholds (RMTs) for qTMS-DCC and MagVenture Cool-B65 were measured. Psychoacoustic titration matched the Cool-B65 loudness to qTMS-DCC pulsed at 80, 100, and 120 % RMT. Event-related potentials (ERPs) were recorded for both coils. The psychoacoustic titration and ERPs were acquired with the coils both on and 6 cm off the scalp, the latter isolating the effects of airborne auditory stimulation from body sound and electromagnetic stimulation. The ERP comparisons focused on a centro-frontal region that encompassed peak responses in the global signal while stimulating the primary motor cortex. Results: RMT did not differ significantly between the coils, with or without the EEG cap on the head. qTMS-DCC was perceived to be substantially quieter than Cool-B65. For example, qTMS-DCC at 100 % coil-specific RMT sounded like Cool-B65 at 34 % RMT. The general ERP waveform and topography were similar between the two coils, as were early-latency components, indicating comparable electromagnetic brain stimulation in the on-scalp condition. qTMS- DCC had a significantly smaller P180 component in both on-scalp and off-scalp conditions, supporting reduced auditory activation. Conclusions: The stimulation efficiency of qTMS-DCC matched Cool-B65 while having substantially lower perceived loudness and auditory-evoked potentials.

Background: Transcranial magnetic stimulation (TMS) coils allow only a slow, mechanical adjustment of the stimulating electric field (E-field) orientation in the cerebral tissue. Fast E-field control is needed to synchronize the stimulation with the ongoing brain activity. Also, empirical models that fully describe the relationship between evoked responses and the stimulus orientation and intensity are still missing. Objective: We aimed to (1) develop a TMS transducer for manipulating the E-field orientation electronically with high accuracy at the neuronally meaningful millisecond-level time scale and (2) devise and validate a physiologically based model describing the orientation selectivity of neuronal excitability. Methods: We designed and manufactured a two-coil TMS transducer. The coil windings were computed with a minimum-energy optimization procedure, and the transducer was controlled with our custom-made electronics. The electronic E-field control was verified with a TMS characterizer. The motor evoked potential amplitude and latency of a hand muscle were mapped in 3° steps of the stimulus orientation in 16 healthy subjects for three stimulation intensities. We fitted a logistic model to the motor response amplitude. Results: The two-coil TMS transducer allows one to manipulate the pulse orientation accurately without manual coil movement. The motor response amplitude followed a logistic function of the stimulus orientation; this dependency was strongly affected by the stimulus intensity. Conclusion: The developed electronic control of the E-field orientation allows exploring new stimulation paradigms and probing neuronal mechanisms. The presented model helps to disentangle the neuronal mechanisms of brain function and guide future non-invasive stimulation protocols.

Background: Transcranial magnetic stimulation (TMS) allows non-invasive stimulation of the cortex. In multi-locus TMS (mTMS), the stimulating electric field (E-field) is controlled electronically without coil movement by adjusting currents in the coils of a transducer. Objective: To develop an mTMS system that allows adjusting the location and orientation of the E-field maximum within a cortical region. Methods: We designed and manufactured a planar 5-coil mTMS transducer to allow controlling the maximum of the induced E-field within a cortical region approximately 30 mm in diameter. We developed electronics with a design consisting of independently controlled H-bridge circuits to drive up to six TMS coils. To control the hardware, we programmed software that runs on a field-programmable gate array and a computer. To induce the desired E-field in the cortex, we developed an optimization method to calculate the currents needed in the coils. We characterized the mTMS system and conducted a proof-of-concept motor-mapping experiment on a healthy volunteer. In the motor mapping, we kept the transducer placement fixed while electronically shifting the E-field maximum on the precentral gyrus and measuring electromyography from the contralateral hand. Results: The transducer consists of an oval coil, two figure-of-eight coils, and two four-leaf-clover coils stacked on top of each other. The technical characterization indicated that the mTMS system performs as designed. The measured motor evoked potential amplitudes varied consistently as a function of the location of the E-field maximum. Conclusion: The developed mTMS system enables electronically targeted brain stimulation within a cortical region.

Background: Accurate data on the sound emitted by transcranial magnetic stimulation (TMS) coils is lacking. Methods: We recorded the sound waveforms of seven coils with high bandwidth. We estimated the neural stimulation strength by measuring the induced electric field and applying a strength–duration model to account for different waveforms. Results: Across coils, at maximum stimulator output and 25 cm distance, the sound pressure level (SPL) was 98–125 dB(Z) per pulse and 76–98 dB(A) for a 20 Hz pulse train. At 5 cm distance, these values were estimated to increase to 112–139 dB(Z) and 90–112 dB(A), respectively. Conclusions: The coils’ airborne sound can exceed some exposure limits for TMS subjects and, in some cases, for operators. These findings are consistent with the current TMS safety guidelines that recommend the use of hearing protection.

Background: Computational simulations of the E-field induced by transcranial magnetic stimulation (TMS) are increasingly used to understand its mechanisms and to inform its administration. However, characterization of the accuracy of the simulation methods and the factors that affect it is lacking. Objective: To ensure the accuracy of TMS E-field simulations, we systematically quantify their numerical error and provide guidelines for their setup. Method: We benchmark the accuracy of computational approaches that are commonly used for TMS E-field simulations, including the finite element method (FEM) with and without superconvergent patch recovery (SPR), boundary element method (BEM), finite difference method (FDM), and coil modeling methods. Results: To achieve cortical E-field error levels below 2%, the commonly used FDM and 1st order FEM require meshes with an average edge length below 0.4 mm, 1st order SPR-FEM requires edge lengths below 0.8 mm, and BEM and 2nd (or higher) order FEM require edge lengths below 2.9 mm. Coil models employing magnetic and current dipoles require at least 200 and 3000 dipoles, respectively. For thick solid-conductor coils and frequencies above 3 kHz, winding eddy currents may have to be modeled. Conclusion: BEM, FDM, and FEM all converge to the same solution. Compared to the common FDM and 1st order FEM approaches, BEM and 2nd (or higher) order FEM require significantly lower mesh densities to achieve the same error level. In some cases, coil winding eddy-currents must be modeled. Both electric current dipole and magnetic dipole models of the coil current can be accurate with sufficiently fine discretization.

Transcranial magnetic stimulation (TMS) coils allow only a slow, mechanical adjustment of the stimulating electric field (E-field) orientation in the cerebral tissue. Fast E-field control is needed to synchronize the stimulation with the ongoing brain activity. Also, empirical models that fully describe the relationship between evoked responses and the stimulus orientation and intensity are still missing. We aimed to (1) develop a TMS transducer for manipulating the E-field orientation electronically with high accuracy at the neuronally meaningful millisecond-level time scale and (2) devise and validate a physiologically based model describing the orientation selectivity of neuronal excitability. We designed and manufactured a two-coil TMS transducer. The coil windings were computed with a minimum-energy optimization procedure, and the transducer was controlled with our custom-made electronics. The electronic E-field control was verified with a TMS characterizer. The motor evoked potential amplitude and latency of a hand muscle were mapped in 3° steps of the stimulus orientation in 16 healthy subjects for three stimulation intensities. We fitted a logistic model to the motor response amplitude. The two-coil TMS transducer allows one to manipulate the pulse orientation accurately without manual coil movement. The motor response amplitude followed a logistic function of the stimulus orientation; this dependency was strongly affected by the stimulus intensity. The developed electronic control of the E-field orientation allows exploring new stimulation paradigms and probing neuronal mechanisms. The presented model helps to disentangle the neuronal mechanisms of brain function and guide future non-invasive stimulation protocols. [Display omitted] • Adjustment of the stimulation orientation at 1° steps in submillisecond intervals. • Multi-coil TMS enables automated, closed-loop brain stimulation protocols. • The orientation sensitivity of motor responses follows a logistic function. • The logistic model captures neurophysiological properties of neuronal excitation. [ABSTRACT FROM AUTHOR]

Transcranial magnetic stimulation (TMS) allows non-invasive stimulation of the cortex. In multi-locus TMS (mTMS), the stimulating electric field (E-field) is controlled electronically without coil movement by adjusting currents in the coils of a transducer. To develop an mTMS system that allows adjusting the location and orientation of the E-field maximum within a cortical region. We designed and manufactured a planar 5-coil mTMS transducer to allow controlling the maximum of the induced E-field within a cortical region approximately 30 mm in diameter. We developed electronics with a design consisting of independently controlled H-bridge circuits to drive up to six TMS coils. To control the hardware, we programmed software that runs on a field-programmable gate array and a computer. To induce the desired E-field in the cortex, we developed an optimization method to calculate the currents needed in the coils. We characterized the mTMS system and conducted a proof-of-concept motor-mapping experiment on a healthy volunteer. In the motor mapping, we kept the transducer placement fixed while electronically shifting the E-field maximum on the precentral gyrus and measuring electromyography from the contralateral hand. The transducer consists of an oval coil, two figure-of-eight coils, and two four-leaf-clover coils stacked on top of each other. The technical characterization indicated that the mTMS system performs as designed. The measured motor evoked potential amplitudes varied consistently as a function of the location of the E-field maximum. The developed mTMS system enables electronically targeted brain stimulation within a cortical region. • Multi-locus TMS system with six independent H-bridge channels. • 5-coil transducer to control the electric field within a 30-mm-diameter cortical region. • Algorithm for targeting the electric field. • Automatic motor mapping without physical coil movement. [ABSTRACT FROM AUTHOR]

Accurate data on the sound emitted by transcranial magnetic stimulation (TMS) coils is lacking. We recorded the sound waveforms of seven coils with high bandwidth. We estimated the neural stimulation strength by measuring the induced electric field and applying a strength–duration model to account for different waveforms. Across coils, at maximum stimulator output and 25 cm distance, the sound pressure level (SPL) was 98–125 dB(Z) per pulse and 76–98 dB(A) for a 20 Hz pulse train. At 5 cm distance, these values were estimated to increase to 112–139 dB(Z) and 90–112 dB(A), respectively. The coils' airborne sound can exceed some exposure limits for TMS subjects and, in some cases, for operators. These findings are consistent with the current TMS safety guidelines that recommend the use of hearing protection. • Coil click varies by over 20 dB between TMS coils at matched stimulation strength. • Close to a TMS coil, airborne sound pressure level may reach nearly 140 dB(Z). • During rTMS, continuous airborne sound level may exceed 110 dB(A). • Sound level of rTMS may exceed some standard safety limits for both subject and operator. [ABSTRACT FROM AUTHOR]

Computational simulations of the E-field induced by transcranial magnetic stimulation (TMS) are increasingly used to understand its mechanisms and to inform its administration. However, characterization of the accuracy of the simulation methods and the factors that affect it is lacking. To ensure the accuracy of TMS E-field simulations, we systematically quantify their numerical error and provide guidelines for their setup. We benchmark the accuracy of computational approaches that are commonly used for TMS E-field simulations, including the finite element method (FEM) with and without superconvergent patch recovery (SPR), boundary element method (BEM), finite difference method (FDM), and coil modeling methods. To achieve cortical E-field error levels below 2%, the commonly used FDM and 1st order FEM require meshes with an average edge length below 0.4 mm, 1st order SPR-FEM requires edge lengths below 0.8 mm, and BEM and 2nd (or higher) order FEM require edge lengths below 2.9 mm. Coil models employing magnetic and current dipoles require at least 200 and 3000 dipoles, respectively. For thick solid-conductor coils and frequencies above 3 kHz, winding eddy currents may have to be modeled. BEM, FDM, and FEM all converge to the same solution. Compared to the common FDM and 1st order FEM approaches, BEM and 2nd (or higher) order FEM require significantly lower mesh densities to achieve the same error level. In some cases, coil winding eddy-currents must be modeled. Both electric current dipole and magnetic dipole models of the coil current can be accurate with sufficiently fine discretization. • FDM and 1st order FEM with 1.5 mm average mesh edge length have numerical errors >7%. • BEM or 2nd (and higher) order FEM with 1.5 mm average mesh edge length achieve numerical errors < 2%. • Coil wire cross-section must be accounted to achieve E-field errors below <2%. • Coil eddy currents can account for >2% of E-field when very brief pulses are used. [ABSTRACT FROM AUTHOR]

Background Transcranial magnetic stimulation (TMS) is a non-invasive brain stimulation method: a magnetic field pulse from a TMS coil can excite neurons in a desired location of the cortex. Conventional TMS coils cause focal stimulation underneath the coil centre; to change the location of the stimulated spot, the coil must be moved over the new target. This physical movement is inherently slow, which limits, for example, feedback-controlled stimulation. Objective To overcome the limitations of physical TMS-coil movement by introducing electronic targeting. Methods We propose electronic stimulation targeting using a set of large overlapping coils and introduce a matrix-factorisation-based method to design such sets of coils. We built one such device and demonstrated the electronic stimulation targeting in vivo . Results The demonstrated two-coil transducer allows translating the stimulated spot along a 30-mm-long line segment in the cortex; with five coils, a target can be selected from within a region of the cortex and stimulated in any direction. Thus, far fewer coils are required by our approach than by previously suggested ones, none of which have resulted in practical devices. Conclusion Already with two coils, we can adjust the location of the induced electric field maximum along one dimension, which is sufficient to study, for example, the primary motor cortex. [ABSTRACT FROM AUTHOR]

Background Transcranial magnetic stimulation (TMS) allows focal, non-invasive stimulation of the cortex. A TMS pulse is inherently weakly coupled to the cortex; thus, magnetic stimulation requires both high current and high voltage to reach sufficient intensity. These requirements limit, for example, the maximum repetition rate and the maximum number of consecutive pulses with the same coil due to the rise of its temperature. Objective To develop methods to optimise, design, and manufacture energy-efficient TMS coils in realistic head geometry with an arbitrary overall coil shape. Methods We derive a semi-analytical integration scheme for computing the magnetic field energy of an arbitrary surface current distribution, compute the electric field induced by this distribution with a boundary element method, and optimise a TMS coil for focal stimulation. Additionally, we introduce a method for manufacturing such a coil by using Litz wire and a coil former machined from polyvinyl chloride. Results We designed, manufactured, and validated an optimised TMS coil and applied it to brain stimulation. Our simulations indicate that this coil requires less than half the power of a commercial figure-of-eight coil, with a 41% reduction due to the optimised winding geometry and a partial contribution due to our thinner coil former and reduced conductor height. With the optimised coil, the resting motor threshold of abductor pollicis brevis was reached with the capacitor voltage below 600 V and peak current below 3000 A. Conclusion The described method allows designing practical TMS coils that have considerably higher efficiency than conventional figure-of-eight coils. [ABSTRACT FROM AUTHOR]

Background In transcranial magnetic stimulation (TMS) a strong, brief current pulse driven through a coil is used for non-invasively stimulating the cortex. Properties of the electric field (E-field) induced by the pulse together with physiological parameters determine the outcome of the stimulation. In research and clinical use, TMS is delivered using a wide range of different coils and stimulator units, all having their own characteristics; however, the parameters of the induced E-field are often inadequately known by the user. Objective To better understand how the use of a specific TMS device may affect the resulting cortical stimulation, our objective was to develop an instrument for automated measurement of the E-fields induced by TMS coils in spherically symmetric conductors approximating the head. Methods We built a saline-free, robotized measurement tool based on the triangle construction. The 5-mm-wide measurement probe allows complete sampling of the induced E-field at the studied depth. We used the instrument to characterize TMS coils and stimulators made by two companies. Results The measurements revealed that all tested stimulators performed as expected, but we also found significant differences between the different stimulators. Measurements of different coil specimens of the same stimulator models agreed with each other. Conclusion The presented TMS calibrator allows a straightforward characterization of the E-fields induced by TMS coils. By performing measurements using this kind of a tool helps in ensuring that an investigator knows the properties of the E-field. [ABSTRACT FROM AUTHOR]

Background In transcranial magnetic stimulation (TMS), the stimulation-coil current is typically increased from 0 to over 5000 A in less than 100 μ s. At the peak current, the energy stored in the magnetic field is over 300 J. Thus, the average power during a pulse exceeds 3 MW; the stimulator needs to be built from high-power electronics. The power requirements often limit the duration and frequency of repetitive TMS, for example, via coil heating. Objective We introduce a method for finding the minimum-energy solution for a TMS coil with given focality constraints. Methods This optimization is performed by using a spherically symmetric head model and by expressing the coil as a continuous surface current density, which is eventually discretized to form the coil windings. For the optimization, we defined TMS focality separately for the directions parallel and perpendicular to the field direction at the maximum of induced electric field. Results The computational model used for optimization was verified by manufacturing a prototype coil and measuring the electric field it induces in a spherically symmetric conductor. The optimized coil design requires significantly less power than existing TMS coil designs (a 73% reduction compared to an existing TMS coil with similar focality). Conclusion The described method allows for more efficient, more focal TMS coils, which may reduce coil heating and the coil click. [ABSTRACT FROM AUTHOR]