Biology subjects

Goetz, S. M.

Publications and source records attributed to Goetz, S. M..

27 records · Page 2Linked to original sources

bioRxiv2021

Detection of Motor-Evoked Potentials Below the Noise Floor: Rethinking the Motor Threshold

BackgroundMotor-evoked potentials (MEP) are one of the most prominent responses to brain stimulation, such as supra-threshold transcranial magnetic stimulation (TMS) and electrical stimulation. Understanding of the neurophysiology and the determination of the lowest stimulation strength that evokes responses requires the detection of even smaller responses, e.g., from single motor units. However, available detection and quantization methods suffer from a large noise floor. ObjectiveThis paper develops a detection method that extracts MEPs hidden below the noise floor. With this method, we aim to estimate excitatory activations of the corticospinal pathways well below the conventional detection level. MethodsThe presented MEP detection method presents a self-learning matched-filter approach for improved robustness against noise. The filter is adaptively generated per subject through iterative learning. For responses that are reliably detected by conventional detection, the new approach is fully compatible with established peak-to-peak readings and provides the same results but extends the dynamic range below the conventional noise floor. ResultsIn contrast to the conventional peak-to-peak measure, the proposed method increases the signal-to-noise ratio by more than a factor of 5. The first detectable responses appear to be substantially lower than the conventional threshold definition of 50 V median peak-to-peak amplitude. ConclusionThe proposed method shows that stimuli well below the conventional 50 V threshold definition can consistently and repeatably evoke muscular responses and thus activate excitable neuron populations in the brain. As a consequence, the IO curve is extended at the lower end, and the noise cut-off is shifted. Importantly, the IO curve extends so far that the 50 V point turns out to be closer to the center of the logarithmic sigmoid curve rather than close to the first detectable responses. The underlying method is applicable to a wide range of evoked potentials and other biosignals, such as in electroencephalography.

neuroscience↗

bioRxiv2021

Characterizing the short-latency evoked response to intracortical microstimulation across a multi-electrode array

ObjectivePersons with tetraplegia can use brain-machine interfaces to make visually guided reaches with robotic arms. Without somatosensory feedback, these movements will likely be slow and imprecise, like those of persons who retain movement but have lost proprioception. Intracortical microstimulation (ICMS) has promise for providing artificial somatosensory feedback. If ICMS can mimic naturally occurring neural activity, afferent interfaces may be more informative and easier to learn than interfaces that evoke unnaturalistic activity. To develop such biomimetic stimulation patterns, it is important to characterize the responses of neurons to ICMS. ApproachUsing a Utah multi-electrode array, we recorded activity evoked by single pulses, and short (~0.2 s) and long (~4 s) trains of ICMS at a wide range of amplitudes and frequencies. As the electrical artifact caused by ICMS typically prevents recording for many milliseconds, we deployed a custom rapid-recovery amplifier with nonlinear gain to limit signal saturation on the stimulated electrode. Across all electrodes after stimulation, we removed the remaining slow return to baseline with acausal high-pass filtering of time-reversed recordings. With these techniques, we could record ~0.7 ms after stimulation offset even on the stimulated electrode. Main resultsWe recorded likely transsynaptically-evoked activity as early as ~0.7 ms after single pulses of stimulation that was immediately followed by suppressed neural activity lasting 10-150 ms. Instead of this long-lasting inhibition, neurons increased their firing rates for ~100 ms after trains. During long trains, the evoked response on the stimulated electrode decayed rapidly while the response was maintained on non-stimulated channels. SignificanceThe detailed description of the spatial and temporal response to ICMS can be used to better interpret results from experiments that probe circuit connectivity or function of cortical areas. These results can also contribute to the design of stimulation patterns to improve afferent interfaces for artificial sensory feedback.

neuroscience↗

bioRxiv2021

Modular multilevel TMS device with wide output range and ultrabrief pulse capability for sound reduction

ObjectiveThis article presents a novel transcranial magnetic stimulation (TMS) pulse generator with a wide range of pulse shape, amplitude, and width. ApproachBased on a modular multilevel TMS (MM-TMS) topology we had proposed previously, we realized the first such device operating at full TMS energy levels. It consists of ten cascaded H-bridge modules, each implemented with insulated-gate bipolar transistors, enabling both novel high-amplitude ultrabrief pulses as well as pulses with conventional amplitude and duration. The MM-TMS device can output pulses including up to 21 voltage levels with a step size of up to 1100 V, allowing relatively flexible generation of various pulse waveforms and sequences. The circuit further allows charging the energy storage capacitor on each of the ten cascaded modules with a conventional TMS power supply. Main resultsThe MM-TMS device can output peak coil voltages and currents of 11 kV and 10 kA, respectively, enabling suprathreshold ultrabrief pulses (> 8.25 s active electric field phase). Further, the MM-TMS device can generate a wide range of near-rectangular monophasic and biphasic pulses, as well as more complex staircase-approximated sinusoidal, polyphasic, and amplitude-modulated pulses. At matched estimated stimulation strength, briefer pulses emit less sound, which could enable quieter TMS. Finally, the MM-TMS device can instantaneously increase or decrease the amplitude from one pulse to the next in discrete steps by adding or removing modules in series, which enables rapid pulse sequences and paired-pulse protocols with variable pulse shapes and amplitudes. SignificanceThe MM-TMS device allows unprecedented control of the pulse characteristics which could enable novel protocols and quieter pulses.

bioengineering↗

bioRxiv2021

High Bandwidth Power Electronics and Magnetic Nanoparticles for Multichannel Magnetogenetic Neurostimulation

ObjectiveWe present a power electronic system and magnetic nanoparticles for multiplexed magnetogenetic neurostimulation with three channels spanning a wide frequency range and rapid channel switching capability. This enables selective heating of magnetic nanoparticles with different coercivity using various frequency-amplitude combinations of the magnetic field. Such multiplexed operation could provide the technical means for selective magnetogenetic neurostimulation beyond its spatial focality limits. ApproachThe electronic system uses a hybrid of silicon metal-oxide-semiconductor and gallium-nitride field-effect transistors, which generate the required high-amplitude current up to 500 A in the sub-MHz range and the high-frequency current in the MHz range, respectively. Via three discrete resonance capacitor banks, the system generates an alternating magnetic field in the same liquid-cooled field coil at three distinct frequency channels spanning 50 kHz to 4 MHz. Fast switching between channels is achieved with high-voltage contactors connecting the coil to different capacitor banks. We characterized the system by the output channels frequencies, field strength, and switching time, as well as the systems overall operation stability. Three types of iron oxide nanoparticles with different coercivity are developed to form three magnetothermal channels. Specific absorption rate and infrared thermal imaging measurements are performed with the nanoparticles to characterize their heating and demonstrate selective actuation for all three channels. Main resultsThe system achieved the desired target field strengths for three frequency channels (70 kA/m at 50 kHz, 10 kA/m at 500 kHz, and 1 kA/m at [≥]2 MHz), with rapid switching speed between channels on the order of milliseconds. The system can operate continuously for at least two hours at 30% duty cycle with 125 Arms load in the coil, corresponding to a stimulation protocol of cycling the three channels at target strength with 3 s pulses and 7 s interpulse intervals. The nanoparticles were heated with selectivity between 2.3x and 9x for their respective frequency channel. The systems intended use was thus validated with three distinct channels available for magnetothermal heating. SignificanceWe describe the first combination of a power electronic system and magnetic nanoparticles that achieves three stimulation channels. Selective actuation of nanoparticles is demonstrated for each channel using the same field coil, including a novel composition responding to magnetic fields in the MHz range. This approach could improve the speed and flexibility of frequency-multiplexed magnetogenetic neural stimulation.

bioengineering↗

bioRxiv2021

Sub-second multi-channel magnetic control of select neural circuits in behaving flies

Precisely timed activation of genetically targeted cells is a powerful tool for studying neural circuits and controlling cell-based therapies. Magnetic control of cell activity or "magnetogenetics" using magnetic nanoparticle heating of temperature-sensitive ion channels enables remote, non-invasive activation of neurons for deep-tissue applications and studies of freely behaving animals. However, the in vivo response time of thermal magnetogenetics is currently tens of seconds, which prevents the precise temporal modulation of neural activity similar to light-based optogenetics. Moreover, magnetogenetics has not provided a means to selectively activate multiple channels to drive behavior. Here we produce sub-second behavioral responses in Drosophila melanogaster by combining magnetic nanoparticles with a rate-sensitive thermoreceptor (TRPA1-A). Furthermore, by tuning the properties of magnetic nanoparticles to respond to different magnetic field strengths and frequencies, we can achieve sub-second, multichannel stimulation, analogous to multi-color optogenetic stimulation. These results bring magnetogenetics closer to the temporal resolution and multiplexed stimulation possible with optogenetics while maintaining the minimal invasiveness and deep-tissue stimulation only possible by magnetic control.

bioengineering↗

bioRxiv2021

Input-Output Slope Curve Estimation in Neural Stimulation Based on Optimal Sampling Principles

This paper discusses some of the practical limitations and issues, which exist for the input-output (IO) slope curve estimation (SCE) in neural, brain and spinal, stimulation techniques. The drawbacks of the SCE techniques by using existing uniform sampling and Fisher-information-based optimal IO curve estimation (FO-IOCE) methods are elaborated. A novel IO SCE technique is proposed with a modified sampling strategy and stopping rule which improve the SCE performance compared to these methods. The effectiveness of the proposed IO SCE is tested on 1000 simulation runs in transcranial magnetic stimulation (TMS), with a realistic model of motor evoked potentials (MEPs). The results show that the proposed IO SCE method successfully satisfies the stopping rule, before reaching the maximum number of TMS pulses in 79.5% of runs, while the estimation based on the uniform sampling technique never converges and satisfies the stopping rule. At the time of successful termination, the proposed IO SCE method decreases the 95th percentile (mean value in the parentheses) of the absolute relative estimation errors (AREs) of the slope curve parameters up to 7.45% (2.2%), with only 18 additional pulses on average compared to that of the FO-IOCE technique. It also decreases the 95th percentile (mean value in the parentheses) of the AREs of the IO slope curve parameters up to 59.33% (16.71%), compared to that of the uniform sampling method. The proposed IO SCE also identifies the peak slope with higher accuracy, with the 95th percentile (mean value in the parentheses) of AREs reduced by up to 9.96% (2.01%) compared to that of the FO-IOCE method, and by up to 46.29% (13.13%) compared to that of the uniform sampling method.

bioinformatics↗

bioRxiv2019

Accuracy of robotic coil positioning during transcranial magnetic stimulation

ObjectiveRobotic positioning systems for transcranial magnetic stimulation (TMS) promise improved accuracy and stability of coil placement, but there is limited data on their performance. This text investigates the usability, accuracy, and limitations of robotic coil placement with a commercial system, ANT Neuro, in a TMS study.\n\nApproach21 subjects underwent a total of 79 TMS sessions corresponding to 160 hours under robotic coil control. Coil position and orientation were monitored concurrently through an additional neuronavigation system.\n\nMain ResultsRobot setup took on average 14.5 min. The robot achieved low position and orientation error with median 1.34 mm and 3.48{degrees}. The error increased over time at a rate of 0.4%/minute for both position and orientation.\n\nSignificanceAfter the elimination of several limitations, robotic TMS systems promise to substantially improve the accuracy and stability of manual coil position and orientation. Lack of pressure feedback and of manual adjustment of all coil degrees of freedom were limitations of this robotic system.

neuroscience↗

bioRxiv2019

Sound comparison of seven TMS coils at matched simulation strength

BackgroundAccurate data on the sound emitted by transcranial magnetic stimulation (TMS) coils is lacking.\n\nMethodsWe 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.\n\nResultsAcross coils, at maximum stimulator output and 25 cm distance, the sound pressure level (SPL) was 98-125 dB(Z) per pulse and 75-97 dB(A) for a 15 Hz pulse train. At 5 cm distance, these values were estimated to increase to 112-139 dB(Z) and 89-111 dB(A), respectively.\n\nConclusionsThe coils sound was below, but near, relevant exposure limits for operators and may exceed some limits for the subject. Exposure standards may inadequately capture some risks to hearing. For persons near operating TMS coils we recommend hearing protection, and we consider it essential for the TMS subject.\n\nHighlights O_LICoil click varies by over 20 dB(Z) between TMS coils at matched stimulation strength.\nC_LIO_LIClose to TMS coil, sound pressure level may reach nearly 140 dB(Z).\nC_LIO_LIFor rTMS, the continuous sound level can exceed 110 dB(A).\nC_LIO_LIHearing protection is recommended during TMS, especially for the subject.\nC_LI

neuroscience↗

bioRxiv2018

Statistical Model of Motor Evoked Potentials for Simulation of Transcranial Magnetic and Electric Stimulation

Motor evoked potentials (MEPs) are widely used for biomarkers and dose individualization in transcranial stimulation. The large variability of MEPs requires sophisticated methods of analysis to extract information fast and correctly. However, models of MEPs that represent their characteristic features are lacking. This work presents a statistical model that can simulate long sequences of individualized MEP amplitude data with properties matching experimental observations. The MEP model includes three sources of trial-to-trial variability to mimic excitability fluctuations, variability in the neural and muscular pathways, and physiological and measurement noise. It also generates virtual human subject data from statistics of population variability. All parameters are extracted as statistical distributions from experimental data from the literature. The model exhibits previously described features, such as stimulusintensity-dependent MEP amplitude distributions, including bimodal ones. The model can generate long sequences of test data for individual subjects with specified parameters or for subjects from a virtual population. The presented MEP model is the most detailed to date and can be used for the development and implementation of dosing and biomarker estimation algorithms for transcranial stimulation.

physiology↗