Modeling motor-evoked potentials from neural field simulations of transcranial magnetic stimulation

Induced neural phase precession through exogenous electric fields

The gradual shifting of preferred neural spiking relative to local field potentials (LFPs), known as phase precession, plays a prominent role in neural coding. Correlations between the phase precession and behavior have been observed throughout various brain regions. As such, phase precession is suggested to be a global neural mechanism that promotes local neuroplasticity. However, causal evidence and neuroplastic mechanisms of phase precession are lacking so far. Here we show a causal link between LFP dynamics and phase precession. In three experiments, we modulated LFPs in humans, a non-human primate, and computational models using alternating current stimulation. We show that continuous stimulation of motor cortex oscillations in humans lead to a gradual phase shift of maximal corticospinal excitability by ~90°. Further, exogenous alternating current stimulation induced phase precession in a subset of entrained neurons (~30%) in the non-human primate. Multiscale modeling of realistic neural circuits suggests that alternating current stimulation-induced phase precession is driven by NMDA-mediated synaptic plasticity. Altogether, the three experiments provide mechanistic and causal evidence for phase precession as a global neocortical process. Alternating current-induced phase precession and consequently synaptic plasticity is crucial for the development of novel therapeutic neuromodulation methods.

Methodological approach for assessing motor cortical excitability changes with single-pulse transcranial magnetic stimulation

Transcranial Magnetic Stimulation (TMS) serves as a crucial tool in evaluating motor cortex excitability by applying short magnetic pulses to the skull, inducing neuron depolarization in the cerebral cortex through electromagnetic induction. This technique leads to the activation of specific skeletal muscles recorded as Motor-Evoked Potentials (MEPs) through electromyography. Although various methodologies assess cortical excitability with TMS, measuring MEP amplitudes offers a straightforward approach, especially when comparing excitability states pre- and post-interventions designed to alter cortical excitability. Despite TMS's widespread use, the absence of a standardized procedure for such measurements in existing literature hinders the comparison of results across different studies. This paper proposes a standardized procedure for assessing changes in motor cortical excitability using single-pulse TMS pre- and post-intervention. The recommended approach utilizes an intensity equating to half of the MEP's maximum amplitude, thereby ensuring equal likelihood of amplitude increase or decrease, providing a consistent basis for future studies and facilitating meaningful comparisons of results.•A method for assessing changes in motor cortical excitability using single-pulse TMS before and after a specified intervention.•We recommend using an intensity equal to half of the MEP's maximum amplitude during evaluations to objectively assess motor cortical excitability changes post-intervention.

Finding synaptic couplings from a biophysical model of motor evoked potentials after theta-burst transcranial magnetic stimulation

OBJECTIVE

We aimed to use measured input-output (IO) data to identify the best fitting model for motor evoked potentials.

METHODS

We analyzed existing IO data before and after intermittent and continuous theta-burst stimulation (iTBS & cTBS) from a small group of subjects (18 for each). We fitted individual synaptic couplings and sensitivity parameters using variations of a biophysical model. A best performing model was selected and analyzed.

RESULTS

cTBS gives a broad reduction in MEPs for amplitudes larger than resting motor threshold (RMT). Close to threshold, iTBS gives strong potentiation. The model captures individual IO curves. There is no change to the population average synaptic weights post TBS but the change in excitatory-to-excitatory synaptic coupling is strongly correlated with the experimental post-TBS response relative to baseline.

CONCLUSIONS

The model describes population-averaged and individual IO curves, and their post-TBS change. Variation among individuals is accounted for with variation in synaptic couplings, and variation in sensitivity of neural response to stimulation.

SIGNIFICANCE

The best fitting model could be applied more broadly and validation studies could elucidate underlying biophysical meaning of parameters.

Design and evaluation of a rodent-specific focal transcranial magnetic stimulation coil with the custom shielding application in rats

Repetitive TMS has been used as an alternative treatment for various neurological disorders. However, most TMS mechanism studies in rodents have been based on the whole brain stimulation, the lack of rodent-specific focal TMS coils restricts the proper translation of human TMS protocols to animal models. In this study, we designed a new shielding device, which was made of high magnetic permeability material, to enhance the spatial focus of animal-use TMS coils. With the finite element method, we analyzed the electromagnetic field of the coil with and without the shielding device. Furthermore, to assess the shielding effect in rodents, we compared the c-fos expression, the ALFF and ReHo values in different groups following a 15 min 5 Hz rTMS paradigm. We found that a smaller focality with an identical core stimulation intensity was achieved in the shielding device. The 1 T magnetic field was reduced from 19.1 mm to 13 mm in diameter, and 7.5 to 5.6 mm in depth. However, the core magnetic field over 1.5 T was almost the same. Meanwhile, the area of electric field was reduced from 4.68 cm² to 4.19 cm², and 3.8 mm to 2.6 mm in depth. Similar to this biomimetic data, the c-fos expression, the ALFF and ReHo values showed more limited cortex activation with the use of the shielding device. However, compared to the rTMS group without the shielding application, more subcortical regions, like the striatum (CPu), the hippocampus, the thalamus, and the hypothalamus were also activated in the shielding group. This indicated that more deep stimulation may be achieved by the shielding device. Generally, compared with the commercial rodents' TMS coil (15 mm in diameter), TMS coils with the shielding device achieved a better focality (~6 mm in diameter) by reducing at least 30% of the magnetic and electric field. This shielding device may provide a useful tool for further TMS studies in rodents, especially for more specific brain area stimulation.

Estimation of the Motor Threshold for Near-Rectangular Stimuli Using the Hodgkin-Huxley Model

The motor threshold measurement is a standard in preintervention probing in TMS experiments. We aim to predict the motor threshold for near-rectangular stimuli to efficiently determine the motor threshold size before any experiments take place. Estimating the behavior of large-scale networks requires dynamically accurate and efficient modeling. We utilized a Hodgkin-Huxley (HH) type model to evaluate motor threshold values and computationally validated its function with known true threshold data from 50 participants trials from state-of-the-art published datasets. For monophasic, bidirectional, and unidirectional rectangular stimuli in posterior-anterior or anterior-posterior directions as generated by the cTMS device, computational modeling of the HH model captured the experimentally measured population-averaged motor threshold values at high precision (maximum error ≤ 8%). The convergence of our biophysically based modeling study with experimental data in humans reveals that the effect of the stimulus shape is strongly correlated with the activation kinetics of the voltage-gated ion channels. The proposed method can reliably predict motor threshold size using the conductance-based neuronal models and could therefore be embedded in new generation neurostimulators. Advancements in neural modeling will make it possible to enhance treatment procedures by reducing the number of delivered magnetic stimuli to participants.

Input-output slope curve estimation in neural stimulation based on optimal sampling principles. J Neural Eng 2021;18:10.1088/1741-2552/abffe5. [PMID: 33975287 PMCID: PMC8384062 DOI: 10.1088/1741-2552/abffe5]

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. 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.