Development of accurate human head models for personalized electromagnetic dosimetry using deep learning.

The development of personalized human head models from medical images has become an important topic in the electromagnetic dosimetry field, including the optimization of electrostimulation, safety assessments, etc. Human head models are commonly generated via the segmentation of magnetic resonance images into different anatomical tissues. This process is time consuming and requires special experience for segmenting a relatively large number of tissues. Thus, it is challenging to accurately compute the electric field in different specific brain regions. Recently, deep learning has been applied for the segmentation of the human brain. However, most studies have focused on the segmentation of brain tissue only and little attention has been paid to other tissues, which are considerably important for electromagnetic dosimetry. In this study, we propose a new architecture for a convolutional neural network, named ForkNet, to perform the segmentation of whole human head structures, which is essential for evaluating the electrical field distribution in the brain. The proposed network can be used to generate personalized head models and applied for the evaluation of the electric field in the brain during transcranial magnetic stimulation. Our computational results indicate that the head models generated using the proposed network exhibit strong matching with those created via manual segmentation in an intra-scanner segmentation task.

A high-resolution computational localization method for transcranial magnetic stimulation mapping.

BACKGROUND: Transcranial magnetic stimulation (TMS) is used for the mapping of brain motor functions. The complexity of the brain deters determining the exact localization of the stimulation site using simplified methods (e.g., the region below the center of the TMS coil) or conventional computational approaches. OBJECTIVE: This study aimed to present a high-precision localization method for a specific motor area by synthesizing computed non-uniform current distributions in the brain for multiple sessions of TMS. METHODS: Peritumoral mapping by TMS was conducted on patients who had intra-axial brain neoplasms located within or close to the motor speech area. The electric field induced by TMS was computed using realistic head models constructed from magnetic resonance images of patients. A post-processing method was implemented to determine a TMS hotspot by combining the computed electric fields for the coil orientations and positions that delivered high motor-evoked potentials during peritumoral mapping. The method was compared to the stimulation site localized via intraoperative direct brain stimulation and navigated TMS. RESULTS: Four main results were obtained: 1) the dependence of the computed hotspot area on the number of peritumoral measurements was evaluated; 2) the estimated localization of the hand motor area in eight non-affected hemispheres was in good agreement with the position of a so-called "hand-knob"; 3) the estimated hotspot areas were not sensitive to variations in tissue conductivity; and 4) the hand motor areas estimated by this proposal and direct electric stimulation (DES) were in good agreement in the ipsilateral hemisphere of four glioma patients. CONCLUSION(S): The TMS localization method was validated by well-known positions of the "hand-knob" in brains for the non-affected hemisphere, and by a hotspot localized via DES during awake craniotomy for the tumor-containing hemisphere.

Temperature elevation in the human brain and skin with thermoregulation during exposure to RF energy.

BACKGROUND: Two international guidelines/standards for human protection from electromagnetic fields define the specific absorption rate (SAR) averaged over 10 g of tissue as a metric for protection against localized radio frequency field exposure due to portable devices operating below 3-10 GHz. Temperature elevation is suggested to be a dominant effect for exposure at frequencies higher than 100 kHz. No previous studies have evaluated temperature elevation in the human head for local exposure considering thermoregulation. This study aims to discuss the temperature elevation in a human head model considering vasodilation, to discuss the conservativeness of the current limit. METHODS: This study computes the temperature elevations in an anatomical human head model exposed to radiation from a dipole antenna and truncated plane waves at 300 MHz-10GHz. The SARs in the human model are first computed using a finite-difference time-domain method. The temperature elevation is calculated by solving the bioheat transfer equation by considering the thermoregulation that simulates the vasodilation. RESULTS: The maximum temperature elevation in the brain appeared around its periphery. At exposures with higher intensity, the temperature elevation became larger and reached around 40 °C at the peak SAR of 100 W/kg, and became lower at higher frequencies. The temperature elevation in the brain at the current limit of 10 W/kg is at most 0.93 °C. The effect of vasodilation became notable for tissue temperature elevations higher than 1-2 °C and for an SAR of 10 W/kg. The temperature at the periphery was below the basal brain temperature (37 °C). CONCLUSIONS: The temperature elevation under the current guideline for occupational exposure is within the ranges of brain temperature variability for environmental changes in daily life. The effect of vasodilation is significant, especially at higher frequencies where skin temperature elevation is dominant.

Perspectives on Optimized Transcranial Electrical Stimulation Based on Spatial Electric Field Modeling in Humans.

Background: Transcranial electrical stimulation (tES) generates an electric field (or current density) in the brain through surface electrodes attached to the scalp. Clinical significance has been demonstrated, although with moderate and heterogeneous results partly due to a lack of control of the delivered electric currents. In the last decade, computational electric field analysis has allowed the estimation and optimization of the electric field using accurate anatomical head models. This review examines recent tES computational studies, providing a comprehensive background on the technical aspects of adopting computational electric field analysis as a standardized procedure in medical applications. Methods: Specific search strategies were designed to retrieve papers from the Web of Science database. The papers were initially screened based on the soundness of the title and abstract and then on their full contents, resulting in a total of 57 studies. Results: Recent trends were identified in individual- and population-level analysis of the electric field, including head models from non-neurotypical individuals. Advanced optimization techniques that allow a high degree of control with the required focality and direction of the electric field were also summarized. There is also growing evidence of a correlation between the computationally estimated electric field and the observed responses in real experiments. Conclusions: Computational pipelines and optimization algorithms have reached a degree of maturity that provides a rationale to improve tES experimental design and a posteriori analysis of the responses for supporting clinical studies.

Population-level insights into temporal interference for focused deep brain neuromodulation.

The ability to stimulate deep brain regions in a focal manner brings new opportunities for treating brain disorders. Temporal interference (TI) stimulation has been suggested as a method to achieve focused stimulation in deep brain targets. Individual-level knowledge of the interferential currents has permitted personalizing TI montage via subject-specific digital human head models, facilitating the estimation of interferential electric currents in the brain. While this individual approach offers a high degree of personalization, the significant intra-and inter-individual variability among specific head models poses challenges when comparing electric-field doses. Furthermore, MRI acquisition to develop a personalized head model, followed by precise methods for placing the optimized electrode positions, is complex and not always available in various clinical settings. Instead, the registration of individual electric fields into brain templates has offered insights into population-level effects and enabled montage optimization using common scalp landmarks. However, population-level knowledge of the interferential currents remains scarce. This work aimed to investigate the effectiveness of targeting deep brain areas using TI in different populations. The results showed a trade-off between deep stimulation and unwanted cortical neuromodulation, which is target-dependent at the group level. A consistent modulated electric field appeared in the deep brain target when the same montage was applied in different populations. However, the performance in terms of focality and variability varied when the same montage was used among populations. Also, group-level TI exhibited greater focality than tACS, reducing unwanted neuromodulation volume in the cortical part by at least 1.5 times, albeit with higher variability. These results provide valuable population-level insights when considering TI montage selection.

Small effects of electric field on motor cortical excitability following anodal tDCS.

The dose-response characteristics of transcranial direct current stimulation (tDCS) remain uncertain but may be related to variability in brain electric fields due to individual anatomical factors. Here, we investigated whether the electric fields influence the responses to motor cortical tDCS. In a randomized cross-over design, 21 participants underwent 10 min of anodal tDCS with 0.5, 1.0, 1.5, or 2.0 mA or sham. Compared to sham, all active conditions increased the size of motor evoked potentials (MEP) normalized to the pre-tDCS baseline, irrespective of anterior or posterior magnetic test stimuli. The electric field calculated in the motor cortex of each participant had a nonlinear effect on the normalized MEP size, but its effects were small compared to those of other participant-specific factors. The findings support the efficacy of anodal tDCS in enhancing the MEP size but do not demonstrate any benefits of personalized electric field modeling in explaining tDCS response variability.

Visualizing intraoperative transcranial motor-evoked potentials during glioma surgery for predicting postoperative paralysis prognosis.

PURPOSE: The primary goals of glioma surgery are maximal tumor resection and preservation of brain function. Intraoperative motor-evoked potential (MEP) monitoring is commonly used to predict and minimize postoperative paralysis. However, studies on intraoperative MEP trends and postoperative paralysis are scarce. This study aimed to determine the relationship between intraoperative MEP trends and postoperative paralysis. METHODS: This retrospective study evaluated 229 patients with supratentorial glioma without preoperative paralysis who underwent tumor resection surgery under general anesthesia at our institution between October 2019 and December 2022. Intraoperative transcranial MEP monitoring was performed, and the entire MEP trends on affected and unaffected sides was visualized. Postoperative paralysis and patient-related factors were analyzed. RESULTS: Postoperative paralysis occurred in 36 patients, with the paralysis improving over time and being permanent in 30 and 6 patients, respectively. In the improvement group, the temporary decrease in transcranial MEP rapidly improved. Even when the MEPs were <50% of the control value, fluctuations indicating improvement were observed after the decrease. However, in the permanent paralysis group, transcranial MEP remained consistently <50% of the control value until the end of surgery, after its initial decrease. The significant factors contributing to permanent paralysis were tumor localization close to the pyramidal tract (p = 0.0304) and postoperative cerebral infarction in the pyramidal tract (p = 0.0009). CONCLUSIONS: The overall intraoperative MEP trend can reflect the risk of postoperative paralysis during glioma surgery. Thus, visualizing this trend can provide a better understanding of the prognosis of postoperative paralysis.

Electro-localization method using a muscle conductive phantom for needle position detection towards medical training.

Simulation in healthcare can help train, improve, and evaluate medical personnel's skills. In the case of needle insertion/manipulation inside the muscle during an nEMG examination, a training simulator Requires estimating the position of the needle to output the electrical muscle activity in real time according to the training plan. External cameras can be used to estimate the needle location; however, different error sources can make its implementation difficult and new medical sensing technologies are needed. This study introduces and demonstrates the feasibility of a conductive phantom that serves as the medium for needle insertion and senses the 3D needle position based on a technique named electro-localization for the first time. The proposed conductive phantom is designed so that different voltage distributions are generated in the phantom using electrodes placed on its borders. The needle is inserted in the phantom, and the recorded voltages are mapped to spatial coordinates using a finite element method (FEM)-based computational model of the conductive phantom to estimate the 3D needle tip position. Experimental and simulation results of phantom voltage distributions agreed. In 2D mapping (no depth consideration), the needle position error was 1.7 mm, which was marginally reduced if only the central area of the phantom was used (1.5 mm). In 3D mapping, the error was 4 mm. This study showed the feasibility of using a conductive muscle phantom as a new embedded sensor that estimates needle position for medical training of nEMG without relying on external sensors.

Mapping Brain Motor Functions Using Transcranial Magnetic Stimulation with a Volume Conductor Model and Electrophysiological Experiments.

Transcranial magnetic stimulation (TMS) activates brain cells in a noninvasive manner and can be used for mapping brain motor functions. However, the complexity of the brain anatomy prevents the determination of the exact location of the stimulated sites, resulting in the limitation of the spatial resolution of multiple targets. The aim of this study is to map two neighboring muscles in cortical motor areas accurately and quickly. Multiple stimuli were applied to the subject using a TMS stimulator to measure the motor-evoked potentials (MEPs) in the corresponding muscles. For each stimulation condition (coil location and angle), the induced electric field (EF) in the brain was computed using a volume conductor model for an individualized head model of the subject constructed from magnetic resonance images. A post-processing method was implemented to determine a TMS hotspot using EF corresponding to multiple stimuli, considering the amplitude of the measured MEPs. The dependence of the computationally estimated hotspot distribution on two target muscles was evaluated (n = 11). The center of gravity of the first dorsal interosseous cortical representation was lateral to the abductor digiti minimi by a minimum of 2 mm. The localizations were consistent with the putative sites obtained from previous EF-based studies and fMRI studies. The simultaneous cortical mapping of two finger muscles was achieved with only several stimuli, which is one or two orders of magnitude smaller than that in previous studies. Our proposal would be useful in the preoperative mapping of motor or speech areas to plan brain surgery interventions.

Computation of group-level electric field in lower limb motor area for different tDCS montages.

OBJECTIVE: Transcranial direct current stimulation (tDCS) injects a weak electric current into the brain via electrodes attached to the scalp to modulate cortical excitability. tDCS is used to rebalance brain activity between affected and unaffected hemispheres in rehabilitation. However, a systematic quantitative evaluation of tDCS montage is not reported for the lower limbs. In this study, we computationally investigated the generated electric field intensity, polarity, and co-stimulation of cortical areas for lower limb targeting using high-resolution head models. METHODS: Volume conductor models have thus been employed to estimate the electric field in the brain. A total of 18 head models of healthy subjects were used to calculate the group-level electric fields generated from four montages of tDCS for modulation of lower limbs. RESULTS: C1-C2 montage delivered higher electric field intensities while reaching deeper regions of the lower-limb motor area. It produced a uniform polarization on the same hemisphere target with comparable intensities between hemispheres but with higher variability. CONCLUSIONS: Proper montage selection allows reaching deeper regions of the lower-limb motor area with uniform polarization. SIGNIFICANCE: First systematic computational study providing support to tDCS experimental studies using montages for the lower limb while considering polarity factor for balancing brain activity.

REC-NN: A reconstruction error compensation neural network for Magnetic Resonance Electrical Property Tomography (MREPT).

Electrical properties (EPs) are expected as biomarkers for early cancer detection. Magnetic resonance electrical properties tomography (MREPT) is a technique to non-invasively estimate the EPs of tissues from MRI measurements. While noise sensitivity and artifact problems of MREPT are being solved progressively through recent efforts, the loss of tissue contrast emerges as an obstacle to the clinical applications of MREPT. To solve the problem, we propose a reconstruction error compensation neural network scheme (REC-NN) for a typical analytic MREPT method, Stab-EPT. Two NN structures: one with only ResNet blocks, and the other hybridizing ResNet blocks with an encoder-decoder structure. Results of experiments with digital brain phantoms show that, compared with Stab-EPT, and conventional NN based reconstruction, REC-NN improves both reconstruction accuracy and tissue contrast. It is found that, the encoder-decoder structure could improve the compensation accuracy of EPs in homogeneous region but showed worse reconstruction than only ResNet structure for tumorous tissues unseen in the training samples. Future research is required to address overcompensation problems, optimization of NN structure and application to clinical data.

Selective stimulation of nociceptive small fibers during intraepidermal electrical stimulation: Experiment and computational analysis.

Electrical stimulation of skin nociceptors is gaining attention in pain research and peripheral neuropathy diagnosis. However, the optimal parameters for selective stimulation are still difficult to determine because they require simultaneous characterization of the electrical response of small fibers (Aδ- and C-fibers). In this study, we measured the in vivo electrical threshold responses of small fibers to train-pulse stimulation in humans for the first time. We also examined selective stimulation via a computational model, which combines electrical analysis, and terminal fiber and synaptic models, including the first cutaneous pain C-fiber model. Selective stimulation of small fibers is performed by injecting train-pulse stimulation via coaxial electrodes with an intraepidermal needle tip at varying pulse counts and frequencies. The activation Aδ- or C-fibers was discriminated from the differences in reaction time. Aδ-fiber elicited a pinpricking sensation with a mean reaction time of 0.522 s, and C-fiber elicited a tingling sensation or slight burning itch with a mean reaction time of 1.243 s. The implemented multiscale electrical model investigates synaptic effects while considering stimulation waveform characteristics. Experimental results showed that perception thresholds decreased with the number of consecutive pulses and frequency up to convergence (five pulses or 70 Hz) during the selective stimulation of Aδ- and C-fibers. Considering the synaptic properties, the optimal stimulus conditions for selective stimulation of Aδ- vs. C-fibers were train of at least four pulses and a frequency of 40-70 Hz at a pulse width of 1 ms. The experimental results were modeled with high fidelity by incorporating temporal synaptic effects into the computational model. Numerical analysis revealed terminal axon thickness to be the most important biophysical factor affecting threshold variability. The computational model can be used to estimate perception thresholds while understanding the mechanisms underlying the selective stimulation of small fibers. The parameters derived here are important in exploring selective stimulation between Aδ- and C-fibers for diagnosing neuropathies.

Effects of cerebellar transcranial direct current stimulation on upper limb motor function after stroke: study protocol for the pilot of a randomized controlled trial.

BACKGROUND: Transcranial direct current stimulation (tDCS) is a technique that can noninvasively modulate neural states in a targeted brain region. As cerebellar activity levels are associated with upper limb motor improvement after stroke, the cerebellum is a plausible target of tDCS. However, the effect of tDCS remains unclear. Here, we designed a pilot study to assess: (1) the feasibility of a study that aims to examine the effects of cerebellar tDCS combined with an intensive rehabilitation approach based on the concept of constraint-induced movement therapy (CIMT) and (2) the preliminary outcome of the combined approach on upper limb motor function in patients with stroke in the chronic stage. METHODS: This pilot study has a double-blind randomized controlled design. Twenty-four chronic stroke patients with mild to moderate levels of upper limb motor impairment will be randomly assigned to an active or sham tDCS group. The participants will receive 20 min of active or sham tDCS to the contralesional cerebellum at the commencement of 4 h of daily intensive training, repeatedly for 5 days per week for 2 weeks. The primary outcomes are recruitment, enrollment, protocol adherence, and retention rates and measures to evaluate the feasibility of the study. The secondary outcome is upper limb motor function which will be evaluated using the Action Research Arm Test, Fugl-Meyer Assessment, for the upper extremity and the Motor Activity Log. Additionally, neurophysiological and neuroanatomical assessments of the cerebellum will be performed using transcranial magnetic stimulation and magnetic resonance imaging. These assessments will be conducted before, at the middle, and after the 2-week intervention, and finally, 1 month after the intervention. Any adverse events that occur during the study will be recorded. DISCUSSION: Cerebellar tDCS combined with intensive upper limb training may increase the gains of motor improvement when compared to the sham condition. The present study should provide valuable evidence regarding the feasibility of the design and the efficacy of cerebellar tDCS for upper limb motor function in patients with stroke before a future large trial is conducted. TRIAL REGISTRATION: This study has been registered at the Japan Registry of Clinical Trials ( jRCTs042200078 ). Registered 17 December 2020.

Nonequivalent After-Effects of Alternating Current Stimulation on Motor Cortex Oscillation and Inhibition: Simulation and Experimental Study.

The effects of transcranial alternating current stimulation (tACS) frequency on brain oscillations and cortical excitability are still controversial. Therefore, this study investigated how different tACS frequencies differentially modulate cortical oscillation and inhibition. To do so, we first determined the optimal positioning of tACS electrodes through an electric field simulation constructed from magnetic resonance images. Seven electrode configurations were tested on the electric field of the precentral gyrus (hand motor area). We determined that the Cz-CP1 configuration was optimal, as it resulted in higher electric field values and minimized the intra-individual differences in the electric field. Therefore, tACS was delivered to the hand motor area through this arrangement at a fixed frequency of 10 Hz (alpha-tACS) or 20 Hz (beta-tACS) with a peak-to-peak amplitude of 0.6 mA for 20 min. We found that alpha- and beta-tACS resulted in larger alpha and beta oscillations, respectively, compared with the oscillations observed after sham-tACS. In addition, alpha- and beta-tACS decreased the amplitudes of conditioned motor evoked potentials and increased alpha and beta activity, respectively. Correspondingly, alpha- and beta-tACSs enhanced cortical inhibition. These results show that tACS frequency differentially affects motor cortex oscillation and inhibition.

Multiscale Computational Model Reveals Nerve Response in a Mouse Model for Temporal Interference Brain Stimulation.

There has been a growing interest in the non-invasive stimulation of specific brain tissues, while reducing unintended stimulation in surrounding regions, for the medical treatment of brain disorders. Traditional methods for non-invasive brain stimulation, such as transcranial direct current stimulation (tDCS) or transcranial magnetic stimulation (TMS), can stimulate brain regions, but they also simultaneously stimulate the brain and non-brain regions that lie between the target and the stimulation site of the source. Temporal interference (TI) stimulation has been suggested to selectively stimulate brain regions by superposing two alternating currents with slightly different frequencies injected through electrodes attached to the scalp. Previous studies have reported promising results for TI applied to the motor area in mice, but the mechanisms are yet to be clarified. As computational techniques can help reveal different aspects of TI, in this study, we computationally investigated TI stimulation using a multiscale model that computes the generated interference current pattern effects in a neural cortical model of a mouse head. The results indicated that the threshold increased with the carrier frequency and that the beat frequency did not influence the threshold. It was also found that the intensity ratio between the alternating currents changed the location of the responding nerve, which is in agreement with previous experiments. Moreover, particular characteristics of the envelope were investigated to predict the stimulation region intuitively. It was found that regions with high modulation depth (| maximum| - | minimum| values of the envelope) and low minimum envelope (near zero) corresponded with the activation region obtained via neural computation.

Influence of segmentation accuracy in structural MR head scans on electric field computation for TMS and tES.

In several diagnosis and therapy procedures based on electrostimulation effect, the internal physical quantity related to the stimulation is the induced electric field. To estimate the induced electric field in an individual human model, the segmentation of anatomical imaging, such as magnetic resonance image (MRI) scans, of the corresponding body parts into tissues is required. Then, electrical properties associated with different annotated tissues are assigned to the digital model to generate a volume conductor. However, the segmentation of different tissues is a tedious task with several associated challenges specially with tissues appear in limited regions and/or low-contrast in anatomical images. An open question is how segmentation accuracy of different tissues would influence the distribution of the induced electric field. In this study, we applied parametric segmentation of different tissues to exploit the segmentation of available MRI to generate different quality of head models using deep learning neural network architecture, named ForkNet. Then, the induced electric field are compared to assess the effect of model segmentation variations. Computational results indicate that the influence of segmentation error is tissue-dependent. In brain, sensitivity to segmentation accuracy is relatively high in cerebrospinal fluid (CSF), moderate in gray matter (GM) and low in white matter for transcranial magnetic stimulation (TMS) and transcranial electrical stimulation (tES). A CSF segmentation accuracy reduction of 10% in terms of Dice coefficient (DC) lead to decrease up to 4% in normalized induced electric field in both applications. However, a GM segmentation accuracy reduction of 5.6% DC leads to increase of normalized induced electric field up to 6%. Opposite trend of electric field variation was found between CSF and GM for both TMS and tES. The finding obtained here would be useful to quantify potential uncertainty of computational results.

Coil orientation affects pain sensation during single-pulse transcranial magnetic stimulation over Broca's area.

OBJECTIVE: Pain sensation at the site of stimulation is a side effect of transcranial magnetic stimulation (TMS). The purpose of this study was to investigate how or whether the coil orientation affected TMS-induced pain on Broca's area (BA) or primary motor cortex (M1). METHODS: In Experiment 1, we measured pain thresholds during single-pulse TMS delivered over BA or left M1 at seven coil orientation angles (-90° to 90°, in 30° increments) relative to the posterior-anterior (PA) orientation. In Experiment 2, we evaluated subjective pain intensity when delivering TMS at an intensity of 110% of the resting motor threshold, which is commonly used in conventional TMS studies. RESULTS: In Experiment 1, we found a significant relationship between coil orientation and pain thresholds during BA stimulation but not M1 stimulation. During BA stimulation, pain thresholds were significantly lower when the coil orientation was 30° upward (-30° condition) relative to the PA orientation compared with 60° downward (60° condition). In Experiment 2, pain sensations were significantly stronger in the -30° condition compared with those in the 60° condition. We also confirmed that the averaged location of pain on the head in both conditions were more than 25 mm from the left lateral orbital rim. CONCLUSIONS: The coil orientation of TMS over BA affects pain sensations. This might be attributable to the activation of nociceptors and nociceptive fibers in the muscle tissues above BA, rather than the orbicularis oculi muscle. SIGNIFICANCE: Although the influence of coil orientation on the TMS efficacy is unclear, this study suggests that manipulating the orientation of the TMS coil may be helpful in reducing pain when applying TMS to BA.

Evaluation of Peripheral Electrostimulation Thresholds in Human Model for Uniform Magnetic Field Exposure.

The external field strength according to the international guidelines and standards for human protection are derived to prevent peripheral nerve system pain at frequencies from 300-750 Hz to 1 MHz. In this frequency range, the stimulation is attributable to axon electrostimulation. One limitation in the current international guidelines is the lack of respective stimulation thresholds in the brain and peripheral nervous system from in vivo human measurements over a wide frequency range. This study investigates peripheral stimulation thresholds using a multi-scale computation based on a human anatomical model for uniform exposure. The nerve parameters are first adjusted from the measured data to fit the peripheral nerve in the trunk. From the parameters, the external magnetic field strength to stimulate the nerve was estimated. Here, the conservativeness of protection limits of the international guidelines and standards for peripheral stimulation was confirmed. The results showed a margin factor of 4-6 and 10-24 times between internal and external protection limits of Institute of Electrical and Electronics Engineers standard (IEEE C95.1) and International Commission on Non-Ionizing Radiation Protection guidelines, with the computed pain thresholds.

Influence of population density, temperature, and absolute humidity on spread and decay durations of COVID-19: A comparative study of scenarios in China, England, Germany, and Japan.

In this study, we analyzed the spread and decay durations of the COVID-19 pandemic in several cities of China, England, Germany, and Japan, where the first wave has undergone decay. Differences in medical and health insurance systems, as well as in regional policies incommoded the comparison of the spread and decay in different cities and countries. The spread and decay durations in the cities of the four studied countries were reordered and calculated based on an asymmetric bell-shaped model. We acquired the values of the ambient temperature, absolute humidity, and population density to perform multivariable analysis. We found a significant correlation (p < 0.05) of the spread and decay durations with population density in the four analyzed countries. Specifically, spread duration showed a high correlation with population density and absolute humidity (p < 0.05), whereas decay duration demonstrated the highest correlation with population density, absolute humidity, and maximum temperature (p < 0.05). The effect of population density was almost nonexistent in China because of the implemented strict lockdown. Our findings will be useful in policy setting and governmental actions in the next pandemic, as well as in the next waves of COVID-19.

Synaptic Effect of Aδ-Fibers by Pulse-Train Electrical Stimulation.

Electrical stimulation of specific small fibers (Aδ- and C-fibers) is used in basic studies on nociception and neuropathic pain and to diagnose neuropathies. For selective stimulation of small fibers, the optimal stimulation waveform parameters are an important aspect together with the study of electrode design. However, determining an optimal stimulation condition is challenging, as it requires the characterization of the response of the small fibers to electrical stimulation. The perception thresholds are generally characterized using single-pulse stimulation based on the strength-duration curve. However, this does not account for the temporal effects of the different waveforms used in practical applications. In this study, we designed an experiment to characterize the effects of multiple pulse stimulation and proposed a computational model that considers electrostimulation of fibers and synaptic effects in a multiscale model. The measurements of perception thresholds showed that the pulse dependency of the threshold was an exponential decay with a maximum reduction of 55%. In addition, the frequency dependence of the threshold showed a U-shaped response with a reduction of 25% at 30 Hz. Moreover, the computational model explained the synaptic effects, which were also confirmed by evoked potential recordings. This study further characterized the activation of small fibers and clarified the synaptic effects, demonstrating the importance of waveform selection.