Reducing scalp pain for pTES of motor cortex using background hums

Reducing scalp pain for pTES of motor cortex using background hums | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Reducing scalp pain for pTES of motor cortex using background hums Mats Forssell, Rabira Tusi, Jeehyun Kim, Maxwell Murphy, Jonathan Shulgach, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6273135/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Pulsed transcranial electrical stimulation (pTES) with short ( 20 mA) pulses can elicit suprathreshold neural activity and drive physiological effects such as motor evoked potentials. While this technique could benefit several neurological and neuropsychiatric conditions, it is not widely used because the injected current pulses cause substantial pain in the scalp. We investigated approaches to reduce scalp sensation of pTES at motor threshold in human subjects. We introduce the concept of background hums , additional high-frequency, low-amplitude pulse trains that reduce scalp pain. We tested their pain dampening effects, along with varying pTES electrode distance and pulse width. In a subset of 7 participants, we obtained a reduction in pain score of 2/10 compared to a standard pulse. Using these methods, we were able to stimulate above motor threshold two patients affected by fibromyalgia, a chronic pain condition that also heightens pain sensitivity, with a reported scalp pain below 3/10. This work demonstrates that stimulation pain associated with pTES can be actively mitigated, opening the way for clinical applications of pTES. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Transcranial electrical stimulation (TES) is a powerful neuromodulation technique which has received substantial attention in the last decade for its potential to improve several neurological and neuropsychiatric conditions. For example, studies have shown the benefits of TES for dystonia, gait ataxia, fibromyalgia, depression, and refractory postoperative pain 1–5 . The most common implementations of TES today consist of transcranial direct current and alternating current stimulation (TDCS/TACS). These techniques use low amplitude currents (< 4 mA) to entrain neural activity or evoke ephaptic coupling, but do not generate electric fields of sufficient amplitude in the brain to directly elicit neuronal action potentials 6,7 . A more direct and physiologically potent alternative, called pulsed TES (pTES) was first introduced by Merton and Morton in 1980 8,9 . Unlike TDCS and TACS, pTES injects high-amplitude (typically >30 mA) short-duration (<1 millisecond) pulses, capable of directly activating neurons. E.g., when targeting the motor cortex, pTES can produce direct “D-Waves” in the corticospinal tract, eliciting motor-evoked potentials (MEPs) in muscles that can be used to assess cortical excitability, and enable individual calibration of stimulation site and intensity 10 . However, despite its potential for both neuroscience and therapeutic applications, pTES has remained underutilized because of its major limitation: high scalp pain that is intolerable for many 11 (see also 12–16 ), and was replaced by transcranial magnetic stimulation (TMS 17 ; discovered in 1985) despite distinct neurophysiological effects that could offer unique therapeutic advantages. The goal of this work is to reduce the scalp pain associated with pTES. Due to its ability to directly stimulate the brain and evoke MEPs, while causing low scalp pain, TMS has been widely used to treat several neurological and neuropsychiatric disorders. However, due to differences in how pTES and TMS affect neurons, the downstream effects of stimulation and, therefore, the clinical potential of these modalities, can be distinct. These mechanistic differences, and other potential benefits of pTES (such as portability) motivate our study of lowering the scalp pain associated with pTES. This lowering of scalp pain opens the gate for new non-invasive stimulation treatments to patient populations not adequately served by current approaches, and new studies of direct brain stimulation in ambulatory settings. Notably, under anesthesia, e.g. for monitoring spinal health during surgery, pTES is still used extensively 10,18,19 , as muscle responses to pTES are less sensitive to anesthesia than those to TMS 20 , and scalp pain is not an issue. However, for non-anesthetized applications, overcoming the barrier of stimulation-induced scalp pain is critical to unlocking pTES’s full potential as a neuromodulation therapy. In this work, we provide a novel technique for reducing scalp pain: addition of a small-amplitude, high-frequency current – termed “background hum” – near the stimulating electrodes. These hums are applied tens to hundreds of milliseconds before and after the primary stimulation pulse. In addition to background hums, we investigated the effects of varying interelectrode distances and pulse widths on pain perception. In a group of healthy volunteers, we systematically explored various combinations of these parameters in an effort to minimize pain when stimulating in the upper-limb representation of the motor cortex. In addition,we demonstrated the potential use of pTES in a treatment protocol where we applied pTES with background hums on two patients with fibromyalgia, targeting the primary motor cortex (M1). Advancing beyond the healthy volunteer study, we examined effects of hums in lowering scalp pain when targeting both upper- and lower-limb M1 representations.Throughout this paper, the scalp pain experienced from varying pTES parameters (including hum conditions and pulse widths) are compared to that of a standard pTES pulse of 200 µs pulse width in the absence of hum at motor threshold. This nominal (i.e. standard) condition has been explored in prior works 16 . Results Pain at motor threshold is not substantially affected by changing the inter-electrode distance We investigated how the upper-limb motor threshold and scalp pain were influenced by the position of stimulation electrodes (in the absence of background hum). Numerical rating scale (NRS) scores of stimulation pain and motor thresholds were recorded for 11 unique participants at interelectrode distances of 20% and 40% TRT distance (corresponding to approximately 7 cm and 14 cm respectively). Due to repeated measurements from some participants, the dataset includes 19 total data points. 40% TRT corresponds to the commonly-used C3/C4 montage, while 20% matches the C3/Cz arrangement. On average, while the motor threshold was significantly lower (p < 5x10 -7 ) for the larger anode-cathode distance, the pain levels at motor threshold showed no significant differences across the two distances (Fig 1b,c). In one participant, a more detailed experiment was conducted at interelectrode distances of 10%, 20%, 30%, and 40% of TRT distance. The resulting motor threshold and the NRS score at motor threshold are plotted in Fig. 1a. Again, a substantial reduction in motor threshold is observed as interelectrode distance increases, with thresholds decreasing from 120 mA at 20% TRT distance to 82 mA at 40% TRT distance. Again, the pain intensity at motor threshold showed little variability across the tested distances with NRS scores consistently measuring between 5/10 and 6/10. These findings suggest that a greater distance between electrodes reduces the current required to reach motor threshold. However, the downward trend in motor threshold is negated by the increased pain at higher interelectrode distances resulting in approximately consistent pain perception across all anode-cathode distances. Despite the minimal variation in quantitative pain intensity, all participants expressed preference for stimulation at 20% TRT distance rather than 40% TRT distance. Stimulation pulse width inconsistently affects scalp pain The average motor threshold (over n=7 participants) for pulse widths in a [50 µs; 500 µs] interval are reported in Fig. 2a. Consistent with the Lapicque equation 24 , we find that the average normalized motor threshold is inversely proportional to the pulse width, with I = 5.1/w+19.9 (r 2 =0.97) (I = threshold current (mA), w = pulse width (µs)). Fig. 2b shows the interindividual variation in pain at motor threshold across different pulse widths: while some participants reported reduced pain at longer pulse durations, others showed inconsistent or even increased pain for the same conditions. This suggests that the pulse width that causes minimum scalp pain at threshold should be tailored to each participant. Background hums reduce scalp pain Pilot experiments: In a set of pilot experiments (n=12), NRS scores were collected across various electrode montages, pulse widths, and hum waveforms. Table S10 details all configurations tested in these pilot experiments. In Fig. 3, for each participant, the lowest pain achieved using hums is compared to the pain obtained without hum for the same stimulation pulse at motor threshold (the electrode montage and the pulse width was varied across participants). Fig. 3 illustrates that, at optimal personalized hum conditions, there is always some attenuation of scalp pain, with an average reduction of 1.69±0.48 points (mean ± s.d.). Fig. S5 plots the effects of all hums tested (including suboptimal hums) on patient reported NRS scores. Systematic hum parameter search and comparison with baseline pain: Guided by the pilot experiment results, we systematically applied a set of hum waveforms using a Box-Behnken design (Fig. 8) on n=7 participants while stimulating upper limb muscles at motor threshold. Fig.‌‌‌ 4 illustrates the net effect of the best hum and pulse width combination on NRS scores. NRS scores for each participant are compared for pTES at motor threshold without hum (at a nominal 200 µs pulse width) and pTES at motor threshold with the best hum and pulse width combination, showing an average reduction of 1.99 points (Fig. 4a, p < 0.0006). These findings highlight the substantial magnitude of pain reduction possible with the observed stimulation parameters. Fig. 4b shows the combined effects of pulse width optimization and hum optimization. Consistent with the results in Fig. 2, pulse width optimization alone does not achieve much pain reduction. When no hums are used, there is no statistically significant difference in NRS scores between the nominal 200 µs-width pulse and the optimal pulse width (Fig. 4b; p = 0.29). With joint pulse width and hum parameter optimization, we see a reduction of 2 points on average (p < 0.001). Fig. 4c shows the data of reduction in scalp pain per participant by use of optimized hum at each pulse width. For each pulse width and each participant, the optimized hum reduces scalp pain. Delving further into the interaction of hum and pulse width on NRS scores, we plot surface curves of the average pain reduction (across 7 participants) in response to different hum parameter value combinations at the different pulse widths (Fig. 5). The differences in the surfaces across the different widths illustrate that the effect of hums and pulse width on the scalp pain is coupled in a non-linear manner rather than purely summative. Furthermore, these surface curves vary from participant to participant (Fig. S6). Nonetheless, the surfaces reveal some trends that can serve as general guidelines in hum parameter decision making: hums with low amplitude performed worse on average, which seems to indicate that hums need to be of sufficient amplitude to have a beneficial effect. However, hums with high amplitude performed better, unless the hum ON time was too high. This indicates that at high amplitude and ON time, the charge delivered into the scalp by the hum is sufficient to add to the scalp pain due to the high amplitude stimulation pulse. The hum frequency tends to have a smaller effect than the amplitude or ON time. Heuristic techniques to find minimal pain conditions in fewer steps In Fig. 6, we compare the NRS scores in the no-hum condition across all pulse widths to the scores aggregated via sequential optimization techniques discussed in the methods. In both cases we see that there is a significant reduction in scalp pain intensity when compared to the no hum condition across all pulse widths (technique 1 average reduction: 1.92, p < 0.0001, technique 2 average reduction: 1.91 p < 0.0005). Of note is that the results of both techniques are comparable to that of the exhaustive search. This suggests that both heuristic techniques provide a similar benefit in terms of scalp reduction as the exhaustive search. While an exhaustive search is guaranteed to return the combination of pTES parameters that reduces pain the most, it comes at the cost of requiring more trials in which the pain response is evaluated, at the detriment of the participant who has to endure an extensive number of suboptimal pTES stimulations. The number of trials required for an exhaustive search is given by the equation (mn k ) (m: number of pulse widths, n: number of hum features, k: number of values per hum feature). Tangentially, the number of steps for the Box Behnken design is m(2n(n-1)) with no dependency on k as we are constrained to three values per feature. Our heuristic techniques 1 and 2 require only (m + n k ) trials to achieve their solution. While the heuristic search performed well in practice, greedy search algorithms are sensitive to initial feature evaluation, and could end up achieving a globally suboptimal solution. To further reduce the required number of stimulation trials, we can forgo the pulse width optimization, and simply optimize the hum condition at a predetermined pulse width of 200µs. This is equivalent to performing only step 2a (as detailed in 2.1.3), without including the subsequent pulse width optimization. This simplified heuristic only requires n k trials to find the local optimum. Fig. S8 demonstrates that the optimum obtained with this method achieves a significant reduction in pTES pain compared to the no hum condition while not being not significantly different from the results of technique 1 or 2. While this method empirically proves to be an effective heuristic for optimizing pTES pain, technique 2 performs a subsequent second optimization (over pulse width) and is therefore guaranteed to match or outperform it. A practical implementation might therefore be to perform step 2a and only optionally perform step 2b if the pain is not sufficiently low. Study with two patients with fibromyalgia on pain reduction on upper and lower limbs Patients with chronic pain, especially fibromyalgia, tend to have lower electrical pain thresholds and are thus expected to be less tolerant of TES-induced scalp-pain 25–27 despite the potential use of TES to treat chronic pain. To assess feasibility of application of pTES with hums and pulse optimization in fibromyalgia, two individuals with fibromyalgia underwent pTES for at least three weeks. During the experimental window, >1000 pulses were delivered to the motor cortex at motor threshold targeting either upper- or lower-limb representations (16 upper-limb days, 13 lower-limb days for the first patient; 9 upper-limb days, 6 lower-limb days for the second patient). Electrode configuration and EMG analysis for lower-limb pTES stimulation is detailed in Fig. S7. On the first day of stimulation, prior to any optimization, the first patient with fibromyalgia could not tolerate upper-limb, sub-threshold pTES. A pain of 6/10 was reported at 0.33Hz stimulation at 27 mA with a pulse width of 200 µs (no MEP response could be produced despite lowering the frequency of stimulation). Similarly, a pain of 7/10 was reported at a 300 µs pulse width (18 mA, 0.33 Hz) and 6/10 at a 500 µs pulse width (13 mA, 0.33 Hz). After hum optimization, an MEP response was observed and pain reported at motor threshold (1 Hz, 40 mA, 200 µs pulse width) was 4/10. Throughout the six week treatment period, pain levels during upper-limb pTES stimulation continued to fall and the average pain across all subsequent 15 upper-limb sessions was 2.80/10. During the first lower-limb session, pain at motor threshold (1 Hz, 75 mA, 200 µs pulse width) was 5/10. Immediately after optimization, pain at motor threshold with the same conditions went down to 3.5/10. Over the course of the subsequent 12 lower-limb sessions, the average pain at motor threshold was 3.07/10. The second patient with fibromyalgia had an initial pain intensity of 5/10 at motor threshold (1 Hz, 33 mA pulses with a 300 µs pulse width) in upper-limb pTES. Similarly, a pain of 5.2/10 was reported at a 300 µs pulse width (1 Hz, 45 mA). Pain at motor threshold did go down with a pulse width of 200 µs (1 Hz, 60 mA) (pain of 4/10). After hum optimization, pain at the same condition (1 Hz, 60 mA, 200 µs) was reported to be 1.5/10. Throughout the subsequent 8 days of upper-limb stimulation, the average pain at motor threshold was 1.9/10. During the first lower-limb session, motor threshold could not be reached without the application of hum. A pain of 4.5/10 was reported at 1 Hz stimulation at 70 mA with a pulse width of 200 µs in the absence of hum. After hum optimization, pain at motor threshold (1 Hz, 95 mA, 200 µs pulse width) was 2.80/10. Over the course of the subsequent 5 lower-limb sessions, the average pain at motor threshold was 1.96/10. Discussion This work provides new techniques to address the primary limitation of pTES, namely, intolerable scalp pain caused by the required currents to evoke motor response. To do so, we make use of background hums, which are additional currents injected in the scalp with the exclusive goal of reducing scalp pain. When optimized jointly with stimulating pulse widths, the technique is able to reduce pain by 2 points on the NRS scale in healthy volunteers. Notably, a reduction in 2/10 points not only meets statistical significance but also the minimum clinically significant difference threshold 28 which underscores the effectiveness of this approach in week long treatment protocols. This is made further evident with the study on patients with fibromyalgia who were able to receive > 1000 stimulation pulses per session for at least three weeks. The variability in optimal parameter conditions across individuals also speaks to the need to move beyond a “one-size-fits-all” approach to non-invasive neuromodulation. Instead, future applications of pTES may benefit from personalization, where stimulation settings are adapted in real time to self-reported responses. Mechanisms of hum-induced analgesia Although the mechanism for scalp pain reduction with hum is unknown, a natural thought is that it may serve as a distraction: shifting attention away from noxious stimuli and thereby reducing perception of pain. This concept aligns with research on vibratory analgesia where mechanical vibration stimulates cortical area 3b/1 leading to suppression of activity in area 3a, ultimately causing suppression of pain 29 . The persistence of this effect, even in anesthetized primates, suggests that distraction alone may not explain vibratory analgesia 30 . Fig. S9 provides credence to the idea that hums may have a more complex interaction than simply distracting the participant. If hums primarily functioned as a distraction, we would expect a consistent attenuation of pain across all pulse widths for the same hum condition. At the very least, we would not expect to see that the same hum condition would exacerbate pain at one pulse width and alleviate pain at another. However, the data suggest that the same hum waveform can have different effects on pain perception depending on the pulse width. Since attentional distraction should not vary substantially with changes in the noxious stimulus, the variation in pain modulation across pulse widths suggests a more complex interaction. Other non attentional mechanisms may also be at play. At the spinal level, processes such as the gate control theory of pain 31 or surround inhibition in wide dynamic range neurons via cervical somatosensory nociceptors 32 may lead to attenuation of pain perception. Together, these findings suggest that hum-induced pain modulation may not merely be a byproduct of attentional distraction but likely a combination of factors that interact in a more dynamic manner. Comparison to TMS Transcranial magnetic stimulation (TMS) also elicits direct neural activity through short pulses of current. Contrary to pTES, the magnetic field crossing the scalp does not elicit substantial sensation, making TMS the preferred method of transcranial cortical stimulation. However, there are important reasons why a lower pain TES approach, as described in this study, could be more effective than TMS in certain applications. Mechanism of Action : The effect of TMS on neurons is mediated by the electric field induced by the magnetic field. This field is orthogonal to the magnetic field, and parallel to the brain surface, while TES-injected fields tend to be normal to the brain surface. Because neuronal activation depends on the orientation of the field with respect to its axon 33 , TMS and TES primarily activate different cells. One consequence of this phenomena is thought to be the cause of differential corticospinal tract activation: when stimulating the motor cortex, TMS typically activates interneurons rather than motor-cortical pyramidal neurons (Betz cells) 34 – 36 . It is not fully known how activation of different subpopulations of neurons affects the expected clinical outcomes. One well-established consequence is the difference in corticospinal volleys following motor stimulation using pTES and TMS. pTES predominantly produces direct D-Waves 34 , 35 , 37 . However, TMS predominantly results in indirect I-waves, thus, the therapeutic effects and treatment implications of pTES may be different than that of TMS. For instance, pharmaceuticals like gabapentin can alter synaptic transmission 38 and thereby alter TMS’s ability to activate corticospinal tracts in patients that would otherwise benefit from the compounding effects of neurostimulation (Y. Zhang et al. 2024).It is possible that this explains the variability in TMS’s treatment effects in heterogeneous patient pools 39 . Because pTES directly activates upper motor neurons, it could maintain a higher efficacy under the action of synaptic inhibition, resulting in more consistent treatment outcomes. Waveform Limitations : TMS also has stark limitations in the types of waveforms that can be delivered. Since TMS relies on electromagnetic induction where time-varying currents in a coil produce magnetic fields 40 , the coupling efficiency depends on the rate of change of the magnetic fields (dB/dt). This limits TMS to specific waveforms like monophasic or biphasic pulses 40 . TMS further relies on high-voltage capacitors to deliver the necessary rapid current changes in the coil restricting pulse-widths and making repetitive monophasic pulses, continuous DC stimuli, and slow-varying waveforms impossible altogether with commercially available architecture. Given that different populations of neurons have distinct geometry, channel expressions, and neuronal dynamics 41 , these restrictions on TMS waveforms greatly constrain the selectivity of stimulation and downstream therapeutic effects. Portability : One last benefit of pTES over TMS lies in its portability. TMS has inherent challenges in downsizing the coils as a result of energy efficiency, heating, and physical constraints. Resistive losses are more significant for smaller coils 40 . Although delivering more energy to the coil can offset its lower energy efficiency, this approach poses challenges such as higher power demands, excessive coil heating, increased internal coil forces, and elevated noise levels 40 . Recent efforts 42 – 44 have made progress towards portable TMS (i.e. a stationary device that can be easily relocated) but stop short of “wearable” neurostimulation. Meanwhile research studies have already validated the effectiveness of miniature wearable tDCS that induces comparable neuromodulatory effects of commercially available products 45 . Limitations This study is limited by its small sample size, with 19 participants and two patients with fibromyalgia, which restricts generalizability. Optimal hum parameters and pain intensity vary between individuals and across sessions, as seen in the patients with fibromyalgia, making consistent optimization challenging. Moreover, NRS scores only capture a limited window of the multifaceted perception of pain.This is evident when noting that pain was similar across all anode-cathode distances but preference was made towards smaller anode-cathode distances. Furthermore, the range of tested hum parameters and electrode spatial configurations was narrow, potentially missing more effective setups. Addressing these factors in future research will improve the clinical utility of pTES. Methods In this experimental study, 19 healthy participants (5 Females, 14 Males, age 30.35 ± 6.49 ) and two participants with fibromyalgia (1 Female, 1 Male) underwent pTES. The experiment protocols were reviewed and approved by the Carnegie Mellon University Institutional Review Board, and all participants provided written informed consent. Self-reported scalp pain intensity scores for participants undergoing pTES were recorded as we varied three key sets of parameters: anode-cathode distance, pulse width, and background hum parameters. Stimulation setup Currents were delivered to the electrodes using a commercial current stimulator (DS8R, Digitimer Ltd.) connected to a computer-controlled data acquisition hardware (BNC-2110, National Instruments) using custom software (Matlab, Mathworks). This setup allowed flexible customization of the pulse parameters, including width, amplitude, and timings. The stimulation pulse consisted of single monophasic anodic rectangular pulses injected through the scalp electrodes. The pulse duration was varied across experiments, ranging from 50 µs to 1000 µs. For each pulse width, the amplitude of the pulses was gradually increased over multiple blocks until the motor threshold was reached (details of threshold determination are provided in Section 2.2). Stimulation at motor threshold was repeated in blocks of 20 to 30 trials at a frequency of 1 Hz for averaging. After any block of stimulation trials, the participant was asked to report their level of pain from 0–10 using a numerical rating scale (NRS) with 0 being “no pain” and 10 being “worst pain imaginable” 22 . To reduce the motor threshold, the participants were asked to grip a dynamometer at 20% of maximum voluntary contraction (MVC) throughout the stimulation period. For measuring evoked responses in muscles, electromyography (EMG) signals were recorded at 4 kHz using 64-channel high-density EMG patches (SAGA, TMSi; 8.75mm interelectrode distance) and additional bipolar electrodes (Norotrode DDN 20, Myotronics; 22 mm interelectrode distance). For upper-limb responses, the EMG patches were placed on the dominant wrist flexor and extensor muscle groups (Fig. 7b). Additionally, bipolar electrodes were used to record EMG signals on the dominant first dorsal interosseous (FDI), abductor pollicis brevis (APB), biceps brachii, and triceps brachii. Electrode montage for assessing pain and motor threshold as inter-electrode distance is varied A study was performed (n = 11) to determine the effect of the inter-electrode distance on the pain level at motor threshold. A common electrode configuration for pTES of upper limbs is to place the anode at C3 and the cathode at C4 (for right-hand dominant participants; reversed for left-handed participants) 10 , corresponding to an inter-electrode distance of 40% of the lateral scalp length (measured as the tragus-to-tragus (TRT) distance). We compared this 40% TRT configuration to placements where the inter-electrode distance was 20% of the scalp length (corresponding to anode placement at C3 and cathode placement at Cz). In one participant, additional inter-electrode distances were used, with the anode at C3 and the cathode positioned laterally at distances of 10%, 20%, 30%, and 40% of the TRT distance. Jointly varying pulse width and background hum parameters for pain minimization Pilot experiments : A set of pilot experiments (n = 12) were conducted to determine whether applying a “background hum” to the scalp consisting of a low-amplitude, high-frequency pulse train injected near the motor stimulation electrodes can alter the scalp sensation caused by the stimulation pulse. Separate anode-cathode pairs and commercial stimulators (DS8R, Digitimer Ltd.) were used to generate these background hum waveforms. The set of background hum waveforms we tested was drawn from high-frequency (100 Hz − 5 kHz), low-amplitude (1 mA − 10 mA) pulse trains. In addition to the frequency and amplitude, various other hum-waveform parameters were tested to identify what hum waveforms lead to the greatest reduction in scalp pain. These parameters include spatial configuration of the electrodes delivering the hum, train duration (100ms − 1000ms), and timing of the stimulation pulse with respect to the background hum. Hum trains, whose amplitude varied throughout the train (i.e. with non-constant envelope), were also tested, but the maximum amplitude never exceeded 10 mA. A complete table of all the stimulation parameters explored are detailed in Table S10. A manual sampling of all these parameters on healthy volunteers, informed by self-reported NRS scores, enabled us to converge onto personalized hum waveforms for patients with fibromyalgia. For each applied hum condition, we compared the reported scalp pain to the scalp pain reported using the same stimulation pulse without the hum. Systematic hum parameter search : Results from these pilot experiments additionally informed the paradigm described below, which was implemented on healthy volunteers (n = 7). Here, the effect of three hum parameters (Fig. 8) was examined, and NRS scores were compared to a no-hum case. A sweep of hum parameters was conducted using a Box-Behnken design 23 to systematically vary hum ON time, frequency, and amplitude in three levels each (Fig. 8b,c). The train duration was kept fixed at 500 ms, the stimulation pulse was consistently delivered at the midpoint of the 500 ms hum, and the hum amplitude was kept constant throughout the train. For upper-limb stimulation, two pairs of hum-delivering gold cup electrodes were placed, each 2 cm to the left and right of the stimulating anode and cathode. The hum anodes were placed laterally from the stimulation electrodes, and the hum cathodes medially (Fig. 7a). A baseline NRS pain score was determined at motor threshold in the absence of the background hum. Following the baseline assessment, the background hums described in Fig. 8b were added to the stimulation pulse in a random order, and the NRS pain score was recorded. After all hum conditions were applied, a final baseline NRS score was determined in the absence of hum. To adjust for habituation, a linear fit (across session time) was applied between the pre-hum and post-hum baseline pain measurements (Fig. S2 illustrates the extent of habituation when averaged across all trials for all participants). The NRS scores for all intermediate measurements were corrected for this linear trend. The effect of the hum is characterized by the difference between the pre-hum baseline pain and the corrected hum pain. The pain reduction for points in the hum parameter space not sampled by the Box-Behnken design are calculated using quadratic regression (detailed in Fig. S3). The systematic hum parameter assessment was performed at four stimulation pulse widths: 100 µs, 200 µs, 300 µs, and 500 µs. Data-efficient Optimization Techniques of Stimulation Pulse Width and Hum Parameters When jointly optimizing pulse width and hum parameters, several methods can be employed. An exhaustive search of the joint effect of each hum parameter and each pulse width is guaranteed to determine which pTES waveform results in the least scalp pain. However, assuming n hum parameters with k possible values each and m different pulse widths, the number of possible conditions is mn k . Experimentally applying all these conditions becomes impractical even for moderate values of m, n, and k. As such, we introduce two greedy coordinate search techniques that sequentially optimize the hum parameters and the pulse width. In technique 1, we first optimize pulse width and then the hum parameters. That is, we first perform motor stimulation at every pulse width (in a discretized set) in the absence of hum, selecting the one that causes the least pain (step 1a). At this “subject-favored pulse width”, we then vary all of the hum parameters and determine which combination of hum parameters and pulse width values results in the least scalp pain (step 1b). In technique 2, we first (step 2a) perform motor stimulation at a nominal pulse width of 200µs (a commonly used pulse width in TES literature) 16 , and select the hum condition that causes the lowest scalp pain. Then (step 2b), we change the stimulation pulse width while using the identified best hum condition in step 2a. Analysis of the two techniques was conducted using the data collected in the Box-Behnken design in 2.1.2 (n = 7). A preliminary exhaustive search was done experimentally to fully explore the search space across three hum parameters (Fig. 4 ) and 4 pulse width values. Analysis of the attained NRS score using techniques 1 and 2 was done post-hoc, once the exhaustive grid search was completed. Furthermore, technique 1 was employed experimentally to optimize pTES parameters for the patients with fibromyalgia. Data analysis Recorded EMG signals were analyzed using custom scripts in MATLAB. The recordings were band-passed filtered using a 4th order Butterworth filter with [60Hz; 600Hz] corner frequencies. The recordings were stimulus-aligned and averaged across trials (20–30 repetitions for each condition). The magnitude of the MEP response was quantified using the ratio of the post-stimulus root mean square (RMS) calculated between [20 ms; 40 ms] relative to stimulus onset, to pre-stimulus RMS value calculated between [-40 ms: -20 ms] relative to stimulus onset. Post-stimulus RMS windowing is consistent with the expected delay for muscle activation in the upper-limbs. MEP threshold was defined as the minimum current required to (1) elicit a visibly clear motor response (Fig. S4), and (2) return a RMS ratio greater than 2, in at least one channel. Two tailed paired t-tests were used for all statistical tests. Declarations Competing interests M.F., V.J., D.W., B.A., and P.G. have equity in Synapse Symphony, a company developing TES systems. References Young SJ, Bertucco M, Sheehan-Stross R, Sanger TD. Cathodal transcranial direct current stimulation in children with dystonia: a pilot open-label trial: A pilot open-label trial. J Child Neurol 2013;28:1238–44. Flöel A. tDCS-enhanced motor and cognitive function in neurological diseases. Neuroimage 2014;85 Pt 3:934–47. Zandieh Z, Niksolat M, Saghafian larijani S, Mirfakhraee H. Anodal stimulation of primary motor cortex in elderly women with fibromyalgia: A randomized, double-blind, placebo-controlled trial. Rheumatol Res 2020;5:167–72. Vanderhasselt M-A, De Raedt R, Namur V, Lotufo PA, Bensenor IM, Boggio PS, et al. Transcranial electric stimulation and neurocognitive training in clinically depressed patients: A pilot study of the effects on rumination. Progress in Neuro-Psychopharmacology and Biological Psychiatry 2015;57:93–9. Borckardt JJ, Romagnuolo J, Reeves ST, Madan A, Frohman H, Beam W, et al. Feasibility, safety, and effectiveness of transcranial direct current stimulation for decreasing post-ERCP pain: a randomized, sham-controlled, pilot study. Gastrointest Endosc 2011;73:1158–64. Agnihotri SK, Cai J. Investigating the effects of transcranial alternating current stimulation on cortical oscillations and network dynamics. Brain Sci 2024;14:767. Lefaucheur J-P, Wendling F. Mechanisms of action of tDCS: A brief and practical overview. Neurophysiol Clin 2019;49:269–75. Merton PA, Morton HB. Stimulation of the cerebral cortex in the intact human subject. Nature 1980;285:227. Merton PA, Hill DK, Morton HB, Marsden CD. Scope of a technique for electrical stimulation of human brain, spinal cord, and muscle. Lancet 1982;2:597–600. Szelényi A, Kothbauer KF, Deletis V. Transcranial electric stimulation for intraoperative motor evoked potential monitoring: Stimulation parameters and electrode montages. Clin Neurophysiol 2007;118:1586–95. Polanía R, Nitsche MA, Ruff CC. Studying and modifying brain function with non-invasive brain stimulation. Nat Neurosci 2018;21:174–87. Rothwell J. Transcranial brain stimulation: Past and future. Brain Neurosci Adv 2018;2:2398212818818070. Rothwell JC. Physiological studies of electric and magnetic stimulation of the human brain. Electroencephalogr Clin Neurophysiol Suppl 1991;43:29–35. Rothwell JC. Techniques and mechanisms of action of transcranial stimulation of the human motor cortex. J Neurosci Methods 1997;74:113–22. Rothwell J, Burke D, Hicks R, Stephen J, Woodforth I, Crawford M. Transcranial electrical stimulation of the motor cortex in man: further evidence for the site of activation. J Physiol 1994;481 (Pt 1):243–50. Caulfield KA, Badran BW, DeVries WH, Summers PM, Kofmehl E, Li X, et al. Transcranial electrical stimulation motor threshold can estimate individualized tDCS dosage from reverse-calculation electric-field modeling. Brain Stimul 2020;13:961–9. Barker AT, Jalinous R, Freeston IL. Non-invasive magnetic stimulation of human motor cortex. The Lancet 1985;325:1106–7. Tsutsui S, Yamada H. Basic principles and recent trends of transcranial motor evoked potentials in intraoperative neurophysiologic monitoring. Neurol Med Chir (Tokyo) 2016;56:451–6. Macdonald D. Safety of intraoperative transcranial electrical stimulation motor evoked potential monitoring. J Clin Neurophysiol 2002;19:416–29. Hargreaves SJ, Watt JWH. Intravenous anaesthesia and repetitive transcranial magnetic stimulation monitoring in spinal column surgery. Br J Anaesth 2005;94:70–3. Klem GH, Lüders HO, Jasper HH, Elger C. The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology. Electroencephalogr Clin Neurophysiol Suppl 1999;52:3–6. Bijur PE, Latimer CT, Gallagher EJ. Validation of a verbally administered numerical rating scale of acute pain for use in the emergency department. Acad Emerg Med 2003;10:390–2. Ferreira SLC, Bruns RE, Ferreira HS, Matos GD, David JM, Brandão GC, et al. Box-Behnken design: an alternative for the optimization of analytical methods. Anal Chim Acta 2007;597:179–86. Geddes LA, Bourland JD. The strength-duration curve. IEEE Trans Biomed Eng 1985;32:458–9. Smeets Y, Soer R, Chatziantoniou E, Preuper RHRS, Reneman MF, Wolff AP, et al. Role of non-invasive objective markers for the rehabilitative diagnosis of central sensitization in patients with fibromyalgia: A systematic review. J Back Musculoskelet Rehabil 2024;37:525–84. Desmeules JA, Cedraschi C, Rapiti E, Baumgartner E, Finckh A, Cohen P, et al. Neurophysiologic evidence for a central sensitization in patients with fibromyalgia. Arthritis Rheum 2003;48:1420–9. Marques AP, Ferreira EAG, Matsutani LA, Pereira CAB, Assumpção A. Quantifying pain threshold and quality of life of fibromyalgia patients. Clin Rheumatol 2005;24:266–71. Kendrick DB, Strout TD. The minimum clinically significant difference in patient-assigned numeric scores for pain. Am J Emerg Med 2005;23:828–32. Tommerdahl M, Delemos KA, Vierck CJ Jr, Favorov OV, Whitsel BL. Anterior parietal cortical response to tactile and skin-heating stimuli applied to the same skin site. J Neurophysiol 1996;75:2662–70. Vierck CJ, Whitsel BL, Favorov OV, Brown AW, Tommerdahl M. Role of primary somatosensory cortex in the coding of pain. Pain 2013;154:334–44. Melzack R, Wall PD. Pain mechanisms: a new theory: A gate control system modulates sensory input from the skin before it evokes pain perception and response. Science 1965;150:971–9. Zhang Z, Zheng H, Yu Q, Jing X. Understanding of spinal wide dynamic range neurons and their modulation on pathological pain. J Pain Res 2024;17:441–57. Laakso I, Hirata A, Ugawa Y. Effects of coil orientation on the electric field induced by TMS over the hand motor area. Phys Med Biol 2014;59:203–18. Terao Y, Ugawa Y. Basic mechanisms of TMS. J Clin Neurophysiol 2002;19:322–43. Journée SL, Journée HL, Berends HI, Reed SM, de Bruijn CM, Delesalle CJG. Comparison of muscle MEPs from transcranial magnetic and electrical stimulation and appearance of reflexes in horses. Front Neurosci 2020;14:570372. Amassian VE, Quirk GJ, Stewart M. A comparison of corticospinal activation by magnetic coil and electrical stimulation of monkey motor cortex. Electroencephalogr Clin Neurophysiol 1990;77:390–401. Legatt AD, Emerson RG, Epstein CM, MacDonald DB, Deletis V, Bravo RJ, et al. ACNS guideline: Transcranial electrical stimulation motor evoked potential monitoring. J Clin Neurophysiol 2016;33:42–50. Sills GJ. The mechanisms of action of gabapentin and pregabalin. Curr Opin Pharmacol 2006;6:108–13. Hordacre B, Goldsworthy MR, Vallence A-M, Darvishi S, Moezzi B, Hamada M, et al. Variability in neural excitability and plasticity induction in the human cortex: A brain stimulation study. Brain Stimul 2017;10:588–95. Peterchev AV, Deng Z-D, Goetz SM. Advances in transcranial magnetic stimulation technology. Brain Stimulation . Hoboken, NJ, USA: John Wiley & Sons, Inc; 2015. p. 165–89. Chung S-H, Anderson OS, Krishnamurthy V, editors. Biological membrane ion channels: Dynamics, structure, and applications . 2007th ed. New York, NY: Springer; 2006. Charlet de Sauvage R, Beuter A, Lagroye I, Veyret B. Design and construction of a portable transcranial magnetic stimulation (TMS) apparatus for migraine treatment. J Med Device 2010;4:015002. Baryshev G, Bozhko Y, Konashenkova N, Kavkaev K, Kuznetsova Y. Principles of development of a mobile system for transcranial magnetic stimulation. Procedia Comput Sci 2020;169:359–64. Epstein CM. A six-pound battery-powered portable transcranial magnetic stimulator. Brain Stimul 2008;1:128–30. Kouzani AZ, Jaberzadeh S, Zoghi M, Usma C, Parastarfeizabadi M. Development and validation of a miniature programmable tDCS device. IEEE Trans Neural Syst Rehabil Eng 2016;24:192–8. Additional Declarations Yes there is potential Competing Interest. M.F., V.J., D.W., B.A., and P.G. have equity in Synapse Symphony, a company developing TES systems. Supplementary Files TESscalppainpapersuppST10.xlsx Supplementary Table S10 TESscalppainpapersupp.docx Supplementary Figures Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6273135","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":438494510,"identity":"0e2468fc-f338-4c15-90ab-7b6213eeffdd","order_by":0,"name":"Mats Forssell","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIiWNgGAWjYDAC5gNgSoYfSEgghNnwaGFLAFM8kg0kazE4QKwW3TbmYx9//LHhMT5+9uDtiorDDPzTzhgwfCg7jFOL2TG25Nm8bWk8Zmfyki3PnDnMIHE7x4Bxxjk8Wu73GDMzNhzmMTuQYybZ2HabwUA6x4CZtw2fLTzGjD/+/Ocx7n8D1PIPquUvAS0MPGwHeAwkQLY0QLUw4tXClgx0RjKPxI03xpYNx/7zSNxOKzjYcy4djxbmw0CH2cnx9+cY3myoSZPjn5288cGPMmucWjAAD4g4QLz6UTAKRsEoGAXYAADGQlBU+32FFAAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-7811-6773","institution":"Carnegie Mellon University","correspondingAuthor":true,"prefix":"","firstName":"Mats","middleName":"","lastName":"Forssell","suffix":""},{"id":438494511,"identity":"4ad7cd2c-188e-4c13-a802-c39c54717c7c","order_by":1,"name":"Rabira Tusi","email":"","orcid":"","institution":"Carnegie Mellon University","correspondingAuthor":false,"prefix":"","firstName":"Rabira","middleName":"","lastName":"Tusi","suffix":""},{"id":438494512,"identity":"4aefd767-0eb7-43f4-a237-5faebeef53f6","order_by":2,"name":"Jeehyun Kim","email":"","orcid":"https://orcid.org/0009-0006-1159-589X","institution":"Carnegie Mellon University","correspondingAuthor":false,"prefix":"","firstName":"Jeehyun","middleName":"","lastName":"Kim","suffix":""},{"id":438494513,"identity":"4068d8f0-c2f6-46cb-9a52-1dcd2465c4f2","order_by":3,"name":"Maxwell Murphy","email":"","orcid":"","institution":"Carnegie Mellon University","correspondingAuthor":false,"prefix":"","firstName":"Maxwell","middleName":"","lastName":"Murphy","suffix":""},{"id":438494514,"identity":"1a47e2a4-443f-4f5e-bc36-971ae3ca3b8a","order_by":4,"name":"Jonathan Shulgach","email":"","orcid":"","institution":"Carnegie Mellon University","correspondingAuthor":false,"prefix":"","firstName":"Jonathan","middleName":"","lastName":"Shulgach","suffix":""},{"id":438494515,"identity":"62dbda71-e5ad-4a26-881e-b819b87cc483","order_by":5,"name":"Prakarsh Yadav","email":"","orcid":"","institution":"Carnegie Mellon University","correspondingAuthor":false,"prefix":"","firstName":"Prakarsh","middleName":"","lastName":"Yadav","suffix":""},{"id":438494516,"identity":"2546a51b-0e14-4789-b32d-a751de0ef455","order_by":6,"name":"Alonso Buitano Tang","email":"","orcid":"","institution":"Carnegie Mellon University","correspondingAuthor":false,"prefix":"","firstName":"Alonso","middleName":"Buitano","lastName":"Tang","suffix":""},{"id":438494517,"identity":"b6635935-4a81-4a1c-8403-343573bf88b0","order_by":7,"name":"Maya Maurer","email":"","orcid":"","institution":"University of Pittsburgh","correspondingAuthor":false,"prefix":"","firstName":"Maya","middleName":"","lastName":"Maurer","suffix":""},{"id":438494518,"identity":"b47fef9a-0723-40f7-b715-b46a37a86495","order_by":8,"name":"Vishal Jain","email":"","orcid":"","institution":"Carnegie Mellon University","correspondingAuthor":false,"prefix":"","firstName":"Vishal","middleName":"","lastName":"Jain","suffix":""},{"id":438494519,"identity":"239a4441-6f5f-4e8a-80be-9dde0603639c","order_by":9,"name":"Douglas Weber","email":"","orcid":"https://orcid.org/0000-0002-9782-3497","institution":"University of Pittsburgh","correspondingAuthor":false,"prefix":"","firstName":"Douglas","middleName":"","lastName":"Weber","suffix":""},{"id":438494520,"identity":"8e67aa46-e102-4a0f-8a79-14076f041e91","order_by":10,"name":"Benedict Alter","email":"","orcid":"","institution":"University of Pittsburgh","correspondingAuthor":false,"prefix":"","firstName":"Benedict","middleName":"","lastName":"Alter","suffix":""},{"id":438494521,"identity":"85c25401-79d6-44dd-a75e-88719fe5fa99","order_by":11,"name":"Pulkit Grover","email":"","orcid":"https://orcid.org/0000-0001-7651-7776","institution":"Carnegie Mellon University","correspondingAuthor":false,"prefix":"","firstName":"Pulkit","middleName":"","lastName":"Grover","suffix":""}],"badges":[],"createdAt":"2025-03-21 01:45:40","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6273135/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6273135/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":80293054,"identity":"56b6bfdf-8c2f-45a5-bcec-11679efb6a85","added_by":"auto","created_at":"2025-04-10 08:13:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":338216,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-6273135/v1/516574ed8509a6009467f6b3.png"},{"id":80294640,"identity":"767dc1e9-2aa2-4fe4-b2c2-feeec06846d9","added_by":"auto","created_at":"2025-04-10 08:29:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":416981,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-6273135/v1/9c37e64dca9023c56cc9e756.png"},{"id":80294639,"identity":"b9d619a1-acd3-4444-9ffc-6632e0815d4b","added_by":"auto","created_at":"2025-04-10 08:29:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":211326,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-6273135/v1/06a306ed3b341ee61c01a93b.png"},{"id":80293555,"identity":"0e30f7da-6ae9-4c4a-bc8e-524423214f2e","added_by":"auto","created_at":"2025-04-10 08:21:28","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":609632,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-6273135/v1/538bc9274097aa1633940ec9.png"},{"id":80293553,"identity":"e319878f-3595-4942-a69b-d224ffab4526","added_by":"auto","created_at":"2025-04-10 08:21:28","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":596744,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-6273135/v1/4c0f4475b2bceb1aad445253.png"},{"id":80293058,"identity":"fb3fe3e6-6a7b-4bc6-ae05-88efe2d0d925","added_by":"auto","created_at":"2025-04-10 08:13:28","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":201571,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-6273135/v1/bf4dce95dedaaab9b8ec6b9f.png"},{"id":80293067,"identity":"b96e8abf-7555-4997-9276-d8bce2c17a39","added_by":"auto","created_at":"2025-04-10 08:13:28","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":328739,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-6273135/v1/503727b017cf1113468a7564.png"},{"id":80294642,"identity":"b00d082a-bbab-4e3b-a143-c5ec19daa560","added_by":"auto","created_at":"2025-04-10 08:29:28","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":492169,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-6273135/v1/5f23a9d120becb2297daebf4.png"},{"id":80642652,"identity":"2f62aca0-d0c2-4d30-89d9-83e8fd9bf806","added_by":"auto","created_at":"2025-04-15 13:32:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3578636,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6273135/v1/604a2e9f-1fc1-4810-a24a-d1f3315485df.pdf"},{"id":80293056,"identity":"258e8b33-07ee-4bcc-afbf-fad1a521e318","added_by":"auto","created_at":"2025-04-10 08:13:28","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":144434,"visible":true,"origin":"","legend":"Supplementary Table S10","description":"","filename":"TESscalppainpapersuppST10.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6273135/v1/8e29b76560ddd0de648993a0.xlsx"},{"id":80293567,"identity":"7a742044-be73-4d97-bdfb-391e83511338","added_by":"auto","created_at":"2025-04-10 08:21:28","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":6134858,"visible":true,"origin":"","legend":"Supplementary Figures","description":"","filename":"TESscalppainpapersupp.docx","url":"https://assets-eu.researchsquare.com/files/rs-6273135/v1/760d629754e2c0c10a92c136.docx"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential Competing Interest.\nM.F., V.J., D.W., B.A., and P.G. have equity in Synapse Symphony, a company developing TES systems.","formattedTitle":"Reducing scalp pain for pTES of motor cortex using background hums","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTranscranial electrical stimulation (TES) is a powerful neuromodulation technique which has received substantial attention in the last decade for its potential to improve several neurological and neuropsychiatric conditions. For example, studies have shown the benefits of TES for dystonia, gait ataxia, fibromyalgia, depression, and refractory postoperative pain \u003csup\u003e1\u0026ndash;5\u003c/sup\u003e. The most common implementations of TES today consist of transcranial direct current and alternating current stimulation (TDCS/TACS). These techniques use low amplitude currents (\u0026lt; 4 mA) to entrain neural activity or evoke ephaptic coupling, but do not generate electric fields of sufficient amplitude in the brain to directly elicit neuronal action potentials \u003csup\u003e6,7\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eA more direct and physiologically potent alternative, called \u003cem\u003epulsed\u003c/em\u003e TES (pTES) was first introduced by Merton and Morton in 1980\u003csup\u003e8,9\u003c/sup\u003e. Unlike TDCS and TACS, pTES injects high-amplitude (typically \u0026gt;30 mA) short-duration (\u0026lt;1 millisecond) pulses, capable of directly activating neurons. E.g., when targeting the motor cortex, pTES can produce direct \u0026ldquo;D-Waves\u0026rdquo; in the corticospinal tract, eliciting motor-evoked potentials (MEPs) in muscles that can be used to assess cortical excitability, and enable individual calibration of stimulation site and intensity \u003csup\u003e10\u003c/sup\u003e. However, despite its potential for both neuroscience and therapeutic applications, pTES has remained underutilized because of its major limitation: high scalp pain that is intolerable for many\u003csup\u003e11\u003c/sup\u003e (see also\u003csup\u003e12\u0026ndash;16\u003c/sup\u003e), and was replaced by transcranial magnetic stimulation (TMS\u003csup\u003e17\u003c/sup\u003e; discovered in 1985) despite distinct neurophysiological effects that could offer unique therapeutic advantages.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe goal of this work is to reduce the scalp pain associated with pTES. Due to its ability to directly stimulate the brain and evoke MEPs, while causing low scalp pain, TMS has been widely used to treat several neurological and neuropsychiatric disorders. However, due to differences in how pTES and TMS affect neurons, the downstream effects of stimulation and, therefore, the clinical potential of these modalities, can be distinct. These mechanistic differences, and other potential benefits of pTES (such as portability) motivate our study of lowering the scalp pain associated with pTES. This lowering of scalp pain opens the gate for new non-invasive stimulation treatments to patient populations not adequately served by current approaches, and new studies of direct brain stimulation in ambulatory settings.\u003c/p\u003e\n\u003cp\u003eNotably, under anesthesia, e.g. for monitoring spinal health during surgery, pTES is still used extensively\u003csup\u003e10,18,19\u003c/sup\u003e, as muscle responses to pTES are less sensitive to anesthesia than those to TMS\u003csup\u003e20\u003c/sup\u003e, and scalp pain is not an issue. However, for non-anesthetized applications, overcoming the barrier of stimulation-induced scalp pain is critical to unlocking pTES\u0026rsquo;s full potential as a neuromodulation therapy.\u003c/p\u003e\n\u003cp\u003eIn this work, we provide a novel technique for reducing scalp pain: addition of a small-amplitude, high-frequency current \u0026ndash; termed \u0026ldquo;background hum\u0026rdquo; \u0026ndash; near the stimulating electrodes. These hums are applied tens to hundreds of milliseconds before and after the primary stimulation pulse. In addition to background hums, we investigated the effects of varying interelectrode distances and pulse widths on pain perception. In a group of healthy volunteers, we systematically explored various combinations of these parameters in an effort to minimize pain when stimulating in the upper-limb representation of the motor cortex. In addition,we demonstrated the potential use of pTES in a treatment protocol where we applied pTES with background hums on two patients with fibromyalgia, targeting the primary motor cortex (M1). Advancing beyond the healthy volunteer study, we examined effects of hums in lowering scalp pain when targeting both upper- and lower-limb M1 representations.Throughout this paper, the scalp pain experienced from varying pTES parameters (including hum conditions and pulse widths) are compared to that of a standard pTES pulse of 200 \u0026micro;s pulse width in the absence of hum at motor threshold. This nominal (i.e. standard) condition has been explored in prior works\u003csup\u003e16\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003ePain at motor threshold is not substantially affected by changing the inter-electrode distance\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe investigated how the upper-limb motor threshold and scalp pain were influenced by the position of stimulation electrodes (in the absence of background hum). Numerical rating scale (NRS) scores of stimulation pain and motor thresholds were recorded for 11 unique participants at interelectrode distances of 20% and 40% TRT distance (corresponding to approximately 7 cm and 14 cm respectively). Due to repeated measurements from some participants, the dataset includes 19 total data points. 40% TRT corresponds to the commonly-used C3/C4 montage, while 20% matches the C3/Cz arrangement. On average, while the motor threshold was significantly lower\u0026nbsp;(p \u0026lt; 5x10\u003csup\u003e-7\u003c/sup\u003e) for the larger anode-cathode distance, the pain levels at motor threshold showed no significant differences across the two distances (Fig 1b,c).\u003c/p\u003e\n\u003cp\u003eIn one participant, a more detailed experiment was conducted at interelectrode distances of 10%, 20%, 30%, and 40% of TRT distance. The resulting motor threshold and the NRS score at motor threshold are plotted in Fig. 1a. Again, a substantial reduction in motor threshold is observed as interelectrode distance increases, with thresholds decreasing from 120 mA at 20% TRT distance to 82 mA at 40% TRT distance. Again, the pain intensity at motor threshold showed little variability across the tested distances with NRS scores consistently measuring between 5/10 and 6/10. These findings suggest that a greater distance between electrodes reduces the current required to reach motor threshold. However, the downward trend in motor threshold is negated by the increased pain at higher interelectrode distances resulting in approximately consistent pain perception across all anode-cathode distances. Despite the minimal variation in quantitative pain intensity, all participants expressed preference for stimulation at 20% TRT distance rather than 40% TRT distance.\u003c/p\u003e\n\u003cp\u003eStimulation pulse width inconsistently affects scalp pain\u003c/p\u003e\n\u003cp\u003eThe average motor threshold (over n=7 participants) for pulse widths in a [50 \u0026micro;s; 500 \u0026micro;s] interval are reported in Fig. 2a. Consistent with the Lapicque equation\u003ca href=\"https://paperpile.com/c/sMlyfO/QqJZ\"\u003e\u003csup\u003e24\u003c/sup\u003e\u003c/a\u003e, we find that the average normalized motor threshold is inversely proportional to the pulse width, with I = 5.1/w+19.9 (r\u003csup\u003e2\u003c/sup\u003e=0.97) (I = threshold current (mA), w = pulse width (\u0026micro;s)). Fig. 2b shows the interindividual variation in pain at motor threshold across different pulse widths: while some participants reported reduced pain at longer pulse durations, others showed inconsistent or even increased pain for the same conditions. This suggests that the pulse width that causes minimum scalp pain at threshold should be tailored to each participant.\u003c/p\u003e\n\u003ch2\u003eBackground hums reduce scalp pain\u003c/h2\u003e\n\u003cp\u003ePilot experiments: In a set of pilot experiments (n=12), NRS scores were collected across various electrode montages, pulse widths, and hum waveforms. Table S10 details all configurations tested in these pilot experiments. In Fig. 3, for each participant, the lowest pain achieved using hums is compared to the pain obtained without hum for the same stimulation pulse at motor threshold (the electrode montage and the pulse width was varied across participants). Fig. 3 illustrates that, at optimal personalized hum conditions, there is always some attenuation of scalp pain, with an average reduction of 1.69\u0026plusmn;0.48 points (mean \u0026plusmn; s.d.). Fig. S5 plots the effects of all hums tested (including suboptimal hums) on patient reported NRS scores.\u003c/p\u003e\n\u003cp\u003eSystematic hum parameter search and comparison with baseline pain: Guided by the pilot experiment results, we systematically applied a set of hum waveforms using a Box-Behnken design (Fig. 8) on n=7 participants while stimulating upper limb muscles at motor threshold. Fig.\u0026zwnj;\u0026zwnj;\u0026zwnj; 4 illustrates the net effect of the best hum and pulse width combination on NRS scores. NRS scores for each participant are compared for pTES at motor threshold without hum (at a nominal 200 \u0026micro;s pulse width) and pTES at motor threshold with the best hum and pulse width combination, showing an average reduction of 1.99 points (Fig. 4a, p \u0026lt; 0.0006). These findings highlight the substantial magnitude of pain reduction possible with the observed stimulation parameters.\u003c/p\u003e\n\u003cp\u003eFig. 4b shows the combined effects of pulse width optimization and hum optimization. Consistent with the results in Fig. 2, pulse width optimization alone does not achieve much pain reduction. When no hums are used, there is no statistically significant difference in NRS scores between the nominal 200 \u0026micro;s-width pulse and the optimal pulse width (Fig. 4b; p = 0.29). With joint pulse width and hum parameter optimization, we see a reduction of 2 points on average (p \u0026lt; 0.001). Fig. 4c shows the data of reduction in scalp pain per participant by use of optimized hum at each pulse width. For each pulse width and each participant, the optimized hum reduces scalp pain.\u003c/p\u003e\n\u003cp\u003eDelving further into the interaction of hum and pulse width on NRS scores, we plot surface curves of the average pain reduction (across 7 participants) in response to different hum parameter value combinations at the different pulse widths (Fig. 5). The differences in the surfaces across the different widths illustrate that the effect of hums and pulse width on the scalp pain is coupled in a non-linear manner rather than purely summative. Furthermore, these surface curves vary from participant to participant (Fig. S6). Nonetheless, the surfaces reveal some trends that can serve as general guidelines in hum parameter decision making: hums with low amplitude performed worse on average, which seems to indicate that hums need to be of sufficient amplitude to have a beneficial effect. However, hums with high amplitude performed better, unless the hum ON time was too high. This indicates that at high amplitude and ON time, the charge delivered into the scalp by the hum is sufficient to add to the scalp pain due to the high amplitude stimulation pulse. The hum frequency tends to have a smaller effect than the amplitude or ON time.\u003c/p\u003e\n\u003cp\u003eHeuristic techniques to find minimal pain conditions in fewer steps\u003c/p\u003e\n\u003cp\u003eIn Fig. 6, we compare the NRS scores in the no-hum condition across all pulse widths to the scores aggregated via sequential optimization techniques discussed in the methods. In both cases we see that there is a significant reduction in scalp pain intensity when compared to the no hum condition across all pulse widths (technique 1 average reduction: 1.92, p \u0026lt; 0.0001, technique 2 average reduction: 1.91 p \u0026lt; 0.0005). Of note is that the results of both techniques are comparable to that of the exhaustive search. This suggests that both heuristic techniques provide a similar benefit in terms of scalp reduction as the exhaustive search.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhile an exhaustive search is guaranteed to return the combination of pTES parameters that reduces pain the most, it comes at the cost of requiring more trials in which the pain response is evaluated, at the detriment of the participant who has to endure an extensive number of suboptimal pTES stimulations. The number of trials required for an exhaustive search is given by the equation (mn\u003csup\u003ek\u003c/sup\u003e) (m: number of pulse widths, n: number of hum features, k: number of values per hum feature). Tangentially, the number of steps for the Box Behnken design is m(2n(n-1)) with no dependency on k as we are constrained to three values per feature. Our heuristic techniques 1 and 2 require only (m + n\u003csup\u003ek\u003c/sup\u003e) trials to achieve their solution. While the heuristic search performed well in practice, greedy search algorithms are sensitive to initial feature evaluation, and could end up achieving a globally suboptimal solution.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo further reduce the required number of stimulation trials, we can forgo the pulse width optimization, and simply optimize the hum condition at a predetermined pulse width of 200\u0026micro;s. This is equivalent to performing only step 2a (as detailed in 2.1.3), without including the subsequent pulse width optimization. This simplified heuristic only requires n\u003csup\u003ek\u003c/sup\u003e trials to find the local optimum. Fig. S8 demonstrates that the optimum obtained with this method achieves a significant reduction in pTES pain compared to the no hum condition while not being not significantly different from the results of technique 1 or 2. While this method empirically proves to be an effective heuristic for optimizing pTES pain, technique 2 performs a subsequent second optimization (over pulse width) and is therefore guaranteed to match or outperform it. A practical implementation might therefore be to perform step 2a and only optionally perform step 2b if the pain is not sufficiently low.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eStudy with two patients with fibromyalgia on pain reduction on upper and lower limbs\u003c/h2\u003e\n\u003cp\u003ePatients with chronic pain, especially fibromyalgia, tend to have lower electrical pain thresholds and are thus expected to be less tolerant of TES-induced scalp-pain\u003csup\u003e25\u0026ndash;27\u003c/sup\u003e despite the potential use of TES to treat chronic pain. To assess feasibility of application of pTES with hums and pulse optimization in fibromyalgia, two individuals with fibromyalgia underwent pTES for at least three weeks. During the experimental window, \u0026gt;1000 pulses were delivered to the motor cortex at motor threshold targeting either upper- or lower-limb representations (16 upper-limb days, 13 lower-limb days for the first patient; 9 upper-limb days, 6 lower-limb days for the second patient). Electrode configuration and EMG analysis for lower-limb pTES stimulation is detailed in Fig. S7.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOn the first day of stimulation, prior to any optimization, the first patient with fibromyalgia could not tolerate upper-limb, sub-threshold pTES. A pain of 6/10 was reported at 0.33Hz stimulation at 27 mA with a pulse width of 200 \u0026micro;s (no MEP response could be produced despite lowering the frequency of stimulation). Similarly, a pain of 7/10 was reported at a 300 \u0026micro;s pulse width (18 mA, 0.33 Hz) and 6/10 at a 500 \u0026micro;s pulse width (13 mA, 0.33 Hz). After hum optimization, an MEP response was observed and pain reported at motor threshold (1 Hz, 40 mA, 200 \u0026micro;s pulse width) was 4/10. Throughout the six week treatment period, pain levels during upper-limb pTES stimulation continued to fall and the average pain across all subsequent 15 upper-limb sessions was 2.80/10. During the first lower-limb session, pain at motor threshold (1 Hz, 75 mA, 200 \u0026micro;s pulse width) was 5/10. Immediately after optimization, pain at motor threshold with the same conditions went down to 3.5/10. Over the course of the subsequent 12 lower-limb sessions, the average pain at motor threshold was 3.07/10.\u003c/p\u003e\n\u003cp\u003eThe second patient with fibromyalgia had an initial pain intensity of 5/10 at motor threshold (1 Hz, 33 mA pulses with a 300 \u0026micro;s pulse width) in upper-limb pTES. Similarly, a pain of 5.2/10 was reported at a 300 \u0026micro;s pulse width (1 Hz, 45 mA). Pain at motor threshold did go down with a pulse width of 200 \u0026micro;s (1 Hz, 60 mA) (pain of 4/10). After hum optimization, pain at the same condition (1 Hz, 60 mA, 200 \u0026micro;s) was reported to be 1.5/10. Throughout the subsequent 8 days of upper-limb stimulation, the average pain at motor threshold was 1.9/10. During the first lower-limb session, motor threshold could not be reached without the application of hum. A pain of 4.5/10 was reported at 1 Hz stimulation at 70 mA with a pulse width of 200 \u0026micro;s in the absence of hum. After hum optimization, pain at motor threshold (1 Hz, 95 mA, 200 \u0026micro;s pulse width) was 2.80/10. Over the course of the subsequent 5 lower-limb sessions, the average pain at motor threshold was 1.96/10.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis work provides new techniques to address the primary limitation of pTES, namely, intolerable scalp pain caused by the required currents to evoke motor response. To do so, we make use of background hums, which are additional currents injected in the scalp with the exclusive goal of reducing scalp pain. When optimized jointly with stimulating pulse widths, the technique is able to reduce pain by 2 points on the NRS scale in healthy volunteers. Notably, a reduction in 2/10 points not only meets statistical significance but also the minimum clinically significant difference threshold\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e which underscores the effectiveness of this approach in week long treatment protocols. This is made further evident with the study on patients with fibromyalgia who were able to receive\u0026thinsp;\u0026gt;\u0026thinsp;1000 stimulation pulses per session for at least three weeks. The variability in optimal parameter conditions across individuals also speaks to the need to move beyond a \u0026ldquo;one-size-fits-all\u0026rdquo; approach to non-invasive neuromodulation. Instead, future applications of pTES may benefit from personalization, where stimulation settings are adapted in real time to self-reported responses.\u003c/p\u003e \u003cp\u003eMechanisms of hum-induced analgesia\u003c/p\u003e \u003cp\u003eAlthough the mechanism for scalp pain reduction with hum is unknown, a natural thought is that it may serve as a distraction: shifting attention away from noxious stimuli and thereby reducing perception of pain. This concept aligns with research on vibratory analgesia where mechanical vibration stimulates cortical area 3b/1 leading to suppression of activity in area 3a, ultimately causing suppression of pain\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. The persistence of this effect, even in anesthetized primates, suggests that distraction alone may not explain vibratory analgesia \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Fig. S9 provides credence to the idea that hums may have a more complex interaction than simply distracting the participant. If hums primarily functioned as a distraction, we would expect a consistent attenuation of pain across all pulse widths for the same hum condition. At the very least, we would not expect to see that the same hum condition would exacerbate pain at one pulse width and alleviate pain at another. However, the data suggest that the same hum waveform can have different effects on pain perception depending on the pulse width. Since attentional distraction should not vary substantially with changes in the noxious stimulus, the variation in pain modulation across pulse widths suggests a more complex interaction. Other non attentional mechanisms may also be at play. At the spinal level, processes such as the gate control theory of pain\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e or surround inhibition in wide dynamic range neurons via cervical somatosensory nociceptors \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e may lead to attenuation of pain perception. Together, these findings suggest that hum-induced pain modulation may not merely be a byproduct of attentional distraction but likely a combination of factors that interact in a more dynamic manner.\u003c/p\u003e \u003cp\u003eComparison to TMS\u003c/p\u003e \u003cp\u003eTranscranial magnetic stimulation (TMS) also elicits direct neural activity through short pulses of current. Contrary to pTES, the magnetic field crossing the scalp does not elicit substantial sensation, making TMS the preferred method of transcranial cortical stimulation. However, there are important reasons why a lower pain TES approach, as described in this study, could be more effective than TMS in certain applications.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eMechanism of Action\u003c/span\u003e: The effect of TMS on neurons is mediated by the electric field induced by the magnetic field. This field is orthogonal to the magnetic field, and parallel to the brain surface, while TES-injected fields tend to be normal to the brain surface. Because neuronal activation depends on the orientation of the field with respect to its axon\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, TMS and TES primarily activate different cells. One consequence of this phenomena is thought to be the cause of differential corticospinal tract activation: when stimulating the motor cortex, TMS typically activates interneurons rather than motor-cortical pyramidal neurons (Betz cells)\u003csup\u003e\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. It is not fully known how activation of different subpopulations of neurons affects the expected clinical outcomes. One well-established consequence is the difference in corticospinal volleys following motor stimulation using pTES and TMS. pTES predominantly produces direct D-Waves\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. However, TMS predominantly results in indirect I-waves, thus, the therapeutic effects and treatment implications of pTES may be different than that of TMS. For instance, pharmaceuticals like gabapentin can alter synaptic transmission\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e and thereby alter TMS\u0026rsquo;s ability to activate corticospinal tracts in patients that would otherwise benefit from the compounding effects of neurostimulation (Y. Zhang et al. 2024).It is possible that this explains the variability in TMS\u0026rsquo;s treatment effects in heterogeneous patient pools\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Because pTES directly activates upper motor neurons, it could maintain a higher efficacy under the action of synaptic inhibition, resulting in more consistent treatment outcomes.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eWaveform Limitations\u003c/span\u003e: TMS also has stark limitations in the types of waveforms that can be delivered. Since TMS relies on electromagnetic induction where time-varying currents in a coil produce magnetic fields \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e, the coupling efficiency depends on the rate of change of the magnetic fields (dB/dt). This limits TMS to specific waveforms like monophasic or biphasic pulses\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. TMS further relies on high-voltage capacitors to deliver the necessary rapid current changes in the coil restricting pulse-widths and making repetitive monophasic pulses, continuous DC stimuli, and slow-varying waveforms impossible altogether with commercially available architecture. Given that different populations of neurons have distinct geometry, channel expressions, and neuronal dynamics \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e, these restrictions on TMS waveforms greatly constrain the selectivity of stimulation and downstream therapeutic effects.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003ePortability\u003c/span\u003e: One last benefit of pTES over TMS lies in its portability. TMS has inherent challenges in downsizing the coils as a result of energy efficiency, heating, and physical constraints. Resistive losses are more significant for smaller coils \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Although delivering more energy to the coil can offset its lower energy efficiency, this approach poses challenges such as higher power demands, excessive coil heating, increased internal coil forces, and elevated noise levels\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Recent efforts\u003csup\u003e\u003cspan additionalcitationids=\"CR43\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e have made progress towards portable TMS (i.e. a stationary device that can be easily relocated) but stop short of \u0026ldquo;wearable\u0026rdquo; neurostimulation. Meanwhile research studies have already validated the effectiveness of miniature wearable tDCS that induces comparable neuromodulatory effects of commercially available products\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eLimitations\u003c/p\u003e \u003cp\u003eThis study is limited by its small sample size, with 19 participants and two patients with fibromyalgia, which restricts generalizability. Optimal hum parameters and pain intensity vary between individuals and across sessions, as seen in the patients with fibromyalgia, making consistent optimization challenging. Moreover, NRS scores only capture a limited window of the multifaceted perception of pain.This is evident when noting that pain was similar across all anode-cathode distances but preference was made towards smaller anode-cathode distances. Furthermore, the range of tested hum parameters and electrode spatial configurations was narrow, potentially missing more effective setups. Addressing these factors in future research will improve the clinical utility of pTES.\u003c/p\u003e "},{"header":"Methods","content":"\u003cp\u003eIn this experimental study, 19 healthy participants (5 Females, 14 Males, age 30.35\u0026thinsp;\u0026plusmn;\u0026thinsp;6.49\u003cem\u003e)\u003c/em\u003e and two participants with fibromyalgia (1 Female, 1 Male) underwent pTES. The experiment protocols were reviewed and approved by the Carnegie Mellon University Institutional Review Board, and all participants provided written informed consent. Self-reported scalp pain intensity scores for participants undergoing pTES were recorded as we varied three key sets of parameters: anode-cathode distance, pulse width, and background hum parameters.\u003c/p\u003e \u003cp\u003eStimulation setup\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCurrents were delivered to the electrodes using a commercial current stimulator (DS8R, Digitimer Ltd.) connected to a computer-controlled data acquisition hardware (BNC-2110, National Instruments) using custom software (Matlab, Mathworks). This setup allowed flexible customization of the pulse parameters, including width, amplitude, and timings.\u003c/p\u003e \u003cp\u003eThe stimulation pulse consisted of single monophasic anodic rectangular pulses injected through the scalp electrodes. The pulse duration was varied across experiments, ranging from 50 \u0026micro;s to 1000 \u0026micro;s. For each pulse width, the amplitude of the pulses was gradually increased over multiple blocks until the motor threshold was reached (details of threshold determination are provided in Section 2.2). Stimulation at motor threshold was repeated in blocks of 20 to 30 trials at a frequency of 1 Hz for averaging. After any block of stimulation trials, the participant was asked to report their level of pain from 0\u0026ndash;10 using a numerical rating scale (NRS) with 0 being \u0026ldquo;no pain\u0026rdquo; and 10 being \u0026ldquo;worst pain imaginable\u0026rdquo;\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. To reduce the motor threshold, the participants were asked to grip a dynamometer at 20% of maximum voluntary contraction (MVC) throughout the stimulation period.\u003c/p\u003e \u003cp\u003eFor measuring evoked responses in muscles, electromyography (EMG) signals were recorded at 4 kHz using 64-channel high-density EMG patches (SAGA, TMSi; 8.75mm interelectrode distance) and additional bipolar electrodes (Norotrode DDN 20, Myotronics; 22 mm interelectrode distance). For upper-limb responses, the EMG patches were placed on the dominant wrist flexor and extensor muscle groups (Fig.\u0026nbsp;7b). Additionally, bipolar electrodes were used to record EMG signals on the dominant first dorsal interosseous (FDI), abductor pollicis brevis (APB), biceps brachii, and triceps brachii.\u003c/p\u003e \u003cp\u003eElectrode montage for assessing pain and motor threshold as inter-electrode distance is varied\u003c/p\u003e \u003cp\u003eA study was performed (n\u0026thinsp;=\u0026thinsp;11) to determine the effect of the inter-electrode distance on the pain level at motor threshold. A common electrode configuration for pTES of upper limbs is to place the anode at C3 and the cathode at C4 (for right-hand dominant participants; reversed for left-handed participants) \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, corresponding to an inter-electrode distance of 40% of the lateral scalp length (measured as the tragus-to-tragus (TRT) distance). We compared this 40% TRT configuration to placements where the inter-electrode distance was 20% of the scalp length (corresponding to anode placement at C3 and cathode placement at Cz). In one participant, additional inter-electrode distances were used, with the anode at C3 and the cathode positioned laterally at distances of 10%, 20%, 30%, and 40% of the TRT distance.\u003c/p\u003e \u003cp\u003eJointly varying pulse width and background hum parameters for pain minimization\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003ePilot experiments\u003c/span\u003e: A set of pilot experiments (n\u0026thinsp;=\u0026thinsp;12) were conducted to determine whether applying a \u0026ldquo;background hum\u0026rdquo; to the scalp consisting of a low-amplitude, high-frequency pulse train injected near the motor stimulation electrodes can alter the scalp sensation caused by the stimulation pulse. Separate anode-cathode pairs and commercial stimulators (DS8R, Digitimer Ltd.) were used to generate these background hum waveforms. The set of background hum waveforms we tested was drawn from high-frequency (100 Hz \u0026minus;\u0026thinsp;5 kHz), low-amplitude (1 mA \u0026minus;\u0026thinsp;10 mA) pulse trains. In addition to the frequency and amplitude, various other hum-waveform parameters were tested to identify what hum waveforms lead to the greatest reduction in scalp pain. These parameters include spatial configuration of the electrodes delivering the hum, train duration (100ms \u0026minus;\u0026thinsp;1000ms), and timing of the stimulation pulse with respect to the background hum. Hum trains, whose amplitude varied throughout the train (i.e. with non-constant envelope), were also tested, but the maximum amplitude never exceeded 10 mA. A complete table of all the stimulation parameters explored are detailed in Table S10. A manual sampling of all these parameters on healthy volunteers, informed by self-reported NRS scores, enabled us to converge onto personalized hum waveforms for patients with fibromyalgia. For each applied hum condition, we compared the reported scalp pain to the scalp pain reported using the same stimulation pulse without the hum.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eSystematic hum parameter search\u003c/span\u003e: Results from these pilot experiments additionally informed the paradigm described below, which was implemented on healthy volunteers (n\u0026thinsp;=\u0026thinsp;7). Here, the effect of three hum parameters (Fig.\u0026nbsp;8) was examined, and NRS scores were compared to a no-hum case. A sweep of hum parameters was conducted using a Box-Behnken design\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e to systematically vary hum ON time, frequency, and amplitude in three levels each (Fig.\u0026nbsp;8b,c). The train duration was kept fixed at 500 ms, the stimulation pulse was consistently delivered at the midpoint of the 500 ms hum, and the hum amplitude was kept constant throughout the train. For upper-limb stimulation, two pairs of hum-delivering gold cup electrodes were placed, each 2 cm to the left and right of the stimulating anode and cathode.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe hum anodes were placed laterally from the stimulation electrodes, and the hum cathodes medially (Fig.\u0026nbsp;7a). A baseline NRS pain score was determined at motor threshold in the absence of the background hum. Following the baseline assessment, the background hums described in Fig.\u0026nbsp;8b were added to the stimulation pulse in a random order, and the NRS pain score was recorded. After all hum conditions were applied, a final baseline NRS score was determined in the absence of hum. To adjust for habituation, a linear fit (across session time) was applied between the pre-hum and post-hum baseline pain measurements (Fig. S2 illustrates the extent of habituation when averaged across all trials for all participants). The NRS scores for all intermediate measurements were corrected for this linear trend. The effect of the hum is characterized by the difference between the pre-hum baseline pain and the corrected hum pain. The pain reduction for points in the hum parameter space not sampled by the Box-Behnken design are calculated using quadratic regression (detailed in Fig. S3). The systematic hum parameter assessment was performed at four stimulation pulse widths: 100 \u0026micro;s, 200 \u0026micro;s, 300 \u0026micro;s, and 500 \u0026micro;s.\u003c/p\u003e \u003cp\u003eData-efficient Optimization Techniques of Stimulation Pulse Width and Hum Parameters\u003c/p\u003e \u003cp\u003eWhen jointly optimizing pulse width and hum parameters, several methods can be employed. An exhaustive search of the joint effect of each hum parameter and each pulse width is guaranteed to determine which pTES waveform results in the least scalp pain. However, assuming n hum parameters with k possible values each and m different pulse widths, the number of possible conditions is mn\u003csup\u003ek\u003c/sup\u003e. Experimentally applying all these conditions becomes impractical even for moderate values of m, n, and k. As such, we introduce two greedy coordinate search techniques that sequentially optimize the hum parameters and the pulse width. In technique 1, we first optimize pulse width and then the hum parameters. That is, we first perform motor stimulation at every pulse width (in a discretized set) in the absence of hum, selecting the one that causes the least pain (step 1a). At this \u0026ldquo;subject-favored pulse width\u0026rdquo;, we then vary all of the hum parameters and determine which combination of hum parameters and pulse width values results in the least scalp pain (step 1b). In technique 2, we first (step 2a) perform motor stimulation at a nominal pulse width of 200\u0026micro;s (a commonly used pulse width in TES literature)\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, and select the hum condition that causes the lowest scalp pain. Then (step 2b), we change the stimulation pulse width while using the identified best hum condition in step 2a.\u003c/p\u003e \u003cp\u003eAnalysis of the two techniques was conducted using the data collected in the Box-Behnken design in 2.1.2 (n\u0026thinsp;=\u0026thinsp;7). A preliminary exhaustive search was done experimentally to fully explore the search space across three hum parameters (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e4\u003c/span\u003e) and 4 pulse width values. Analysis of the attained NRS score using techniques 1 and 2 was done post-hoc, once the exhaustive grid search was completed. Furthermore, technique 1 was employed experimentally to optimize pTES parameters for the patients with fibromyalgia.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eRecorded EMG signals were analyzed using custom scripts in MATLAB. The recordings were band-passed filtered using a 4th order Butterworth filter with [60Hz; 600Hz] corner frequencies. The recordings were stimulus-aligned and averaged across trials (20\u0026ndash;30 repetitions for each condition). The magnitude of the MEP response was quantified using the ratio of the post-stimulus root mean square (RMS) calculated between [20 ms; 40 ms] relative to stimulus onset, to pre-stimulus RMS value calculated between [-40 ms: -20 ms] relative to stimulus onset. Post-stimulus RMS windowing is consistent with the expected delay for muscle activation in the upper-limbs. MEP threshold was defined as the minimum current required to (1) elicit a visibly clear motor response (Fig. S4), and (2) return a RMS ratio greater than 2, in at least one channel. Two tailed paired t-tests were used for all statistical tests.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eM.F., V.J., D.W., B.A., and P.G. have equity in Synapse Symphony, a company developing TES systems.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eYoung SJ, Bertucco M, Sheehan-Stross R, Sanger TD. Cathodal transcranial direct current stimulation in children with dystonia: a pilot open-label trial: A pilot open-label trial. J Child Neurol 2013;28:1238\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFl\u0026ouml;el A. tDCS-enhanced motor and cognitive function in neurological diseases. Neuroimage 2014;85 Pt 3:934\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZandieh Z, Niksolat M, Saghafian larijani S, Mirfakhraee H. Anodal stimulation of primary motor cortex in elderly women with fibromyalgia: A randomized, double-blind, placebo-controlled trial. Rheumatol Res 2020;5:167\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVanderhasselt M-A, De Raedt R, Namur V, Lotufo PA, Bensenor IM, Boggio PS, \u003cem\u003eet al.\u003c/em\u003e Transcranial electric stimulation and neurocognitive training in clinically depressed patients: A pilot study of the effects on rumination. Progress in Neuro-Psychopharmacology and Biological Psychiatry 2015;57:93\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBorckardt JJ, Romagnuolo J, Reeves ST, Madan A, Frohman H, Beam W, \u003cem\u003eet al.\u003c/em\u003e Feasibility, safety, and effectiveness of transcranial direct current stimulation for decreasing post-ERCP pain: a randomized, sham-controlled, pilot study. Gastrointest Endosc 2011;73:1158\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAgnihotri SK, Cai J. Investigating the effects of transcranial alternating current stimulation on cortical oscillations and network dynamics. Brain Sci 2024;14:767.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLefaucheur J-P, Wendling F. Mechanisms of action of tDCS: A brief and practical overview. Neurophysiol Clin 2019;49:269\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMerton PA, Morton HB. Stimulation of the cerebral cortex in the intact human subject. Nature 1980;285:227.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMerton PA, Hill DK, Morton HB, Marsden CD. Scope of a technique for electrical stimulation of human brain, spinal cord, and muscle. Lancet 1982;2:597\u0026ndash;600.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSzel\u0026eacute;nyi A, Kothbauer KF, Deletis V. Transcranial electric stimulation for intraoperative motor evoked potential monitoring: Stimulation parameters and electrode montages. Clin Neurophysiol 2007;118:1586\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePolan\u0026iacute;a R, Nitsche MA, Ruff CC. Studying and modifying brain function with non-invasive brain stimulation. Nat Neurosci 2018;21:174\u0026ndash;87.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRothwell J. Transcranial brain stimulation: Past and future. Brain Neurosci Adv 2018;2:2398212818818070.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRothwell JC. Physiological studies of electric and magnetic stimulation of the human brain. Electroencephalogr Clin Neurophysiol Suppl 1991;43:29\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRothwell JC. Techniques and mechanisms of action of transcranial stimulation of the human motor cortex. J Neurosci Methods 1997;74:113\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRothwell J, Burke D, Hicks R, Stephen J, Woodforth I, Crawford M. Transcranial electrical stimulation of the motor cortex in man: further evidence for the site of activation. J Physiol 1994;481 (Pt 1):243\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCaulfield KA, Badran BW, DeVries WH, Summers PM, Kofmehl E, Li X, \u003cem\u003eet al.\u003c/em\u003e Transcranial electrical stimulation motor threshold can estimate individualized tDCS dosage from reverse-calculation electric-field modeling. Brain Stimul 2020;13:961\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarker AT, Jalinous R, Freeston IL. Non-invasive magnetic stimulation of human motor cortex. The Lancet 1985;325:1106\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTsutsui S, Yamada H. Basic principles and recent trends of transcranial motor evoked potentials in intraoperative neurophysiologic monitoring. Neurol Med Chir (Tokyo) 2016;56:451\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMacdonald D. Safety of intraoperative transcranial electrical stimulation motor evoked potential monitoring. J Clin Neurophysiol 2002;19:416\u0026ndash;29.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHargreaves SJ, Watt JWH. Intravenous anaesthesia and repetitive transcranial magnetic stimulation monitoring in spinal column surgery. Br J Anaesth 2005;94:70\u0026ndash;3.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlem GH, L\u0026uuml;ders HO, Jasper HH, Elger C. The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology. Electroencephalogr Clin Neurophysiol Suppl 1999;52:3\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBijur PE, Latimer CT, Gallagher EJ. Validation of a verbally administered numerical rating scale of acute pain for use in the emergency department. Acad Emerg Med 2003;10:390\u0026ndash;2.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerreira SLC, Bruns RE, Ferreira HS, Matos GD, David JM, Brand\u0026atilde;o GC, \u003cem\u003eet al.\u003c/em\u003e Box-Behnken design: an alternative for the optimization of analytical methods. Anal Chim Acta 2007;597:179\u0026ndash;86.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGeddes LA, Bourland JD. The strength-duration curve. IEEE Trans Biomed Eng 1985;32:458\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmeets Y, Soer R, Chatziantoniou E, Preuper RHRS, Reneman MF, Wolff AP, \u003cem\u003eet al.\u003c/em\u003e Role of non-invasive objective markers for the rehabilitative diagnosis of central sensitization in patients with fibromyalgia: A systematic review. J Back Musculoskelet Rehabil 2024;37:525\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDesmeules JA, Cedraschi C, Rapiti E, Baumgartner E, Finckh A, Cohen P, \u003cem\u003eet al.\u003c/em\u003e Neurophysiologic evidence for a central sensitization in patients with fibromyalgia. Arthritis Rheum 2003;48:1420\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarques AP, Ferreira EAG, Matsutani LA, Pereira CAB, Assump\u0026ccedil;\u0026atilde;o A. Quantifying pain threshold and quality of life of fibromyalgia patients. Clin Rheumatol 2005;24:266\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKendrick DB, Strout TD. The minimum clinically significant difference in patient-assigned numeric scores for pain. Am J Emerg Med 2005;23:828\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTommerdahl M, Delemos KA, Vierck CJ Jr, Favorov OV, Whitsel BL. Anterior parietal cortical response to tactile and skin-heating stimuli applied to the same skin site. J Neurophysiol 1996;75:2662\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVierck CJ, Whitsel BL, Favorov OV, Brown AW, Tommerdahl M. Role of primary somatosensory cortex in the coding of pain. Pain 2013;154:334\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMelzack R, Wall PD. Pain mechanisms: a new theory: A gate control system modulates sensory input from the skin before it evokes pain perception and response. Science 1965;150:971\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang Z, Zheng H, Yu Q, Jing X. Understanding of spinal wide dynamic range neurons and their modulation on pathological pain. J Pain Res 2024;17:441\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLaakso I, Hirata A, Ugawa Y. Effects of coil orientation on the electric field induced by TMS over the hand motor area. Phys Med Biol 2014;59:203\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTerao Y, Ugawa Y. Basic mechanisms of TMS. J Clin Neurophysiol 2002;19:322\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJourn\u0026eacute;e SL, Journ\u0026eacute;e HL, Berends HI, Reed SM, de Bruijn CM, Delesalle CJG. Comparison of muscle MEPs from transcranial magnetic and electrical stimulation and appearance of reflexes in horses. Front Neurosci 2020;14:570372.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmassian VE, Quirk GJ, Stewart M. A comparison of corticospinal activation by magnetic coil and electrical stimulation of monkey motor cortex. Electroencephalogr Clin Neurophysiol 1990;77:390\u0026ndash;401.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLegatt AD, Emerson RG, Epstein CM, MacDonald DB, Deletis V, Bravo RJ, \u003cem\u003eet al.\u003c/em\u003e ACNS guideline: Transcranial electrical stimulation motor evoked potential monitoring. J Clin Neurophysiol 2016;33:42\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSills GJ. The mechanisms of action of gabapentin and pregabalin. Curr Opin Pharmacol 2006;6:108\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHordacre B, Goldsworthy MR, Vallence A-M, Darvishi S, Moezzi B, Hamada M, \u003cem\u003eet al.\u003c/em\u003e Variability in neural excitability and plasticity induction in the human cortex: A brain stimulation study. Brain Stimul 2017;10:588\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePeterchev AV, Deng Z-D, Goetz SM. Advances in transcranial magnetic stimulation technology. \u003cem\u003eBrain Stimulation\u003c/em\u003e. Hoboken, NJ, USA: John Wiley \u0026amp; Sons, Inc; 2015. p. 165\u0026ndash;89.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChung S-H, Anderson OS, Krishnamurthy V, editors. \u003cem\u003eBiological membrane ion channels: Dynamics, structure, and applications\u003c/em\u003e. 2007th ed. New York, NY: Springer; 2006.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCharlet de Sauvage R, Beuter A, Lagroye I, Veyret B. Design and construction of a portable transcranial magnetic stimulation (TMS) apparatus for migraine treatment. J Med Device 2010;4:015002.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaryshev G, Bozhko Y, Konashenkova N, Kavkaev K, Kuznetsova Y. Principles of development of a mobile system for transcranial magnetic stimulation. Procedia Comput Sci 2020;169:359\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEpstein CM. A six-pound battery-powered portable transcranial magnetic stimulator. Brain Stimul 2008;1:128\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKouzani AZ, Jaberzadeh S, Zoghi M, Usma C, Parastarfeizabadi M. Development and validation of a miniature programmable tDCS device. IEEE Trans Neural Syst Rehabil Eng 2016;24:192\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6273135/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6273135/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePulsed transcranial electrical stimulation (pTES) with short (\u0026lt; 1ms) high amplitude (\u0026gt; 20 mA) pulses can elicit suprathreshold neural activity and drive physiological effects such as motor evoked potentials. While this technique could benefit several neurological and neuropsychiatric conditions, it is not widely used because the injected current pulses cause substantial pain in the scalp. We investigated approaches to reduce scalp sensation of pTES at motor threshold in human subjects. We introduce the concept of \u003cem\u003ebackground hums\u003c/em\u003e, additional high-frequency, low-amplitude pulse trains that reduce scalp pain. We tested their pain dampening effects, along with varying pTES electrode distance and pulse width. In a subset of 7 participants, we obtained a reduction in pain score of 2/10 compared to a standard pulse. Using these methods, we were able to stimulate above motor threshold two patients affected by fibromyalgia, a chronic pain condition that also heightens pain sensitivity, with a reported scalp pain below 3/10. This work demonstrates that stimulation pain associated with pTES can be actively mitigated, opening the way for clinical applications of pTES.\u003c/p\u003e","manuscriptTitle":"Reducing scalp pain for pTES of motor cortex using background hums","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-10 08:13:23","doi":"10.21203/rs.3.rs-6273135/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"79f1ecc8-7a30-4595-9a99-7f79002dcdcb","owner":[],"postedDate":"April 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-15T13:16:24+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-10 08:13:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6273135","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6273135","identity":"rs-6273135","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}