Diagnostic Ultrasound Modulates Human Motor Cortex: Neurophysiological Evidence from Paired-Pulse TMS and Computational Modelling

Diagnostic Ultrasound Modulates Human Motor Cortex: Neurophysiological Evidence from Paired-Pulse TMS and Computational Modelling | 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 Research Article Diagnostic Ultrasound Modulates Human Motor Cortex: Neurophysiological Evidence from Paired-Pulse TMS and Computational Modelling Matteo Guidetti, Sara Annaloro, Silvia Gallucci, Marta Parazzini, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9029217/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Background Transcranial ultrasound (tUS) represents a promising brain stimulation technique, yet its physiological effects using standard diagnostic protocols remain poorly characterized. This study examines the impact of conventional diagnostic ultrasound (dUS) on intracortical excitability. Methods Healthy subjects received 30 minutes of transcranial ultrasound (2.0 MHz) over the right motor cortex. Cortical excitation and inhibition were assessed bilaterally via paired-pulse TMS, quantifying resting motor threshold (RMT), short intracortical inhibition (SICI), intracortical facilitation (ICF) and long intracortical inhibition LICI before and after stimulation. The vasomotor reserve (through the breath-holding index) was also assessed. A computational model was developed to confirm the spatial selectivity of our protocol. Non-parametric and Bayesian analyses were used. Results Sixteen healthy adults (mean age 31.9 ± 11.0 years) were enrolled. dUS induced a significant reduction in SICI in the stimulated hemisphere (p = 0.016; Bayes Factor BF = 7.65), and a robust increase in LICI in the control hemisphere (p = 0.010; BF = 7.88). Between hemispheres, SICI was higher in the stimulated than in the control side (p = 0.046; BF = 3.90), while LICI was greater in the control hemisphere (p = 0.015; BF = 10.06). ICF, RMT and BHI showed no significant changes (all p > 0.05). Conclusions dUS elicits focal changes in cortical excitability, towards an overall excitatory effect, in the absence of detectable vascular changes. The observed changes also engage compensatory transcallosal mechanisms, likely involving GABA-B-mediated pathways within the contralateral hemisphere. These findings provide mechanistic evidence supporting further translational investigation. NIBS non-invasive brain stimulation ultrasound diagnostic ultrasound neuromodulation cortical excitability interhemispheric balance Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION Ultrasound (US) have been widely used in clinical practice with a broad range of applications, both diagnostic and therapeutic ( 1 ), including focused ultrasound (FUS) for the treatment of medication-refractory essential tremor (ET) ( 2 ) and advanced Parkinson’s disease (PD) ( 3 ). Recently, transcranial ultrasound (tUS) has emerged as a novel non-invasive brain stimulation technique, providing high spatial resolution and deep penetration into brain tissues ( 4 – 6 ). An increasing body of evidence supports the use of tUS in neurological disorders ( 7 ), as it appears to modulate both cortical and subcortical functional connectivity ( 8 ), inducing focal changes within sensory and motor areas ( 5 , 9 – 11 ). Despite these promising attributes, the clinical translation of tUS remains limited by the absence of standardized stimulation protocols, with considerable heterogeneity in sonication parameters, probe designs, and delivery methods, resulting in inconsistent and sometimes conflicting neurophysiological and clinical outcomes in both preclinical and human studies ( 12 – 14 ). In this context, recent studies have demonstrated that low-intensity tUS reduces GABAA-ergic short intracortical inhibition (SICI), with the effect scaling linearly with sonication duration and duty cycle ( 15 ). Conversely, other reports have shown increased cortical excitability following prolonged sonication ( 16 ). Moreover, although no severe adverse events have been reported, mild to moderate side effects occur in approximately 4% of healthy participants, including headache, mood or cognitive alterations, sleepiness, anxiety, and neck pain ( 17 ). To address these limitations, we investigated the neuromodulatory potential of non-focused transcranial ultrasound targeting primary motor cortex (M1), delivered using the same parameters applied in routine cerebrovascular assessments – a technique commonly referred to as Transcranial Colour Sonography (TCCS) or diagnostic ultrasound (dUS). Specifically, we first developed a computational model to estimate elastic wave propagation within brain tissue and characterize the differential engagement of M1 dynamics induced by non-focused transcranial ultrasound. Then, we evaluated changes in cortical excitability, measured by paired-pulse Transcranial Magnetic Stimulation (TMS), before and immediately after dUS in healthy subjects. Concurrently, we assessed vasomotor reserve to control for potential hemodynamic confounders that could bias neurophysiological readouts during insonation. MATERIALS AND METHODS High-Resolution computational model Ultrasound wave propagation within the human head was assessed through numerical simulations, in which acoustic intensity (W/cm²) was computed to quantify the magnitude of acoustic energy reaching the target region, defined as the M1. Figure 1 -A shows the simulated scenario. A mock-up US probe was modelled to reproduce the technical specifications of the linear phased-array probe used in the experimental protocol (focal distance = 25–125 mm, size 25 × 15 mm²). Each element of the probe was modelled as a source of a sinusoidal acoustic wave at the fundamental frequency of 2 MHz. We used a realistic human anatomical model from the Virtual Population (ViP), i.e., Duke model (34-year-old, male) ( 18 ), which comprises 319 discretized tissues with acoustic properties assigned according to literature values ( 19 ). The M1 region was identified as a chain of cubic sensors (1 cm side length) positioned along the central sulcus profile, spanning the entire region of interest. Acoustic intensity was subsequently analysed on three pseudo-coronal cross-sections (Fig. 1 -B). The scenario was simulated using the acoustic solver implemented in Sim4Life v.9.2. This solver was developed based on the Westervelt–Lighthill Eq. (20), extended by incorporating a density variation term to account for acoustic impedance differences between heterogeneous tissues. This yields the Linear Acoustic Pressure Wave Equation (LAPWE): $$\rho\nabla\bullet\frac{1}{\rho}\nabla\text{p}-\frac{1}{{c}^{2}}\frac{{\partial}^{2}p}{\partial{t}^{2}}-\frac{\stackrel{\sim}{a}}{{c}^{2}}\frac{\partial p}{\partial t}=0$$ 𝑝 is the pressure, 𝑐 denotes the speed of sound, 𝑡 is time, 𝜌 is mass density, and \(\stackrel{\sim}{a}\) is a factor describing absorption behaviour as a function of the absorption coefficient α (Np/m) and angular frequency ω. The Finite-Difference Time-Domain (FDTD) method solved the LAPWE, with Perfectly Matched Layers (PML) set as boundary conditions to prevent back-reflections. Neurophysiological study Participants Healthy volunteers with no history of neurological disorders were enrolled in the study. No subject was taking medications at the time of, or one month before, the inclusion in the study, and they all had suspended alcohol or caffeine consumption at least 48 h before. The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki, and the protocol was approved by the local Ethics Committee. Written informed consent was obtained from all participants prior to study inclusion. Also, the methodology and reporting of this study follow the guidelines for reporting non-randomised studies ( 21 ). Experimental protocol Patients underwent 30min of sonication delivered through the right trans-temporal window to target M1 using a linear probe (2.0 MHz). The diencephalic plane along the superior orbitomeatal line was used as the anatomical landmark throughout the procedure. The validity of the entire intervention was confirmed by the correct visualization of the entire ipsilateral middle cerebral artery. The same parameters employed in the transcranial diagnostic study were used ( 22 ). Neurophysiological parameters, including SICI, intracortical facilitation (ICF), and long-interval intracortical inhibition (LICI), were assessed both before (T0) and immediately following (T1) the intervention, in both the hemispheres. Active stimulation was delivered over one hemisphere (stimulated hemisphere, SH), while sham stimulation over the contralateral hemisphere (control hemisphere, CH), with the order of treatment and the stimulated side pseudo-randomized across participants. A detailed description and timeline are provided in Fig. 2 . At the same time points (T0 and T1), vasomotor reserve (through breath-holding index - BHI) was evaluated in SH using the same probe delivering stimulation, to avoid potential confounding effects of changes in small vessel diameter and hemodynamic on paired-pulse TMS parameters. Although no adverse effects were expected being out dUS protocol in line with those routinely employed for patients ( 22 – 24 ), all participants were systematically monitored for adverse events throughout the experimental session. Adverse events were predefined as any unexpected or undesirable sign or symptom temporally associated with ultrasound exposure, including but not limited to headache, dizziness, nausea, visual disturbances, mood changes, cognitive alterations, fatigue, neck discomfort, or local skin irritation. Particular attention was paid to symptoms previously reported in human transcranial ultrasound studies ( 17 ). Monitoring was conducted at three time points: I) immediately before the intervention (baseline screening), II) continuously during the 30-minute insonation period through direct clinical observation and spontaneous reporting, and III) immediately after the intervention through structured questioning. Participants were explicitly asked whether they experienced any new neurological, sensory, cognitive, or systemic symptoms during or after stimulation. Additionally, they were instructed to report any delayed symptoms occurring within the subsequent 24 hours. Paired-pulse Transcranial Magnetic Stimulation Electromyographic (EMG) recordings were obtained by two standard nonpolarizable Ag/AgCl surface electrodes (diameter 9 mm; Technomed Europe®), one placed over the belly of the abductor digiti minimi (ADM) muscle, either left or right, and the other over its distal tendon. A Magstim Super Rapid Transcranial Magnetic Stimulator (Magstim Company, Dyfed, UK, 2.2 T maximum field output), connected to a figure-of-eight coil was used (outer diameter 70.0 mm). The coil was held to induce a current in the lateral–posterior to medial–anterior direction in the brain, approximately 45° from the sagittal plane ( 25 ). The M1 contralateral to the recording site was determined as the point that produced the largest and most consistent motor evoked potential (MEP). The optimal coil position to elicit a reliable MEP was marked on the scalp to ensure identical placement of the coil throughout the experiment ( 26 ). Resting motor threshold (RMT) was preliminary assessed for each patient and it is defined as the minimum stimulator output that induces MEPs of more than 50 µV in at least five out of ten trials when a muscle is completely relaxed, starting from 35% and upgrading by incremental steps of 3% ( 27 – 29 ). As concerns paired pulse TMS, we adopted the original protocol proposed and described by Kujirai and colleagues ( 30 ). SICI and ICF were obtained at rest with a subthreshold conditioning stimulus (CS) followed by a suprathreshold test stimulus (TS) at an interstimulus interval (ISI) of 3.0 and 12.0 ms, respectively. TS was set at an intensity of 130% RMT. The CS were set at 70% of the RMT, corresponding at about 90% of the active motor threshold (AMT) ( 30 ). Although an influence of short intracortical facilitation (SICF) on SICI cannot be ruled out, this contamination occurs at intervals typically sparing the ISI of 3.0 ms and with stimulus intensities higher than those used here (ISI ∼ 4.5 ms and S1 intensity > 90% AMT) ( 31 ). LICI was then assessed by delivering two stimuli (CS and TS) with the same intensity (130% RMT) and assuming an ISI of 150.0 ms. This value avoids paradoxical facilitation as reported to occur for both lower and higher ISIs, especially when stimulating the dominant hemisphere ( 32 ). For each SICI and ICF measure, 10 consecutive paired-pulse TMS pulses were administered randomly every 6-8s to secure reproducible traces, whereas 20 consecutive pulses were delivered to obtain LICI ( 33 ). SICI reflects GABAA receptor-mediated fast inhibitory post-synaptic potentials (IPSPs) in corticospinal neurons, while ICF reflects glutamatergic signalling and LICI depends on slow IPSPs mediated through GABAB receptors ( 34 ). For paired-pulse recordings, full muscle relaxation was ensured by providing the subjects with audio-visual feedback of the raw EMG at high gain (microV). Assessment of the Vasomotor Reserve The experiments were conducted using a DWL Multi-Dop X4 transcranial Doppler (TCD) system, with subjects positioned comfortably in the supine posture. Pulsed-wave Doppler probes (2 MHz) were secured over the right transtemporal window employing a dedicated probe holder and fixation device. Optimal insonation of the middle cerebral artery (MCA) was achieved at a depth ranging from 45 to 58 mm. The proprietary software integral to the DWL system enabled continuous recording of mean blood flow velocity in insonated arteries during baseline and breath-holding protocols. Baseline measurements were defined as the stable mean flow velocity recorded during the final 3 minutes of an initial 10-minute resting period. The breath-holding challenge, designed to elicit cerebral vasomotor reactivity, involved instructing subjects to sustain breath-holding for 30 seconds. Velocity data were analysed offline. No adverse effects were reported during the breath-holding manoeuvre. Cerebrovascular reactivity was quantified using the breath-holding index (BHI), calculated as the percentage increase in mean cerebral blood flow velocity during breath-holding relative to baseline, normalized by the duration of breath-holding. Specifically, BHI was computed as: [(mean flow velocity at the end of breath-holding − mean flow velocity at rest) / mean flow velocity at rest] × 100 / duration of breath-holding (30 seconds) ( 35 , 36 ). Statistical Analysis MEP amplitudes were measured peak to peak. The MEP amplitudes evoked by paired-pulse stimulation were expressed as a percentage of the mean MEP amplitude of test stimulus (TS) alone for SICI and ICF, whereas when evaluating LICI the MEPs following TS were compared to MEPs as induced by CS. Normal distributions of the dependent variables (RMT, ICF, SICI, LICI and BHI) were assessed using the Shapiro-Wilk test for normality ( 37 ). Since most of them did not pass the test (p > 0.05), non-parametric statistical analysis was applied. As within analysis, Wilcoxon signed-rank test was applied for each of the two hemispheres (SH and CH) to disclose significant changes in times (T0 vs T1). As between analysis, changes in variation of outcomes (∆, calculated as: ∆ score = T1 score − T0 score) were assessed through Wilcoxon signed-rank test since we considered the hemispheres as coming from the same tested population. Also, we performed one-sample Wilcoxon test comparing the ratio of each ∆ (ratio = ∆ score in SH / ∆ score in CH) with a median = 1, to verify whether the ratio was inferior (one-tailed test). Given the limited sample size and the derived nature of ratios, these analyses were considered as only exploratory. A p-value < 0.05 was considered statistically significant for all analyses, except for one-sample Wilcoxon test (p = 0.025). In all analyses, effect sizes were quantified using the paired rank-biserial correlation (r rb ), with 95% confidence intervals. Given the limited sample size, Bayesian statistics were additionally applied to corroborate the classical, frequentist, non-parametric findings ( 38 ). The Bayesian approach allows distinguishing between an absence of evidence and evidence of absence, by quantifying the relative likelihood of the alternative and null hypotheses in explaining the observed data. Evidence is expressed on a continuous scale through the Bayes Factor (BF), which represents the ratio between the likelihood of a model including the tested effect and that of the null model ( 38 ). Accordingly, Bayesian Wilcoxon signed-rank tests and Bayesian one-sample Wilcoxon tests were performed. Evidence was interpreted following standard criteria: BF > 3 was considered moderate and BF > 10 strong evidences in favour of the alternative hypothesis, whereas BF < 1/3 and BF < 1/10 indicated moderate and strong evidence in favour of the null hypothesis, respectively. Values within 1/3 < BF < 3 were regarded as inconclusive evidence. Data were analysed using JASP version 0.16.3 for Windows (JASP Team, 2022). RESULTS Computational estimations Results were evaluated in terms of acoustic intensity, defined as the acoustic energy propagating through a unit surface per unit time. Analysis of the intensity distribution into the whole volume of M1 revealed that 65% and 26% of the data exceeded 50% and 70% of the local maximum, respectively (Fig. 3 -A). Figure 3 -B shows the normalized acoustic intensity distributions extracted from three pseudo-coronal slices within the M1 region, revealing ultrasound propagation patterns affecting the M1. Neurophysiological outcomes Sixteen healthy volunteers (mean age ± SD: 31.88 ± 10.99 years, 7 F) were enrolled. No adverse events were reported during the insonation procedure or at post-stimulation assessment. No participant discontinued the experiment due to discomfort, and no delayed adverse effects were communicated during the follow-up period. Figure 4 shows exemplificative traces recorded from the same subject, before and after sonication, from either SH or CH. As for within analysis, Wilcoxon signed-rank test disclosed a significant modulation of SICI in the SH (z = − 2.38, p = 0.016; r rb = -0.68 95% CI [-0.88, -0.26]), with no changes in the CH (p = 0.856). Bayesian analysis supported this finding, showing moderate-to-strong evidence for the SH (strong Bayesian evidence for the alternative hypothesis, BF₁₀ = 7.65), and anecdotal evidence for the CH (anecdotal Bayesian evidence for the null hypothesis, BF₁₀ = 0.257) (see Fig. 5 -A). Similarly, LICI significantly increased in CH from T0 to T1 (z = − 2.59, p = 0.010 r rb = -0.74 95% CI [-0.91, -0.37]; strong Bayesian evidence for the alternative hypothesis, BF₁₀ = 7.88), whereas no significant difference was detected in the SH (p = 0.213; anecdotal Bayesian evidence for the null hypothesis, BF₁₀ = 0.546) (see Fig. 5 -B). No significant pre-post differences were found for RMT, BHI or ICF in either hemisphere (all p > 0.05; anecdotal-to-moderate evidence for the null hypothesis, BF₁₀ < 1). Detailed median (IQR) values and test statistics are reported in Table 1 . Table 1 Neurophysiological results for T0 and T1 assessments. Values are reported as median ± IQR. Stimulated Hemisphere Within analysis* Control Hemisphere Within analysis* T0 T1 z pValue BF 10 T0 T1 z pValue BF 10 RMT 46 ± 13.75 47 ± 12.5 -0.53 0.62 0.31 46.5 ± 8.25 46.5 ± 7.5 1.48 0.15 0.77 SICI 65 ± 29.5 67.5 ± 49.75 -2.38 0.02 7.65 62 ± 40 64 ± 21.25 -0.21 0.87 0.26 ICF 151 ± 73 156.5 ± 61.75 -1.03 0.32 0.33 163 ± 65 165 ± 83.75 -0.72 0.49 0.30 LICI 89 ± 23.25 75 ± 18.25 1.27 0.21 0.55 54 ± 17.75 86 ± 13.5 -2.59 0.01 7.88 BHI 0.87 ± 0.41 0.68 ± 0.52 1.50 0.14 0.58 - - - - - RMT = resting motor threshold; SICI = short-interval intracortical inhibition; ICF = intracortical facilitation; LICI = long-interval intracortical inhibition; BHI = breath-holding index. *pValue refers to Wilcoxon signed-rank test (significance at 0.05), BF 10 refers to Bayesian Wilcoxon signed-rank test. As for between analysis, Wilcoxon signed-rank test revealed a significant difference in ΔSICI values, being higher in the SH compared with the CH (z = 2.01, p = 0.046; r rb = 0.57 95% CI [0.09, 0.84], moderate Bayesian evidence for an inter-hemispheric difference, BF₁₀ = 3.91), and in ΔLICI values, being greater in the CH compared with the SH (z = -2.45, p = 0.015; r rb = -0.70 95% CI [-0.89, -0.30], strong Bayesian evidence for an inter-hemispheric difference, BF₁₀ = 10.06) (see Fig. 5 -C). No significant differences were found between hemispheres for ΔRMT and ΔICF (all p > 0.05; anecdotal-to-moderate evidence for the null hypothesis, BF₁₀ < 1). Detailed median (IQR) values and test statistics are reported in Table 2 . Table 2 Neurophysiological results for Δ = (T1 – T0). Values are reported as median ± IQR. Hemisphere Between analysis* SH CH z pValue BF 10 Δ RMT 0 ± 3.5 0 ± 2 1.20 0.25 0.46 Δ SICI 19.5 ± 40 2.5 ± 48.25 2.02 0.046 3.90 Δ ICF 24 ± 70.25 9.5 ± 55.75 0.31 0.78 0.27 Δ LICI -20 ± 27 32 ± 33 -2.46 0.015 10.06 RMT = resting motor threshold; SICI = short-interval intracortical inhibition; ICF = intracortical facilitation; LICI = long-interval intracortical inhibition; SH = stimulated hemisphere; CH = control hemisphere. *pValue refers to Wilcoxon signed-rank test (significance at 0.05), BF 10 refers to Bayesian Wilcoxon signed-rank test. As for the analysis on Δ’s ratio, one-sample Wilcoxon test showed that RMT and LICI ratio values were significantly lower than 1 (V = 3, p = 0.021; r rb = -0.83 95% CI [−∞, -0.5] and V = 17, p = 0.004; r rb = -0.75, 95% CI [−∞, -0.5], respectively), with anecdotal Bayesian evidence for a reduction in RMT ratio (BF₁₀ = 0.83) and moderate Bayesian evidence for the null hypothesis in LICI ratio (BF₁₀ = 0.31). No significant differences were found for ICF ratio (p = 0.126; moderate Bayesian evidence for the null hypothesis, BF₁₀ = 0.20) and SICI ratio (p = 0.047; moderate Bayesian evidence for the null hypothesis, BF₁₀ = 0.19). Detailed median (IQR) values and test statistics are reported in Table 3 . Table 3 Neurophysiological results for ratios = (Δ SH / Δ CH). Values are reported as median ± IQR. median ± IQR one-sample Wilcoxon test * V pValue BF 10 ratio RMT 0.0 ± 3.69 3.00 0.021 0.83 ratio SICI 0.33 ± 2.42 35.00 0.047 0.19 ratio ICF 0.12 ± 1.48 45.00 0.126 0.20 ratio LICI -0.22 ± 1.60 17.00 0.004 0.31 RMT = resting motor threshold; SICI = short-interval intracortical inhibition; ICF = intracortical facilitation; LICI = long-interval intracortical inhibition. *pValue refers to one-sample Wilcoxon test (one-tailed test), significance at 0.025, BF 10 refers to Bayesian Wilcoxon signed-rank test. DISCUSSION To our knowledge, this is the first study demonstrating that acoustic waves, delivered using parameters and bone windows identical to those routinely employed in dUS ( 22 – 24 ), can modulate cortical excitability in healthy subjects. Importantly, this work integrates computational acoustic modelling with in vivo neurophysiological measurements, bridging engineering-based exposure characterization and functional cortical readouts. Our results reveal a robust attenuation of SICI, a neurophysiological marker predominantly driven by the GABAAergic inhibitory system ( 34 ), leading to a net excitation of cortical circuits. This modulatory phenomenon transcends indirect vascular effects, as confirmed by the lack of meaningful changes in vasomotor reactivity, supporting the interpretation that the observed modulation reflects a direct neural effect rather than purely vascular mechanisms. Overall, the observed effect of enhanced cortical excitability fits with recent studies employing slightly different tUS protocols, specifically delivering stimulation in a theta burst pattern ( 39 – 41 ). Another noteworthy finding is the reduction of LICI observed in the CH, resulting in an increased MEP amplitude during the LICI protocol. This effect, confirmed by both within- and between-subject analyses, is unlikely to be explained solely by nonspecific mechanical or thermal effects, given the selectivity of the observed neurophysiological changes. A possible explanation is that reduced inhibition in the SH, indicated by a significant decline in SICI, triggers compensatory responses in the contralateral cortex through interhemispheric balance ( 42 ). This hypothesis is supported by the fact that transcallosal interhemispheric connections are predominantly GABA-B-mediated, mirroring the mechanisms underlying LICI ( 43 , 44 ). These results are unlikely to stem from methodological bias, such as LICI contamination by excitatory processes, since such effects are typically excluded at the interstimulus intervals used here ( 32 , 45 , 46 ). The lack of analogous effects on SICI upon evaluation of the contralateral M1 provides additional confirmation of the spatial specificity of our stimulation protocol and the associated computational model. This constitutes a rigorous experimental control, as these assessments were performed on the same subjects, during the same experimental session, and under identical methodological conditions. However, the present findings should be interpreted primarily as a mechanistic proof-of-concept rather than as evidence of clinical efficacy. Indeed, although the convergence between neurophysiological changes and computational modelling of acoustic propagation supports the biological plausibility of a direct cortical effect within the insonated region, the study was conducted in healthy volunteers without behavioural or therapeutic outcomes. Therefore, while providing a physiological validation, the clinical relevance, durability, and functional impact of such modulation remain to be established. While two antecedent studies partially intersect with our investigation ( 16 , 47 ), they fall short of capturing the comprehensive scope of our work. Guerra et al. demonstrated that acoustic stimuli, delivered trans-temporally as in dUS, exert no modulation upon brainstem reflexes; although their computational models of elastic wave propagation yield valuable theoretical insights, direct assessment of cortical excitability remained unexplored ( 47 ). Conversely, Gibson and colleagues reported changes in MEP amplitudes using dUS probes; however, their study did not leverage paired-pulse TMS protocols to disentangle cortical inhibitory/excitatory dynamics nor implement computational models to characterize wave propagation ( 16 ). Their approach also diverged anatomically, targeting the M1 region covered by significantly thicker cranial bone, in contrast to our focused application on the trans-temporal acoustic window ( 16 ). Finally, our findings may also align with previous clinical observations reporting transient motor improvements during prolonged trans-temporal insonation in patients with acute ischemic stroke undergoing systemic thrombolysis (sonothrombolysis) ( 48 , 49 ). While large trials and meta-analyses indicate that sonothrombolysis is safe, its functional benefits appear short-lived and more evident in younger patients. These data may be consistent with acute ultrasound-induced modulation of cortical excitability in the affected hemisphere, in addition to the established mechanical disruption of the fibrin clot ( 50 ). This study presents some limitations. First, the relatively small sample size of healthy participants warrants expansion in future research. For example, the ratio analyses showed partial divergence between frequentist and Bayesian approaches, with statistically significant p-values not consistently accompanied by Bayes factors supporting the alternative hypothesis. Such discrepancies, particularly in small samples, suggest that these findings should be interpreted as exploratory. Second, the representation of intrinsic hand muscles at the M1 level does not fully align with the conventional trans-temporal window. Nonetheless, the computational model, an investigation used to further inform on neuromodulatory effects of physical forces applied to central nervous system ( 51 , 52 ), supports the plausibility of efficient elastic wave propagation to the M1. The specific modulation of parameters such as SICI and ICF, coupled with the absence of changes in the CH, confirms the spatial specificity of our protocol. Lastly, unlike measures such as the RMT, cortical excitability indices (SICI, ICF, and LICI) reflect the activity of widely distributed neural networks rather than focal cortical regions. CONCLUSIONS In this study, we provide mechanistic evidence that trans-temporal dUS can modulate intracortical inhibitory circuits in healthy individuals. The spatial specificity supported by computational modelling, together with the absence of significant vascular changes or effects in the control hemisphere, strengthens the biological plausibility of a direct cortical effect under conventional sonographic parameters. These findings should be interpreted as a physiological proof-of-concept in healthy subjects. Whether such modulation translates into meaningful functional or clinical effects remains to be determined in controlled studies involving patient populations and behavioural outcomes. Future studies will be required to define durability of effects, and potential translational relevance. Abbreviations AMT Active Motor Threshold BHI Breath–Holding Index CH Control Hemisphere CS Conditioning Stimulus dUS Diagnostic Ultrasound FUS Focused Ultrasound GABA Gamma–Aminobutyric Acid ICF Intracortical Facilitation ISI Interstimulus Interval LICI Long–Interval Intracortical Inhibition M1 Primary Motor Cortex MCA Middle Cerebral Artery MEP Motor Evoked Potential RMT Resting Motor Threshold SH Stimulated Hemisphere SICI Short–Interval Intracortical Inhibition SICF Short–Interval Intracortical Facilitation TMS Transcranial Magnetic Stimulation TS Test Stimulus tUS Transcranial Ultrasound US Ultrasound Declarations Ethics approval and consent to participate The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki, and the protocol was approved by the local Ethics Committee. Written informed consent was obtained from all participants prior to study inclusion. Competing interests The authors declare that they have no competing interests. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not‑for‑profit sectors. Author Contribution Conceptualization: T.B., S.A.; Data curation: M.G., S.A., T.B.; Formal analysis: M.G., S.M., S.G., M.P.; Investigation: T.B., S.A., S.G., M.P.; Methodology: T.B., M.P.; Supervision: T.B., A.P.; Visualization: M.G., S.G., M.P., E.G.; Writing – original draft: M.G., T.B., S.G., M.P.; Writing – review & editing: M.G., S.A., S.G., M.P., E.C., A.DG., S.M., N.M., M.B., A.P., T.B. All authors read and approved the submitted version of the manuscript. Acknowledgement The authors wish to thank ZMT Zurich MedTech AG (www.zmt.swiss) for providing the simulation software Sim4Life. Data Availability The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. 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Development of a new generation of high-resolution anatomical models for medical device evaluation: the Virtual Population 3.0. Phys Med Biol. 2014;59(18):5287–303. IT’IS Foundation. Tissue properties database V4. 0. 2018. Westervelt PJ. Parametric acoustic array. J Acoust Soc Am. 1963;35(4):535–7. Reeves B, Gaus W. Guidelines for reporting non-randomised studies. Forschende Komplementarmedizin Und Klassische Naturheilkunde. 2004;11:46–52. Nedelmann M, Stolz E, Gerriets T, Baumgartner RW, Malferrari G, Seidel G, et al. Consensus Recommendations for Transcranial Color-Coded Duplex Sonography for the Assessment of Intracranial Arteries in Clinical Trials on Acute Stroke. Stroke ottobre. 2009;40(10):3238–44. 10.1161/STROKEAHA.109.555169 . Baumgartner RW. Transcranial color duplex sonography in cerebrovascular disease: a systematic review. Cerebrovasc Dis 1 gennaio. 2003;16(1):4–13. doi:10.1159/000070108 PubMed PMID: 12766355. Krejza J, Baumgartner RW. Clinical applications of transcranial color-coded duplex sonography. J Neuroimaging 1 luglio. 2004;14(3):215–25. doi:10.1177/1051228403259274 PubMed PMID: 15228761. Rossini PM, Burke D, Chen R, Cohen LG, Daskalakis Z, Di Iorio R, et al. Non-invasive electrical and magnetic stimulation of the brain, spinal cord, roots and peripheral nerves: Basic principles and procedures for routine clinical and research application. An updated report from an I.F.C.N. Committee. Clin Neurophysiol giugno. 2015;126(6):1071–107. .001 PubMed PMID: 25797650; PubMed Central PMCID: PMC6350257. Samotus O, Chen R, Jog M. Changes in Cortical Excitability and Parkinson Tremor After Botulinum Toxin Therapy. Neurol 5 ottobre. 2021;97(14):e1413–24. 10.1212/WNL.0000000000012662 . Groppa S, Oliviero A, Eisen A, Quartarone A, Cohen LG, Mall V, et al. A practical guide to diagnostic transcranial magnetic stimulation: Report of an IFCN committee. Clin Neurophysiol 1 maggio. 2012;123(5):858–82. 10.1016/j.clinph.2012.01.010 . Ni Z, Gunraj C, Chen R. Short interval intracortical inhibition and facilitation during the silent period in human. J Physiol 1 settembre. 2007;583(3):971–82. 10.1113/JPHYSIOL.2007.135749 . Rossi S, Antal A, Bestmann S, Bikson M, Brewer C, Brockmöller J, et al. Safety and recommendations for TMS use in healthy subjects and patient populations, with updates on training, ethical and regulatory issues: Expert Guidelines. Clin Neurophysiol gennaio. 2021;132(1):269–306. 10.1016/j.clinph.2020.10.003 . PubMed PMID: 33243615; PubMed Central PMCID: PMC9094636. Kujirai T, Caramia MD, Rothwell JC, Day BL, Thompson PD, Ferbert A, et al. Corticocortical inhibition in human motor cortex. J Physiol. 1993;471(1):501–19. 10.1113/jphysiol.1993.sp019912 . Peurala SH, Müller-Dahlhaus M, Arai JF, Ziemann N. Interference of short-interval intracortical inhibition (SICI) and short-interval intracortical facilitation (SICF). Clin Neurophysiol 1 ottobre. 2008;119(10):2291–7. 10.1016/j.clinph.2008.05.031 . de Goede AA, van Putten MJAM. Repeatability of long intracortical inhibition in healthy subjects. Clin Neurophysiol Pract 1 gennaio. 2017;2:26–34. 10.1016/j.cnp.2016.12.004 . Chang WH, Fried PJ, Saxena S, Jannati A, Gomes-Osman J, Kim YH, et al. Optimal number of pulses as outcome measures of neuronavigated transcranial magnetic stimulation. Clin Neurophysiol 1 agosto. 2016;127(8):2892–7. 10.1016/j.clinph.2016.04.001 . Ziemann U, Reis J, Schwenkreis P, Rosanova M, Strafella A, Badawy R, et al. TMS and drugs revisited 2014. Clin Neurophysiol 1 ottobre. 2015;126(10):1847–68. 10.1016/j.clinph.2014.08.028 . Giorli E, Tognazzi S, Briscese L, Bocci T, Mazzatenta A, Priori A, et al. Transcranial Direct Current Stimulation and Cerebral Vasomotor Reserve: A Study in Healthy Subjects. J Neuroimaging. 2015;25(4):571–4. 10.1111/jon.12162 . Silvestrini M, Vernieri F, Pasqualetti P, Matteis M, Passarelli F, Troisi E et al. Impaired Cerebral Vasoreactivity and Risk of Stroke in Patients With Asymptomatic Carotid Artery Stenosis. JAMA. 26 aprile. 2000;283(16):2122–7. 10.1001/jama.283.16.2122 Mishra P, Pandey CM, Singh U, Gupta A, Sahu C, Keshri A. Annals Cardiac Anaesth 1 gennaio. 2019;22(1):67. 10. 4103/ACA.ACA_157_18 PubMed PMID: 30648682. Descriptive Statistics and Normality Tests for Statistical Data. Keysers C, Gazzola V, Wagenmakers EJ. Using Bayes factor hypothesis testing in neuroscience to establish evidence of absence. Nat Neurosci 1 luglio. 2020;23(7):788–99. 10.1038/s41593-020-0660-4 . PubMed PMID: 32601411; PubMed Central PMCID: PMC7610527. Samuel N, Zeng K, Harmsen IE, Ding MYR, Darmani G, Sarica C, et al. Multi-modal investigation of transcranial ultrasound-induced neuroplasticity of the human motor cortex. Brain Stimul. 2022;15(6):1337–47. Zeng K, Li Z, Xia X, Wang Z, Darmani G, Li X, et al. Effects of different sonication parameters of theta burst transcranial ultrasound stimulation on human motor cortex. Brain Stimul. 2024;17(2):258–68. Zeng K, Darmani G, Fomenko A, Xia X, Tran S, Nankoo J, et al. Induction of human motor cortex plasticity by theta burst transcranial ultrasound stimulation. Ann Neurol. 2022;91(2):238–52. Lee H, Gunraj C, Chen R. The effects of inhibitory and facilitatory intracortical circuits on interhemispheric inhibition in the human motor cortex. J Physiol. 2007;580(3):1021–32. 10.1113/jphysiol.2006.126011 . He Xfei, Lan Y, Zhang Q, Liang F, yin, Luo C ming, Xu Gqing et al. GABA-ergic interneurons involved in transcallosal inhibition of the visual cortices in vivo in mice. Physiology & Behavior. 1 novembre. 2015;151:502–8. 10.1016/j.physbeh.2015.08.026 Chowdhury SA, Matsunami KI. GABA-B-related activity in processing of transcallosal response in cat motor cortex. J Neurosci Res. 2002;68(4):489–95. 10.1002/jnr.10223 . de Goede AA, ter Braack EM, van Putten MJAM. Single and paired pulse transcranial magnetic stimulation in drug naïve epilepsy. Clin Neurophysiol 1 settembre. 2016;127(9):3140–55. 10.1016/j.clinph.2016.06.025 . Opie GM, Rogasch NC, Goldsworthy MR, Ridding MC, Semmler JG. Investigating TMS–EEG Indices of Long-Interval Intracortical Inhibition at Different Interstimulus Intervals. Brain Stimulation 1 gennaio. 2017;10(1):65–74. 10.1016/j.brs.2016.08.004 . Guerra A, Vicenzini E, Cioffi E, Colella D, Cannavacciuolo A, Pozzi S, et al. Effects of transcranial ultrasound stimulation on trigeminal blink reflex excitability. Brain Sci. 2021;11(5):645. Tsivgoulis G, Katsanos AH, Eggers J, Larrue V, Thomassen L, Grotta JC, et al. Sonothrombolysis in Patients With Acute Ischemic Stroke With Large Vessel Occlusion: An Individual Patient Data Meta-Analysis. Stroke dicembre. 2021;52(12):3786–95. 10.1161/STROKEAHA.120.030960 . Alexandrov AV, Köhrmann M, Soinne L, Tsivgoulis G, Barreto AD, Demchuk AM, et al. Safety and efficacy of sonothrombolysis for acute ischaemic stroke: a multicentre, double-blind, phase 3, randomised controlled trial. Lancet Neurol 1 aprile. 2019;18(4):338–47. 10.1016/S1474-4422(19)30026-2 . May B. Sonothrombolysis Improves Odds of Complete Recanalization in Acute Ischemic Stroke. The Cardiology Advisor. NA-NA; 2021. Guidetti M, Giannoni-Luza S, Bocci T, Pacheco-Barrios K, Bianchi AM, Parazzini M, et al. Modeling Electric Fields in Transcutaneous Spinal Direct Current Stimulation: A Clinical Perspective. Biomedicines 26 aprile. 2023;11(5):5. 10.3390/biomedicines11051283 . Berger TA, Wischnewski M, Opitz A, Alekseichuk I. Human head models and populational framework for simulating brain stimulations. Sci Data 27 marzo. 2025;12(1):516. 10.1038/s41597-025-04886-0 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 30 Apr, 2026 Reviewers agreed at journal 09 Apr, 2026 Reviewers invited by journal 08 Apr, 2026 Editor assigned by journal 05 Mar, 2026 Submission checks completed at journal 05 Mar, 2026 First submitted to journal 04 Mar, 2026 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-9029217","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":623564145,"identity":"cd7d6e5b-bbfc-4d0a-98f3-840db49c00e0","order_by":0,"name":"Matteo Guidetti","email":"","orcid":"","institution":"University of Milan","correspondingAuthor":false,"prefix":"","firstName":"Matteo","middleName":"","lastName":"Guidetti","suffix":""},{"id":623564147,"identity":"c46625c6-607e-42a8-9655-20ef878ba741","order_by":1,"name":"Sara Annaloro","email":"","orcid":"","institution":"University of Milan","correspondingAuthor":false,"prefix":"","firstName":"Sara","middleName":"","lastName":"Annaloro","suffix":""},{"id":623564148,"identity":"bc021b9e-b98d-432c-a3d8-8af7de56f2c1","order_by":2,"name":"Silvia Gallucci","email":"","orcid":"","institution":"Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni (IEIIT), Consiglio Nazionale delle Ricerche","correspondingAuthor":false,"prefix":"","firstName":"Silvia","middleName":"","lastName":"Gallucci","suffix":""},{"id":623564151,"identity":"23e6e5bd-8e1c-4ffb-a589-48c1405e63ae","order_by":3,"name":"Marta Parazzini","email":"","orcid":"","institution":"Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni (IEIIT), Consiglio Nazionale delle Ricerche","correspondingAuthor":false,"prefix":"","firstName":"Marta","middleName":"","lastName":"Parazzini","suffix":""},{"id":623564152,"identity":"d2f9207c-921f-42e6-9fb3-db416ee6e691","order_by":4,"name":"Emma Chiaramello","email":"","orcid":"","institution":"Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni (IEIIT), Consiglio Nazionale delle Ricerche","correspondingAuthor":false,"prefix":"","firstName":"Emma","middleName":"","lastName":"Chiaramello","suffix":""},{"id":623564153,"identity":"8bfcd5c4-5960-4efc-8bb1-56a05b806070","order_by":5,"name":"Amedeo Grado","email":"","orcid":"","institution":"University of Milan","correspondingAuthor":false,"prefix":"","firstName":"Amedeo","middleName":"","lastName":"Grado","suffix":""},{"id":623564154,"identity":"01dfbe43-47a2-43f0-918a-2e3f8464dce8","order_by":6,"name":"Sara Marceglia","email":"","orcid":"","institution":"University of Milan","correspondingAuthor":false,"prefix":"","firstName":"Sara","middleName":"","lastName":"Marceglia","suffix":""},{"id":623564155,"identity":"3f462bfd-c8b6-4619-8179-ca6c44ba5797","order_by":7,"name":"Nicola Morelli","email":"","orcid":"","institution":"Guglielmo da Saliceto Hospital","correspondingAuthor":false,"prefix":"","firstName":"Nicola","middleName":"","lastName":"Morelli","suffix":""},{"id":623564156,"identity":"85263954-8b75-48db-91ee-9aac0c747cbb","order_by":8,"name":"Matteo Bologna","email":"","orcid":"","institution":"Sapienza University of Rome","correspondingAuthor":false,"prefix":"","firstName":"Matteo","middleName":"","lastName":"Bologna","suffix":""},{"id":623564157,"identity":"1d072b7d-0edf-4c93-977f-0c7760924808","order_by":9,"name":"Alberto Priori","email":"","orcid":"","institution":"University of Milan","correspondingAuthor":false,"prefix":"","firstName":"Alberto","middleName":"","lastName":"Priori","suffix":""},{"id":623564158,"identity":"6f0a4de2-269e-4351-91e0-2c451549c7e5","order_by":10,"name":"Tommaso Bocci","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYDADAxCRUMHAwMbA2MCQgEclD6qWMzAtePSgamFsg3HxaLFn707d8OOPDYM5e/PDDw/nHc7jEzvcwPDwBx5beM5uu9nblsZg2XPMWCJx2+FiNulEAg6TyN12g7fhMIPBjRw2BqCWxDZitNz88wemZQ6RWm7zsMG0NBCj5czZbbdl29J4wH5JOJYO1nIgIQ23Fvb23m033/yxkQOF2McfNdaJ82enP3z4wwa3FrhtKLwDhDWMglEwCkbBKMAHAEZZUwsfILb4AAAAAElFTkSuQmCC","orcid":"","institution":"University of Milan","correspondingAuthor":true,"prefix":"","firstName":"Tommaso","middleName":"","lastName":"Bocci","suffix":""}],"badges":[],"createdAt":"2026-03-04 10:40:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9029217/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9029217/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107087233,"identity":"f1e9fec7-c6f3-4186-a798-56d8411eb5b1","added_by":"auto","created_at":"2026-04-16 15:13:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1869062,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComputational workflow overview. (A)\u003c/strong\u003e Probe placement in accordance with clinical application on an adult male human model (Duke anatomical dataset). \u003cstrong\u003e(B)\u003c/strong\u003e Localization of pseudo-coronal sections A, B, and C within the M1 volume. These sections are mutually parallel and parallel to the plane identified as the vertical projection of the central sulcus.\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-9029217/v1/84179cfd4b0c992eaedb8f03.png"},{"id":107087235,"identity":"13b7a4a7-6d93-4ca5-a740-c30a20688769","added_by":"auto","created_at":"2026-04-16 15:13:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":4575839,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGraphical representation of the study design\u003c/strong\u003e. TMS = transcranial magnetic stimulation; RMT = resting motor threshold; ICF = intracortical facilitation; SICI = short-interval intracortical inhibition; LICI = long-interval intracortical inhibition; BHI = Breath-Holding Index; CH = control hemisphere; SH = stimulated hemisphere\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-9029217/v1/2dfc0098907b9dbd439c3190.png"},{"id":107087234,"identity":"defbea8d-7fe7-42d0-9a12-3e17b839d4ad","added_by":"auto","created_at":"2026-04-16 15:13:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1234584,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComputational Results. A)\u003c/strong\u003e \u003cstrong\u003eIntensity distribution into the whole volume of M1; B) Spatial distributions of acoustic intensity on pseudo-coronal sections A, B, and C.\u003c/strong\u003e All acoustic intensity values are normalized with respect to the local maximum intensity within the M1 region.\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-9029217/v1/79e9196fc16f67c63df8f6db.png"},{"id":107087237,"identity":"6636c8fc-e197-4112-a9a1-fc52e14d55fa","added_by":"auto","created_at":"2026-04-16 15:13:13","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":612857,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChanges in intracortical excitability\u003c/strong\u003e. Traces were recorded from the same subject, before (T0) and after (T1) sonication, either from the stimulated (sonicated) hemisphere (SH) or the control hemisphere (CH). TS: Testing Stimulus alone; SICI: Short IntraCortical Inhibition; ICF: IntraCortical Facilitation; LICI: Long IntraCortical Inhibition.\u003c/p\u003e","description":"","filename":"Fig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-9029217/v1/7d6d398b11d8313381333403.png"},{"id":107087236,"identity":"d3d17931-a85d-4d75-9404-03c9e524b7b8","added_by":"auto","created_at":"2026-04-16 15:13:13","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":433154,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGraphical representation of the statistically significant changes\u003c/strong\u003e. A) Changes in short-interval intracortical inhibition (SICI) across timepoints for control and stimulated hemisphere (CH and SH, respectively) (* p \u0026lt; 0.05, Wilcoxon signed-rank test). B) Changes in long-interval intracortical inhibition (LICI) across timepoints for control and stimulated hemisphere (CH and SH, respectively) (* p \u0026lt; 0.05, Wilcoxon signed-rank test). C) Changes in Δ SICI and Δ LICI (Δ = T1 – T0) for control and stimulated hemisphere (CH and SH, respectively) (* p \u0026lt; 0.05, Wilcoxon signed-rank test). Data are reported as median ± IQR.\u003c/p\u003e","description":"","filename":"Fig.5.png","url":"https://assets-eu.researchsquare.com/files/rs-9029217/v1/fe1e5311e6ffe11d8949a3a8.png"},{"id":107481013,"identity":"333917fb-8e24-480a-9b96-e96b3bced848","added_by":"auto","created_at":"2026-04-22 02:15:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8379347,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9029217/v1/71cdb09b-8a35-47d8-9f73-f935f2faf060.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Diagnostic Ultrasound Modulates Human Motor Cortex: Neurophysiological Evidence from Paired-Pulse TMS and Computational Modelling","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eUltrasound (US) have been widely used in clinical practice with a broad range of applications, both diagnostic and therapeutic (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), including focused ultrasound (FUS) for the treatment of medication-refractory essential tremor (ET) (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) and advanced Parkinson\u0026rsquo;s disease (PD) (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Recently, transcranial ultrasound (tUS) has emerged as a novel non-invasive brain stimulation technique, providing high spatial resolution and deep penetration into brain tissues (\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). An increasing body of evidence supports the use of tUS in neurological disorders (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), as it appears to modulate both cortical and subcortical functional connectivity (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), inducing focal changes within sensory and motor areas (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Despite these promising attributes, the clinical translation of tUS remains limited by the absence of standardized stimulation protocols, with considerable heterogeneity in sonication parameters, probe designs, and delivery methods, resulting in inconsistent and sometimes conflicting neurophysiological and clinical outcomes in both preclinical and human studies (\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). In this context, recent studies have demonstrated that low-intensity tUS reduces GABAA-ergic short intracortical inhibition (SICI), with the effect scaling linearly with sonication duration and duty cycle (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Conversely, other reports have shown increased cortical excitability following prolonged sonication (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Moreover, although no severe adverse events have been reported, mild to moderate side effects occur in approximately 4% of healthy participants, including headache, mood or cognitive alterations, sleepiness, anxiety, and neck pain (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo address these limitations, we investigated the neuromodulatory potential of non-focused transcranial ultrasound targeting primary motor cortex (M1), delivered using the same parameters applied in routine cerebrovascular assessments \u0026ndash; a technique commonly referred to as Transcranial Colour Sonography (TCCS) or diagnostic ultrasound (dUS). Specifically, we first developed a computational model to estimate elastic wave propagation within brain tissue and characterize the differential engagement of M1 dynamics induced by non-focused transcranial ultrasound. Then, we evaluated changes in cortical excitability, measured by paired-pulse Transcranial Magnetic Stimulation (TMS), before and immediately after dUS in healthy subjects. Concurrently, we assessed vasomotor reserve to control for potential hemodynamic confounders that could bias neurophysiological readouts during insonation.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eHigh-Resolution computational model\u003c/h2\u003e \u003cp\u003eUltrasound wave propagation within the human head was assessed through numerical simulations, in which acoustic intensity (W/cm\u0026sup2;) was computed to quantify the magnitude of acoustic energy reaching the target region, defined as the M1. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e-A shows the simulated scenario.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA mock-up US probe was modelled to reproduce the technical specifications of the linear phased-array probe used in the experimental protocol (focal distance\u0026thinsp;=\u0026thinsp;25\u0026ndash;125 mm, size 25 \u0026times; 15 mm\u0026sup2;). Each element of the probe was modelled as a source of a sinusoidal acoustic wave at the fundamental frequency of 2 MHz. We used a realistic human anatomical model from the Virtual Population (ViP), i.e., Duke model (34-year-old, male) (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), which comprises 319 discretized tissues with acoustic properties assigned according to literature values (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). The M1 region was identified as a chain of cubic sensors (1 cm side length) positioned along the central sulcus profile, spanning the entire region of interest. Acoustic intensity was subsequently analysed on three pseudo-coronal cross-sections (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e-B). The scenario was simulated using the acoustic solver implemented in Sim4Life v.9.2. This solver was developed based on the Westervelt\u0026ndash;Lighthill Eq.\u0026nbsp;(20), extended by incorporating a density variation term to account for acoustic impedance differences between heterogeneous tissues. This yields the Linear Acoustic Pressure Wave Equation (LAPWE):\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\rho\\nabla\\bullet\\frac{1}{\\rho}\\nabla\\text{p}-\\frac{1}{{c}^{2}}\\frac{{\\partial}^{2}p}{\\partial{t}^{2}}-\\frac{\\stackrel{\\sim}{a}}{{c}^{2}}\\frac{\\partial p}{\\partial t}=0$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e\u0026#119901; is the pressure, \u0026#119888; denotes the speed of sound, \u0026#119905; is time, \u0026#120588; is mass density, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\stackrel{\\sim}{a}\\)\u003c/span\u003e\u003c/span\u003e is a factor describing absorption behaviour as a function of the absorption coefficient α (Np/m) and angular frequency ω. The Finite-Difference Time-Domain (FDTD) method solved the LAPWE, with Perfectly Matched Layers (PML) set as boundary conditions to prevent back-reflections.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eNeurophysiological study\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eHealthy volunteers with no history of neurological disorders were enrolled in the study. No subject was taking medications at the time of, or one month before, the inclusion in the study, and they all had suspended alcohol or caffeine consumption at least 48 h before. The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki, and the protocol was approved by the local Ethics Committee. Written informed consent was obtained from all participants prior to study inclusion. Also, the methodology and reporting of this study follow the guidelines for reporting non-randomised studies (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eExperimental protocol\u003c/h3\u003e\n\u003cp\u003ePatients underwent 30min of sonication delivered through the right trans-temporal window to target M1 using a linear probe (2.0 MHz). The diencephalic plane along the superior orbitomeatal line was used as the anatomical landmark throughout the procedure. The validity of the entire intervention was confirmed by the correct visualization of the entire ipsilateral middle cerebral artery. The same parameters employed in the transcranial diagnostic study were used (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Neurophysiological parameters, including SICI, intracortical facilitation (ICF), and long-interval intracortical inhibition (LICI), were assessed both before (T0) and immediately following (T1) the intervention, in both the hemispheres. Active stimulation was delivered over one hemisphere (stimulated hemisphere, SH), while sham stimulation over the contralateral hemisphere (control hemisphere, CH), with the order of treatment and the stimulated side pseudo-randomized across participants. A detailed description and timeline are provided in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. At the same time points (T0 and T1), vasomotor reserve (through breath-holding index - BHI) was evaluated in SH using the same probe delivering stimulation, to avoid potential confounding effects of changes in small vessel diameter and hemodynamic on paired-pulse TMS parameters. Although no adverse effects were expected being out dUS protocol in line with those routinely employed for patients (\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e), all participants were systematically monitored for adverse events throughout the experimental session. Adverse events were predefined as any unexpected or undesirable sign or symptom temporally associated with ultrasound exposure, including but not limited to headache, dizziness, nausea, visual disturbances, mood changes, cognitive alterations, fatigue, neck discomfort, or local skin irritation. Particular attention was paid to symptoms previously reported in human transcranial ultrasound studies (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Monitoring was conducted at three time points: I) immediately before the intervention (baseline screening), II) continuously during the 30-minute insonation period through direct clinical observation and spontaneous reporting, and III) immediately after the intervention through structured questioning. Participants were explicitly asked whether they experienced any new neurological, sensory, cognitive, or systemic symptoms during or after stimulation. Additionally, they were instructed to report any delayed symptoms occurring within the subsequent 24 hours.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003ePaired-pulse Transcranial Magnetic Stimulation\u003c/h3\u003e\n\u003cp\u003eElectromyographic (EMG) recordings were obtained by two standard nonpolarizable Ag/AgCl surface electrodes (diameter 9 mm; Technomed Europe\u0026reg;), one placed over the belly of the abductor digiti minimi (ADM) muscle, either left or right, and the other over its distal tendon. A Magstim Super Rapid Transcranial Magnetic Stimulator (Magstim Company, Dyfed, UK, 2.2 T maximum field output), connected to a figure-of-eight coil was used (outer diameter 70.0 mm). The coil was held to induce a current in the lateral\u0026ndash;posterior to medial\u0026ndash;anterior direction in the brain, approximately 45\u0026deg; from the sagittal plane (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). The M1 contralateral to the recording site was determined as the point that produced the largest and most consistent motor evoked potential (MEP). The optimal coil position to elicit a reliable MEP was marked on the scalp to ensure identical placement of the coil throughout the experiment (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Resting motor threshold (RMT) was preliminary assessed for each patient and it is defined as the minimum stimulator output that induces MEPs of more than 50 \u0026micro;V in at least five out of ten trials when a muscle is completely relaxed, starting from 35% and upgrading by incremental steps of 3% (\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). As concerns paired pulse TMS, we adopted the original protocol proposed and described by Kujirai and colleagues (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). SICI and ICF were obtained at rest with a subthreshold conditioning stimulus (CS) followed by a suprathreshold test stimulus (TS) at an interstimulus interval (ISI) of 3.0 and 12.0 ms, respectively. TS was set at an intensity of 130% RMT. The CS were set at 70% of the RMT, corresponding at about 90% of the active motor threshold (AMT) (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Although an influence of short intracortical facilitation (SICF) on SICI cannot be ruled out, this contamination occurs at intervals typically sparing the ISI of 3.0 ms and with stimulus intensities higher than those used here (ISI \u0026sim; 4.5 ms and S1 intensity\u0026thinsp;\u0026gt;\u0026thinsp;90% AMT) (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). LICI was then assessed by delivering two stimuli (CS and TS) with the same intensity (130% RMT) and assuming an ISI of 150.0 ms. This value avoids paradoxical facilitation as reported to occur for both lower and higher ISIs, especially when stimulating the dominant hemisphere (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). For each SICI and ICF measure, 10 consecutive paired-pulse TMS pulses were administered randomly every 6-8s to secure reproducible traces, whereas 20 consecutive pulses were delivered to obtain LICI (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). SICI reflects GABAA receptor-mediated fast inhibitory post-synaptic potentials (IPSPs) in corticospinal neurons, while ICF reflects glutamatergic signalling and LICI depends on slow IPSPs mediated through GABAB receptors (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). For paired-pulse recordings, full muscle relaxation was ensured by providing the subjects with audio-visual feedback of the raw EMG at high gain (microV).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAssessment of the Vasomotor Reserve\u003c/h2\u003e \u003cp\u003eThe experiments were conducted using a DWL Multi-Dop X4 transcranial Doppler (TCD) system, with subjects positioned comfortably in the supine posture. Pulsed-wave Doppler probes (2 MHz) were secured over the right transtemporal window employing a dedicated probe holder and fixation device. Optimal insonation of the middle cerebral artery (MCA) was achieved at a depth ranging from 45 to 58 mm. The proprietary software integral to the DWL system enabled continuous recording of mean blood flow velocity in insonated arteries during baseline and breath-holding protocols. Baseline measurements were defined as the stable mean flow velocity recorded during the final 3 minutes of an initial 10-minute resting period. The breath-holding challenge, designed to elicit cerebral vasomotor reactivity, involved instructing subjects to sustain breath-holding for 30 seconds. Velocity data were analysed offline. No adverse effects were reported during the breath-holding manoeuvre. Cerebrovascular reactivity was quantified using the breath-holding index (BHI), calculated as the percentage increase in mean cerebral blood flow velocity during breath-holding relative to baseline, normalized by the duration of breath-holding. Specifically, BHI was computed as: [(mean flow velocity at the end of breath-holding\u0026thinsp;\u0026minus;\u0026thinsp;mean flow velocity at rest) / mean flow velocity at rest] \u0026times; 100 / duration of breath-holding (30 seconds) (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eMEP amplitudes were measured peak to peak. The MEP amplitudes evoked by paired-pulse stimulation were expressed as a percentage of the mean MEP amplitude of test stimulus (TS) alone for SICI and ICF, whereas when evaluating LICI the MEPs following TS were compared to MEPs as induced by CS. Normal distributions of the dependent variables (RMT, ICF, SICI, LICI and BHI) were assessed using the Shapiro-Wilk test for normality (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). Since most of them did not pass the test (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), non-parametric statistical analysis was applied. As within analysis, Wilcoxon signed-rank test was applied for each of the two hemispheres (SH and CH) to disclose significant changes in times (T0 vs T1). As between analysis, changes in variation of outcomes (∆, calculated as: ∆ score\u0026thinsp;=\u0026thinsp;T1 score\u0026thinsp;\u0026minus;\u0026thinsp;T0 score) were assessed through Wilcoxon signed-rank test since we considered the hemispheres as coming from the same tested population. Also, we performed one-sample Wilcoxon test comparing the ratio of each ∆ (ratio = ∆ score in SH / ∆ score in CH) with a median\u0026thinsp;=\u0026thinsp;1, to verify whether the ratio was inferior (one-tailed test). Given the limited sample size and the derived nature of ratios, these analyses were considered as only exploratory. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant for all analyses, except for one-sample Wilcoxon test (p\u0026thinsp;=\u0026thinsp;0.025). In all analyses, effect sizes were quantified using the paired rank-biserial correlation (r\u003csub\u003erb\u003c/sub\u003e), with 95% confidence intervals.\u003c/p\u003e \u003cp\u003eGiven the limited sample size, Bayesian statistics were additionally applied to corroborate the classical, frequentist, non-parametric findings (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). The Bayesian approach allows distinguishing between an absence of evidence and evidence of absence, by quantifying the relative likelihood of the alternative and null hypotheses in explaining the observed data. Evidence is expressed on a continuous scale through the Bayes Factor (BF), which represents the ratio between the likelihood of a model including the tested effect and that of the null model (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Accordingly, Bayesian Wilcoxon signed-rank tests and Bayesian one-sample Wilcoxon tests were performed. Evidence was interpreted following standard criteria: BF\u0026thinsp;\u0026gt;\u0026thinsp;3 was considered moderate and BF\u0026thinsp;\u0026gt;\u0026thinsp;10 strong evidences in favour of the alternative hypothesis, whereas BF\u0026thinsp;\u0026lt;\u0026thinsp;1/3 and BF\u0026thinsp;\u0026lt;\u0026thinsp;1/10 indicated moderate and strong evidence in favour of the null hypothesis, respectively. Values within 1/3\u0026thinsp;\u0026lt;\u0026thinsp;BF\u0026thinsp;\u0026lt;\u0026thinsp;3 were regarded as inconclusive evidence. Data were analysed using JASP version 0.16.3 for Windows (JASP Team, 2022).\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eComputational estimations\u003c/h2\u003e \u003cp\u003eResults were evaluated in terms of acoustic intensity, defined as the acoustic energy propagating through a unit surface per unit time. Analysis of the intensity distribution into the whole volume of M1 revealed that 65% and 26% of the data exceeded 50% and 70% of the local maximum, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e-A). Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e-B shows the normalized acoustic intensity distributions extracted from three pseudo-coronal slices within the M1 region, revealing ultrasound propagation patterns affecting the M1.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eNeurophysiological outcomes\u003c/h2\u003e \u003cp\u003eSixteen healthy volunteers (mean age\u0026thinsp;\u0026plusmn;\u0026thinsp;SD: 31.88\u0026thinsp;\u0026plusmn;\u0026thinsp;10.99 years, 7 F) were enrolled. No adverse events were reported during the insonation procedure or at post-stimulation assessment. No participant discontinued the experiment due to discomfort, and no delayed adverse effects were communicated during the follow-up period. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows exemplificative traces recorded from the same subject, before and after sonication, from either SH or CH.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs for within analysis, Wilcoxon signed-rank test disclosed a significant modulation of SICI in the SH (z\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;2.38, p\u0026thinsp;=\u0026thinsp;0.016; r\u003csub\u003erb\u003c/sub\u003e = -0.68 95% CI [-0.88, -0.26]), with no changes in the CH (p\u0026thinsp;=\u0026thinsp;0.856). Bayesian analysis supported this finding, showing moderate-to-strong evidence for the SH (strong Bayesian evidence for the alternative hypothesis, BF₁₀ = 7.65), and anecdotal evidence for the CH (anecdotal Bayesian evidence for the null hypothesis, BF₁₀ = 0.257) (see Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e-A). Similarly, LICI significantly increased in CH from T0 to T1 (z\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;2.59, p\u0026thinsp;=\u0026thinsp;0.010 r\u003csub\u003erb\u003c/sub\u003e = -0.74 95% CI [-0.91, -0.37]; strong Bayesian evidence for the alternative hypothesis, BF₁₀ = 7.88), whereas no significant difference was detected in the SH (p\u0026thinsp;=\u0026thinsp;0.213; anecdotal Bayesian evidence for the null hypothesis, BF₁₀ = 0.546) (see Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e-B). No significant pre-post differences were found for RMT, BHI or ICF in either hemisphere (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05; anecdotal-to-moderate evidence for the null hypothesis, BF₁₀ \u0026lt; 1). Detailed median (IQR) values and test statistics are reported in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eNeurophysiological results for T0 and T1 assessments.\u003c/b\u003e Values are reported as median\u0026thinsp;\u0026plusmn;\u0026thinsp;IQR.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eStimulated Hemisphere\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eWithin analysis*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eControl Hemisphere\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e \u003cp\u003eWithin analysis*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT0\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ez\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003epValue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBF\u003csub\u003e10\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eT0\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ez\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003epValue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eBF\u003csub\u003e10\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRMT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e46\u0026thinsp;\u0026plusmn;\u0026thinsp;13.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e47\u0026thinsp;\u0026plusmn;\u0026thinsp;12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e46.5\u0026thinsp;\u0026plusmn;\u0026thinsp;8.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e46.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSICI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e65\u0026thinsp;\u0026plusmn;\u0026thinsp;29.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e67.5\u0026thinsp;\u0026plusmn;\u0026thinsp;49.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e7.65\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e62\u0026thinsp;\u0026plusmn;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e64\u0026thinsp;\u0026plusmn;\u0026thinsp;21.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eICF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e151\u0026thinsp;\u0026plusmn;\u0026thinsp;73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e156.5\u0026thinsp;\u0026plusmn;\u0026thinsp;61.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e163\u0026thinsp;\u0026plusmn;\u0026thinsp;65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e165\u0026thinsp;\u0026plusmn;\u0026thinsp;83.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLICI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e89\u0026thinsp;\u0026plusmn;\u0026thinsp;23.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e75\u0026thinsp;\u0026plusmn;\u0026thinsp;18.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e54\u0026thinsp;\u0026plusmn;\u0026thinsp;17.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e86\u0026thinsp;\u0026plusmn;\u0026thinsp;13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-2.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e7.88\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBHI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003eRMT\u0026thinsp;=\u0026thinsp;resting motor threshold; SICI\u0026thinsp;=\u0026thinsp;short-interval intracortical inhibition; ICF\u0026thinsp;=\u0026thinsp;intracortical facilitation; LICI\u0026thinsp;=\u0026thinsp;long-interval intracortical inhibition; BHI\u0026thinsp;=\u0026thinsp;breath-holding index. *pValue refers to Wilcoxon signed-rank test (significance at 0.05), BF\u003csub\u003e10\u003c/sub\u003e refers to Bayesian Wilcoxon signed-rank test.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs for between analysis, Wilcoxon signed-rank test revealed a significant difference in ΔSICI values, being higher in the SH compared with the CH (z\u0026thinsp;=\u0026thinsp;2.01, p\u0026thinsp;=\u0026thinsp;0.046; r\u003csub\u003erb\u003c/sub\u003e = 0.57 95% CI [0.09, 0.84], moderate Bayesian evidence for an inter-hemispheric difference, BF₁₀ = 3.91), and in ΔLICI values, being greater in the CH compared with the SH (z = -2.45, p\u0026thinsp;=\u0026thinsp;0.015; r\u003csub\u003erb\u003c/sub\u003e = -0.70 95% CI [-0.89, -0.30], strong Bayesian evidence for an inter-hemispheric difference, BF₁₀ = 10.06) (see Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e-C). No significant differences were found between hemispheres for ΔRMT and ΔICF (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05; anecdotal-to-moderate evidence for the null hypothesis, BF₁₀ \u0026lt; 1). Detailed median (IQR) values and test statistics are reported in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eNeurophysiological results for Δ = (T1 \u0026ndash; T0).\u003c/b\u003e Values are reported as median\u0026thinsp;\u0026plusmn;\u0026thinsp;IQR.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eHemisphere\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eBetween analysis*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ez\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003epValue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBF\u003csub\u003e10\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eΔ RMT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eΔ SICI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e19.5\u0026thinsp;\u0026plusmn;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;48.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.046\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e3.90\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eΔ ICF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e24\u0026thinsp;\u0026plusmn;\u0026thinsp;70.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e9.5\u0026thinsp;\u0026plusmn;\u0026thinsp;55.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eΔ LICI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-20\u0026thinsp;\u0026plusmn;\u0026thinsp;27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e32\u0026thinsp;\u0026plusmn;\u0026thinsp;33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.015\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e10.06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eRMT\u0026thinsp;=\u0026thinsp;resting motor threshold; SICI\u0026thinsp;=\u0026thinsp;short-interval intracortical inhibition; ICF\u0026thinsp;=\u0026thinsp;intracortical facilitation; LICI\u0026thinsp;=\u0026thinsp;long-interval intracortical inhibition; SH\u0026thinsp;=\u0026thinsp;stimulated hemisphere; CH\u0026thinsp;=\u0026thinsp;control hemisphere. *pValue refers to Wilcoxon signed-rank test (significance at 0.05), BF\u003csub\u003e10\u003c/sub\u003e refers to Bayesian Wilcoxon signed-rank test.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs for the analysis on Δ\u0026rsquo;s ratio, one-sample Wilcoxon test showed that RMT and LICI ratio values were significantly lower than 1 (V\u0026thinsp;=\u0026thinsp;3, p\u0026thinsp;=\u0026thinsp;0.021; r\u003csub\u003erb\u003c/sub\u003e = -0.83 95% CI [\u0026minus;\u0026infin;, -0.5] and V\u0026thinsp;=\u0026thinsp;17, p\u0026thinsp;=\u0026thinsp;0.004; r\u003csub\u003erb\u003c/sub\u003e = -0.75, 95% CI [\u0026minus;\u0026infin;, -0.5], respectively), with anecdotal Bayesian evidence for a reduction in RMT ratio (BF₁₀ = 0.83) and moderate Bayesian evidence for the null hypothesis in LICI ratio (BF₁₀ = 0.31). No significant differences were found for ICF ratio (p\u0026thinsp;=\u0026thinsp;0.126; moderate Bayesian evidence for the null hypothesis, BF₁₀ = 0.20) and SICI ratio (p\u0026thinsp;=\u0026thinsp;0.047; moderate Bayesian evidence for the null hypothesis, BF₁₀ = 0.19). Detailed median (IQR) values and test statistics are reported in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eNeurophysiological results for ratios = (Δ SH / Δ CH).\u003c/b\u003e Values are reported as median\u0026thinsp;\u0026plusmn;\u0026thinsp;IQR.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003emedian\u0026thinsp;\u0026plusmn;\u0026thinsp;IQR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eone-sample Wilcoxon test *\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003epValue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBF\u003csub\u003e10\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eratio RMT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.021\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.83\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eratio SICI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eratio ICF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eratio LICI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.31\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eRMT\u0026thinsp;=\u0026thinsp;resting motor threshold; SICI\u0026thinsp;=\u0026thinsp;short-interval intracortical inhibition; ICF\u0026thinsp;=\u0026thinsp;intracortical facilitation; LICI\u0026thinsp;=\u0026thinsp;long-interval intracortical inhibition. *pValue refers to one-sample Wilcoxon test (one-tailed test), significance at 0.025, BF\u003csub\u003e10\u003c/sub\u003e refers to Bayesian Wilcoxon signed-rank test.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eTo our knowledge, this is the first study demonstrating that acoustic waves, delivered using parameters and bone windows identical to those routinely employed in dUS (\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e), can modulate cortical excitability in healthy subjects. Importantly, this work integrates computational acoustic modelling with in vivo neurophysiological measurements, bridging engineering-based exposure characterization and functional cortical readouts.\u003c/p\u003e \u003cp\u003eOur results reveal a robust attenuation of SICI, a neurophysiological marker predominantly driven by the GABAAergic inhibitory system (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e), leading to a net excitation of cortical circuits. This modulatory phenomenon transcends indirect vascular effects, as confirmed by the lack of meaningful changes in vasomotor reactivity, supporting the interpretation that the observed modulation reflects a direct neural effect rather than purely vascular mechanisms. Overall, the observed effect of enhanced cortical excitability fits with recent studies employing slightly different tUS protocols, specifically delivering stimulation in a theta burst pattern (\u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Another noteworthy finding is the reduction of LICI observed in the CH, resulting in an increased MEP amplitude during the LICI protocol. This effect, confirmed by both within- and between-subject analyses, is unlikely to be explained solely by nonspecific mechanical or thermal effects, given the selectivity of the observed neurophysiological changes. A possible explanation is that reduced inhibition in the SH, indicated by a significant decline in SICI, triggers compensatory responses in the contralateral cortex through interhemispheric balance (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). This hypothesis is supported by the fact that transcallosal interhemispheric connections are predominantly GABA-B-mediated, mirroring the mechanisms underlying LICI (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). These results are unlikely to stem from methodological bias, such as LICI contamination by excitatory processes, since such effects are typically excluded at the interstimulus intervals used here (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). The lack of analogous effects on SICI upon evaluation of the contralateral M1 provides additional confirmation of the spatial specificity of our stimulation protocol and the associated computational model. This constitutes a rigorous experimental control, as these assessments were performed on the same subjects, during the same experimental session, and under identical methodological conditions. However, the present findings should be interpreted primarily as a mechanistic proof-of-concept rather than as evidence of clinical efficacy. Indeed, although the convergence between neurophysiological changes and computational modelling of acoustic propagation supports the biological plausibility of a direct cortical effect within the insonated region, the study was conducted in healthy volunteers without behavioural or therapeutic outcomes. Therefore, while providing a physiological validation, the clinical relevance, durability, and functional impact of such modulation remain to be established.\u003c/p\u003e \u003cp\u003eWhile two antecedent studies partially intersect with our investigation (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e), they fall short of capturing the comprehensive scope of our work. Guerra et al. demonstrated that acoustic stimuli, delivered trans-temporally as in dUS, exert no modulation upon brainstem reflexes; although their computational models of elastic wave propagation yield valuable theoretical insights, direct assessment of cortical excitability remained unexplored (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). Conversely, Gibson and colleagues reported changes in MEP amplitudes using dUS probes; however, their study did not leverage paired-pulse TMS protocols to disentangle cortical inhibitory/excitatory dynamics nor implement computational models to characterize wave propagation (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Their approach also diverged anatomically, targeting the M1 region covered by significantly thicker cranial bone, in contrast to our focused application on the trans-temporal acoustic window (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Finally, our findings may also align with previous clinical observations reporting transient motor improvements during prolonged trans-temporal insonation in patients with acute ischemic stroke undergoing systemic thrombolysis (sonothrombolysis) (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e). While large trials and meta-analyses indicate that sonothrombolysis is safe, its functional benefits appear short-lived and more evident in younger patients. These data may be consistent with acute ultrasound-induced modulation of cortical excitability in the affected hemisphere, in addition to the established mechanical disruption of the fibrin clot (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study presents some limitations. First, the relatively small sample size of healthy participants warrants expansion in future research. For example, the ratio analyses showed partial divergence between frequentist and Bayesian approaches, with statistically significant p-values not consistently accompanied by Bayes factors supporting the alternative hypothesis. Such discrepancies, particularly in small samples, suggest that these findings should be interpreted as exploratory. Second, the representation of intrinsic hand muscles at the M1 level does not fully align with the conventional trans-temporal window. Nonetheless, the computational model, an investigation used to further inform on neuromodulatory effects of physical forces applied to central nervous system (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e), supports the plausibility of efficient elastic wave propagation to the M1. The specific modulation of parameters such as SICI and ICF, coupled with the absence of changes in the CH, confirms the spatial specificity of our protocol. Lastly, unlike measures such as the RMT, cortical excitability indices (SICI, ICF, and LICI) reflect the activity of widely distributed neural networks rather than focal cortical regions.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eIn this study, we provide mechanistic evidence that trans-temporal dUS can modulate intracortical inhibitory circuits in healthy individuals. The spatial specificity supported by computational modelling, together with the absence of significant vascular changes or effects in the control hemisphere, strengthens the biological plausibility of a direct cortical effect under conventional sonographic parameters. These findings should be interpreted as a physiological proof-of-concept in healthy subjects. Whether such modulation translates into meaningful functional or clinical effects remains to be determined in controlled studies involving patient populations and behavioural outcomes. Future studies will be required to define durability of effects, and potential translational relevance.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAMT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eActive Motor Threshold\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBHI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBreath\u0026ndash;Holding Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eControl Hemisphere\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConditioning Stimulus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003edUS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDiagnostic Ultrasound\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFUS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFocused Ultrasound\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGABA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGamma\u0026ndash;Aminobutyric Acid\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIntracortical Facilitation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eISI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterstimulus Interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLICI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLong\u0026ndash;Interval Intracortical Inhibition\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eM1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePrimary Motor Cortex\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMCA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMiddle Cerebral Artery\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMEP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMotor Evoked Potential\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRMT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eResting Motor Threshold\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStimulated Hemisphere\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSICI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eShort\u0026ndash;Interval Intracortical Inhibition\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSICF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eShort\u0026ndash;Interval Intracortical Facilitation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTMS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTranscranial Magnetic Stimulation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTest Stimulus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003etUS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTranscranial Ultrasound\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUltrasound\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e \u003cp\u003eThe study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki, and the protocol was approved by the local Ethics Committee. Written informed consent was obtained from all participants prior to study inclusion.\u003c/p\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not‑for‑profit sectors.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization: T.B., S.A.; Data curation: M.G., S.A., T.B.; Formal analysis: M.G., S.M., S.G., M.P.; Investigation: T.B., S.A., S.G., M.P.; Methodology: T.B., M.P.; Supervision: T.B., A.P.; Visualization: M.G., S.G., M.P., E.G.; Writing \u0026ndash; original draft: M.G., T.B., S.G., M.P.; Writing \u0026ndash; review \u0026amp; editing: M.G., S.A., S.G., M.P., E.C., A.DG., S.M., N.M., M.B., A.P., T.B. All authors read and approved the submitted version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e \u003cp\u003eThe authors wish to thank ZMT Zurich MedTech AG (www.zmt.swiss) for providing the simulation software Sim4Life.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eQuarato CMI, Lacedonia D, Salvemini M, Tuccari G, Mastrodonato G, Villani R, et al. A Review on Biological Effects of Ultrasounds: Key Messages for Clinicians. 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Sci Data 27 marzo. 2025;12(1):516. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41597-025-04886-0\u003c/span\u003e\u003cspan address=\"10.1038/s41597-025-04886-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"journal-of-neuroengineering-and-rehabilitation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jner","sideBox":"Learn more about [Journal of NeuroEngineering and Rehabilitation](http://jneuroengrehab.biomedcentral.com/)","snPcode":"12984","submissionUrl":"https://submission.nature.com/new-submission/12984/3","title":"Journal of NeuroEngineering and Rehabilitation","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"NIBS, non-invasive brain stimulation, ultrasound, diagnostic ultrasound, neuromodulation, cortical excitability, interhemispheric balance","lastPublishedDoi":"10.21203/rs.3.rs-9029217/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9029217/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eTranscranial ultrasound (tUS) represents a promising brain stimulation technique, yet its physiological effects using standard diagnostic protocols remain poorly characterized. This study examines the impact of conventional diagnostic ultrasound (dUS) on intracortical excitability.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eHealthy subjects received 30 minutes of transcranial ultrasound (2.0 MHz) over the right motor cortex. Cortical excitation and inhibition were assessed bilaterally via paired-pulse TMS, quantifying resting motor threshold (RMT), short intracortical inhibition (SICI), intracortical facilitation (ICF) and long intracortical inhibition LICI before and after stimulation. The vasomotor reserve (through the breath-holding index) was also assessed. A computational model was developed to confirm the spatial selectivity of our protocol. Non-parametric and Bayesian analyses were used.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSixteen healthy adults (mean age 31.9\u0026thinsp;\u0026plusmn;\u0026thinsp;11.0 years) were enrolled. dUS induced a significant reduction in SICI in the stimulated hemisphere (p\u0026thinsp;=\u0026thinsp;0.016; Bayes Factor BF\u0026thinsp;=\u0026thinsp;7.65), and a robust increase in LICI in the control hemisphere (p\u0026thinsp;=\u0026thinsp;0.010; BF\u0026thinsp;=\u0026thinsp;7.88). Between hemispheres, SICI was higher in the stimulated than in the control side (p\u0026thinsp;=\u0026thinsp;0.046; BF\u0026thinsp;=\u0026thinsp;3.90), while LICI was greater in the control hemisphere (p\u0026thinsp;=\u0026thinsp;0.015; BF\u0026thinsp;=\u0026thinsp;10.06). ICF, RMT and BHI showed no significant changes (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003edUS elicits focal changes in cortical excitability, towards an overall excitatory effect, in the absence of detectable vascular changes. The observed changes also engage compensatory transcallosal mechanisms, likely involving GABA-B-mediated pathways within the contralateral hemisphere. These findings provide mechanistic evidence supporting further translational investigation.\u003c/p\u003e","manuscriptTitle":"Diagnostic Ultrasound Modulates Human Motor Cortex: Neurophysiological Evidence from Paired-Pulse TMS and Computational Modelling","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-16 15:13:02","doi":"10.21203/rs.3.rs-9029217/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-30T17:46:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"155642850703212546003659081553166953279","date":"2026-04-09T12:53:35+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-08T17:44:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-05T08:15:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-05T08:11:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of NeuroEngineering and Rehabilitation","date":"2026-03-04T10:22:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-neuroengineering-and-rehabilitation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jner","sideBox":"Learn more about [Journal of NeuroEngineering and Rehabilitation](http://jneuroengrehab.biomedcentral.com/)","snPcode":"12984","submissionUrl":"https://submission.nature.com/new-submission/12984/3","title":"Journal of NeuroEngineering and Rehabilitation","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b84bf7de-c9bd-4177-ab33-057f89a5cba9","owner":[],"postedDate":"April 16th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-04-30T17:46:11+00:00","index":19,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-16T15:13:03+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-16 15:13:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9029217","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9029217","identity":"rs-9029217","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}