Postural modulation of prepulse inhibition and its link to postural control: Insights from healthy subjects

Postural modulation of prepulse inhibition and its link to postural control: Insights from healthy subjects | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Postural modulation of prepulse inhibition and its link to postural control: Insights from healthy subjects Matteo Ciocca, Sarah Hosli, Zaeem Hadi, Jingqi Hong, Yen Tai, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6528482/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract An unexpected loud sound typically triggers a reflex eye-blink. A reliable pre-warning attenuates reflex blinking, a phenomenon known as ‘pre-pulse inhibition’ (PPI). PPI is enhanced when standing, suggesting that PPI might contribute to adaptive postural control. Here, we tested whether PPI is modulated under different postural conditions and identifies the determinants of this modulation. Forty-five participants’ PPI and postural sway were tested while supine, standing on a hard surface, soft surface, and in tandem stance. The effect of visual feedback, auditory (aPPI) and somatosensory (sPPI) prepulse modalities, and different interstimulus-intervals were tested. Compared to hard-surface, PPI is attenuated by soft-surface and tandem standing (p < 0.0125). sPPI correlates with sway area during hard surface standing (ρ=+0.321; p = 0.032) and sway velocity on tandem standing (ρ=+0.344; p = 0.021). While both sPPI and aPPI are modulated, sPPI shows greater inhibition. Abolishing the visual feedback by closing the eyes only minimally reduces sPPI. PPI changes depending on postural demands, with less inhibition during tasks requiring enhanced balance control. This suggests that PPI network adjusts to regulate sensory inputs, enhancing inhibition to prevent sensory overflow when postural control is less demanding and reducing inhibition to increase sensory feedback as task difficulty increases. This study establishes a link between PPI and postural control, which opens the possibility to test PPI as a marker of postural control network activity under specific circumstances. Biological sciences/Neuroscience Biological sciences/Physiology prepulse inhibition blink reflex postural control sway balance control posturography Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Reviewing a paper while on a train or a bus requires the ability to maintain attentional focus despite environmental distractions. This ability relies on sensory gating, a neurophysiological mechanism that prevents sensory overload in the central nervous system by suppressing irrelevant stimuli 1 . Stronger sensory gating is associated with greater cognitive efficiency 2 , which may, in turn, improve the quality of the revision. This process involves pre-attentive neural mechanisms, primarily in the brainstem, thalamus, and cortex 3 . Prepulse inhibition (PPI), an operational measure of sensory gating, is a neurophysiological phenomenon in which a weak sensory stimulus reduces the R2 and R2c responses while facilitating the R1 response 4 . Inhibition has been observed across different sensory modalities - auditory, somatosensory, visual, and vestibular 1 , 5 . Interestingly, recent findings suggest that PPI may also play a role in postural control, with research indicating enhanced somatosensory PPI (sPPI) when standing 6 . This connection between sensory gating and postural control has led to two primary hypotheses. The first, the “peripheral feedback” hypothesis, suggests that greater reliance on visual feedback for postural stability enhances PPI by reducing orbicularis oculi activation 7 . The second, the “central tuning” hypothesis, posits that cortical control of key structures shared by the PPI and postural control networks modulates PPI. This cortical modulation of PPI is mediated through structures such as the pedunculopontine nucleus (PPN), which plays a key role in postural control, by modulating inputs from the periphery and filtering the ascending inflow to the thalamus 8 . The PPN-thalamic pathway is particularly relevant in postural control, as its activity is directly associated with increased postural sway, a well-recognised risk factor for falls 9 . Additionally, the PPN is thought to enhance PPI by dynamically modulating somatosensory feedback, facilitating the adaptation of postural control to environmental demands 6 . Despite these initial observations, the precise mechanisms through which postural control modulates PPI remain unclear. This paper addresses some uncertainties surrounding PPI and its role in postural control. We hypothesise that PPI participates in adaptive postural control and predict that sPPI modulation is linked to measures of static balance. Furthermore, we hypothesise that peripheral sensory feedback influences sPPI when standing and predict that sPPI will be reduced when one of the peripheral sensory inputs is perturbed, as less sensory filtering is required to maintain balance control. Finally, we propose that postural modulation of PPI is centrally modulated and inherently structured within the network. Therefore, we expect it to be independent of prepulse relevance and to vary only with ISIs reflecting the integration of the prepulse in the PPN. Results All participants completed the experiments without any adverse effects. Preliminary Experiments: input-output curve for sPPI Data for Preliminary Experiment 1 and 2 are in Supplementary Tables 1 and 2, and Fig. 1 . In Preliminary Experiment 1, we compared the amount of sPPI for ISI from 70 ms to 120 ms. A one-way ANOVA showed no difference in R1 amplitude (F(7.120) = 1.667, p = 0.124, Cohen’s f = 0.19). However, statistically significant differences were observed for R2 (F(7,120) = 4.347, p = 0.0002, Cohen’s f = 0.427), and R2c area (F(7,120) = 3.698, p = 0.001, Cohen’s f = 0.384). Post-hoc analysis revealed statistically significant differences among unconditioned and conditioned stimuli at ISI 110 ms (p = 0.000123) for both R2 and R2c area. In Preliminary Experiment 2, we compared sPPI for ISIs 110, 200, 400, 600 ms. There was no difference in R1 amplitude (F(4, 65) = 0.373, p = 0.827; Cohen’s f = 0). Statistically significant differences were found in R2 area (F(4, 65) = 5.598, p = 0.001; Cohen’s f = 0.5125), with post-hoc analysis showing statistically significant differences at ISI 110 ms (p = 0.003), 200 ms (p = 0.004), and 400 ms (p = 0.002). A trend towards an inhibition was observed in R2c area (F(4, 65) = 3.316, p = 0.016; Cohen’s f = 0.3637), with strongest inhibition at ISI 110 (p = 0.027) and ISI 200 ms (p = 0.024). Strong inhibition at ISI 110 ms was consistent across experiments (R2 area inhibition: 32.21% in Preliminary Experiment 1, 27.58% in Preliminary Experiment 2; R2c area inhibition: 32.55% in Preliminary Experiment 1, 28.66% in Preliminary Experiment 2). A paired t-test compared 12 subjects who participated in both experiments, showing no significant difference in PPI at ISI 110 ms between Preliminary Experiment 1 (mean 36.33%; SD = 20.10) and Preliminary Experiment 2 (mean 28.38%; SD = 15.58) [t(11) = -1.457, p = 0.173] (See Supplementary Fig. 1). Therefore, ISI 110 ms was selected for the main experiments with a somatosensory prepulse. Main Experiment 1- PPI modulation under different postural conditions In this experiment, we initially compared latencies and the amount of sPPI at ISI 110 ms in four different postural conditions: supine, HS-EO, SS-EO, and TS. Paired t-tests comparing unconditioned and conditioned R1, R2, and R2c latencies within each postural condition revealed no differences for R1 latency (Supplementary Table 3). However, conditioned R2 and R2c latencies were consistently longer than unconditioned latencies across all postural conditions (Supplementary Table 3). Comparing latency differences between supine and standing conditions showed no significant effects of postural changes (Supplementary Table 4). We then assessed whether blink reflex responses were modulated by postural conditions (Table 1 and Fig. 2 ). R1 amplitude showed no significant differences across conditions (F(3,176) = 0.068, p = 0.977, Cohen’s f = 0). However, R2 and R2c area inhibition varied significantly (R2: F(3,176) = 13.589, p < 0.0001, Cohen’s f = 0.458; R2c: F(3,176) = 6.869, p < 0.0005, Cohen’s f = 0.313). Post-hoc analysis showed significant differences between supine and HS-EO, HS-EO and SS-EO, and HS-EO and TS-EO for both R2 and R2c responses (Fig. 2 ). Then, to assess whether sPPI modulation correlates with sway parameters, we performed a Spearman correlation analysis (Supplementary Table 5, Fig. 3 ), which revealed significant positive correlations between sPPI and sway measures. Higher sPPI levels were associated with greater sway area on HS and higher sway velocity on TS. Subsequently, to compare the Spearman’s correlation coefficients of sway area and velocity between HS, and SS and TS, we applied Fisher’s Z-transformation to normalize the correlation values. Data are reported in Supplementary table 5. A two-tailed test resulted in a non-statistically significant difference between HS and SS for sway area (p = 0.204), and a trend towards a statistically significant difference with a reduction in correlation for sway velocity (p = 0.075). Similarly, a two-tailed test resulted in a non-statistically significant difference between Hs and TS for both sway area (p = 0.868) and velocity (p = 0.657). Main Experiment 2 – effect of visual feedback on postural PPI-modulation We investigate the effect of visual feedback (EO vs EC) on the R1 amplitude of R1 and R2/R2c area across postural conditions using repeated measures ANOVA. Means and standard deviations for latency differences, R1 amplitude, and R2/R2c area inhibition are in Table 2 . Table 2 visual and postural modulation of PPI for each blink reflex response . Mean changes and standard deviation in latency (ms) for R1, R2, and R2c are reported according to the presence (Eye opened) or absence (eyes closed) of visual feedback and according to the postural condition. Relative changes (%) and standard deviation for the R1 amplitude (mV) and R2 and R2c area (mV*ms) are reported. EO: eyes opened. EC: eyes closed. HS: hard surface; SS: soft surface. Mean Change (ms) Std. Deviation Percentage change (%) Std. Deviation R1 Latency R1 Amplitude Supine-EO + 0.0256 0.3049 Supine-EO + 36.18% 32.507 Supine-EC + 0.1250 0.5063 Supine-EC + 21.13% 40.655 HS-EO + 0.1122 0.3775 HS-EO + 35.11% 40.074 HS-EC + 0.1967 0.3856 HS-EC + 15.92% 25.011 SS-EO + 0.1106 0.5470 SS-EO + 42.68% 66.266 SS-EC + 0.1783 0.4083 SS-EC + 13.29% 25.195 R2 Latency R2 Area Supine-EO + 1.253 1.3664 Supine-EO -16.07% 9.77 Supine-EC + 1.335 2.0743 Supine-EC -19.80% 16.33 HS-EO + 1.286 1.6822 HS-EO -29.50% 14.91 HS-EC + 0.762 1.5538 HS-EC -25.52% 18.70 SS-EO + 1.318 2.3707 SS-EO -18.52% 14.41 SS-EC + 1.572 1.3885 SS-EC -16.18% 23.05 R2c Latency R2c Area Supine-EO + 1.5211 1.5310 Supine-EO -19.42% 7.47 Supine-EC + 0.6856 1.6388 Supine-EC -21.62% 20.10 HS-EO + 1.5950 1.5267 HS-EO -29.33% 10.21 HS-EC + 1.1506 1.7748 HS-EC -30.74% 18.49 SS-EO + 1.3817 3.8917 SS-EO -16.47% 9.08 SS-EC + 2.257 1.6237 SS-EC -17.17% 26.70 Visual feedback and postural conditions had no significant effect on R1, R2, or R2c latency (Supplementary Table 6). However, R1 amplitude was significantly larger with eyes open than eyes closed (p = 0.029; Table 2 , Supplementary Table 6, Supplementary Fig. 2). Neither postural conditions nor their interaction with visual feedback significantly influenced R1 amplitude. The effect of visual feedback on R2 and R2c areas was not significant. However, postural condition alone significantly influenced R2 and R2c inhibition. Post-hoc pairwise comparisons showed stronger inhibition on a hard surface compared to supine (R2: p = 0.005; R2c: p = 0.007) and soft surfaces (R2: p = 0.001; R2c: p = 0.001). Separate one-way ANOVA analyses confirmed significant differences in sPPI between supine and hard-surface standing with eyes open (F(2,54) = 4.389, p = 0.016, Cohen’s f = 0.345; R2: p = 0.02; R2c: p = 0.005). No significant differences were found for eyes-closed conditions (F(2,57) = 1.070, p = 0.350, Cohen’s f = 0.05), though a trend towards increased inhibition was observed (Table 2 , Supplementary Table 6, Supplementary Fig. 2). Pearson correlations between sPPI and sway velocity/area were not significant (Supplementary Table 7). Main Experiment 3 – effect of ISI on postural PPI-modulation For Experiments 3a and 3b, repeated measures ANOVA results and descriptive statistics are in Table 3 , Fig. 4 , and Supplementary Tables 8 and 9. Table 3 postural modulation of sPPI according to the ISIs deployed for each blink reflex response . Percentage changes (%) and standard deviation for R1, R2, and R2c are reported according to the specified ISI (80 ms vs 110 ms and 110 ms vs 200 ms) and according to the postural condition. HS: hard surface; SS: soft surface, TS: tandem standing. Percentage change (%) Std. Deviation Percentage change (%) Std. Deviation R1 Amplitude R1 Amplitude Supine 80 ms + 41.72% 33.67 Supine 110 ms + 39.75% 63.22 110 ms + 36.18% 33.39 200 ms + 31.86% 56.18 HS 80 ms + 19.61% 33.97 HS 110 ms + 32.25% 73.10 110 ms + 35.11% 41.17 200 ms + 30.41% 42.74 SS 80 ms + 38.59% 65.67 SS 110 ms + 18.15% 38.52 110 ms + 42.68% 68.08 200 ms + 36.74% 57.91 TS 80 ms + 13.69% 40.34 TS 110 ms + 36.06% 28.97 110 ms + 30.59% 49.83 200 ms + 47.50% 57.59 R2 Area R2 Area Supine 80 ms -10.54% 21.26 Supine 110 ms -19.71% 16.00 110 ms -16.10% 9.7 200 ms -37.06% 28.67 HS 80 ms -22.13% 12.63 HS 110 ms -35.79% 20.15 110 ms -27.27% 11.16 200 ms -43.37% 23.86 SS 80 ms -18.12% 14.98 SS 110 ms -18.01% 22.11 110 ms -18.52% 14.41 200 ms -37.61% 19.32 TS 80 ms -19.35% 26.11 TS 110 ms -22.31% 18.60 110 ms -13.58% 12.93 200 ms -31.16% 28.94 R2c Amplitude R2c Area Supine 80 ms -6.39% 25.04 Supine 110 ms -26.59% 26.62 110 ms -19.42% 7.47 200 ms -41.06% 33.11 HS 80 ms -18.96% 19.30 HS 110 ms -27.75% 25.66 110 ms -29.33% 10.21 200 ms -39.59% 24.76 SS 80 ms -19.17% 21.87 SS 110 ms -23.89% 26.66 110 ms -16.47% 9.08 200 ms -39.53% 24.45 TS 80 ms -17.19% 34.55 TS 110 ms -30.63% 23.80 110 ms -13.19% 12.05 200 ms -39.12% 23.57 Experiment 3a – comparing 80 ms vs 110 ms A significant latency difference was found between 80 ms and 110 ms ISIs (F(1,19) = 8.092; p = 0.010; Cohen’s f = 0.581). T-tests showed longer latency for 110 ms ISI in R2 (t = -2.149; p = 0.045) and R2c (t = -2.425; p = 0.025). Latency differences across postural conditions were not significant at either ISI. R1 amplitude modulation across postural conditions was not significant (F(1,18) = 1.143; p = 0.340; Cohen’s f = 0.08). ISI did not significantly affect R2 (F(1,18) = 1.582; p = 0.204; Cohen’s f = 0.17) or R2c area (F(1,18) = 2.407; p = 0.077; Cohen’s f = 0.265). Separate one-way ANOVA confirmed stronger sPPI at 110 ms ISI for both R2 (F(3,72) = 4.308; p = 0.007; Cohen’s f = 0.361) and R2c (F(3,72) = 9.129; p < 0.0001; Cohen’s f = 0.566). Post-hoc tests revealed stronger inhibition on a hard surface compared to supine (R2: p = 0.044; R2c: p = 0.019) and tandem standing (R2: p = 0.007; R2c: p < 0.0001). No significant differences were found for R2 (F(3,72) = 1.142; p = 0.338; Cohen’s f = 0.07) or R2c (F(3,72) = 0.993; p = 0.401; Cohen’s f = 0) at 80 ms ISI. Experiment 3b – comparing 110 ms vs 200 ms No significant latency differences were found between 110 ms and 200 ms ISIs for R1 (F(3,54) = 0.580; p = 0.631; Cohen’s f = 0), R2 (F(3,54) = 1.878; p = 0.144; Cohen’s f = 0.213), or R2c (F(3,54) = 2.509; p = 0.068; Cohen’s f = 0.122). The interaction between ISI and postural condition was not significant for R1 amplitude (F(3,54) = 1.307; p = 0.282; Cohen’s f = 0.126), R2 (F(3,54) = 2.458; p = 0.073; Cohen’s f = 0.275), or R2c areas (F(3,54) = 0.813; p = 0.492; Cohen’s f = 0). However, paired sample t-tests showed stronger inhibition with a 200 ms ISI in all postural conditions (Supplementary Table 9, Fig. 4 ). Main Experiment 4 – effect of prepulse modality on postural PPI-modulation We compared the latency of unconditioned and conditioned R1, R2, and R2c responses within each postural condition using paired t-tests. No significant difference was found for R1 latency. However, conditioned R2 and R2c latencies were consistently longer than unconditioned latencies across all postural conditions (Supplementary Table 10). Postural changes did not significantly affect these latency differences (Supplementary Table 11). We then examined the modulation of blink reflex responses across postural conditions, focusing on R1 amplitude and R2 and R2c area. One-way ANOVA showed no significant difference in R1 amplitude across postural conditions (F(3,79) = 0.929; p = 0.431; Cohen’s f = 0). Conversely, prepulse inhibition of R2 and R2c area varied significantly (R2: F(3,79) = 4.476; p = 0.006; Cohen’s f = 0.361; R2c: F(3,79) = 5.266; p = 0.002; Cohen’s f = 0.399). Post-hoc tests revealed significant differences for R2 between HS-EO and TS-EO (p = 0.006) and for R2c between HS-EO and SS-EO (p = 0.004) (Supplementary Table 12 and Fig. 5 ). A one-way ANOVA did not show any significant difference in the amplitude of R1 across different postural conditions (F(3,79) = 0.929, p = 0.431, Cohen’s f = 0). Conversely, prepulse inhibition of the R2 and R2c area is modulated across different postural conditions (R2: F(3,79) = 4.476, p = 0.006, Cohen’s f = 0.361; R2c: F(3,79) = 5.266, p = 0.002, Cohen’s f = 0. 399). A post-hoc analysis revealed a statistically significant difference between HS-EO and TS-EO for the R2 area (p = 0.006), and between HS-EO and SS-EO for the R2c area (p = 0.004) (see Fig. 5 ). Subsequently, we evaluated the effect of visual feedback (EO vs EC) on aPPI using repeated measures ANOVA. No significant differences were found in R1 amplitude (F(2,38) = 0.554; p = 0.579), R2 area (F(3,38) = 0.793; p = 0.460), or R2c area (F(2,38) = 1.715; p = 0.194). Finally, a Spearman correlation analysis revealed a significant positive correlation between aPPI and sway area in TS, with higher aPPI associated with greater sway area (Supplementary Fig. 3; Supplementary Table 13). Discussion In this study, we investigated the link between PPI and postural control. Our findings revealed that (a) PPI is modulated by postural conditions, with stronger inhibition when standing on HS. Notably, both sPPI and aPPI exhibit this modulation, though sPPI shows greater inhibition, suggesting PPI modulation is centrally regulated and it is only partially dependent on the prepulse modality. (b) PPI correlates with sway parameters. On HS and TS, sPPI positively correlates with sway area and velocity, indicating that greater sway is associated with stronger inhibition. A weaker correlation is observed between aPPI and sway during TS. (c) Peripheral sensory feedback perturbations reduce inhibition. Standing on SS or with EC reduces inhibition, with a greater reduction on SS, highlighting the role of sensory feedback in modulating PPI. (d) sPPI modulation is ISI-specific, peaking at 110 ms and disappearing by 200 ms, indicating time-dependent sensitivity in PPI modulation. These findings suggest that, similar to its role in attentional and cognitive processes, PPI might influence how we maintain balance and posture in a dynamic environment. The magnitude of inhibition varies across postural conditions, as previously observed 6 . Our study confirms this and further demonstrates that PPI modulation reflects the adaptability of sensorimotor integration within the postural control network. PPI likely prevents sensory overflow during less challenging tasks (e.g., standing on HS) and enhances peripheral feedback during more demanding tasks (e.g., standing on SS or TS). Neural activity within shared structures, such as the PPN and the caudal pontine reticular nucleus (CPRN), is critical in this process, with concurrent bottom-up and top-down control mechanisms. PPI modulation varies with sensory feedback perturbations, such as those affecting proprioceptive (e.g. SS and TS), or visual (e.g. EC) systems. In these conditions, reduced inhibition likely reflects decreased sensory filtering to maintain balance when peripheral inputs are disrupted 7 , 10 . This result is in line with previous data showing how the startle reflex is reduced when the afferent volley comes from the lower limbs, likely a “defensive” mechanism of the postural control network to guarantee balance control in challenging situations 6 , 7 . The correlation between PPI and sway parameters further suggests that PPI reflects activity within the postural control network. Notably, PPI correlates with sway when proprioceptive feedback remains intact but not when it is perturbed. This indicates that PPI primarily reflects proprioceptive feedback integration, highlighting the importance of proprioceptive inputs from muscles, joints, and cutaneous receptors 10 . The time-dependent nature of PPI modulation, observed at specific ISIs (80–110 ms), supports this interpretation, as it aligns with the temporal integration of proprioceptive feedback at cortical and subcortical levels 6 . However, the absence of PPI modulation at longer ISIs likely reflects central top-down mechanisms. This might indicate the involvement of structures modulating PPI, such as limbic structures 11 , which are less involved in regulating balance during quiet standing in young healthy subjects 12 . A top-down control mechanism is further supported by the observation that PPI is not modulated based on the relevance of the prepulse stimuli. Both sPPI and aPPI show a similar pattern of modulation, though the magnitude of inhibition is higher for sPPI than for aPPI. Thus, the PPI network’s response to postural changes appears to be inherently structured within the network and is not dependent on the relevance of the somatosensory prepulse. In summary, our results seem to support the coexistence of a central tuning hypothesis and a peripheral feedback hypothesis, which are mutually contributing to modulate PPI when balancing. The possible involvement of structures modulating PPI offers an alternative interpretation of our findings, particularly regarding task difficulty. On HS, participants with greater inhibition exhibited more sway. However, this task did not challenge the postural control network, as none of the participants reported feelings of instability or unsteadiness, although we did not specifically query this. We therefore infer that all participants maintained optimal postural control, with PPI potentially reflecting a form of “balance reserve”, where individuals with higher PPI might better adapt and reduce sway during more demanding tasks. This would align with the concept of “cognitive reserve” as representing the physiological robustness within the (postural control) brain network 13 , 14 . Nevertheless, we observed no correlation between changes in PPI from HS to TS and the corresponding changes in sway area and velocity. Consequently, this hypothesis cannot be fully supported. A significant limitation in this context is the lack of control for individual perception of task difficulty. Participants were not systematically interviewed about their perceived instability or the effort required to maintain postural control. Instead, we assumed that the transition from HS to TS posed an increased challenge for all participants, which may not have been uniformly true. Interestingly, correlation between PPI and sway parameters did not change between HS and TS, likely reflecting a physiological robustness within the postural control network, again potentially indicating a "balance reserve". Conversely, changes in correlation between sPPI and sway parameters may reflect a maladaptive response, where cognitively-driven mechanisms assume control over posture from automatic processes 15 . In this scenario, PPI may only reliably reflect postural control when subcortical automatic processes dominate. The reduction in correlation when transitioning from HS to SS supports this hypothesis. An important limitation to this interpretation is that we did not test PPI while participants were standing and concurrently performing a cognitive task. A dual-task paradigm would have allowed for a clearer understanding of whether cognitive control interferes with automatic postural processes and whether this results in a maladaptive response. The absence of such a challenge to cognitive processes in this study limits the ability to definitively assess whether higher cognitive demands affect PPI’s role in postural control. Further studies incorporating a dual-task approach and larger sample sizes are needed to clarify this relationship. PPI modulation may reflect attentional influences on the postural control network. The PPN and CPRN, which are critical in both networks, are primarily involved in automatic balance control. However, balance also requires attentional resources, particularly under challenging conditions 16 , 17 . Attention facilitates the integration of sensory inputs from visual, vestibular, and proprioceptive systems, which are crucial for maintaining stability 16 . When sensory inputs are limited, such as on SS or with EC, attentional resources are reallocated to process residual inputs and maintain balance 18 , 19 . When cognitive demands further rise, attentional resources may be diverted away from maintaining posture, potentially leading to compromised stability 17 . This is particularly evident in tasks requiring precise balance adjustments, such as TS or walking on unstable surfaces 19 . To this extent, excessive attentional focus on stabilising posture can disrupt compensatory neural responses, leading to increased instability 20 . This possibility is consistent with our findings of reduced PPI when sensory feedback (e.g., SS), visual input (e.g., EC), or vestibular feedback (e.g., TS) are disrupted, suggesting that attentional resources are redirected to managing these sensory challenges. PPI is sensitive to attentional modulation 21 , 22 . Increased attention to the prepulse enhances PPI, while shifting attention away diminishes it 21 , 22 . However, some studies report no PPI modulation under low-attention tasks 23 . Thus, under certain conditions, changes in PPI during different postural tasks could reflect attention-related modulation. Sensory feedback alteration (e.g., SS, EC) likely shifts attention towards balance maintenance, reducing PPI and potentially increasing sensory overflow, contributing to instability. Once again, one possible explanation is the involvement of PPI-modulating structures within the balance control network. During complex postural tasks, the automatic processes of balance control influence the PPI network by reducing sensory filtering, as the brain integrates residual proprioceptive, vestibular, and visual inputs to sustain stability. Data from PPI during EC conditions, standing on SS, and TS support this mechanism. However, when the postural task becomes extremely challenging, the balance control mechanism shifts from an automatic to cognitively driven processes, as observed in older adults with an age-related decline in balance and somatosensory function 15 , 24 . In this context, increased attentional load on the balance control network affects the PPI network similarly to when attention is focused away from the prepulse stimulus. This heightened attentional demand leads to decreased PPI, causing a sensory overflow and potentially contributing to increased sway. Excessive inhibition during such tasks could indicate the network’s reliance on attentional control to maintain stability, disrupting efficiency. Conclusion PPI participates in postural control by modulating the peripheral sensory feedback. It is conceivable that PPI might be used as a surrogate marker of activity within the postural control network, although further studies will need to confirm this possibility. Modulation of peripheral sensory feedback, particularly proprioceptive input, significantly influences PPI, underscoring its role as a marker of sensorimotor integration during standing. However, central modulation also plays a role, as evidenced by PPI’s independence from the prepulse type. This suggests that the PPI network’s response to postural changes is inherently structured within the network itself. Finally, further research is needed to elucidate how attention and task difficulty influence PPI and its relationship with balance control. Methods The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Ethics Committee of London Harrow (REC reference 21/LO/0112, date of approval 21/04/2021). Informed consent was obtained from all subjects involved in the study. Blink Reflex The electrically-elicited blink reflex was used in this study. Surface electrodes were used to deliver supraorbital nerve stimuli, with the cathode placed over the supraorbital notch and the anode positioned 3 cm away along the course of the nerve on the ipsilateral forehead. Percutaneous stimuli lasting 0.2 ms were applied to the right supraorbital nerve at irregular intervals of 25–30 seconds. The stimulus intensity was set at three times the R2 motor threshold, defined as the minimum stimulus intensity able to elicit a 50 uV baseline-to-peak amplitude in at least 4 out of 8 consecutive electromyographic (EMG) responses. The blink reflex response was recorded via EMG of the orbicularis oculi muscles. The active recording electrodes were positioned bilaterally on the lower eyelid, halfway between the inner and outer edges of the orbit, while the corresponding reference electrode was placed on the ipsilateral temple on each side. Amplification of the responses (x1000) was performed using a Digitimer D360R-4 device (Digitimer, Welwyn Garden City, UK). The signal was filtered using a frequency range of 30 Hz to 3 kHz. Data acquisition was carried out using Signal software, version 7.02 (Cambridge Electronic Devices, Cambridge, UK), and recorded on a laptop computer. For analysis, EMG traces were rectified, and all traces contaminated by EMG artifacts were discarded. Prepulse Inhibition Somatosensory stimuli: Conditioning somatosensory stimuli (prepulses) consisted of single pulses of electrical stimulation lasting 0.2 ms, delivered via bipolar electrodes to the sural nerve at the ankle. Specifically, the electrode placement was posterior to the lateral malleolus, secured in position using a Velcro strap. The intensity was set at twice the sensory threshold, defined as the minimum stimulus intensity perceived in at least 4 out of 8 consecutive stimuli, determined through both ascending and descending stepwise approaches. This intensity level was confirmed before each acquisition for every postural condition. Auditory stimuli: The auditory conditioning stimuli comprised a 500 Hz tone, lasting 20 microseconds, and with an intensity of 70 dB. These stimuli were administered bilaterally using a pair of headphones. Throughout the tasks, a background room noise of around 35–40 dB was consistently present. The tones were produced via a custom-made tone generator. Experimental Design Preliminary Experiments As data on the best ISI to evoke a consistent sPPI from the leg are scant in the literature, we initially set up an input-output curve exploring ISIs ranging from 70 to 120 ms in steps of 10 ms; in addition, we tested an ISI of 116 ms, as this was previously used by Versace et al. 6 . Therefore, a total of 7 conditions were tested in 16 young healthy subjects (10 females; aged 21–33) (Preliminary Experiment 1). Additionally, we expanded the investigations in the input-out curve for sPPI by investigating three longer ISIs, namely 200, 400 and 600 ms, and we ran a test-retest reliability protocol by retesting the ISI that in the first preliminary experiment showed the strongest inhibition. Therefore, a total of four conditions were tested in 14 young healthy subjects (8 females; aged 21–33) (Preliminary Experiment 2). Main Experiments Main Experiment 1 – PPI modulation under different postural conditions A total of 45 subjects (16 females; aged 21–40) participated in this experiment. The ISI indicating the strongest inhibition from preliminary experiments 1 and 2 (i.e. 110 ms) was used in this experiment. Subjects were tested in 4 different conditions: 1) supine – eyes open; 2) standing on hard surface – eyes open (HS-EO); 3) standing on soft surface – eyes open (SS-EO); and 4) standing on hard surface in tandem stance (TS). The order of testing was pseudorandom, as the supine condition was always tested first, followed by a standing condition randomly assigned using a randomisation list. For each postural condition, 5 unconditioned and 5 conditioned blink reflexes were acquired in a random order (total of 10 responses). Participants stood on a soft rectangular foam pad (50 × 41 × 6 cm, Airex) for the soft condition. In this experiment, postural control varies according to the different peripheral feedback in each condition. In the HS-EO condition, visual, proprioceptive, and vestibular input contributes to postural control. In the SS-EO condition, primarily visual and vestibular input contributes to postural control while the proprioceptive feedback is reduced. By using the tandem condition, we chose to minimise the antero-posterior oscillations, highlighting the medio-lateral sway 25 . Visual input mainly contributes to postural control when tandem standing, while both proprioceptive and vestibular input are perturbed. While acquiring sPPI in different postural conditions, we concomitantly measured static balance using a force platform. All subjects were asked to stand on a force platform with their arms hanging loosely by their sides, with heels 8 cm apart for the hard and soft-surface balance measure, and in the heel-to-toe position for the tandem standing. Area and velocity measures of sway were calculated for each condition, and were correlated with the amount of PPI for each subject. Main Experiment 2 – effect of visual feedback on postural PPI-modulation A total of 18 subjects (10 females; aged 21–37) participated in this experiment. Subjects were tested in a total of 6 different conditions: 1) supine – eyes open; 2) supine – eyes closed; 3) HS-EO; 4) hard surface – eyes closed (HS-EC); 5) SS-EO; and 6) soft surface – eyes closed (SS-EC). The order of testing was pseudorandom, as the supine condition was always tested first, followed by a standing condition randomly assigned using a randomisation list. For each condition, 5 unconditioned and 5 conditioned blink reflexes were acquired in a random order (total of 10 responses). Participants stood on a soft rectangular foam pad for the soft condition. Once again, we concomitantly measured static balance for each condition by means of postural sway using a force platform. Main Experiment 3 – effect of ISI on postural PPI-modulation In this experiment, we investigated whether sPPI modulation according to posture depends on the timing between the prepulse and the test pulse. We divided this experiment in two parts, namely 3a and 3b. In experiment 3a, we compared the optimal ISI (i.e. 110ms) against a shorter, suboptimal ISI of 80 ms. In experiment 3b, we compared the optimal ISI with a longer ISI of 200 ms. A total of 19 subjects (10 females; aged 21–37) participated in experiment 3a, while a total of 20 subjects (all males; aged 21–32) participated in experiment 3b. Experiment 4 – effect of prepulse modality on postural PPI-modulation A total of 20 subjects (10 females, aged 21–30) participated in this experiment. We run the same tests deployed in experiments 1 and 2 using an auditory prepulse and an ISI of 100 ms. Data analysis and statistics In all experiments, we measured latency of the R1, R2, and R2c responses, amplitude of R1, and area-under-the-curve (area) of the R2 and R2c components of the blink reflex in each single rectified trace in control and test trials. We then normalised the amount of inhibition for each subject, and we averaged the result per subject and per condition. We reported the percentage of facilitation/inhibition for the R1 and R2/R2c according to these formulas: for R1 \(\:\left(\frac{\text{R}1\text{c}\text{o}\text{n}\text{d}\text{i}\text{t}\text{i}\text{o}\text{n}\text{e}\text{d}\:\text{a}\text{r}\text{e}\text{a}}{\text{R}1\text{u}\text{n}\text{c}\text{o}\text{n}\text{d}\text{i}\text{t}\text{i}\text{o}\text{n}\text{e}\text{d}\:\text{a}\text{r}\text{e}\text{a}}-1\right)*100\) , for R2/R2c ( \(\:\frac{\text{R}2\text{c}\text{o}\text{n}\text{d}\text{i}\text{t}\text{i}\text{o}\text{n}\text{e}\text{d}\:\text{a}\text{r}\text{e}\text{a}}{\text{R}2\text{u}\text{n}\text{c}\text{o}\text{n}\text{d}\text{i}\text{t}\text{i}\text{o}\text{n}\text{e}\text{d}\:\text{a}\text{r}\text{e}\text{a}}-1)*100\) . A positive value reflects a facilitation, a negative value an inhibition. For experiments 1, an a-priori power analysis was conducted using G*Power version 3.1.9.6 26 to determine the minimum sample size required to test the study hypotheses. We based our power analysis on the amount of inhibition observed in the previous paper from Versace et al. 6 . Results indicated the required sample size to achieve 80% power for detecting a large effect, at a significance criterion of α = .05, was N = 48 for fixed effects one-way analysis of variance (ANOVA) test. Thus, the obtained sample size of N = 45 for experiment 1 is adequate to test the study hypotheses. Similarly, for Main Experiment 2 and 3, results indicated the required sample size to achieve 80% power for detecting a medium effect, at a significance criterion of α = .05, for repeated measure, within-between interaction ANOVA was N = 20 for Main Experiment 2, and N = 18 for Main Experiment 3. Thus, the obtained sample size of N = 20 is adequate to test the study hypotheses. We did not run a power-analysis for Main Experiment 4, but we recruited a number of subjects in line with Main Experiments 2 and 3. Homogeneity of variances was confirmed via Levene's test for equality of variances. Effect size was calculated by using Cohen’s f 27 . In case of a statistically significant main effect, Bonferroni corrected post-hoc tests were performed. For linear correlation analysis between sPPI of the ipsilateral R2 component and posturography data, specifically sway velocity and sway area, data distribution was first evaluated using the Shapiro-Wilk test, which revealed that sway data for the eyes-open condition were not normally distributed (p < 0.05. Consequently, a Spearman correlation was used. All statistical analyses were performed in SPSS version 26. Declarations Data Availability Statement The original contributions presented in this study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author(s). Author Contributions Conceptualization, M.C. and B.M.S.; Methodology, M.C.; Software, M.C. and Z.H.; Data Acquisition: M.C., J.H., and S.H.; Formal Analysis, M.C. and S.H.; Data Curation, M.C. and S.H.; Writing – Original Draft Preparation, M.C.; Writing – Review & Editing, M.C., Z.H, B.M.S; Supervision, Y.T. and B.M.S.; Project Administration, B.M.S.; Funding Acquisition, Y.T and B.M.S. Funding Funding received from the Medical Research Council (MRC) and the Jon Moulton Charity Trust, the Imperial NIHR Biomedical Research Centre, Imperial Health Charity, the US Department of Defense, the UK Ministry of Defence, and the Koetser Foundation for Brain Research. Conflict of Interest All co-authors have reviewed and approved the contents of the manuscript, and the submission is not under review at any other publication. The authors report no competing interests References Garcia-Rill, E. et al. Focus on the pedunculopontine nucleus. Consensus review from the May 2018 brainstem society meeting in Washington, DC, USA. Clin Neurophysiol 130 , 925-940, doi:10.1016/j.clinph.2019.03.008 (2019). Jones, L. A., Hills, P. J., Dick, K. M., Jones, S. P. & Bright, P. Cognitive mechanisms associated with auditory sensory gating. Brain Cogn 102 , 33-45, doi:10.1016/j.bandc.2015.12.005 (2016). Fendt, M., Li, L. & Yeomans, J. S. Brain stem circuits mediating prepulse inhibition of the startle reflex. Psychopharmacology (Berl) 156 , 216-224, doi:10.1007/s002130100794 (2001). Valls-Sole, J., Cammarota, A., Alvarez, R. & Hallett, M. Orbicularis oculi responses to stimulation of nerve afferents from upper and lower limbs in normal humans. Brain Res 650 , 313-316, doi:10.1016/0006-8993(94)91797-3 (1994). Ciocca, M. et al. Vestibular prepulse inhibition of the human blink reflex. Clin Neurophysiol 167 , 1-11, doi:10.1016/j.clinph.2024.08.008 (2024). Versace, V. et al. Influence of posture on blink reflex prepulse inhibition induced by somatosensory inputs from upper and lower limbs. Gait Posture 73 , 120-125, doi:10.1016/j.gaitpost.2019.07.194 (2019). Alvarez-Blanco, S., Leon, L. & Valls-Sole, J. The startle reaction to somatosensory inputs: different response pattern to stimuli of upper and lower limbs. Exp Brain Res 195 , 285-292, doi:10.1007/s00221-009-1784-7 (2009). Mena-Segovia, J. & Bolam, J. P. Rethinking the Pedunculopontine Nucleus: From Cellular Organization to Function. Neuron 94 , 7-18, doi:10.1016/j.neuron.2017.02.027 (2017). Muller, M. L. et al. Thalamic cholinergic innervation and postural sensory integration function in Parkinson's disease. Brain 136 , 3282-3289, doi:10.1093/brain/awt247 (2013). MacKinnon, C. D. Sensorimotor anatomy of gait, balance, and falls. Handb Clin Neurol 159 , 3-26, doi:10.1016/B978-0-444-63916-5.00001-X (2018). Schmajuk, N. A. & Larrauri, J. A. Neural network model of prepulse inhibition. Behav Neurosci 119 , 1546-1562, doi:10.1037/0735-7044.119.6.1546 (2005). Hall, K. J., Van Ooteghem, K. & McIlroy, W. E. Emotional state as a modulator of autonomic and somatic nervous system activity in postural control: a review. Front Neurol 14 , 1188799, doi:10.3389/fneur.2023.1188799 (2023). Stern, Y. What is cognitive reserve? Theory and research application of the reserve concept. J Int Neuropsychol Soc 8 , 448-460 (2002). Medaglia, J. D., Pasqualetti, F., Hamilton, R. H., Thompson-Schill, S. L. & Bassett, D. S. Brain and cognitive reserve: Translation via network control theory. Neurosci Biobehav Rev 75 , 53-64, doi:10.1016/j.neubiorev.2017.01.016 (2017). Kal, E. C., Young, W. R. & Ellmers, T. J. Balance capacity influences the effects of conscious movement processing on postural control in older adults. Hum Mov Sci 82 , 102933, doi:10.1016/j.humov.2022.102933 (2022). Takakusaki, K. Functional Neuroanatomy for Posture and Gait Control. J Mov Disord 10 , 1-17, doi:10.14802/jmd.16062 (2017). Barra, J., Auclair, L., Charvillat, A., Vidal, M. & Perennou, D. Postural control system influences intrinsic alerting state. Neuropsychology 29 , 226-234, doi:10.1037/neu0000174 (2015). Boisgontier, M. P. et al. Age-related differences in attentional cost associated with postural dual tasks: increased recruitment of generic cognitive resources in older adults. Neurosci Biobehav Rev 37 , 1824-1837, doi:10.1016/j.neubiorev.2013.07.014 (2013). Honeine, J. L., Crisafulli, O. & Schieppati, M. Body sway adaptation to addition but not withdrawal of stabilizing visual information is delayed by a concurrent cognitive task. J Neurophysiol 117 , 777-785, doi:10.1152/jn.00725.2016 (2017). Parr, J. V. V., Mills, R., Kal, E., Bronstein, A. M. & Ellmers, T. J. A "conscious" loss of balance: Directing attention to movement can impair the cortical response to postural perturbations. J Neurosci , doi:10.1523/JNEUROSCI.0810-24.2024 (2024). Thorne, G. L., Dawson, M. E. & Schell, A. M. Attention and prepulse inhibition: the effects of task-relevant, irrelevant, and no-task conditions. Int J Psychophysiol 56 , 121-128, doi:10.1016/j.ijpsycho.2004.11.006 (2005). Filion, D. L. & Poje, A. B. Selective and nonselective attention effects on prepulse inhibition of startle: a comparison of task and no-task protocols. Biol Psychol 64 , 283-296, doi:10.1016/s0301-0511(03)00077-2 (2003). De la Casa, L. G., Mena, A. & Ruiz-Salas, J. C. Effect of stress and attention on startle response and prepulse inhibition. Physiol Behav 165 , 179-186, doi:10.1016/j.physbeh.2016.07.022 (2016). Muir-Hunter, S. W. & Wittwer, J. E. Dual-task testing to predict falls in community-dwelling older adults: a systematic review. Physiotherapy 102 , 29-40, doi:10.1016/j.physio.2015.04.011 (2016). Jonsson, E., Seiger, A. & Hirschfeld, H. Postural steadiness and weight distribution during tandem stance in healthy young and elderly adults. Clin Biomech (Bristol) 20 , 202-208, doi:10.1016/j.clinbiomech.2004.09.008 (2005). Faul, F., Erdfelder, E., Lang, A. G. & Buchner, A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods 39 , 175-191, doi:10.3758/bf03193146 (2007). Cohen, J. Statistical power analysis for the behavioral sciences . (Academic press, 2013). Table 1 Table 1 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTables.docx SupplementaryFigures.docx Table1.docx Cite Share Download PDF Status: Published Journal Publication published 20 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 14 Jul, 2025 Reviews received at journal 11 Jul, 2025 Reviewers agreed at journal 04 Jul, 2025 Reviews received at journal 07 Jun, 2025 Reviewers agreed at journal 02 Jun, 2025 Reviewers invited by journal 01 Jun, 2025 Editor assigned by journal 23 May, 2025 Editor invited by journal 09 May, 2025 Submission checks completed at journal 07 May, 2025 First submitted to journal 25 Apr, 2025 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. 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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-6528482","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":465349803,"identity":"22806ee1-b76a-4281-a628-ae3430ce6427","order_by":0,"name":"Matteo Ciocca","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABA0lEQVRIiWNgGAWjYJCCAyCCn5n5AJjBxsDcABaWIKRFsr0tAaqFkbAWMDA4c8YAyiSgRbeB+eGBDzV28gw3cj4eurnDJp+P/WADw48ahsSZDdi1mB1gMzg441iyYeOM3A2Hc8+kWbbxJDYw9hxjSJyNwxazAzwMh3kbDjA2S4C0tB02YGNIbGDgbWBInEdAi32bRM4DoJb/Bmz8DxsY/xKhJbGH5wwDUMsBAzaJxAZmkC04HXYY4pfkGextBkC/JAO1PGw4LHNMwhin9483P/4ADDHb/YeZH3/O3WFnIN+ffPDhmxob2RkHcFjDjMyBxggocglGJJqWUTAKRsEoGAXIAACjhmGDAOgdywAAAABJRU5ErkJggg==","orcid":"","institution":"Centre for Vestibular Neurology, Department of Brain Sciences, Imperial College London","correspondingAuthor":true,"prefix":"","firstName":"Matteo","middleName":"","lastName":"Ciocca","suffix":""},{"id":465349804,"identity":"d4c8f1ad-1bd3-4778-b0f0-64db35651c3f","order_by":1,"name":"Sarah Hosli","email":"","orcid":"","institution":"Centre for Vestibular Neurology, Department of Brain Sciences, Imperial College London","correspondingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"","lastName":"Hosli","suffix":""},{"id":465349805,"identity":"e76c7bc4-8345-4ff5-bcea-82c96c93eed1","order_by":2,"name":"Zaeem Hadi","email":"","orcid":"","institution":"Centre for Vestibular Neurology, Department of Brain Sciences, Imperial College London","correspondingAuthor":false,"prefix":"","firstName":"Zaeem","middleName":"","lastName":"Hadi","suffix":""},{"id":465349806,"identity":"7cee6c83-2d3b-4461-87d7-b3ed04154dd1","order_by":3,"name":"Jingqi Hong","email":"","orcid":"","institution":"Centre for Vestibular Neurology, Department of Brain Sciences, Imperial College London","correspondingAuthor":false,"prefix":"","firstName":"Jingqi","middleName":"","lastName":"Hong","suffix":""},{"id":465349814,"identity":"2fbeec9d-0293-4d15-8126-212efe1623a2","order_by":4,"name":"Yen Tai","email":"","orcid":"","institution":"Centre for Vestibular Neurology, Department of Brain Sciences, Imperial College London","correspondingAuthor":false,"prefix":"","firstName":"Yen","middleName":"","lastName":"Tai","suffix":""},{"id":465349815,"identity":"4c110833-b055-4cab-9fdd-e71f472405ad","order_by":5,"name":"Barry M. Seemungal","email":"","orcid":"","institution":"Centre for Vestibular Neurology, Department of Brain Sciences, Imperial College London","correspondingAuthor":false,"prefix":"","firstName":"Barry","middleName":"M.","lastName":"Seemungal","suffix":""}],"badges":[],"createdAt":"2025-04-25 11:23:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6528482/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6528482/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-27097-4","type":"published","date":"2025-12-20T15:57:25+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":83917843,"identity":"13024684-4e54-4938-9d6e-eb811c20e38d","added_by":"auto","created_at":"2025-06-04 13:07:18","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":468693,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003emodulation of R2 area according to the applied ISI. \u003c/strong\u003eRelative changes (%) in the R2 area are illustrated. Single dots represent the amount of facilitation (black filled circles) or inhibition (empty circles) for each participant at each specific ISIs. At an ISI of 110 ms, all participants consistently exhibit an inhibition in the R2 area of the conditioned response.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6528482/v1/21d8b9e7389c408dd6f10082.jpg"},{"id":83919239,"identity":"5b2662bc-ce34-4a92-ab56-b4674e9fbece","added_by":"auto","created_at":"2025-06-04 13:23:18","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":600720,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003emodulation of the R2 and R2c area according to posture. \u003c/strong\u003eRelative changes (%) in the R2 (A) and R2c (B) area are illustrated. Black filled circles represent a facilitation of the conditioned response, whereas empty filled circles represent an inhibition of the conditioned response. A statistically significant difference after Bonferroni correction is present between supine and HS-EO, HS-EO and SS-EO, HS-EO and TS-EO for both the R2 and R2c responses. HS-EO: hard surface – eyes open; SS-EO: soft surface – eyes open; TS-EO: tandem standing – eyes open. *: p \u0026lt; 0.0125.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6528482/v1/1c9dae39f62c1da138f16a71.jpg"},{"id":83917851,"identity":"92906f03-dc6d-4315-9068-fe0bbf26871c","added_by":"auto","created_at":"2025-06-04 13:07:18","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":975113,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003elinear correlation between sPPI and sway parameters.\u003c/strong\u003e There is a positive linear correlation between sPPI and sway area while standing on hard surface and between sPPI and sway velocity while tandem standing. A trend towards a positive correlation is also present between sPPI and sway velocity while standing on hard surface and sPPI and sway area while tandem standing. The blacked dotted line represents the regression line, while the two blue dashed lines represent the 95% confident interval.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6528482/v1/efca204bc1642ce0a016631b.jpg"},{"id":83918868,"identity":"c8310ac1-c122-4c03-affb-dac75378da55","added_by":"auto","created_at":"2025-06-04 13:15:18","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":796586,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003emodulation of the R2 area according to posture and two different ISIs.\u003c/strong\u003e Relative changes (%) in the R2 area (mV*ms) are illustrated. Black filled circles represent a facilitation of the conditioned response, whereas empty circles represent an inhibition of the conditioned response. In A, a statistically significant difference after Bonferroni correction is present between supine and hard surface and hard-surface and tandem standing at ISI 110 ms, whereas a trend towards an inhibition is present at ISI 80 ms. In B, a statistically significant difference is present according to the ISI deployed in the supine and SS-EO conditions. Inhibition is present with both ISIs, with a stronger inhibition for the 200 ms ISI, but a lack of postural modulation. HS-EO: hard surface – eyes open; SS-EO: soft surface – eyes open; TS-EO: tandem standing – eyes open. *: p \u0026lt; 0.05\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6528482/v1/3ba0c1ff8203ca011ba4e530.jpg"},{"id":83917848,"identity":"5567f63b-9268-4697-8328-952a9747772d","added_by":"auto","created_at":"2025-06-04 13:07:18","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":583298,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003emodulation of aPPI according to posture.\u003c/strong\u003eRelative changes (%) in the R2 (A) and R2c (B) area are illustrated. Black filled circles represent a facilitation of the conditioned response, whereas empty circles represent an inhibition of the conditioned response. A statistically significant difference after Bonferroni correction is present between HS-EO and TS-EO for the R2 response and between HS-EO and SS-EO for the R2c response. HS: hard surface; SS: soft surface; TS: tandem standing. *: p \u0026lt; 0.0125.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6528482/v1/661d933e40a741836274f3e4.jpg"},{"id":98813898,"identity":"f5590c75-198b-4488-aaa8-d8128010dd66","added_by":"auto","created_at":"2025-12-22 16:06:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4802224,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6528482/v1/ddb55e96-f661-4a73-bd91-0cf5dd07f390.pdf"},{"id":83917847,"identity":"c1363a91-0b2f-4855-a8cb-36a0c81aa793","added_by":"auto","created_at":"2025-06-04 13:07:18","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":93384,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-6528482/v1/41e2801e3ee308edce242fb8.docx"},{"id":83917849,"identity":"31d9a7e6-d860-4e8d-a925-0ce00da397ea","added_by":"auto","created_at":"2025-06-04 13:07:18","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":736920,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigures.docx","url":"https://assets-eu.researchsquare.com/files/rs-6528482/v1/728d5b28a573c9d5e757787d.docx"},{"id":83918866,"identity":"cbb8b86a-9db0-4fd3-82c3-2924f5afc43a","added_by":"auto","created_at":"2025-06-04 13:15:18","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":19542,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6528482/v1/6bc3ba7e38469195f0e288e5.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Postural modulation of prepulse inhibition and its link to postural control: Insights from healthy subjects","fulltext":[{"header":"Introduction","content":"\u003cp\u003eReviewing a paper while on a train or a bus requires the ability to maintain attentional focus despite environmental distractions. This ability relies on sensory gating, a neurophysiological mechanism that prevents sensory overload in the central nervous system by suppressing irrelevant stimuli\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Stronger sensory gating is associated with greater cognitive efficiency\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, which may, in turn, improve the quality of the revision. This process involves pre-attentive neural mechanisms, primarily in the brainstem, thalamus, and cortex\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePrepulse inhibition (PPI), an operational measure of sensory gating, is a neurophysiological phenomenon in which a weak sensory stimulus reduces the R2 and R2c responses while facilitating the R1 response\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Inhibition has been observed across different sensory modalities - auditory, somatosensory, visual, and vestibular\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Interestingly, recent findings suggest that PPI may also play a role in postural control, with research indicating enhanced somatosensory PPI (sPPI) when standing\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. This connection between sensory gating and postural control has led to two primary hypotheses. The first, the \u0026ldquo;peripheral feedback\u0026rdquo; hypothesis, suggests that greater reliance on visual feedback for postural stability enhances PPI by reducing orbicularis oculi activation\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. The second, the \u0026ldquo;central tuning\u0026rdquo; hypothesis, posits that cortical control of key structures shared by the PPI and postural control networks modulates PPI. This cortical modulation of PPI is mediated through structures such as the pedunculopontine nucleus (PPN), which plays a key role in postural control, by modulating inputs from the periphery and filtering the ascending inflow to the thalamus\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. The PPN-thalamic pathway is particularly relevant in postural control, as its activity is directly associated with increased postural sway, a well-recognised risk factor for falls\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Additionally, the PPN is thought to enhance PPI by dynamically modulating somatosensory feedback, facilitating the adaptation of postural control to environmental demands\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Despite these initial observations, the precise mechanisms through which postural control modulates PPI remain unclear.\u003c/p\u003e \u003cp\u003eThis paper addresses some uncertainties surrounding PPI and its role in postural control. We hypothesise that PPI participates in adaptive postural control and predict that sPPI modulation is linked to measures of static balance. Furthermore, we hypothesise that peripheral sensory feedback influences sPPI when standing and predict that sPPI will be reduced when one of the peripheral sensory inputs is perturbed, as less sensory filtering is required to maintain balance control. Finally, we propose that postural modulation of PPI is centrally modulated and inherently structured within the network. Therefore, we expect it to be independent of prepulse relevance and to vary only with ISIs reflecting the integration of the prepulse in the PPN.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eAll participants completed the experiments without any adverse effects.\u003c/p\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003ePreliminary Experiments: input-output curve for sPPI\u003c/h2\u003e\n \u003cp\u003eData for Preliminary Experiment 1 and 2 are in Supplementary Tables 1 and 2, and Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eIn Preliminary Experiment 1, we compared the amount of sPPI for ISI from 70 ms to 120 ms. A one-way ANOVA showed no difference in R1 amplitude (F(7.120)\u0026thinsp;=\u0026thinsp;1.667, p\u0026thinsp;=\u0026thinsp;0.124, Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.19). However, statistically significant differences were observed for R2 (F(7,120)\u0026thinsp;=\u0026thinsp;4.347, p\u0026thinsp;=\u0026thinsp;0.0002, Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.427), and R2c area (F(7,120)\u0026thinsp;=\u0026thinsp;3.698, p\u0026thinsp;=\u0026thinsp;0.001, Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.384). Post-hoc analysis revealed statistically significant differences among unconditioned and conditioned stimuli at ISI 110 ms (p\u0026thinsp;=\u0026thinsp;0.000123) for both R2 and R2c area.\u003c/p\u003e\n \u003cp\u003eIn Preliminary Experiment 2, we compared sPPI for ISIs 110, 200, 400, 600 ms. There was no difference in R1 amplitude (F(4, 65)\u0026thinsp;=\u0026thinsp;0.373, p\u0026thinsp;=\u0026thinsp;0.827; Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0). Statistically significant differences were found in R2 area (F(4, 65)\u0026thinsp;=\u0026thinsp;5.598, p\u0026thinsp;=\u0026thinsp;0.001; Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.5125), with post-hoc analysis showing statistically significant differences at ISI 110 ms (p\u0026thinsp;=\u0026thinsp;0.003), 200 ms (p\u0026thinsp;=\u0026thinsp;0.004), and 400 ms (p\u0026thinsp;=\u0026thinsp;0.002). A trend towards an inhibition was observed in R2c area (F(4, 65)\u0026thinsp;=\u0026thinsp;3.316, p\u0026thinsp;=\u0026thinsp;0.016; Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.3637), with strongest inhibition at ISI 110 (p\u0026thinsp;=\u0026thinsp;0.027) and ISI 200 ms (p\u0026thinsp;=\u0026thinsp;0.024).\u003c/p\u003e\n \u003cp\u003eStrong inhibition at ISI 110 ms was consistent across experiments (R2 area inhibition: 32.21% in Preliminary Experiment 1, 27.58% in Preliminary Experiment 2; R2c area inhibition: 32.55% in Preliminary Experiment 1, 28.66% in Preliminary Experiment 2). A paired t-test compared 12 subjects who participated in both experiments, showing no significant difference in PPI at ISI 110 ms between Preliminary Experiment 1 (mean 36.33%; SD\u0026thinsp;=\u0026thinsp;20.10) and Preliminary Experiment 2 (mean 28.38%; SD\u0026thinsp;=\u0026thinsp;15.58) [t(11) = -1.457, p\u0026thinsp;=\u0026thinsp;0.173] (See Supplementary Fig.\u0026nbsp;1). Therefore, ISI 110 ms was selected for the main experiments with a somatosensory prepulse.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eMain Experiment 1- PPI modulation under different postural conditions\u003c/h3\u003e\n\u003cp\u003eIn this experiment, we initially compared latencies and the amount of sPPI at ISI 110 ms in four different postural conditions: supine, HS-EO, SS-EO, and TS.\u003c/p\u003e\n\u003cp\u003ePaired t-tests comparing unconditioned and conditioned R1, R2, and R2c latencies within each postural condition revealed no differences for R1 latency (Supplementary Table\u0026nbsp;3). However, conditioned R2 and R2c latencies were consistently longer than unconditioned latencies across all postural conditions (Supplementary Table\u0026nbsp;3). Comparing latency differences between supine and standing conditions showed no significant effects of postural changes (Supplementary Table\u0026nbsp;4).\u003c/p\u003e\n\u003cp\u003eWe then assessed whether blink reflex responses were modulated by postural conditions (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eR1 amplitude showed no significant differences across conditions (F(3,176)\u0026thinsp;=\u0026thinsp;0.068, p\u0026thinsp;=\u0026thinsp;0.977, Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0). However, R2 and R2c area inhibition varied significantly (R2: F(3,176)\u0026thinsp;=\u0026thinsp;13.589, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.458; R2c: F(3,176)\u0026thinsp;=\u0026thinsp;6.869, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0005, Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.313). Post-hoc analysis showed significant differences between supine and HS-EO, HS-EO and SS-EO, and HS-EO and TS-EO for both R2 and R2c responses (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThen, to assess whether sPPI modulation correlates with sway parameters, we performed a Spearman correlation analysis (Supplementary Table 5, Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e), which revealed significant positive correlations between sPPI and sway measures. Higher sPPI levels were associated with greater sway area on HS and higher sway velocity on TS.\u003c/p\u003e\n\u003cp\u003eSubsequently, to compare the Spearman\u0026rsquo;s correlation coefficients of sway area and velocity between HS, and SS and TS, we applied Fisher\u0026rsquo;s Z-transformation to normalize the correlation values. Data are reported in Supplementary table 5. A two-tailed test resulted in a non-statistically significant difference between HS and SS for sway area (p\u0026thinsp;=\u0026thinsp;0.204), and a trend towards a statistically significant difference with a reduction in correlation for sway velocity (p\u0026thinsp;=\u0026thinsp;0.075). Similarly, a two-tailed test resulted in a non-statistically significant difference between Hs and TS for both sway area (p\u0026thinsp;=\u0026thinsp;0.868) and velocity (p\u0026thinsp;=\u0026thinsp;0.657).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMain Experiment 2\u003c/em\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ndash;\u003c/span\u003e \u003cem\u003eeffect of visual feedback on postural PPI-modulation\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe investigate the effect of visual feedback (EO vs EC) on the R1 amplitude of R1 and R2/R2c area across postural conditions using repeated measures ANOVA. Means and standard deviations for latency differences, R1 amplitude, and R2/R2c area inhibition are in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003ctable id=\"Tab2\" border=\"1\" class=\"fr-table-selection-hover\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cstrong\u003evisual and postural modulation of PPI for each blink reflex response\u003c/strong\u003e. Mean changes and standard deviation in latency (ms) for R1, R2, and R2c are reported according to the presence (Eye opened) or absence (eyes closed) of visual feedback and according to the postural condition. Relative changes (%) and standard deviation for the R1 amplitude (mV) and R2 and R2c area (mV*ms) are reported. EO: eyes opened. EC: eyes closed. HS: hard surface; SS: soft surface.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003cp\u003eChange\u003c/p\u003e\n \u003cp\u003e(ms)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStd. Deviation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePercentage change (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStd. Deviation\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eR1 Latency\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eR1 Amplitude\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupine-EO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;0.0256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.3049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupine-EO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e+\u0026thinsp;36.18%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.507\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupine-EC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;0.1250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.5063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupine-EC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e+\u0026thinsp;21.13%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.655\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHS-EO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;0.1122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.3775\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHS-EO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e+\u0026thinsp;35.11%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.074\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHS-EC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;0.1967\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.3856\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHS-EC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e+\u0026thinsp;15.92%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSS-EO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;0.1106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.5470\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSS-EO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e+\u0026thinsp;42.68%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66.266\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSS-EC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;0.1783\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e0.4083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSS-EC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e+\u0026thinsp;13.29%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.195\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eR2 Latency\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eR2 Area\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupine-EO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;1.253\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.3664\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupine-EO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-16.07%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupine-EC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;1.335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e2.0743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupine-EC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-19.80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHS-EO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;1.286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.6822\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHS-EO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-29.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHS-EC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;0.762\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.5538\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHS-EC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-25.52%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSS-EO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;1.318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e2.3707\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSS-EO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-18.52%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSS-EC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;1.572\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.3885\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSS-EC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-16.18%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eR2c Latency\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eR2c Area\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupine-EO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;1.5211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.5310\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupine-EO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-19.42%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupine-EC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;0.6856\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.6388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupine-EC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-21.62%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHS-EO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;1.5950\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.5267\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHS-EO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-29.33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHS-EC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;1.1506\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.7748\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHS-EC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-30.74%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSS-EO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;1.3817\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e3.8917\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSS-EO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-16.47%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSS-EC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;2.257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.6237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSS-EC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e-17.17%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003eVisual feedback and postural conditions had no significant effect on R1, R2, or R2c latency (Supplementary Table 6). However, R1 amplitude was significantly larger with eyes open than eyes closed (p\u0026thinsp;=\u0026thinsp;0.029; Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, Supplementary Table\u0026nbsp;6, Supplementary Fig.\u0026nbsp;2). Neither postural conditions nor their interaction with visual feedback significantly influenced R1 amplitude.\u003c/p\u003e\n\u003cp\u003eThe effect of visual feedback on R2 and R2c areas was not significant. However, postural condition alone significantly influenced R2 and R2c inhibition. Post-hoc pairwise comparisons showed stronger inhibition on a hard surface compared to supine (R2: p\u0026thinsp;=\u0026thinsp;0.005; R2c: p\u0026thinsp;=\u0026thinsp;0.007) and soft surfaces (R2: p\u0026thinsp;=\u0026thinsp;0.001; R2c: p\u0026thinsp;=\u0026thinsp;0.001). Separate one-way ANOVA analyses confirmed significant differences in sPPI between supine and hard-surface standing with eyes open (F(2,54)\u0026thinsp;=\u0026thinsp;4.389, p\u0026thinsp;=\u0026thinsp;0.016, Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.345; R2: p\u0026thinsp;=\u0026thinsp;0.02; R2c: p\u0026thinsp;=\u0026thinsp;0.005). No significant differences were found for eyes-closed conditions (F(2,57)\u0026thinsp;=\u0026thinsp;1.070, p\u0026thinsp;=\u0026thinsp;0.350, Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.05), though a trend towards increased inhibition was observed (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, Supplementary Table\u0026nbsp;6, Supplementary Fig.\u0026nbsp;2).\u003c/p\u003e\n\u003cp\u003ePearson correlations between sPPI and sway velocity/area were not significant (Supplementary Table\u0026nbsp;7).\u003c/p\u003e\n\u003ch3\u003eMain Experiment 3 \u0026ndash; effect of ISI on postural PPI-modulation\u003c/h3\u003e\n\u003cp\u003eFor Experiments 3a and 3b, repeated measures ANOVA results and descriptive statistics are in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, and Supplementary Tables 8 and 9.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cstrong\u003epostural modulation of sPPI according to the ISIs deployed for each blink reflex response\u003c/strong\u003e. Percentage changes (%) and standard deviation for R1, R2, and R2c are reported according to the specified ISI (80 ms vs 110 ms and 110 ms vs 200 ms) and according to the postural condition. HS: hard surface; SS: soft surface, TS: tandem standing.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"14\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePercentage change\u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStd. Deviation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePercentage change (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eStd. Deviation\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eR1 Amplitude\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003eR1 Amplitude\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;41.72%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e33.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e+\u0026thinsp;39.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e63.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;36.18%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e33.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e+\u0026thinsp;31.86%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e56.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;19.61%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e33.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e+\u0026thinsp;32.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e73.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;35.11%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e41.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e+\u0026thinsp;30.41%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e42.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;38.59%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e65.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e+\u0026thinsp;18.15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e38.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;42.68%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e68.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e+\u0026thinsp;36.74%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e57.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;13.69%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e40.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e+\u0026thinsp;36.06%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e28.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e+\u0026thinsp;30.59%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e49.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e+\u0026thinsp;47.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e57.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eR2 Area\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eR2 Area\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-10.54%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e21.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e-19.71%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e16.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-16.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e9.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e-37.06%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e28.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-22.13%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e12.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e-35.79%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e20.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-27.27%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e11.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e-43.37%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e23.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-18.12%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e14.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e-18.01%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e22.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-18.52%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e14.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e-37.61%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e19.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-19.35%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e26.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e-22.31%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e18.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-13.58%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e12.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e-31.16%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e28.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eR2c Amplitude\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eR2c Area\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-6.39%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e25.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e-26.59%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e26.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-19.42%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e7.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e-41.06%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e33.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-18.96%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e19.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e-27.75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e25.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-29.33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e10.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e-39.59%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e24.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-19.17%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e21.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e-23.89%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e26.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-16.47%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e9.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e-39.53%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e24.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-17.19%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e34.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e-30.63%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e23.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-13.19%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e12.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e200 ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e-39.12%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e23.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003ch3\u003eExperiment 3a \u0026ndash; comparing 80 ms vs 110 ms\u003c/h3\u003e\n\u003cp\u003eA significant latency difference was found between 80 ms and 110 ms ISIs (F(1,19)\u0026thinsp;=\u0026thinsp;8.092; p\u0026thinsp;=\u0026thinsp;0.010; Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.581). T-tests showed longer latency for 110 ms ISI in R2 (t = -2.149; p\u0026thinsp;=\u0026thinsp;0.045) and R2c (t = -2.425; p\u0026thinsp;=\u0026thinsp;0.025). Latency differences across postural conditions were not significant at either ISI.\u003c/p\u003e\n\u003cp\u003eR1 amplitude modulation across postural conditions was not significant (F(1,18)\u0026thinsp;=\u0026thinsp;1.143; p\u0026thinsp;=\u0026thinsp;0.340; Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.08). ISI did not significantly affect R2 (F(1,18)\u0026thinsp;=\u0026thinsp;1.582; p\u0026thinsp;=\u0026thinsp;0.204; Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.17) or R2c area (F(1,18)\u0026thinsp;=\u0026thinsp;2.407; p\u0026thinsp;=\u0026thinsp;0.077; Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.265).\u003c/p\u003e\n\u003cp\u003eSeparate one-way ANOVA confirmed stronger sPPI at 110 ms ISI for both R2 (F(3,72)\u0026thinsp;=\u0026thinsp;4.308; p\u0026thinsp;=\u0026thinsp;0.007; Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.361) and R2c (F(3,72)\u0026thinsp;=\u0026thinsp;9.129; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.566). Post-hoc tests revealed stronger inhibition on a hard surface compared to supine (R2: p\u0026thinsp;=\u0026thinsp;0.044; R2c: p\u0026thinsp;=\u0026thinsp;0.019) and tandem standing (R2: p\u0026thinsp;=\u0026thinsp;0.007; R2c: p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). No significant differences were found for R2 (F(3,72)\u0026thinsp;=\u0026thinsp;1.142; p\u0026thinsp;=\u0026thinsp;0.338; Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.07) or R2c (F(3,72)\u0026thinsp;=\u0026thinsp;0.993; p\u0026thinsp;=\u0026thinsp;0.401; Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0) at 80 ms ISI.\u003c/p\u003e\n\u003ch3\u003eExperiment 3b \u0026ndash; comparing 110 ms vs 200 ms\u003c/h3\u003e\n\u003cp\u003eNo significant latency differences were found between 110 ms and 200 ms ISIs for R1 (F(3,54)\u0026thinsp;=\u0026thinsp;0.580; p\u0026thinsp;=\u0026thinsp;0.631; Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0), R2 (F(3,54)\u0026thinsp;=\u0026thinsp;1.878; p\u0026thinsp;=\u0026thinsp;0.144; Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.213), or R2c (F(3,54)\u0026thinsp;=\u0026thinsp;2.509; p\u0026thinsp;=\u0026thinsp;0.068; Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.122).\u003c/p\u003e\n\u003cp\u003eThe interaction between ISI and postural condition was not significant for R1 amplitude (F(3,54)\u0026thinsp;=\u0026thinsp;1.307; p\u0026thinsp;=\u0026thinsp;0.282; Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.126), R2 (F(3,54)\u0026thinsp;=\u0026thinsp;2.458; p\u0026thinsp;=\u0026thinsp;0.073; Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.275), or R2c areas (F(3,54)\u0026thinsp;=\u0026thinsp;0.813; p\u0026thinsp;=\u0026thinsp;0.492; Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0). However, paired sample t-tests showed stronger inhibition with a 200 ms ISI in all postural conditions (Supplementary Table\u0026nbsp;9, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eMain Experiment 4 \u0026ndash; effect of prepulse modality on postural PPI-modulation\u003c/h2\u003e\n \u003cp\u003eWe compared the latency of unconditioned and conditioned R1, R2, and R2c responses within each postural condition using paired t-tests. No significant difference was found for R1 latency. However, conditioned R2 and R2c latencies were consistently longer than unconditioned latencies across all postural conditions (Supplementary Table\u0026nbsp;10). Postural changes did not significantly affect these latency differences (Supplementary Table\u0026nbsp;11).\u003c/p\u003e\n \u003cp\u003eWe then examined the modulation of blink reflex responses across postural conditions, focusing on R1 amplitude and R2 and R2c area. One-way ANOVA showed no significant difference in R1 amplitude across postural conditions (F(3,79)\u0026thinsp;=\u0026thinsp;0.929; p\u0026thinsp;=\u0026thinsp;0.431; Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0). Conversely, prepulse inhibition of R2 and R2c area varied significantly (R2: F(3,79)\u0026thinsp;=\u0026thinsp;4.476; p\u0026thinsp;=\u0026thinsp;0.006; Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.361; R2c: F(3,79)\u0026thinsp;=\u0026thinsp;5.266; p\u0026thinsp;=\u0026thinsp;0.002; Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.399). Post-hoc tests revealed significant differences for R2 between HS-EO and TS-EO (p\u0026thinsp;=\u0026thinsp;0.006) and for R2c between HS-EO and SS-EO (p\u0026thinsp;=\u0026thinsp;0.004) (Supplementary Table 12 and Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eA one-way ANOVA did not show any significant difference in the amplitude of R1 across different postural conditions (F(3,79)\u0026thinsp;=\u0026thinsp;0.929, p\u0026thinsp;=\u0026thinsp;0.431, Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0). Conversely, prepulse inhibition of the R2 and R2c area is modulated across different postural conditions (R2: F(3,79)\u0026thinsp;=\u0026thinsp;4.476, p\u0026thinsp;=\u0026thinsp;0.006, Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0.361; R2c: F(3,79)\u0026thinsp;=\u0026thinsp;5.266, p\u0026thinsp;=\u0026thinsp;0.002, Cohen\u0026rsquo;s f\u0026thinsp;=\u0026thinsp;0. 399). A post-hoc analysis revealed a statistically significant difference between HS-EO and TS-EO for the R2 area (p\u0026thinsp;=\u0026thinsp;0.006), and between HS-EO and SS-EO for the R2c area (p\u0026thinsp;=\u0026thinsp;0.004) (see Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eSubsequently, we evaluated the effect of visual feedback (EO vs EC) on aPPI using repeated measures ANOVA. No significant differences were found in R1 amplitude (F(2,38)\u0026thinsp;=\u0026thinsp;0.554; p\u0026thinsp;=\u0026thinsp;0.579), R2 area (F(3,38)\u0026thinsp;=\u0026thinsp;0.793; p\u0026thinsp;=\u0026thinsp;0.460), or R2c area (F(2,38)\u0026thinsp;=\u0026thinsp;1.715; p\u0026thinsp;=\u0026thinsp;0.194).\u003c/p\u003e\n \u003cp\u003eFinally, a Spearman correlation analysis revealed a significant positive correlation between aPPI and sway area in TS, with higher aPPI associated with greater sway area (Supplementary Fig.\u0026nbsp;3; Supplementary Table\u0026nbsp;13).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we investigated the link between PPI and postural control. Our findings revealed that (a) PPI is modulated by postural conditions, with stronger inhibition when standing on HS. Notably, both sPPI and aPPI exhibit this modulation, though sPPI shows greater inhibition, suggesting PPI modulation is centrally regulated and it is only partially dependent on the prepulse modality. (b) PPI correlates with sway parameters. On HS and TS, sPPI positively correlates with sway area and velocity, indicating that greater sway is associated with stronger inhibition. A weaker correlation is observed between aPPI and sway during TS. (c) Peripheral sensory feedback perturbations reduce inhibition. Standing on SS or with EC reduces inhibition, with a greater reduction on SS, highlighting the role of sensory feedback in modulating PPI. (d) sPPI modulation is ISI-specific, peaking at 110 ms and disappearing by 200 ms, indicating time-dependent sensitivity in PPI modulation.\u003c/p\u003e \u003cp\u003eThese findings suggest that, similar to its role in attentional and cognitive processes, PPI might influence how we maintain balance and posture in a dynamic environment.\u003c/p\u003e \u003cp\u003eThe magnitude of inhibition varies across postural conditions, as previously observed\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Our study confirms this and further demonstrates that PPI modulation reflects the adaptability of sensorimotor integration within the postural control network. PPI likely prevents sensory overflow during less challenging tasks (e.g., standing on HS) and enhances peripheral feedback during more demanding tasks (e.g., standing on SS or TS). Neural activity within shared structures, such as the PPN and the caudal pontine reticular nucleus (CPRN), is critical in this process, with concurrent bottom-up and top-down control mechanisms.\u003c/p\u003e \u003cp\u003ePPI modulation varies with sensory feedback perturbations, such as those affecting proprioceptive (e.g. SS and TS), or visual (e.g. EC) systems. In these conditions, reduced inhibition likely reflects decreased sensory filtering to maintain balance when peripheral inputs are disrupted\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. This result is in line with previous data showing how the startle reflex is reduced when the afferent volley comes from the lower limbs, likely a \u0026ldquo;defensive\u0026rdquo; mechanism of the postural control network to guarantee balance control in challenging situations\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe correlation between PPI and sway parameters further suggests that PPI reflects activity within the postural control network. Notably, PPI correlates with sway when proprioceptive feedback remains intact but not when it is perturbed. This indicates that PPI primarily reflects proprioceptive feedback integration, highlighting the importance of proprioceptive inputs from muscles, joints, and cutaneous receptors\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. The time-dependent nature of PPI modulation, observed at specific ISIs (80\u0026ndash;110 ms), supports this interpretation, as it aligns with the temporal integration of proprioceptive feedback at cortical and subcortical levels\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. However, the absence of PPI modulation at longer ISIs likely reflects central top-down mechanisms. This might indicate the involvement of structures modulating PPI, such as limbic structures\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, which are less involved in regulating balance during quiet standing in young healthy subjects\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. A top-down control mechanism is further supported by the observation that PPI is not modulated based on the relevance of the prepulse stimuli. Both sPPI and aPPI show a similar pattern of modulation, though the magnitude of inhibition is higher for sPPI than for aPPI. Thus, the PPI network\u0026rsquo;s response to postural changes appears to be inherently structured within the network and is not dependent on the relevance of the somatosensory prepulse.\u003c/p\u003e \u003cp\u003eIn summary, our results seem to support the coexistence of a central tuning hypothesis and a peripheral feedback hypothesis, which are mutually contributing to modulate PPI when balancing.\u003c/p\u003e \u003cp\u003eThe possible involvement of structures modulating PPI offers an alternative interpretation of our findings, particularly regarding task difficulty. On HS, participants with greater inhibition exhibited more sway. However, this task did not challenge the postural control network, as none of the participants reported feelings of instability or unsteadiness, although we did not specifically query this. We therefore infer that all participants maintained optimal postural control, with PPI potentially reflecting a form of \u0026ldquo;balance reserve\u0026rdquo;, where individuals with higher PPI might better adapt and reduce sway during more demanding tasks. This would align with the concept of \u0026ldquo;cognitive reserve\u0026rdquo; as representing the physiological robustness within the (postural control) brain network\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Nevertheless, we observed no correlation between changes in PPI from HS to TS and the corresponding changes in sway area and velocity. Consequently, this hypothesis cannot be fully supported.\u003c/p\u003e \u003cp\u003eA significant limitation in this context is the lack of control for individual perception of task difficulty. Participants were not systematically interviewed about their perceived instability or the effort required to maintain postural control. Instead, we assumed that the transition from HS to TS posed an increased challenge for all participants, which may not have been uniformly true. Interestingly, correlation between PPI and sway parameters did not change between HS and TS, likely reflecting a physiological robustness within the postural control network, again potentially indicating a \"balance reserve\".\u003c/p\u003e \u003cp\u003eConversely, changes in correlation between sPPI and sway parameters may reflect a maladaptive response, where cognitively-driven mechanisms assume control over posture from automatic processes\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. In this scenario, PPI may only reliably reflect postural control when subcortical automatic processes dominate. The reduction in correlation when transitioning from HS to SS supports this hypothesis. An important limitation to this interpretation is that we did not test PPI while participants were standing and concurrently performing a cognitive task. A dual-task paradigm would have allowed for a clearer understanding of whether cognitive control interferes with automatic postural processes and whether this results in a maladaptive response. The absence of such a challenge to cognitive processes in this study limits the ability to definitively assess whether higher cognitive demands affect PPI\u0026rsquo;s role in postural control. Further studies incorporating a dual-task approach and larger sample sizes are needed to clarify this relationship.\u003c/p\u003e \u003cp\u003ePPI modulation may reflect attentional influences on the postural control network. The PPN and CPRN, which are critical in both networks, are primarily involved in automatic balance control. However, balance also requires attentional resources, particularly under challenging conditions\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Attention facilitates the integration of sensory inputs from visual, vestibular, and proprioceptive systems, which are crucial for maintaining stability\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. When sensory inputs are limited, such as on SS or with EC, attentional resources are reallocated to process residual inputs and maintain balance\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. When cognitive demands further rise, attentional resources may be diverted away from maintaining posture, potentially leading to compromised stability\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. This is particularly evident in tasks requiring precise balance adjustments, such as TS or walking on unstable surfaces\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. To this extent, excessive attentional focus on stabilising posture can disrupt compensatory neural responses, leading to increased instability\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. This possibility is consistent with our findings of reduced PPI when sensory feedback (e.g., SS), visual input (e.g., EC), or vestibular feedback (e.g., TS) are disrupted, suggesting that attentional resources are redirected to managing these sensory challenges.\u003c/p\u003e \u003cp\u003ePPI is sensitive to attentional modulation\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Increased attention to the prepulse enhances PPI, while shifting attention away diminishes it\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. However, some studies report no PPI modulation under low-attention tasks\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Thus, under certain conditions, changes in PPI during different postural tasks could reflect attention-related modulation. Sensory feedback alteration (e.g., SS, EC) likely shifts attention towards balance maintenance, reducing PPI and potentially increasing sensory overflow, contributing to instability.\u003c/p\u003e \u003cp\u003eOnce again, one possible explanation is the involvement of PPI-modulating structures within the balance control network. During complex postural tasks, the automatic processes of balance control influence the PPI network by reducing sensory filtering, as the brain integrates residual proprioceptive, vestibular, and visual inputs to sustain stability. Data from PPI during EC conditions, standing on SS, and TS support this mechanism. However, when the postural task becomes extremely challenging, the balance control mechanism shifts from an automatic to cognitively driven processes, as observed in older adults with an age-related decline in balance and somatosensory function\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. In this context, increased attentional load on the balance control network affects the PPI network similarly to when attention is focused away from the prepulse stimulus. This heightened attentional demand leads to decreased PPI, causing a sensory overflow and potentially contributing to increased sway. Excessive inhibition during such tasks could indicate the network\u0026rsquo;s reliance on attentional control to maintain stability, disrupting efficiency.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003ePPI participates in postural control by modulating the peripheral sensory feedback. It is conceivable that PPI might be used as a surrogate marker of activity within the postural control network, although further studies will need to confirm this possibility.\u003c/p\u003e \u003cp\u003eModulation of peripheral sensory feedback, particularly proprioceptive input, significantly influences PPI, underscoring its role as a marker of sensorimotor integration during standing. However, central modulation also plays a role, as evidenced by PPI’s independence from the prepulse type. This suggests that the PPI network’s response to postural changes is inherently structured within the network itself. Finally, further research is needed to elucidate how attention and task difficulty influence PPI and its relationship with balance control.\u003c/p\u003e \u003c/div\u003e "},{"header":"Methods","content":"\u003cp\u003e The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Ethics Committee of London Harrow (REC reference 21/LO/0112, date of approval 21/04/2021). Informed consent was obtained from all subjects involved in the study.\u003c/p\u003e\u003ch2\u003eBlink Reflex\u003c/h2\u003e\u003cp\u003eThe electrically-elicited blink reflex was used in this study. Surface electrodes were used to deliver supraorbital nerve stimuli, with the cathode placed over the supraorbital notch and the anode positioned 3 cm away along the course of the nerve on the ipsilateral forehead. Percutaneous stimuli lasting 0.2 ms were applied to the right supraorbital nerve at irregular intervals of 25–30 seconds. The stimulus intensity was set at three times the R2 motor threshold, defined as the minimum stimulus intensity able to elicit a 50 uV baseline-to-peak amplitude in at least 4 out of 8 consecutive electromyographic (EMG) responses.\u003c/p\u003e\u003cp\u003eThe blink reflex response was recorded via EMG of the orbicularis oculi muscles. The active recording electrodes were positioned bilaterally on the lower eyelid, halfway between the inner and outer edges of the orbit, while the corresponding reference electrode was placed on the ipsilateral temple on each side. Amplification of the responses (x1000) was performed using a Digitimer D360R-4 device (Digitimer, Welwyn Garden City, UK). The signal was filtered using a frequency range of 30 Hz to 3 kHz. Data acquisition was carried out using Signal software, version 7.02 (Cambridge Electronic Devices, Cambridge, UK), and recorded on a laptop computer. For analysis, EMG traces were rectified, and all traces contaminated by EMG artifacts were discarded.\u003c/p\u003e\u003ch2\u003ePrepulse Inhibition\u003c/h2\u003e\u003cp\u003eSomatosensory stimuli: Conditioning somatosensory stimuli (prepulses) consisted of single pulses of electrical stimulation lasting 0.2 ms, delivered via bipolar electrodes to the sural nerve at the ankle. Specifically, the electrode placement was posterior to the lateral malleolus, secured in position using a Velcro strap. The intensity was set at twice the sensory threshold, defined as the minimum stimulus intensity perceived in at least 4 out of 8 consecutive stimuli, determined through both ascending and descending stepwise approaches. This intensity level was confirmed before each acquisition for every postural condition.\u003c/p\u003e\u003cp\u003eAuditory stimuli: The auditory conditioning stimuli comprised a 500 Hz tone, lasting 20 microseconds, and with an intensity of 70 dB. These stimuli were administered bilaterally using a pair of headphones. Throughout the tasks, a background room noise of around 35–40 dB was consistently present. The tones were produced via a custom-made tone generator.\u003c/p\u003e\u003ch2\u003eExperimental Design\u003c/h2\u003e\u003ch2\u003ePreliminary Experiments\u003c/h2\u003e\u003cp\u003eAs data on the best ISI to evoke a consistent sPPI from the leg are scant in the literature, we initially set up an input-output curve exploring ISIs ranging from 70 to 120 ms in steps of 10 ms; in addition, we tested an ISI of 116 ms, as this was previously used by Versace et al.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Therefore, a total of 7 conditions were tested in 16 young healthy subjects (10 females; aged 21–33) (Preliminary Experiment 1). Additionally, we expanded the investigations in the input-out curve for sPPI by investigating three longer ISIs, namely 200, 400 and 600 ms, and we ran a test-retest reliability protocol by retesting the ISI that in the first preliminary experiment showed the strongest inhibition. Therefore, a total of four conditions were tested in 14 young healthy subjects (8 females; aged 21–33) (Preliminary Experiment 2).\u003c/p\u003e\u003ch2\u003eMain Experiments\u003c/h2\u003e\u003ch2\u003eMain Experiment 1 – PPI modulation under different postural conditions\u003c/h2\u003e\u003cp\u003eA total of 45 subjects (16 females; aged 21–40) participated in this experiment. The ISI indicating the strongest inhibition from preliminary experiments 1 and 2 (i.e. 110 ms) was used in this experiment.\u003c/p\u003e\u003cp\u003eSubjects were tested in 4 different conditions: 1) supine – eyes open; 2) standing on hard surface – eyes open (HS-EO); 3) standing on soft surface – eyes open (SS-EO); and 4) standing on hard surface in tandem stance (TS). The order of testing was pseudorandom, as the supine condition was always tested first, followed by a standing condition randomly assigned using a randomisation list. For each postural condition, 5 unconditioned and 5 conditioned blink reflexes were acquired in a random order (total of 10 responses). Participants stood on a soft rectangular foam pad (50 × 41 × 6 cm, Airex) for the soft condition.\u003c/p\u003e\u003cp\u003eIn this experiment, postural control varies according to the different peripheral feedback in each condition. In the HS-EO condition, visual, proprioceptive, and vestibular input contributes to postural control. In the SS-EO condition, primarily visual and vestibular input contributes to postural control while the proprioceptive feedback is reduced. By using the tandem condition, we chose to minimise the antero-posterior oscillations, highlighting the medio-lateral sway\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Visual input mainly contributes to postural control when tandem standing, while both proprioceptive and vestibular input are perturbed.\u003c/p\u003e\u003cp\u003eWhile acquiring sPPI in different postural conditions, we concomitantly measured static balance using a force platform. All subjects were asked to stand on a force platform with their arms hanging loosely by their sides, with heels 8 cm apart for the hard and soft-surface balance measure, and in the heel-to-toe position for the tandem standing. Area and velocity measures of sway were calculated for each condition, and were correlated with the amount of PPI for each subject.\u003c/p\u003e\u003ch2\u003eMain Experiment 2 – effect of visual feedback on postural PPI-modulation\u003c/h2\u003e\u003cp\u003eA total of 18 subjects (10 females; aged 21–37) participated in this experiment. Subjects were tested in a total of 6 different conditions: 1) supine – eyes open; 2) supine – eyes closed; 3) HS-EO; 4) hard surface – eyes closed (HS-EC); 5) SS-EO; and 6) soft surface – eyes closed (SS-EC). The order of testing was pseudorandom, as the supine condition was always tested first, followed by a standing condition randomly assigned using a randomisation list. For each condition, 5 unconditioned and 5 conditioned blink reflexes were acquired in a random order (total of 10 responses). Participants stood on a soft rectangular foam pad for the soft condition. Once again, we concomitantly measured static balance for each condition by means of postural sway using a force platform.\u003c/p\u003e\u003ch2\u003eMain Experiment 3 – effect of ISI on postural PPI-modulation\u003c/h2\u003e\u003cp\u003eIn this experiment, we investigated whether sPPI modulation according to posture depends on the timing between the prepulse and the test pulse. We divided this experiment in two parts, namely 3a and 3b. In experiment 3a, we compared the optimal ISI (i.e. 110ms) against a shorter, suboptimal ISI of 80 ms. In experiment 3b, we compared the optimal ISI with a longer ISI of 200 ms. A total of 19 subjects (10 females; aged 21–37) participated in experiment 3a, while a total of 20 subjects (all males; aged 21–32) participated in experiment 3b.\u003c/p\u003e\u003ch2\u003eExperiment 4 – effect of prepulse modality on postural PPI-modulation\u003c/h2\u003e\u003cp\u003eA total of 20 subjects (10 females, aged 21–30) participated in this experiment. We run the same tests deployed in experiments 1 and 2 using an auditory prepulse and an ISI of 100 ms.\u003c/p\u003e\u003ch2\u003eData analysis and statistics\u003c/h2\u003e\u003cp\u003eIn all experiments, we measured latency of the R1, R2, and R2c responses, amplitude of R1, and area-under-the-curve (area) of the R2 and R2c components of the blink reflex in each single rectified trace in control and test trials. We then normalised the amount of inhibition for each subject, and we averaged the result per subject and per condition. We reported the percentage of facilitation/inhibition for the R1 and R2/R2c according to these formulas: for R1\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(\\frac{\\text{R}1\\text{c}\\text{o}\\text{n}\\text{d}\\text{i}\\text{t}\\text{i}\\text{o}\\text{n}\\text{e}\\text{d}\\:\\text{a}\\text{r}\\text{e}\\text{a}}{\\text{R}1\\text{u}\\text{n}\\text{c}\\text{o}\\text{n}\\text{d}\\text{i}\\text{t}\\text{i}\\text{o}\\text{n}\\text{e}\\text{d}\\:\\text{a}\\text{r}\\text{e}\\text{a}}-1\\right)*100\\)\u003c/span\u003e\u003c/span\u003e, for R2/R2c (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{\\text{R}2\\text{c}\\text{o}\\text{n}\\text{d}\\text{i}\\text{t}\\text{i}\\text{o}\\text{n}\\text{e}\\text{d}\\:\\text{a}\\text{r}\\text{e}\\text{a}}{\\text{R}2\\text{u}\\text{n}\\text{c}\\text{o}\\text{n}\\text{d}\\text{i}\\text{t}\\text{i}\\text{o}\\text{n}\\text{e}\\text{d}\\:\\text{a}\\text{r}\\text{e}\\text{a}}-1)*100\\)\u003c/span\u003e\u003c/span\u003e. A positive value reflects a facilitation, a negative value an inhibition.\u003c/p\u003e\u003cp\u003eFor experiments 1, an a-priori power analysis was conducted using G*Power version 3.1.9.6\u003csup\u003e26\u003c/sup\u003e to determine the minimum sample size required to test the study hypotheses. We based our power analysis on the amount of inhibition observed in the previous paper from Versace et al.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Results indicated the required sample size to achieve 80% power for detecting a large effect, at a significance criterion of α = .05, was N = 48 for fixed effects one-way analysis of variance (ANOVA) test. Thus, the obtained sample size of N = 45 for experiment 1 is adequate to test the study hypotheses.\u003c/p\u003e\u003cp\u003eSimilarly, for Main Experiment 2 and 3, results indicated the required sample size to achieve 80% power for detecting a medium effect, at a significance criterion of α = .05, for repeated measure, within-between interaction ANOVA was N = 20 for Main Experiment 2, and N = 18 for Main Experiment 3. Thus, the obtained sample size of N = 20 is adequate to test the study hypotheses. We did not run a power-analysis for Main Experiment 4, but we recruited a number of subjects in line with Main Experiments 2 and 3.\u003c/p\u003e\u003cp\u003eHomogeneity of variances was confirmed via Levene's test for equality of variances. Effect size was calculated by using Cohen’s f\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. In case of a statistically significant main effect, Bonferroni corrected post-hoc tests were performed.\u003c/p\u003e\u003cp\u003eFor linear correlation analysis between sPPI of the ipsilateral R2 component and posturography data, specifically sway velocity and sway area, data distribution was first evaluated using the Shapiro-Wilk test, which revealed that sway data for the eyes-open condition were not normally distributed (p \u0026lt; 0.05. Consequently, a Spearman correlation was used. All statistical analyses were performed in SPSS version 26.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe original contributions presented in this study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author(s).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, M.C. and B.M.S.; Methodology, M.C.; Software, M.C. and Z.H.; Data Acquisition: M.C., J.H., and S.H.; Formal Analysis, M.C. and S.H.; Data Curation, M.C. and S.H.; Writing \u0026ndash; Original Draft Preparation, M.C.; Writing \u0026ndash; Review \u0026amp; Editing, M.C., Z.H, B.M.S; Supervision, Y.T. and B.M.S.; Project Administration, B.M.S.; Funding Acquisition, Y.T and B.M.S.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunding received from the Medical Research Council (MRC) and the Jon Moulton Charity Trust, the Imperial NIHR Biomedical Research Centre, Imperial Health Charity, the US Department of Defense, the UK Ministry of Defence, and the Koetser Foundation for Brain Research.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll co-authors have reviewed and approved the contents of the manuscript, and the submission is not under review at any other publication. The authors report no competing interests\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGarcia-Rill, E.\u003cem\u003e et al.\u003c/em\u003e Focus on the pedunculopontine nucleus. Consensus review from the May 2018 brainstem society meeting in Washington, DC, USA. \u003cem\u003eClin Neurophysiol\u003c/em\u003e \u003cstrong\u003e130\u003c/strong\u003e, 925-940, doi:10.1016/j.clinph.2019.03.008 (2019).\u003c/li\u003e\n\u003cli\u003eJones, L. A., Hills, P. J., Dick, K. M., Jones, S. P. \u0026amp; Bright, P. Cognitive mechanisms associated with auditory sensory gating. \u003cem\u003eBrain Cogn\u003c/em\u003e \u003cstrong\u003e102\u003c/strong\u003e, 33-45, doi:10.1016/j.bandc.2015.12.005 (2016).\u003c/li\u003e\n\u003cli\u003eFendt, M., Li, L. \u0026amp; Yeomans, J. S. 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(Academic press, 2013).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"prepulse inhibition, blink reflex, postural control, sway, balance control, posturography","lastPublishedDoi":"10.21203/rs.3.rs-6528482/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6528482/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAn unexpected loud sound typically triggers a reflex eye-blink. A reliable pre-warning attenuates reflex blinking, a phenomenon known as \u0026lsquo;pre-pulse inhibition\u0026rsquo; (PPI). PPI is enhanced when standing, suggesting that PPI might contribute to adaptive postural control. Here, we tested whether PPI is modulated under different postural conditions and identifies the determinants of this modulation. Forty-five participants\u0026rsquo; PPI and postural sway were tested while supine, standing on a hard surface, soft surface, and in tandem stance. The effect of visual feedback, auditory (aPPI) and somatosensory (sPPI) prepulse modalities, and different interstimulus-intervals were tested. Compared to hard-surface, PPI is attenuated by soft-surface and tandem standing (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0125). sPPI correlates with sway area during hard surface standing (ρ=+0.321; p\u0026thinsp;=\u0026thinsp;0.032) and sway velocity on tandem standing (ρ=+0.344; p\u0026thinsp;=\u0026thinsp;0.021). While both sPPI and aPPI are modulated, sPPI shows greater inhibition. Abolishing the visual feedback by closing the eyes only minimally reduces sPPI. PPI changes depending on postural demands, with less inhibition during tasks requiring enhanced balance control. This suggests that PPI network adjusts to regulate sensory inputs, enhancing inhibition to prevent sensory overflow when postural control is less demanding and reducing inhibition to increase sensory feedback as task difficulty increases. This study establishes a link between PPI and postural control, which opens the possibility to test PPI as a marker of postural control network activity under specific circumstances.\u003c/p\u003e","manuscriptTitle":"Postural modulation of prepulse inhibition and its link to postural control: Insights from healthy subjects","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-04 13:07:13","doi":"10.21203/rs.3.rs-6528482/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-14T18:01:39+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-11T20:13:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"302607342111933477696617558706172137956","date":"2025-07-04T13:52:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-07T13:43:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"197430895218504432362012158589850467472","date":"2025-06-02T14:56:47+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-01T19:59:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-23T14:01:29+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-05-09T05:31:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-07T11:19:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-04-25T11:19:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7187ced9-0c4b-4c72-85df-d46327771dd3","owner":[],"postedDate":"June 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":49400338,"name":"Biological sciences/Neuroscience"},{"id":49400339,"name":"Biological sciences/Physiology"}],"tags":[],"updatedAt":"2025-12-22T16:00:26+00:00","versionOfRecord":{"articleIdentity":"rs-6528482","link":"https://doi.org/10.1038/s41598-025-27097-4","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-12-20 15:57:25","publishedOnDateReadable":"December 20th, 2025"},"versionCreatedAt":"2025-06-04 13:07:13","video":"","vorDoi":"10.1038/s41598-025-27097-4","vorDoiUrl":"https://doi.org/10.1038/s41598-025-27097-4","workflowStages":[]},"version":"v1","identity":"rs-6528482","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6528482","identity":"rs-6528482","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}