Short latency afferent inhibition differs with load type during isometric finger abduction

Short latency afferent inhibition differs with load type during isometric finger abduction | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Short latency afferent inhibition differs with load type during isometric finger abduction Kangjing Yang, Tatsunori Watanabe, Takayuki Horinouchi, Sumi Miyoshi, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7691656/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Feb, 2026 Read the published version in Journal of Physiological Anthropology → Version 1 posted You are reading this latest preprint version Abstract Background Static muscle contraction involves two distinct load types. One type, called a position task, entails holding the limb in a fixed position while counteracting an inertial load, while the other type, known as a force task, involves exerting a consistent force against a solid constraint. While proprioceptive information has been shown to be required more during the position task, it has remained to be elucidated how sensorimotor integration differs between these two tasks. Methods This study investigated differences in short latency afferent inhibition (SAI) and heteronymous reflex responses between the force and position conditions. Sixteen participants performed static contractions of the first dorsal interosseous (FDI) muscle. In the force task, they exerted a constant force corresponding to 10% maximum voluntary contraction (MVC) against a rigid restraint. In the position task, they sustained a target abduction angle of 20° while holding a load equivalent to 10% MVC. SAI was induced by the paired application of electrical stimulation to the right median nerve and transcranial magnetic stimulation over the left motor cortex at an N20 + 2 msec interval. Motor evoked potentials (MEPs) were recorded from the FDI muscle to quantify the magnitude of SAI. Heteronymous short and long latency reflexes (SLR and LLR) were also examined, and their amplitudes were compared between the force and position tasks. Results SAI was significantly attenuated in the position task ( p < 0.05). Additionally, SLR and LLR amplitudes were significantly greater during position task ( p < 0.05). Conclusions These findings suggest distinct sensorimotor processing strategies depending on the load type. Short-latency afferent inhibition Heteronymous short latency reflex Heteronymous long latency reflex Primary motor cortex Sensorimotor integration Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction The interplay between sensory feedback and motor output is a crucial element of the human motor control system, facilitating precise and adaptive movements. In particular, the capacity to modify the relative weighting of proprioceptive and/or cutaneous sensory feedback information in accordance with the intended movement is crucial for precise control of hand kinematics [ 1 – 5 ]. Exerting a constant force by resisting a rigid constraint (force task) and maintaining a steady limb angle under an identical inertial load (position task) involve distinct neural control strategies, despites these two tasks resulting in comparable net muscle torque as described by Newtonian mechanics. For example, previous studies [ 6 – 8 ] assessing the first dorsal interosseous (FDI) muscle reported that the amplitude of the short-latency reflex (SLR) was greater in the position than force task when elicited by electrical stimulation of the median nerve. The SLR is known to be exclusively regulated by Ia afferents and spinal neuronal networks [ 9 ], and its amplitude can serve as a surrogate marker for presynaptic inhibition of Ia afferents [ 10 ]. Thus, the observed increase in SLR amplitude during the position task suggests that heteronymous afferent input to the motor neuron pool of the FDI is increased due to greater reduction of presynaptic inhibition in this task condition. On the other hand, some studies also reported that the amplitude of the long-latency reflex (LLR) was greater in the position than force task following median nerve stimulation. As the LLR descends the corticospinal tract via the thalamocortical pathway and is regulated by the basal ganglia [ 11 , 12 ], reductions in its amplitude and increases in its latency have been observed in various neurological disorders affecting this pathway. However, this does not necessarily imply that patients with central nervous system lesions will always exhibit abnormal LLR amplitudes or latencies. A recent systematic review have concluded that further detailed research is needed before LLR characteristics can be established as definitive diagnostic criteria [ 13 ]. Therefore, task-related differences in LLR amplitude should not be directly interpreted as evidence of differences in sensory information processing within the central nervous system or in the excitability of the primary motor cortex. Meanwhile, somatosensory evoked potential (SEP) gating, indicated by a reduction in SEP amplitude, was greater during the position than force task when the ulnar nerve was stimulated, an effect not observed with median nerve stimulation [ 7 ]. These findings suggest that proprioceptive information processing differs depending on the load type during static muscle contraction. However, the effect of load type differences on the relationship between somatosensory information processing and motor patterns in the central nervous system, that is on sensorimotor integration, remains unclear. A commonly utilized method for evaluating sensorimotor integration is short latency afferent inhibition (SAI), a protocol based on transcranial magnetic stimulation (TMS) [ 14 – 16 ]. SAI is characterized by a suppression in motor evoked potentials (MEPs) amplitudes following a conditioning afferent electrical stimulation delivered through a peripheral mixed nerve [ 15 , 16 ]. Specifically, when the interval between the peripheral nerve conditioning stimulus and the TMS pulse targeting the primary motor cortex (M1) slightly exceeds the N20 latency of SEPs, the conditioned MEP amplitude is attenuated relative to its unconditioned counterpart [ 14 ]. This reduction is mediated by cholinergic neurons, which facilitate GABAergic interneuron excitation and subsequently suppress pyramidal cells during the relay of sensory inputs from the primary somatosensory cortex (S1) to M1 [ 17 – 19 ]. The magnitude of SAI varies significantly depending on task conditions. Different types of somatosensory stimulation induce varying levels of synchronous S1 activity, with higher S1 activity being associated with greater SAI [ 20 ]. During movement initiation, SAI is significantly reduced in muscles involved in task performance, ensuring that task-related sensory afferents are prioritized [ 21 ]. Furthermore, the intensity of SAI is directly proportional to the burst of sensory afferent input [ 22 ]. From a clinical perspective, particularly in rehabilitation, SAI has provided valuable insights into cholinergic circuit disorders that affect cognition and motor function, including Alzheimer's disease, idiopathic normal pressure hydrocephalus, Parkinson's disease, and dystonia. These findings have established SAI as a reliable neurophysiological indicator of cortical cholinergic activity, making it a useful tool for evaluating interventions targeting cortical cholinergic dysfunction. Based on these findings, the present study may contribute to the development of rehabilitation strategies tailored to individual motor control characteristics and the design of novel intervention methods for neurological disorders. Accordingly, the present study aims to investigate whether the modulation of SAI varies between the force and position tasks. Considering the position task requires more proprioceptive information than the force task, we hypothesized that the ascending sensory information generated by the electrical stimulation of peripheral nerve would be more inhibited during the position task, resulting in a weakened SAI. From a physiological anthropology perspective, the task-specific modulation of SAI observed in this study provides valuable insight into the fundamental mechanisms by which humans adapt to different load conditions through sensory processing adjustments. This knowledge can inform the development of personalized rehabilitation strategies that optimize sensory processing and motor function, especially for patients with proprioceptive deficits, such as stroke survivors. Materials and Methods Participants A priori power analysis was conducted using G*Power [ 23 ], indicating that a sample size of 12 participants was required for an effect size of 0.4 (α = 0.05, power = 0.8). Based on this calculation, we recruited 16 participants through a notification on our laboratory homepage. Sixteen healthy students from Hiroshima University (12 males and 4 females, 24.12 ± 3.85 years old) participated in this study between January 6 and March 31, 2024. All participants were confirmed to be free of diseases and dysfunctions of the nervous and motor systems. The handedness of participants were assessed using the Oldfield Inventory scores (score range: 0.9-1.0), confirming that all participants were right-handed [ 24 ]. Additionally, all individuals demonstrated either normal or corrected-to-normal vision. Informed written consent was secured from each participant prior to initiating the experimental procedures. Ethical approval was granted by the Ethics Committee of Hiroshima University (No. E-2261) and the study adhered to the principles outlined in the Declaration of Helsinki. Experimental setup Participants were seated upright with their right hand positioned in the custom-designed device that has been used in our prior research methodologies (Fig. 1 ) [ 7 , 25 ]. The apparatus included a rotating wheel linked to either a force transducer (TU-QR, TEAC, Tokyo, Japan) or an inertial load connected via a pulley and a nylon line. The participant’s posture was carefully standardized: the right shoulder was abducted at 10–20°, the elbow was maintained at a flexion angle of 110°, and the forearm and wrist were stabilized in a neutral alignment to minimize compensatory movements. The right index finger was secured to a bar attached to the wheel (7.5 cm diameter), aligning the rotational axis of the wheel with the metacarpophalangeal joint’s rotational axis for precise movements. Flexion and extension of the metacarpophalangeal joint and interphalangeal joints were constrained, allowing only abduction-adduction. In addition, the thumb was abducted to an angle of 45°, and the remaining fingers were fixed at fully extended positions. We carefully observed that this posture was maintained at all times while the experiment was being conducted. The participants engaged in two submaximal contraction tasks: the force task and the position task, both performed at equivalent torque levels. During the force task (Fig. 1 A), they sustained a force level of 10% of their maximum voluntary contraction (MVC) at the index metacarpophalangeal joint, positioned at 20˚ of abduction. During the position task (Fig. 1 B), they maintained the same abduction angle of 20˚ while resisting an inertial load corresponding to 10% MVC. An electro-goniometer (SG65, Biometrics, Gwent, UK) measured the abduction-adduction angle during the position task. Visual feedback related to joint angle and force was displayed on a monitor (LCD-MF235XDBR, I–O Data, Japan) located 1 m ahead of the participants, and the online visual feedback was shown as red line for the force task and blue line for the position task progressing with time from left to right using LabChart 8 (AD Instruments, Bella Vista, Australia). The participants were instructed to match their force or position to a gray horizontal target line and maintain the target force or angle as steadily and accurately as possible. The feedback gain was calibrated to 2.5% / cm, corresponding to the maximal performance range during the position task and to the MVC level for the force task [ 7 , 25 – 27 ]. The force and electro-goniometer signals were low-pass filtered at 20 Hz and digitized at 10 kHz (PowerLab, AD Instruments, Bella Vista, Australia). The processed data was saved for subsequent offline analysis using LabChart 8 (AD Instruments, Bella Vista, Australia). EMG signals were acquired from the right FDI muscle using disposable Ag/AgCl surface electrodes. The acquired signals underwent a series of processing steps, including amplification to ×100 (FA-DL-160, 4 Assist, Tokyo, Japan), band-pass filtering between 5 and 500 Hz, and digitization at 10 kHz using PowerLab (AD Instruments, Australia). The data were stored for off-line analysis (LabChart 8, AD Instruments, Bella Vista, Australia). Protocol During all protocols, the force and position tasks were always performed under the visual feedback described above. At the beginning of the session, we assessed maximum voluntary contraction (MVC) of the right index finger abduction. The procedure for assessing MVC followed the previously established protocol [ 7 , 25 ], where participants gradually increased their force output from rest to maximum over 3 sec and held the peak force for an additional 3 sec with verbal encouragement. MVC was measured at least three times for each participant with 90 sec rest intervals between trials. If the peak of force values across trials exhibited a variation within 5%, the highest value was considered as the fine MVC. Otherwise, additional trials were conducted until a variation of 5% or less was achieved (the MVC trials were carried out 3–5 times). The highest MVC value was subsequently used to define submaximal contraction levels. Next, to familiarize the participants with the tasks, they performed 30-sec static contractions of the FDI muscle at 10% MVC for the force task and at 20°abduction for the position task. They executed both tasks twice in a randomized order, with a 1-min rest between trials. To ensure task accuracy, the absolute error rate of torque in the force task and the angle in the position task was monitored. If the error exceeded 5%, participants practiced again until it was within the determined range (the number of trials ranged from 2 to 5). Then, they performed 1-min static contractions for each task twice, in a randomized order, with a 1-min rest between trials, during which median nerve stimulation was applied at a rate of 0.1–0.2 Hz with 6–8 stimulations per task (Fig. 2 A). The absolute error rate and EMG amplitude were reassessed to confirm consistency. After the familiarization, the latency of the N20 component of SEPs was measured at rest (Fig. 2 B). Subsequently, the SAI was recorded at rest and during both tasks (Fig. 2 C), and the SLRs and LLRs were recorded during both tasks (Fig. 2 D). The recordings of SAI and SLRs/LLRs were conducted in separate submaximal contraction trials in a randomized order. Each trial lasted approximately 50 sec, with a 60-sec rest period between trials to avoid fatigue. To minimize the influence of transient force fluctuations, stimuli were delivered when the force and position signals had reached their respective targets and remained stable for at least 1 sec. Throughout the recordings, we monitored the EMG activity of the right FDI muscle to ensure consistency between the two tasks. N20 latency measurement An Ag/AgCl electrode was positioned 2cm posterior to the C3 (C3’) site according to the international 10–20 system and a reference electrode attached to the right earlobe. Stimulation of the right median nerve was applied using a road electrode, with the anode placed distally. A total of 300 stimulations were delivered by a constant current stimulator (Digitimer DS3, Digitimer, Welwyn Garden City, UK) in the form of 0.2 msec square-wave pulses at 3.3 Hz. The stimulus intensity was set to 1.2 times the motor threshold required to evoke contraction in the right FDI muscle. The resulting signals were averaged across 300 epochs to calculate the latency of SEPs N20. MEPs and SAI recordings There were three conditions: rest, force task, and position task. TMS was performed using a 70-mm Fig-of-eight coil connected to a monophasic magnetic stimulator (Magstim 200, Magstim, Carmarthenshire, UK). The coil was aligned over the left M1 and maintained at 45° to the sagittal plane. The motor hotspot was located as the position where consistent stimulation above the threshold produced the largest MEP in the FDI muscle. The resting motor threshold (RMT) and active motor threshold (AMT) were defined as minimal stimulus intensities capable of eliciting consistent 1 mV MEPs at rest and during muscle contraction, respectively. RMT was used for rest, whereas the AMT was used for the force and position conditions. SAI was elicited by a brief suprathreshold electrical stimulation of the right median nerve before applying TMS. The interstimulus interval between electrical stimulation and TMS was set to the latency of the N20 + 2 msec, and the intertrial interval was set to 4000 ± 200 msec. There were two blocks for each condition (rest, force task, and position task). In each block of 12 TMS trials, the right median nerve stimulation was randomly provided 6 times. Thus, within each condition, 12 MEPs were conditioned, and 12 MEPs were not conditioned. Each condition was performed in a random order, and each block was separated by a rest period of 60 sec to avoid fatigue. SLRs and LLRs Electrode position and stimulus intensity for the right median nerve stimulation were described above. This approach enables the evaluation of the agonist response to feedback from low-threshold afferent inputs without activating the antagonist muscle, minimizing contamination from F-wave [ 28 ]. The stimulation frequency and duration were set as 1.3 Hz and 1 msec, respectively. Reflexes were recorded 100 times in two blocks of 50 stimulations each, for both position and force tasks in a randomized order. Each block was separated by a rest period of 60 sec to avoid fatigue. Potentials were amplified and band-pass filtered (1–3000 Hz). Data analysis To quantify the maximum EMG activity of the right FDI muscle, EMG activity during MVC trials was rectified and averaged over a 1-sec window centered on the peak force. The EMG recorded during static contraction in two tasks was normalized to the EMG amplitude during MVC (%EMG). Using data during task familiarization, we evaluated the absolute error rate (AER) and background EMG (BEMG) during the two tasks. Specifically, we calculated the average EMG amplitude and force/angle values during the middle 20 sec s of a 30-sec static contractions, without median nerve stimulation, at 10% MVC in the force task or at 20° of abduction in the position task. Also, we calculated the average EMG and force/angle values over 1-s period, with 500 msec before and after median nerve stimulation. The AER of force and angle was calculated using the following formula: $$\:\text{A}\text{E}\text{R}=\frac{\left|Measured\:Value-Target\:Value\right|}{Target\:Value}\:\times\:100$$ Reproducibility of BEMG and AER for the two tasks was verified in all 16 participants. Due to the limited number of channels on the A/D converter and constraints of the analysis software, force and angle were not recorded during the SAI and SLR/LLR recordings. For the SAI and SLR/LLR measurements, only the reproducibility of BEMB was evaluated. The magnitude of SAI was quantified as the percentage change in the average amplitude of MEPs, calculated as follows: %SAI = [unconditioned MEPs — conditioned MEPs] / unconditioned MEPs To evaluate the BEMG during SAI recording, the average amplitude was calculated over a 100-msec window preceding median nerve stimulation. The amplitudes of SLRs and LLRs were determined by subtracting the average BEMG activity, computed over a 50-msec period preceding right median nerve stimulation, from the peak amplitude after rectifying the EMG [ 6 – 8 ]. They were defined as the difference between baseline and peak values: SLR/LLR amplitude = Peak - BEMG The SLR (20–50 msec post-stimulation) and LLR (50–100 msec post-stimulation) were analyzed over a time window extending from 50 msec before to 200 msec after stimulation. After the automatic removal of trials with excessive artifacts by the software, a total of 100 trails were summed on average to obtain a waveform for each participant and each task. Statistical analysis was conducted using MATLAB R2023b (The MathWorks, Inc., Natick, MA, USA) and OriginPro 2025 (OriginLab Corporation, Northampton, MA, USA). Results are presented as mean values with standard errors of the mean. We utilized the Shapiro-Wilk test to verify the normality of the data distribution. BEMG amplitudes and the AER with and without median nerve stimulation during the two tasks were compared using two-way repeated measures analysis of variance (ANOVA). Intraclass correlation coefficients, ICC (2,1), were used to measure the reproducibility of inter-load type BEMG activity for the FDI and the AER of force and angle. The %SAI was compared between conditions (rest, force task, and position task) using one-way repeated measures ANOVA. Post-hoc tests were performed using Tukey’s honest significant difference (HSD) for all relevant pairwise comparisons. SLR and LLR amplitudes were compared between the force and position tasks using a paired t-test. The significance level was set at p < 0.05. Results Figure 3 A shows raw waveforms of EMG activity, muscle torque, and metacarpophalangeal joint angle recorded from a representative subject during MVC and submaximal static contraction for the force and position tasks, both with and without median nerve stimulation during task familiarization. The mean torque and EMG activity during MVC across all subjects were 0.968 ± 0.075 Nm and 0.895 ± 0.085 mV, respectively. The BEMG of the FDI muscle with and without median nerve stimulation during the force task (0.091 ± 0.008 mV and 0.096 ± 0.010 mV, respectively) and the position task (0.090 ± 0.008 mV and 0.094 ± 0.010 mV, respectively) did not differ significantly (all p > 0.076) (Fig. 3 B). These EMG activities corresponded to about 10–11% of MVC, which was consistent with the load intensity of 10% of maximum muscle strength. Similarly, the AERs with and without median nerve stimulation during the force task (2.033 ± 0.228% and 2.054 ± 0.188%, respectively) and the position task (1.548 ± 0.201% and 1.575 ± 0.194%, respectively) did not show significant differences (all p > 0.110) (Fig. 3 C). The mean latency of SEPs component of N20 was 19.731 ± 0.473 msec. Figure 4 A shows raw MEP waveforms recorded during SAI measurements, both with and without conditioning electrical stimulation at rest and during the force and position task, from a representative participant. Light gray lines indicate MEP waveforms from all 12 trials, while thick lines indicate the average waveforms. Figure 4 B shows representative raw, rectified, and averaged EMG waveforms from SLR and LLR recordings during the force and position tasks. As shown in Fig. 5 A, the average %SAI was highest during the rest (0.593 ± 0.037), followed by the force task (0.399 ± 0.056), and was lowest during the position task (0.226 ± 0.060). One-way repeated measures ANOVA revealed a significant main effect of task condition on %SAI (F (2,30) = 16.118, p < 0.001, partial η 2 = 0.518). Tukey’s HSD post-hoc analysis identified significant %SAI differences among task conditions, with the rest differing from both the position ( p = 0.0003) and force ( p = 0.041) tasks, and the force differing from the position tasks ( p = 0.009). BEMG during SAI recording were 0.084 ± 0.007 mV in the force task and 0.085 ± 0.007 mV in the position task. There was no significant difference between the two tasks ( p = 0.906), and BEMG was highly reproducible (ICC (2,1) = 0.958, p < 0.001). The amplitude of SLR was higher during the position than force task (force task: 0.092 ± 0.025 mV, position task: 0.109 ± 0.028 mV; p = 0.020) (Fig. 6 A). The amplitude of LLR was also higher during the position than force task (force task: 0.029 ± 0.006 mV, position task: 0.043 ± 0.007 mV; p = 0.003) (Fig. 6 B). BEMG during SLR and LLR recordings were 0.095 ± 0.008 mV in the force task and 0.097 ± 0.011 mV in the position task. There was no significant difference between the two tasks ( p = 0.662), and BEMG was highly reproducible (ICC (2,1) = 0.908, p < 0.001). Discussion A novel observation in our study was that, during static contraction of the FDI muscle at 10% MVC and 20 degrees of abduction, %SAI was significantly smaller during the position task than the force tasks. In line with previous reports [ 6 – 8 ], the amplitude of the heteronymous SLR was significantly greater during the position than force task. Furthermore, the amplitude of heteronomy LLR was greater during the position than force task, as reported in earlier studies [ 7 , 8 ]. These findings suggest the position task requires more proprioceptive information and involves different sensorimotor integration mechanisms compared to the constant finger force task. In this study, we found that %SAI was weaker during movement (force and position tasks) compared with rest. This pattern has also been described in previous studies [ 29 ], suggesting that voluntary motor commands may partially override or modulate afferent inhibition. More importantly, %SAI was weaker in the position than force tasks. Before interpreting our results, it should be noted that under the same experimental setup used in our SAI experiment, the latency of the N20 component of SEP evoked by median nerve stimulation did not show significant differences between the force and position tasks [ 7 , 25 ], indicating that differences in stimulation timing for SAI measurement due to load type are not a significant factor. Our finding of greater reduction of SAI in position task may be related to SEPs gating, as suggested by previous research [ 30 – 32 ]. SEPs gating is the phenomenon where SEPs are reduced during voluntary movement compared to rest [ 33 – 37 ], which is believed to reflect the filtering of irrelevant sensory information during movement, allowing only essential inputs to be processed [ 34 , 35 , 38 ]. This mechanism, which modulates the influence of sensory input on the motor cortex, helps optimize motor responses and varies according to different motor perceptual demands [ 25 , 39 , 40 ]. In previous studies of position and force tasks, the P45 component was found to be larger during the position task, while the N33 component was larger during the force task, indicating different cortical processing of sensory inputs [ 7 , 25 ]. Since the peripheral mixed nerve stimulation used in this study to evaluate SAI primarily stimulates larger diameter Group Ia sensory nerves, the position task which requires more proprioceptive information may have involved greater filtering of information from Group Ia sensory nerves derived from the electrical stimulation. This could have resulted in decreased inhibitory input from S1 to M1, consequently leading to reduced SAI. The gating of SEPs, interpreted as being related to the attenuation of SAI, arises not only from the competition between afferent signals following electrical stimulation and those associated with the motor output itself (afferent gating) but also from a central mechanism where output from the motor center suppresses the sensory afferent pathway (efferent gating). This is supported by findings showing that SEPs gating can occur before movement onset [ 7 ]. Given that SEPs gating can occur at any stage along the afferent sensory pathway, or within the cerebral cortex, the mechanism underlying the reduced SAI in the position task relative to the force task should be explored in the context of efferent gating mechanisms. The amplitudes of SLRs and LLRs have been reported to be greater during the position than force task [ 6 – 8 ], and our findings are consistent with the previous studies. Furthermore, the results of the present study, conducted at 10% MVC, were similar to those of previous studies conducted at 20% MVC [ 7 , 8 ] or at multiple load intensities of 20%, 40%, and 60% MVC [ 6 ], supporting the view that differences in reflex responses depend on the load type rather than differences in voluntary contraction force [ 6 ]. SLR is known to be regulated exclusively by Ia afferents and spinal neural networks [ 9 ], and its amplitude can serve as a surrogate marker for presynaptic inhibition of Ia afferents [ 10 ]. The observed increase in SLR amplitude during the position task thus suggests that Ia afferent excitation was enhanced under this condition. Meanwhile, LLRs involve spinal circuits and supraspinal circuits including M1 [ 12 , 41 – 44 ]. Therefore, the increased amplitude of LLRs can indicate enhanced excitability of spinal α-motoneurons projected from the M1. To prevent simultaneous activation of the FDI and its antagonist and to minimize contamination of the F-wave recordings [ 28 ], most previous studies have used a heteronymous pathway to elicit the SLR from the FDI [ 6 , 8 , 45 ]. Since the F-wave represents the response of motor neurons to an antidromic volley [ 46 , 47 ], it does not occur when activating a heteronymous pathway. On the other hand, co-contraction can occur under unstable load conditions, significantly increasing the background muscle activity of the agonist group [ 48 , 49 ], which may contribute to increased heteronymous SLR amplitudes. However, both in previous studies and the present one, we did not observe an increase in muscle activity during the unstable position task compared to the stable force task. Nonetheless, it remains possible that the activity of muscles involved in adduction (such as the palmar interosseous muscle) increased to an extent that did not affect the abduction torque of the index finger. Recently, a non-invasive method for measuring hand muscle activity using surface EMG has been developed [ 50 ]. Future studies should adopt this method to conduct more detailed investigations. Clinical Application Somatosensory discrimination training, such as limb position discrimination, has been demonstrated to enhance sensory functions in stroke patients [ 51 , 52 ]. Our study indicates greater Ia facilitation during the position task compared to the force task. The difference may be related to the decreased mechanical stability during the position task. Thus, the position task may be useful to enhance postural stability and fine motor control in patients with proprioceptive deficits post-stroke [ 53 , 54 ]. Additionally, the magnitude of SAI can correlate with motor deficits and prognosis in stroke patients, suggesting that SAI could serve as a neurophysiological biomarker for predicting post-stroke outcomes and a guidance for personalized rehabilitation strategies [ 55 , 56 ]. Greater understanding of task-dependent modulation of SAI may allow clinicians to develop proper rehabilitation protocols that optimize sensory processing and motor function. Limitations and Future Directions Firstly, several methodological aspects regarding SAI measurement parameters warrant attention. The intensity of the electrical stimulation (1.2×motor threshold) for the median nerve may have approached the saturation point of the sensory nerve action potential (SNAP). Future studies should optimize this by selecting a conditioning intensity between 25% and 40% of SNAP (max), as determined by an SNAP stimulus-response curve [ 22 ]. Additionally, the TMS intensity used to evoke 1mV MEPs based on RMT/AMT might have been too strong. Higher TMS intensities can paradoxically reduce or abolish SAI, which could decrease sensitivity to inhibition [ 19 ]. A better approach is to construct an MEP input–output curve at rest [ 57 ] and select an intensity that elicits 0.5–1.0 mV MEPs. This intensity should be applied consistently across conditions to ensure a sensitive SAI measurement. Secondly, no data on task performance during the force and position tasks were collected. While the primary aim of this study was to compare SAI, SLR, and LLR between these two tasks, task performance data would have strengthened our discussion. Thirdly, we did not assess fatigue during the experiment. Although there were no differences in EMG amplitude between tasks, the potential effects of fatigue should have been considered. Future studies should incorporate fatigue assessments to determine whether it influences SAI, SLR, and LLR responses. Finally, we only focused on SAI, despite the widely recognized interaction between SAI and short-interval cortical inhibition (SICI) [ 15 , 16 , 56 ]. In particular, it has been suggested that a decrease in SAI could be accompanied by an increase in SICI [ 16 ]. Thus, whether SICI also exhibits the load-dependent difference in SAI remains to be elucidated. Moreover, intraneural microsimulation has been considered an ideal method for investigating cutaneous versus proprioceptive contributions [ 16 ]. Future investigations should consider this method to study SAI during the force and position tasks. Additionally, future studies should utilize electroencephalography to further elucidate the neural mechanisms underlying the difference in SAI between two tasks. Incorporating additional sensory inputs, such as visual and auditory cues, may also provide a more comprehensive understanding of how these factors modulate sensorimotor integration and SAI during position and force tasks. Conclusion This study demonstrated a significantly smaller SAI during position than force task. This finding highlights the load type-specific modulation of SAI, reflecting distinct sensorimotor processing strategies that are adapted to different load conditions. Abbreviations SAI, short latency afferent inhibition; MVC, maximum voluntary contraction; M1, primary motor cortex; S1, primary somatosensory cortex; TMS, transcranial magnetic stimulation; MEP, motor evoked potential, SEP, somatosensory evoked potential; SLRs and LLRs, heteronymous short and long latency reflexes; FDI, first dorsal interosseous muscle; EMG, electromyography; RMT, resting motor threshold; AMT, active motor threshold; ANOVA, analysis of variance; Tukey’s HSD, Tukey’s honest significant difference; AER, absolute error rate; BEMG, background EMG; SNAP, sensory nerve action potential; SICI, short-interval cortical inhibition. Declarations Ethics approval and consent to participate Written informed consent was obtained from all participants before beginning the experiment, which was conducted according to principles of the Declaration of Helsinki. The experimental protocol was also approved by the Ethics Committee for Epidemiology of Hiroshima University (No. E-2261) and was conducted according to principles of the Declaration of Helsinki Consent for publication Not applicable. Availability of data and materials The datasets generated and/or analyzed during the present study are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests. Funding This research was partially supported by Grants-in-Aid (KAKENHI) from the Japan Society for the Promotion of Science [22K1777 (TW), 23KJ1643 (TH), 23K14734 (KS), 24K20530 (SD), 22H03454 (HK), and 24K21309 (HK)]. Authors’ contributions Kangjing Yang: Conceptualization, Methodology, Formal analysis, Investigation, Data curation, Writing – original draft, Visualization. Tatsunori Watanabe: Supervision, Writing – original draft & editing, Funding acquisition. Takayuki Horinouchi: Conceptualization, Methodology, Investigation, Writing – original draft, Funding acquisition. Sumi Miyoshi: Conceptualization, Methodology, Formal analysis, Writing – original draft. Jingnan Li: Conceptualization, Methodology, Formal analysis, Writing – original draft. Kazuya Saita: Conceptualization, Writing – original draft & editing, Funding acquisition. Shota Date: Conceptualization, Writing – original draft & editing, Funding acquisition. Hikari Kirimoto: Supervision, Writing – original draft & editing, Funding acquisition. Acknowledgments We would like to extend our sincere appreciation to all participants whose involvement and commitment were indispensable to the completion of this study. References Enders LR, Seo NJ. Effects of Sensory Deficit on Phalanx Force Deviation During Power Grip Post Stroke. J Mot Behav. 2017;49(1):55-66. doi: 10.1080/00222895.2016.1191416. Johansson RS, Flanagan JR. 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J Neuroeng Rehabil. 2014;11:40. doi: 10.1186/1743-0003-11-40. Additional Declarations No competing interests reported. Supplementary Files S1Dataset.xlsx Cite Share Download PDF Status: Published Journal Publication published 25 Feb, 2026 Read the published version in Journal of Physiological Anthropology → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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12:24:03","extension":"tif","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":300356,"visible":true,"origin":"","legend":"","description":"","filename":"Fig6.tif","url":"https://assets-eu.researchsquare.com/files/rs-7691656/v1/780e9f6f98fd03ed2a9fcd38.tif"},{"id":93774257,"identity":"02d21317-f8be-408f-a936-d3fecfe153b4","added_by":"auto","created_at":"2025-10-17 12:24:04","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":83275,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig1.png","url":"https://assets-eu.researchsquare.com/files/rs-7691656/v1/5ad029b397a995d02c864237.png"},{"id":93774231,"identity":"cf36a9df-97e0-4a67-8e6e-1b945038a938","added_by":"auto","created_at":"2025-10-17 12:24:02","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":95172,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig2.png","url":"https://assets-eu.researchsquare.com/files/rs-7691656/v1/d4686a6450999973bc6103ad.png"},{"id":93774227,"identity":"004bc037-96f5-4186-833b-21d2cad4f522","added_by":"auto","created_at":"2025-10-17 12:24:02","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":94975,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig3.png","url":"https://assets-eu.researchsquare.com/files/rs-7691656/v1/2512df1ca17330bdb40d4623.png"},{"id":93774256,"identity":"0c6c803e-eca5-490a-be04-b4885c1745e0","added_by":"auto","created_at":"2025-10-17 12:24:04","extension":"png","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":152551,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig4.png","url":"https://assets-eu.researchsquare.com/files/rs-7691656/v1/c0a2d6f3dd8e5c35b2fa5329.png"},{"id":93774251,"identity":"b3e01771-3ea0-43ec-9cff-cc9c91e565ba","added_by":"auto","created_at":"2025-10-17 12:24:04","extension":"png","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":50730,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig5.png","url":"https://assets-eu.researchsquare.com/files/rs-7691656/v1/d6089713a34db01c8090560c.png"},{"id":93774248,"identity":"bff95935-b9f7-42e6-8daa-5b52dd3deb4d","added_by":"auto","created_at":"2025-10-17 12:24:04","extension":"png","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":64582,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig6.png","url":"https://assets-eu.researchsquare.com/files/rs-7691656/v1/ef11894fb3a611cdc78dcda2.png"},{"id":93774241,"identity":"6e8c8576-a516-427c-ae95-2280a30ee455","added_by":"auto","created_at":"2025-10-17 12:24:03","extension":"xml","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":142599,"visible":true,"origin":"","legend":"","description":"","filename":"6eb89bdfb4ed4d2a8ae044213b142e011structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7691656/v1/e9254010459f9542a6c8ac01.xml"},{"id":93774262,"identity":"7edb4de8-c595-4677-b1f4-44ee42f68809","added_by":"auto","created_at":"2025-10-17 12:24:05","extension":"html","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":156712,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7691656/v1/7b869d4133a6086f4874a12c.html"},{"id":93774254,"identity":"9643f03d-47db-4ef4-b591-0fd4b4d795f5","added_by":"auto","created_at":"2025-10-17 12:24:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":869903,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIllustration of the experimental setup depicting the force and position tasks.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe apparatus involved a rotating wheel linked to either a force transducer (A) or inertial load (B) through a pulley system and nylon cord. An electro-goniometer was attached to the right hand during the position task to measure the angle of metacarpophalangeal joint abduction [25].\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-7691656/v1/749465a6482c70869af6da87.png"},{"id":93774253,"identity":"d21eeb11-91f0-4d53-8baf-f11547a450ef","added_by":"auto","created_at":"2025-10-17 12:24:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":582464,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExperimental procedure\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eExperimental procedure for MVC and familiarization of tasks (A), the N20 components of SEPs measurement (B), SAI recordings (C), and heteronymous reflex responses recordings (D). During SAI measurement, TMS was presented in a random order with and without conditioning electrical stimulation to the median nerve. The recordings of SAI and SLRs/LLRs were conducted in separate submaximal contraction trials in a randomized order.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-7691656/v1/d2b84c218ebfe40c8e729ba2.png"},{"id":93775585,"identity":"17b25081-0577-41a4-a6c2-eedbb2327f52","added_by":"auto","created_at":"2025-10-17 12:32:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":759072,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRaw waveforms of EMG, torque, and metacarpophalangeal joint angle during MVC and submaximal static contraction.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Raw waveforms recorded from a representative subject during MVC and submaximal static contraction in force and position tasks, with and without median nerve stimulation (ES). EMG activity and muscle torque during MVC are shown in black, muscle torque during the force tasks, with and without ES, is shown in red, and joint angle during the position tasks is shown in blue. (B) Box plots show reproducibility of BEMG. (C) Box plots show absolute error rates (AER) during two tasks, with and without ES.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-7691656/v1/c6e4997a82dba8c6532b29d3.png"},{"id":93774246,"identity":"2b6bd85d-0501-44fd-b92b-edee796b67be","added_by":"auto","created_at":"2025-10-17 12:24:03","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1191840,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRaw waveforms of SAI and SLRs and LLRs recorded from a representative participant.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Representative raw MEP waveforms elicited by single-pulse TMS and TMS with a conditioning electrical stimulation (ES) during rest and the force and position tasks. Light gray lines indicate MEP waveforms from all 12 trials, while thick lines indicate the average waveforms. A reduction in MEP amplitude with conditioned median nerve stimulation (SAI) compared to single pulse MEPs (%SAI) is observed during the position task compared to rest and the force task. (B) Raw, rectified, and averaged EMG waveforms from SLR and LLR recordings during the force and position tasks. The amplitudes of the SLR and LLR are greater during the position task compared to the force task.\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-7691656/v1/7fc1e6c27beae1e11f6faf78.png"},{"id":93774232,"identity":"f190a143-dd4d-439f-a56c-bff71ed9c3ea","added_by":"auto","created_at":"2025-10-17 12:24:02","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":355653,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferences in %SAI between tasks and reproducibility of BEMG.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Box plots of %SAI during rest, force, and position tasks. Significant differences are marked with asingleasterisk (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05), a double asterisk (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01) and triple asterisk (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). (B) Intraclass correlation coefficients (ICC) of BEMG between the two tasks.\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-7691656/v1/9c08d8bc07c4cb8ddda6c227.png"},{"id":93774261,"identity":"7a4a7e8e-74ad-4a04-a507-f9941e38c93a","added_by":"auto","created_at":"2025-10-17 12:24:05","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":487377,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferences in the amplitudes of the SLRs and LLRs between tasks and reproducibility of BEMG.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Box plots comparing reflex amplitudes for SLR between tasks. (B) Box plots comparing reflex amplitudes for LLR between tasks. Statistically significant differences are marked with an asterisk (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) and a double asterisk (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01). (C) Intraclass correlation coefficients (ICC) of BEMG between the two tasks.\u003c/p\u003e","description":"","filename":"Fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-7691656/v1/7c460fb852280b939d47d89b.png"},{"id":103765466,"identity":"f6f06a48-5994-4274-b542-6760d1129450","added_by":"auto","created_at":"2026-03-02 16:02:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4985993,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7691656/v1/e54d607c-c1ab-48d6-9226-d67b1e76b183.pdf"},{"id":93774236,"identity":"f5751a4c-0ca1-42af-b10d-bc97b6ccb9f1","added_by":"auto","created_at":"2025-10-17 12:24:02","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":32334,"visible":true,"origin":"","legend":"","description":"","filename":"S1Dataset.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7691656/v1/d8446dbe92e9f1db7efd483d.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Short latency afferent inhibition differs with load type during isometric finger abduction","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe interplay between sensory feedback and motor output is a crucial element of the human motor control system, facilitating precise and adaptive movements. In particular, the capacity to modify the relative weighting of proprioceptive and/or cutaneous sensory feedback information in accordance with the intended movement is crucial for precise control of hand kinematics [\u003cspan additionalcitationids=\"CR2 CR3 CR4\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eExerting a constant force by resisting a rigid constraint (force task) and maintaining a steady limb angle under an identical inertial load (position task) involve distinct neural control strategies, despites these two tasks resulting in comparable net muscle torque as described by Newtonian mechanics. For example, previous studies [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] assessing the first dorsal interosseous (FDI) muscle reported that the amplitude of the short-latency reflex (SLR) was greater in the position than force task when elicited by electrical stimulation of the median nerve. The SLR is known to be exclusively regulated by Ia afferents and spinal neuronal networks [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], and its amplitude can serve as a surrogate marker for presynaptic inhibition of Ia afferents [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Thus, the observed increase in SLR amplitude during the position task suggests that heteronymous afferent input to the motor neuron pool of the FDI is increased due to greater reduction of presynaptic inhibition in this task condition. On the other hand, some studies also reported that the amplitude of the long-latency reflex (LLR) was greater in the position than force task following median nerve stimulation. As the LLR descends the corticospinal tract via the thalamocortical pathway and is regulated by the basal ganglia [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], reductions in its amplitude and increases in its latency have been observed in various neurological disorders affecting this pathway. However, this does not necessarily imply that patients with central nervous system lesions will always exhibit abnormal LLR amplitudes or latencies. A recent systematic review have concluded that further detailed research is needed before LLR characteristics can be established as definitive diagnostic criteria [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Therefore, task-related differences in LLR amplitude should not be directly interpreted as evidence of differences in sensory information processing within the central nervous system or in the excitability of the primary motor cortex. Meanwhile, somatosensory evoked potential (SEP) gating, indicated by a reduction in SEP amplitude, was greater during the position than force task when the ulnar nerve was stimulated, an effect not observed with median nerve stimulation [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These findings suggest that proprioceptive information processing differs depending on the load type during static muscle contraction. However, the effect of load type differences on the relationship between somatosensory information processing and motor patterns in the central nervous system, that is on sensorimotor integration, remains unclear.\u003c/p\u003e\u003cp\u003eA commonly utilized method for evaluating sensorimotor integration is short latency afferent inhibition (SAI), a protocol based on transcranial magnetic stimulation (TMS) [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. SAI is characterized by a suppression in motor evoked potentials (MEPs) amplitudes following a conditioning afferent electrical stimulation delivered through a peripheral mixed nerve [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Specifically, when the interval between the peripheral nerve conditioning stimulus and the TMS pulse targeting the primary motor cortex (M1) slightly exceeds the N20 latency of SEPs, the conditioned MEP amplitude is attenuated relative to its unconditioned counterpart [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. This reduction is mediated by cholinergic neurons, which facilitate GABAergic interneuron excitation and subsequently suppress pyramidal cells during the relay of sensory inputs from the primary somatosensory cortex (S1) to M1 [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The magnitude of SAI varies significantly depending on task conditions. Different types of somatosensory stimulation induce varying levels of synchronous S1 activity, with higher S1 activity being associated with greater SAI [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. During movement initiation, SAI is significantly reduced in muscles involved in task performance, ensuring that task-related sensory afferents are prioritized [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Furthermore, the intensity of SAI is directly proportional to the burst of sensory afferent input [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. From a clinical perspective, particularly in rehabilitation, SAI has provided valuable insights into cholinergic circuit disorders that affect cognition and motor function, including Alzheimer's disease, idiopathic normal pressure hydrocephalus, Parkinson's disease, and dystonia. These findings have established SAI as a reliable neurophysiological indicator of cortical cholinergic activity, making it a useful tool for evaluating interventions targeting cortical cholinergic dysfunction. Based on these findings, the present study may contribute to the development of rehabilitation strategies tailored to individual motor control characteristics and the design of novel intervention methods for neurological disorders.\u003c/p\u003e\u003cp\u003eAccordingly, the present study aims to investigate whether the modulation of SAI varies between the force and position tasks. Considering the position task requires more proprioceptive information than the force task, we hypothesized that the ascending sensory information generated by the electrical stimulation of peripheral nerve would be more inhibited during the position task, resulting in a weakened SAI. From a physiological anthropology perspective, the task-specific modulation of SAI observed in this study provides valuable insight into the fundamental mechanisms by which humans adapt to different load conditions through sensory processing adjustments. This knowledge can inform the development of personalized rehabilitation strategies that optimize sensory processing and motor function, especially for patients with proprioceptive deficits, such as stroke survivors.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eParticipants\u003c/p\u003e\u003cp\u003eA priori power analysis was conducted using G*Power [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], indicating that a sample size of 12 participants was required for an effect size of 0.4 (α\u0026thinsp;=\u0026thinsp;0.05, power\u0026thinsp;=\u0026thinsp;0.8). Based on this calculation, we recruited 16 participants through a notification on our laboratory homepage. Sixteen healthy students from Hiroshima University (12 males and 4 females, 24.12\u0026thinsp;\u0026plusmn;\u0026thinsp;3.85 years old) participated in this study between January 6 and March 31, 2024. All participants were confirmed to be free of diseases and dysfunctions of the nervous and motor systems. The handedness of participants were assessed using the Oldfield Inventory scores (score range: 0.9-1.0), confirming that all participants were right-handed [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Additionally, all individuals demonstrated either normal or corrected-to-normal vision. Informed written consent was secured from each participant prior to initiating the experimental procedures. Ethical approval was granted by the Ethics Committee of Hiroshima University (No. E-2261) and the study adhered to the principles outlined in the Declaration of Helsinki.\u003c/p\u003e\u003cp\u003eExperimental setup\u003c/p\u003e\u003cp\u003eParticipants were seated upright with their right hand positioned in the custom-designed device that has been used in our prior research methodologies (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The apparatus included a rotating wheel linked to either a force transducer (TU-QR, TEAC, Tokyo, Japan) or an inertial load connected via a pulley and a nylon line. The participant\u0026rsquo;s posture was carefully standardized: the right shoulder was abducted at 10\u0026ndash;20\u0026deg;, the elbow was maintained at a flexion angle of 110\u0026deg;, and the forearm and wrist were stabilized in a neutral alignment to minimize compensatory movements. The right index finger was secured to a bar attached to the wheel (7.5 cm diameter), aligning the rotational axis of the wheel with the metacarpophalangeal joint\u0026rsquo;s rotational axis for precise movements. Flexion and extension of the metacarpophalangeal joint and interphalangeal joints were constrained, allowing only abduction-adduction. In addition, the thumb was abducted to an angle of 45\u0026deg;, and the remaining fingers were fixed at fully extended positions. We carefully observed that this posture was maintained at all times while the experiment was being conducted. The participants engaged in two submaximal contraction tasks: the force task and the position task, both performed at equivalent torque levels. During the force task (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), they sustained a force level of 10% of their maximum voluntary contraction (MVC) at the index metacarpophalangeal joint, positioned at 20˚ of abduction. During the position task (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), they maintained the same abduction angle of 20˚ while resisting an inertial load corresponding to 10% MVC. An electro-goniometer (SG65, Biometrics, Gwent, UK) measured the abduction-adduction angle during the position task. Visual feedback related to joint angle and force was displayed on a monitor (LCD-MF235XDBR, I\u0026ndash;O Data, Japan) located 1 m ahead of the participants, and the online visual feedback was shown as red line for the force task and blue line for the position task progressing with time from left to right using LabChart 8 (AD Instruments, Bella Vista, Australia). The participants were instructed to match their force or position to a gray horizontal target line and maintain the target force or angle as steadily and accurately as possible. The feedback gain was calibrated to 2.5% / cm, corresponding to the maximal performance range during the position task and to the MVC level for the force task [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe force and electro-goniometer signals were low-pass filtered at 20 Hz and digitized at 10 kHz (PowerLab, AD Instruments, Bella Vista, Australia). The processed data was saved for subsequent offline analysis using LabChart 8 (AD Instruments, Bella Vista, Australia). EMG signals were acquired from the right FDI muscle using disposable Ag/AgCl surface electrodes. The acquired signals underwent a series of processing steps, including amplification to \u0026times;100 (FA-DL-160, 4 Assist, Tokyo, Japan), band-pass filtering between 5 and 500 Hz, and digitization at 10 kHz using PowerLab (AD Instruments, Australia). The data were stored for off-line analysis (LabChart 8, AD Instruments, Bella Vista, Australia).\u003c/p\u003e\u003cp\u003eProtocol\u003c/p\u003e\u003cp\u003eDuring all protocols, the force and position tasks were always performed under the visual feedback described above. At the beginning of the session, we assessed maximum voluntary contraction (MVC) of the right index finger abduction. The procedure for assessing MVC followed the previously established protocol [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], where participants gradually increased their force output from rest to maximum over 3 sec and held the peak force for an additional 3 sec with verbal encouragement. MVC was measured at least three times for each participant with 90 sec rest intervals between trials. If the peak of force values across trials exhibited a variation within 5%, the highest value was considered as the fine MVC. Otherwise, additional trials were conducted until a variation of 5% or less was achieved (the MVC trials were carried out 3\u0026ndash;5 times). The highest MVC value was subsequently used to define submaximal contraction levels.\u003c/p\u003e\u003cp\u003e Next, to familiarize the participants with the tasks, they performed 30-sec static contractions of the FDI muscle at 10% MVC for the force task and at 20\u0026deg;abduction for the position task. They executed both tasks twice in a randomized order, with a 1-min rest between trials. To ensure task accuracy, the absolute error rate of torque in the force task and the angle in the position task was monitored. If the error exceeded 5%, participants practiced again until it was within the determined range (the number of trials ranged from 2 to 5). Then, they performed 1-min static contractions for each task twice, in a randomized order, with a 1-min rest between trials, during which median nerve stimulation was applied at a rate of 0.1\u0026ndash;0.2 Hz with 6\u0026ndash;8 stimulations per task (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The absolute error rate and EMG amplitude were reassessed to confirm consistency.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAfter the familiarization, the latency of the N20 component of SEPs was measured at rest (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Subsequently, the SAI was recorded at rest and during both tasks (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC), and the SLRs and LLRs were recorded during both tasks (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). The recordings of SAI and SLRs/LLRs were conducted in separate submaximal contraction trials in a randomized order. Each trial lasted approximately 50 sec, with a 60-sec rest period between trials to avoid fatigue. To minimize the influence of transient force fluctuations, stimuli were delivered when the force and position signals had reached their respective targets and remained stable for at least 1 sec. Throughout the recordings, we monitored the EMG activity of the right FDI muscle to ensure consistency between the two tasks.\u003c/p\u003e\u003cp\u003eN20 latency measurement\u003c/p\u003e\u003cp\u003eAn Ag/AgCl electrode was positioned 2cm posterior to the C3 (C3\u0026rsquo;) site according to the international 10\u0026ndash;20 system and a reference electrode attached to the right earlobe. Stimulation of the right median nerve was applied using a road electrode, with the anode placed distally. A total of 300 stimulations were delivered by a constant current stimulator (Digitimer DS3, Digitimer, Welwyn Garden City, UK) in the form of 0.2 msec square-wave pulses at 3.3 Hz. The stimulus intensity was set to 1.2 times the motor threshold required to evoke contraction in the right FDI muscle. The resulting signals were averaged across 300 epochs to calculate the latency of SEPs N20.\u003c/p\u003e\u003cp\u003eMEPs and SAI recordings\u003c/p\u003e\u003cp\u003eThere were three conditions: rest, force task, and position task. TMS was performed using a 70-mm Fig-of-eight coil connected to a monophasic magnetic stimulator (Magstim 200, Magstim, Carmarthenshire, UK). The coil was aligned over the left M1 and maintained at 45\u0026deg; to the sagittal plane. The motor hotspot was located as the position where consistent stimulation above the threshold produced the largest MEP in the FDI muscle. The resting motor threshold (RMT) and active motor threshold (AMT) were defined as minimal stimulus intensities capable of eliciting consistent 1 mV MEPs at rest and during muscle contraction, respectively. RMT was used for rest, whereas the AMT was used for the force and position conditions.\u003c/p\u003e\u003cp\u003eSAI was elicited by a brief suprathreshold electrical stimulation of the right median nerve before applying TMS. The interstimulus interval between electrical stimulation and TMS was set to the latency of the N20\u0026thinsp;+\u0026thinsp;2 msec, and the intertrial interval was set to 4000\u0026thinsp;\u0026plusmn;\u0026thinsp;200 msec. There were two blocks for each condition (rest, force task, and position task). In each block of 12 TMS trials, the right median nerve stimulation was randomly provided 6 times. Thus, within each condition, 12 MEPs were conditioned, and 12 MEPs were not conditioned. Each condition was performed in a random order, and each block was separated by a rest period of 60 sec to avoid fatigue.\u003c/p\u003e\u003cp\u003eSLRs and LLRs\u003c/p\u003e\u003cp\u003eElectrode position and stimulus intensity for the right median nerve stimulation were described above. This approach enables the evaluation of the agonist response to feedback from low-threshold afferent inputs without activating the antagonist muscle, minimizing contamination from F-wave [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The stimulation frequency and duration were set as 1.3 Hz and 1 msec, respectively. Reflexes were recorded 100 times in two blocks of 50 stimulations each, for both position and force tasks in a randomized order. Each block was separated by a rest period of 60 sec to avoid fatigue. Potentials were amplified and band-pass filtered (1\u0026ndash;3000 Hz).\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eTo quantify the maximum EMG activity of the right FDI muscle, EMG activity during MVC trials was rectified and averaged over a 1-sec window centered on the peak force. The EMG recorded during static contraction in two tasks was normalized to the EMG amplitude during MVC (%EMG).\u003c/p\u003e\u003cp\u003eUsing data during task familiarization, we evaluated the absolute error rate (AER) and background EMG (BEMG) during the two tasks. Specifically, we calculated the average EMG amplitude and force/angle values during the middle 20 sec s of a 30-sec static contractions, without median nerve stimulation, at 10% MVC in the force task or at 20\u0026deg; of abduction in the position task. Also, we calculated the average EMG and force/angle values over 1-s period, with 500 msec before and after median nerve stimulation. The AER of force and angle was calculated using the following formula:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\text{A}\\text{E}\\text{R}=\\frac{\\left|Measured\\:Value-Target\\:Value\\right|}{Target\\:Value}\\:\\times\\:100$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eReproducibility of BEMG and AER for the two tasks was verified in all 16 participants. Due to the limited number of channels on the A/D converter and constraints of the analysis software, force and angle were not recorded during the SAI and SLR/LLR recordings. For the SAI and SLR/LLR measurements, only the reproducibility of BEMB was evaluated.\u003c/p\u003e\u003cp\u003eThe magnitude of SAI was quantified as the percentage change in the average amplitude of MEPs, calculated as follows:\u003c/p\u003e\u003cp\u003e%SAI = [unconditioned MEPs \u0026mdash; conditioned MEPs] / unconditioned MEPs\u003c/p\u003e\u003cp\u003eTo evaluate the BEMG during SAI recording, the average amplitude was calculated over a 100-msec window preceding median nerve stimulation.\u003c/p\u003e\u003cp\u003eThe amplitudes of SLRs and LLRs were determined by subtracting the average BEMG activity, computed over a 50-msec period preceding right median nerve stimulation, from the peak amplitude after rectifying the EMG [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. They were defined as the difference between baseline and peak values:\u003c/p\u003e\u003cp\u003eSLR/LLR amplitude\u0026thinsp;=\u0026thinsp;Peak - BEMG\u003c/p\u003e\u003cp\u003eThe SLR (20\u0026ndash;50 msec post-stimulation) and LLR (50\u0026ndash;100 msec post-stimulation) were analyzed over a time window extending from 50 msec before to 200 msec after stimulation. After the automatic removal of trials with excessive artifacts by the software, a total of 100 trails were summed on average to obtain a waveform for each participant and each task.\u003c/p\u003e\u003cp\u003eStatistical analysis was conducted using MATLAB R2023b (The MathWorks, Inc., Natick, MA, USA) and OriginPro 2025 (OriginLab Corporation, Northampton, MA, USA). Results are presented as mean values with standard errors of the mean. We utilized the Shapiro-Wilk test to verify the normality of the data distribution. BEMG amplitudes and the AER with and without median nerve stimulation during the two tasks were compared using two-way repeated measures analysis of variance (ANOVA). Intraclass correlation coefficients, ICC (2,1), were used to measure the reproducibility of inter-load type BEMG activity for the FDI and the AER of force and angle. The %SAI was compared between conditions (rest, force task, and position task) using one-way repeated measures ANOVA. Post-hoc tests were performed using Tukey\u0026rsquo;s honest significant difference (HSD) for all relevant pairwise comparisons. SLR and LLR amplitudes were compared between the force and position tasks using a paired t-test. The significance level was set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA shows raw waveforms of EMG activity, muscle torque, and metacarpophalangeal joint angle recorded from a representative subject during MVC and submaximal static contraction for the force and position tasks, both with and without median nerve stimulation during task familiarization. The mean torque and EMG activity during MVC across all subjects were 0.968\u0026thinsp;\u0026plusmn;\u0026thinsp;0.075 Nm and 0.895\u0026thinsp;\u0026plusmn;\u0026thinsp;0.085 mV, respectively. The BEMG of the FDI muscle with and without median nerve stimulation during the force task (0.091\u0026thinsp;\u0026plusmn;\u0026thinsp;0.008 mV and 0.096\u0026thinsp;\u0026plusmn;\u0026thinsp;0.010 mV, respectively) and the position task (0.090\u0026thinsp;\u0026plusmn;\u0026thinsp;0.008 mV and 0.094\u0026thinsp;\u0026plusmn;\u0026thinsp;0.010 mV, respectively) did not differ significantly (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.076) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). These EMG activities corresponded to about 10\u0026ndash;11% of MVC, which was consistent with the load intensity of 10% of maximum muscle strength. Similarly, the AERs with and without median nerve stimulation during the force task (2.033\u0026thinsp;\u0026plusmn;\u0026thinsp;0.228% and 2.054\u0026thinsp;\u0026plusmn;\u0026thinsp;0.188%, respectively) and the position task (1.548\u0026thinsp;\u0026plusmn;\u0026thinsp;0.201% and 1.575\u0026thinsp;\u0026plusmn;\u0026thinsp;0.194%, respectively) did not show significant differences (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.110) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe mean latency of SEPs component of N20 was 19.731\u0026thinsp;\u0026plusmn;\u0026thinsp;0.473 msec. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA shows raw MEP waveforms recorded during SAI measurements, both with and without conditioning electrical stimulation at rest and during the force and position task, from a representative participant. Light gray lines indicate MEP waveforms from all 12 trials, while thick lines indicate the average waveforms. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB shows representative raw, rectified, and averaged EMG waveforms from SLR and LLR recordings during the force and position tasks.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, the average %SAI was highest during the rest (0.593\u0026thinsp;\u0026plusmn;\u0026thinsp;0.037), followed by the force task (0.399\u0026thinsp;\u0026plusmn;\u0026thinsp;0.056), and was lowest during the position task (0.226\u0026thinsp;\u0026plusmn;\u0026thinsp;0.060). One-way repeated measures ANOVA revealed a significant main effect of task condition on %SAI (F \u003csub\u003e(2,30)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;16.118, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, partial η\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.518). Tukey\u0026rsquo;s HSD post-hoc analysis identified significant %SAI differences among task conditions, with the rest differing from both the position (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0003) and force (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.041) tasks, and the force differing from the position tasks (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009). BEMG during SAI recording were 0.084\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007 mV in the force task and 0.085\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007 mV in the position task. There was no significant difference between the two tasks (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.906), and BEMG was highly reproducible (ICC (2,1)\u0026thinsp;=\u0026thinsp;0.958, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe amplitude of SLR was higher during the position than force task (force task: 0.092\u0026thinsp;\u0026plusmn;\u0026thinsp;0.025 mV, position task: 0.109\u0026thinsp;\u0026plusmn;\u0026thinsp;0.028 mV; \u003cem\u003ep\u003c/em\u003e = 0.020) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). The amplitude of LLR was also higher during the position than force task (force task: 0.029\u0026thinsp;\u0026plusmn;\u0026thinsp;0.006 mV, position task: 0.043\u0026thinsp;\u0026plusmn;\u0026thinsp;0.007 mV; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). BEMG during SLR and LLR recordings were 0.095\u0026thinsp;\u0026plusmn;\u0026thinsp;0.008 mV in the force task and 0.097\u0026thinsp;\u0026plusmn;\u0026thinsp;0.011 mV in the position task. There was no significant difference between the two tasks (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.662), and BEMG was highly reproducible (ICC (2,1)\u0026thinsp;=\u0026thinsp;0.908, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eA novel observation in our study was that, during static contraction of the FDI muscle at 10% MVC and 20 degrees of abduction, %SAI was significantly smaller during the position task than the force tasks. In line with previous reports [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], the amplitude of the heteronymous SLR was significantly greater during the position than force task. Furthermore, the amplitude of heteronomy LLR was greater during the position than force task, as reported in earlier studies [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. These findings suggest the position task requires more proprioceptive information and involves different sensorimotor integration mechanisms compared to the constant finger force task.\u003c/p\u003e\u003cp\u003eIn this study, we found that %SAI was weaker during movement (force and position tasks) compared with rest. This pattern has also been described in previous studies [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], suggesting that voluntary motor commands may partially override or modulate afferent inhibition. More importantly, %SAI was weaker in the position than force tasks. Before interpreting our results, it should be noted that under the same experimental setup used in our SAI experiment, the latency of the N20 component of SEP evoked by median nerve stimulation did not show significant differences between the force and position tasks [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], indicating that differences in stimulation timing for SAI measurement due to load type are not a significant factor. Our finding of greater reduction of SAI in position task may be related to SEPs gating, as suggested by previous research [\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. SEPs gating is the phenomenon where SEPs are reduced during voluntary movement compared to rest [\u003cspan additionalcitationids=\"CR34 CR35 CR36\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], which is believed to reflect the filtering of irrelevant sensory information during movement, allowing only essential inputs to be processed [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. This mechanism, which modulates the influence of sensory input on the motor cortex, helps optimize motor responses and varies according to different motor perceptual demands [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In previous studies of position and force tasks, the P45 component was found to be larger during the position task, while the N33 component was larger during the force task, indicating different cortical processing of sensory inputs [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Since the peripheral mixed nerve stimulation used in this study to evaluate SAI primarily stimulates larger diameter Group Ia sensory nerves, the position task which requires more proprioceptive information may have involved greater filtering of information from Group Ia sensory nerves derived from the electrical stimulation. This could have resulted in decreased inhibitory input from S1 to M1, consequently leading to reduced SAI.\u003c/p\u003e\u003cp\u003eThe gating of SEPs, interpreted as being related to the attenuation of SAI, arises not only from the competition between afferent signals following electrical stimulation and those associated with the motor output itself (afferent gating) but also from a central mechanism where output from the motor center suppresses the sensory afferent pathway (efferent gating). This is supported by findings showing that SEPs gating can occur before movement onset [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Given that SEPs gating can occur at any stage along the afferent sensory pathway, or within the cerebral cortex, the mechanism underlying the reduced SAI in the position task relative to the force task should be explored in the context of efferent gating mechanisms.\u003c/p\u003e\u003cp\u003eThe amplitudes of SLRs and LLRs have been reported to be greater during the position than force task [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], and our findings are consistent with the previous studies. Furthermore, the results of the present study, conducted at 10% MVC, were similar to those of previous studies conducted at 20% MVC [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] or at multiple load intensities of 20%, 40%, and 60% MVC [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], supporting the view that differences in reflex responses depend on the load type rather than differences in voluntary contraction force [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. SLR is known to be regulated exclusively by Ia afferents and spinal neural networks [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], and its amplitude can serve as a surrogate marker for presynaptic inhibition of Ia afferents [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The observed increase in SLR amplitude during the position task thus suggests that Ia afferent excitation was enhanced under this condition. Meanwhile, LLRs involve spinal circuits and supraspinal circuits including M1 [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR42 CR43\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Therefore, the increased amplitude of LLRs can indicate enhanced excitability of spinal α-motoneurons projected from the M1.\u003c/p\u003e\u003cp\u003eTo prevent simultaneous activation of the FDI and its antagonist and to minimize contamination of the F-wave recordings [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], most previous studies have used a heteronymous pathway to elicit the SLR from the FDI [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Since the F-wave represents the response of motor neurons to an antidromic volley [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], it does not occur when activating a heteronymous pathway. On the other hand, co-contraction can occur under unstable load conditions, significantly increasing the background muscle activity of the agonist group [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], which may contribute to increased heteronymous SLR amplitudes. However, both in previous studies and the present one, we did not observe an increase in muscle activity during the unstable position task compared to the stable force task. Nonetheless, it remains possible that the activity of muscles involved in adduction (such as the palmar interosseous muscle) increased to an extent that did not affect the abduction torque of the index finger. Recently, a non-invasive method for measuring hand muscle activity using surface EMG has been developed [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Future studies should adopt this method to conduct more detailed investigations.\u003c/p\u003e\u003cp\u003eClinical Application\u003c/p\u003e\u003cp\u003eSomatosensory discrimination training, such as limb position discrimination, has been demonstrated to enhance sensory functions in stroke patients [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Our study indicates greater Ia facilitation during the position task compared to the force task. The difference may be related to the decreased mechanical stability during the position task. Thus, the position task may be useful to enhance postural stability and fine motor control in patients with proprioceptive deficits post-stroke [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Additionally, the magnitude of SAI can correlate with motor deficits and prognosis in stroke patients, suggesting that SAI could serve as a neurophysiological biomarker for predicting post-stroke outcomes and a guidance for personalized rehabilitation strategies [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Greater understanding of task-dependent modulation of SAI may allow clinicians to develop proper rehabilitation protocols that optimize sensory processing and motor function.\u003c/p\u003e\u003cp\u003eLimitations and Future Directions\u003c/p\u003e\u003cp\u003eFirstly, several methodological aspects regarding SAI measurement parameters warrant attention. The intensity of the electrical stimulation (1.2\u0026times;motor threshold) for the median nerve may have approached the saturation point of the sensory nerve action potential (SNAP). Future studies should optimize this by selecting a conditioning intensity between 25% and 40% of SNAP (max), as determined by an SNAP stimulus-response curve [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Additionally, the TMS intensity used to evoke 1mV MEPs based on RMT/AMT might have been too strong. Higher TMS intensities can paradoxically reduce or abolish SAI, which could decrease sensitivity to inhibition [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. A better approach is to construct an MEP input\u0026ndash;output curve at rest [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e] and select an intensity that elicits 0.5\u0026ndash;1.0 mV MEPs. This intensity should be applied consistently across conditions to ensure a sensitive SAI measurement. Secondly, no data on task performance during the force and position tasks were collected. While the primary aim of this study was to compare SAI, SLR, and LLR between these two tasks, task performance data would have strengthened our discussion. Thirdly, we did not assess fatigue during the experiment. Although there were no differences in EMG amplitude between tasks, the potential effects of fatigue should have been considered. Future studies should incorporate fatigue assessments to determine whether it influences SAI, SLR, and LLR responses. Finally, we only focused on SAI, despite the widely recognized interaction between SAI and short-interval cortical inhibition (SICI) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. In particular, it has been suggested that a decrease in SAI could be accompanied by an increase in SICI [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Thus, whether SICI also exhibits the load-dependent difference in SAI remains to be elucidated. Moreover, intraneural microsimulation has been considered an ideal method for investigating cutaneous versus proprioceptive contributions [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Future investigations should consider this method to study SAI during the force and position tasks. Additionally, future studies should utilize electroencephalography to further elucidate the neural mechanisms underlying the difference in SAI between two tasks. Incorporating additional sensory inputs, such as visual and auditory cues, may also provide a more comprehensive understanding of how these factors modulate sensorimotor integration and SAI during position and force tasks.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study demonstrated a significantly smaller SAI during position than force task. This finding highlights the load type-specific modulation of SAI, reflecting distinct sensorimotor processing strategies that are adapted to different load conditions.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eSAI, short latency afferent inhibition; MVC, maximum voluntary contraction; M1, primary motor cortex; S1, primary somatosensory cortex; TMS, transcranial magnetic stimulation; MEP, motor evoked potential, SEP, somatosensory evoked potential; SLRs and LLRs, heteronymous short and long latency reflexes; FDI, first dorsal interosseous muscle; EMG, electromyography; RMT, resting motor threshold; AMT, active motor threshold; ANOVA, analysis of variance; Tukey\u0026rsquo;s HSD, Tukey\u0026rsquo;s honest significant difference; AER, absolute error rate; BEMG, background EMG; SNAP, sensory nerve action potential; SICI, short-interval cortical inhibition.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eWritten informed consent was obtained from all participants before beginning the experiment, which was conducted according to principles of the Declaration of Helsinki. The experimental protocol was also approved by the Ethics Committee for Epidemiology of Hiroshima University (No. E-2261) and was conducted according to principles of the Declaration of Helsinki\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the present study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis research was partially supported by Grants-in-Aid (KAKENHI) from the Japan Society for the Promotion of Science [22K1777 (TW), 23KJ1643 (TH), 23K14734 (KS), 24K20530 (SD), 22H03454 (HK), and 24K21309 (HK)].\u003c/p\u003e\n\u003cp\u003eAuthors\u0026rsquo; contributions\u003c/p\u003e\n\u003cp\u003eKangjing Yang: Conceptualization, Methodology, Formal analysis, Investigation, Data curation, Writing \u0026ndash; original draft, Visualization. Tatsunori Watanabe: Supervision, Writing \u0026ndash; original draft \u0026amp; editing, Funding acquisition. Takayuki Horinouchi: Conceptualization, Methodology, Investigation, Writing \u0026ndash; original draft, Funding acquisition. Sumi Miyoshi: Conceptualization, Methodology, Formal analysis, Writing \u0026ndash; original draft. Jingnan Li: Conceptualization, Methodology, Formal analysis, Writing \u0026ndash; original draft. Kazuya Saita: Conceptualization, Writing \u0026ndash; original draft \u0026amp; editing, Funding acquisition. Shota Date: Conceptualization, \u0026nbsp;Writing \u0026ndash; original draft \u0026amp; editing, Funding acquisition. \u0026nbsp;Hikari Kirimoto: Supervision, Writing \u0026ndash; original draft \u0026amp; editing, Funding acquisition.\u003c/p\u003e\n\u003cp\u003eAcknowledgments\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe would like to extend our sincere appreciation to all participants whose involvement and commitment were indispensable to the completion of this study.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eEnders LR, Seo NJ. Effects of Sensory Deficit on Phalanx Force Deviation During Power Grip Post Stroke. J Mot Behav. 2017;49(1):55-66. doi: 10.1080/00222895.2016.1191416.\u003c/li\u003e\n\u003cli\u003eJohansson RS, Flanagan JR. Coding and use of tactile signals from the fingertips in object manipulation tasks. Nat Rev Neurosci. 2009;10(5):345-59. doi: 10.1038/nrn2621.\u003c/li\u003e\n\u003cli\u003eProske U, Gandevia SC. 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Exp Brain Res. 2009;199(1):83-8. doi: 10.1007/s00221-009-1951-x.\u003c/li\u003e\n\u003cli\u003eDi Lazzaro V, Profice P, Pilato F, Capone F, Ranieri F, Florio L, et al. The level of cortical afferent inhibition in acute stroke correlates with long-term functional recovery in humans. Stroke. 2012;43(1):250-2. doi: 10.1161/STROKEAHA.111.631085.\u003c/li\u003e\n\u003cli\u003eAlle H, Heidegger T, Krivanekova L, Ziemann U. Interactions between short-interval intracortical inhibition and short-latency afferent inhibition in human motor cortex. J Physiol. 2009;587(Pt 21):5163-76. doi: 10.1113/jphysiol.2009.179820.\u003c/li\u003e\n\u003cli\u003eTemesi J, Gruet M, Rupp T, Verges S, Millet GY. Resting and active motor thresholds versus stimulus-response curves to determine transcranial magnetic stimulation intensity in quadriceps femoris. J Neuroeng Rehabil. 2014;11:40. doi: 10.1186/1743-0003-11-40.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Short-latency afferent inhibition, Heteronymous short latency reflex, Heteronymous long latency reflex, Primary motor cortex, Sensorimotor integration","lastPublishedDoi":"10.21203/rs.3.rs-7691656/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7691656/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eStatic muscle contraction involves two distinct load types. One type, called a position task, entails holding the limb in a fixed position while counteracting an inertial load, while the other type, known as a force task, involves exerting a consistent force against a solid constraint. While proprioceptive information has been shown to be required more during the position task, it has remained to be elucidated how sensorimotor integration differs between these two tasks.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis study investigated differences in short latency afferent inhibition (SAI) and heteronymous reflex responses between the force and position conditions. Sixteen participants performed static contractions of the first dorsal interosseous (FDI) muscle. In the force task, they exerted a constant force corresponding to 10% maximum voluntary contraction (MVC) against a rigid restraint. In the position task, they sustained a target abduction angle of 20\u0026deg; while holding a load equivalent to 10% MVC. SAI was induced by the paired application of electrical stimulation to the right median nerve and transcranial magnetic stimulation over the left motor cortex at an N20\u0026thinsp;+\u0026thinsp;2 msec interval. Motor evoked potentials (MEPs) were recorded from the FDI muscle to quantify the magnitude of SAI. Heteronymous short and long latency reflexes (SLR and LLR) were also examined, and their amplitudes were compared between the force and position tasks.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eSAI was significantly attenuated in the position task (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Additionally, SLR and LLR amplitudes were significantly greater during position task (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThese findings suggest distinct sensorimotor processing strategies depending on the load type.\u003c/p\u003e","manuscriptTitle":"Short latency afferent inhibition differs with load type during isometric finger abduction","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-17 12:23:56","doi":"10.21203/rs.3.rs-7691656/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"763b06b0-8e78-48e7-bbc7-f81db5126bdd","owner":[],"postedDate":"October 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-02T16:00:46+00:00","versionOfRecord":{"articleIdentity":"rs-7691656","link":"https://doi.org/10.1186/s40101-026-00424-y","journal":{"identity":"journal-of-physiological-anthropology","isVorOnly":false,"title":"Journal of Physiological Anthropology"},"publishedOn":"2026-02-25 15:57:11","publishedOnDateReadable":"February 25th, 2026"},"versionCreatedAt":"2025-10-17 12:23:56","video":"","vorDoi":"10.1186/s40101-026-00424-y","vorDoiUrl":"https://doi.org/10.1186/s40101-026-00424-y","workflowStages":[]},"version":"v1","identity":"rs-7691656","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7691656","identity":"rs-7691656","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}