Transcutaneous spinal stimulation aims to target dorsal spinal roots, which deliver sensory information to the spinal cord. However, the stimulation waveform that most effectively recruits sensory fibers at the lowest intensity has not been identified. The purpose of this study was to compare conventional and high-frequency burst-modulated stimulation waveforms in their ability to recruit sensory fibers, as assessed by H-reflex threshold, recruitment characteristics, and motor fiber activation. In participants with intact neurological function (n = 12), soleus H-reflex recruitment curves were recorded for 10 stimulation waveforms: a conventional waveform (400 μs), serving as the reference condition, high-frequency burst-modulated waveforms (2, 5, and 10 kHz) with the same total phase duration, and a longer conventional waveform (1,000 μs), each delivered as biphasic and monophasic pulses. H-reflex threshold was higher for high-frequency waveforms: 2 kHz (biphasic: +63%, monophasic: +35%); 5 kHz (biphasic: +179%, monophasic: +109%); 10 kHz (biphasic: +307%, monophasic: +249%); and lower for the conventional 1,000 μs waveform (biphasic: -39%, monophasic: -44%). Similarly, recruitment curve peak slope (mV/mA) was less steep for high-frequency waveforms: 2 kHz (biphasic: -43%, monophasic: -40%); 5 kHz (biphasic: -77%, monophasic: -40%); 10 kHz (biphasic: -82%, monophasic: -48%); and increased (+38%) for the monophasic conventional 1,000 μs waveform. At stimulus intensity near the H-reflex threshold, M-wave amplitude was larger for high-frequency waveforms. Overall, high-frequency waveforms were less effective than conventional waveforms of equal phase duration at eliciting H-reflexes and showed more motor activation at near-threshold intensities.NEW & NOTEWORTHY Compared with high-frequency burst-modulated waveforms (2, 5, and 10 kHz), conventional waveforms (400 μs) elicited H-reflexes more efficiently, as evidenced by lower thresholds and steeper recruitment curves, and less motor activation, as evidenced by smaller M-waves near threshold and larger Hmax/Mmax ratios. Monophasic 5 and 10 kHz waveforms also produced lower H-reflex thresholds and steeper slopes than their biphasic versions, suggesting that the anodal phase impairs sensory fiber recruitment with high-frequency stimulation.

[This corrects the article DOI: 10.1016/j.eclinm.2026.103802.].

We compared proprioceptive judgements made within a single frame of reference (e.g., grasp → grasp; i.e., low-level) and those made between frames of reference (e.g., grasp → vision; i.e., high-level) at the hand and jaw in 30 healthy participants. Participants judged the size of grasped or bitten objects of different sizes. Compared to high-level judgements, low-level judgements were more accurate (hand: mean difference in mean absolute error: 0.20 mm [95% CI 0.12 to 0.27]; jaw: (0.15 mm [0.09 to 0.20]) and precise (hand: mean difference in RMSE: 3.94 [2.73 to 5.15]; jaw: 1.67 [1.19 to 2.14]). A regression line was fit to a participant’s high-level proprioception responses to reflect the central transformation used to make these judgements. Comparing the regression lines for the hand and jaw conditions indicates the brain does not appear to apply a similar calibration to make high-level proprioceptive judgements with these distinct yet functionally related body parts.

Proprioceptive deficits are thought to contribute to age-related decline in upper-limb function. We aimed to estimate the effect of proprioceptive ability on upper-limb function under an explicitly specified causal framework and to determine whether this effect varied with age. A causal graph was developed to outline plausible relationships among proprioceptive ability, upper-limb function, and related factors (e.g., age, tactile acuity, cognition, and muscle strength). A total of 184 healthy individuals (18-95 yr; 98 females and 86 males) completed a test battery. Proprioception was assessed using grasp-based measures of low-level proprioception (judgements within a single reference frame) and high-level proprioception (judgements across different frames of reference, involving transformations between visual and proprioceptive information). The causal graph identified the minimal adjustment set to reduce bias, and generalized linear models were used to estimate the effect of proprioceptive accuracy and precision on upper-limb function under the assumed causal structure. Poor high-level proprioception precision was linked with impaired performance on a functional task requiring participants to put on and button up a shirt, with the effect increasing with age. For example, at the median precision value, an 80-yr-old required on average 13 s longer than a 60-yr-old to complete the task. No evidence was found for an effect of low-level proprioception on functional performance. Although effect sizes were generally modest, the observed associations were consistent and demonstrated age-dependent effects. These findings are consistent with a role for high-level proprioception in upper-limb function and provide normative data across the lifespan, highlighting proprioception as a potential therapeutic target to mitigate age-related functional decline.NEW & NOTEWORTHY This is the first study to estimate the effect of proprioception on upper-limb function across the lifespan within an explicitly defined causal framework. Specifically, we investigated whether deficits in low-level proprioceptive judgements (made within a single frame of reference) or high-level proprioceptive judgements (made between frames of reference) impair upper-limb function across the lifespan. We provide novel evidence that imprecise high-level proprioceptive judgements impair an everyday upper-limb functional task, with this relationship strengthening with age.

Spinal cord stimulation is an emerging treatment in spinal cord injury and chronic low back pain. This scoping review aimed to identify and consolidate key criteria for rigor, transparency and reproducibility across reporting guidelines for research on spinal cord stimulation, and ensure all relevant criteria are captured, as a first step to identify and evaluate broader strategies for good research practices. Findings were used to to refine mechanisms for rigor, transparency and reproducibility in a causal graph. Four databases were searched from inception to 12 September 2024, and monitored through weekly article alerts up till 29 November 2024. Reviewers independently assessed articles for inclusion if they were (1) standards, guidelines, recommendations, or statements for research on humans, (2) on rigor, transparency and reproducibility, in stimulation or neuromodulation, and (3) written in English. The following data were extracted and synthesized: stimulation type, clinical area, type of responsible practice, and article text on responsible practice. Differences between reviewers were resolved by consensus, and findings used to refine the causal graph. Eleven articles of the following types were included: formal reporting guidelines, standards or checklists (n = 6), general recommendations (n = 4) or systematic review (n = 1). Data were synthesized and used to refine the initial causal graph. The nodes Reporting of experimental conditions , Protocol registration , and Open science practices were unchanged. The node Reporting study design to minimize bias was refined as Reporting study, participant, and investigator characteristics ; the node Reporting stimulation parameters was refined as Reporting stimulation configuration and parameters; and the new node Reporting adverse events was added. The responsible reporting of spinal cord stimulation research should also explicitly include study, participant and investigator characteristics, stimulation configuration and parameters, and adverse events.

Proprioceptive judgements can be divided into two broad categories: low‐level and high‐level. Low‐level judgements of limb position require a person to detect, discriminate or match the position of a body part, whereas high‐level judgements require a person to report the position of an unseen body part relative to the external world. It has been suggested that muscle thixotropy – the influence of recent contraction or stretch on the passive properties of a muscle – impacts both the accuracy of low‐level judgements of limb position and the degree to which these judgements drift over time. However, high‐level proprioceptive judgements of upper limb position and the degree to which they drift over time may not be affected by thixotropy. This was investigated here. Twenty‐five healthy adult participants made visual judgements about the perceived position of their hidden index finger after their elbow muscles had been conditioned with a flexion or extension contraction, or after a series of large passive elbow movements. After conditioning contractions, participants made small errors (∼2°) in perceived index finger position in the direction of elbow flexion, regardless of the contraction type. There was little to no effect of either contraction type on drift in perceived index‐finger position in our test. Our results support the view that high‐level proprioceptive judgements of hand position can be minimally affected by the effects of muscle thixotropy. Thus, we suggest that muscle spindle signals do not dominate the central, cross‐modal transformations of sensory information that are required for high‐level proprioceptive judgements.

The relationship between proprioceptive ability and physical function is commonly assessed in people with stroke, Parkinson's disease, and multiple sclerosis to investigate the etiology of functional deficits. The primary aim of this systematic review was to evaluate the magnitude of this association. We also investigated whether the magnitude of these associations was influenced by 1) study sample size, 2) the pairing of body regions targeted by assessments of proprioceptive ability and physical function, 3) the proprioceptive sense assessed, and 4) the type of proprioceptive assessment (low-level proprioception; high-level proprioception). A total of 56 studies reporting 438 measures of association were included. The magnitude of the associations ranged from -0.31 to 0.93 (r and ρ), with 92% being positive (better proprioceptive ability associated with better physical function). Study sample size, pairing of assessments, and type of low-level proprioceptive assessment (detect, discriminate, match) did not systematically influence the direction or magnitude of the associations. Ninety-seven percent of assessments focused on low-level proprioception and kinesthesia (position and movement sense). When studies discussed their measures of association, 50% used language that implied causality. Despite a detailed breakdown of measures of association, no clear pattern emerged regarding the link between proprioceptive ability and physical function. Future studies in people with stroke, Parkinson's disease, and multiple sclerosis should 1) move away from simple measures of association to infer causation given that several interrelated and potentially confounding deficits coexist, and 2) assess various aspects of proprioception, including high-level proprioception, as they differentially contribute to physical function.

Lumbar transcutaneous spinal cord stimulation (TSS) evokes synchronized muscle responses, termed spinally evoked motor response (sEMR). Whether the structures TSS activates to evoke sEMRs differ when TSS intensity and waveform are varied is unknown. In 15 participants (9 F, 6 M), sEMRs were evoked by TSS over L1-L3 (at sEMR threshold and suprathreshold intensities) with conventional (one 400-mu s biphasic pulse) or high-frequency burst (ten 40-mu s biphasic pulses at 10 kHz) stimulus waveforms in vastus medialis (VM), tibialis anterior (TA), and medial gastrocnemius (MG) muscles. TSS was paired with transcranial magnetic stimulation (TMS) over the contralateral motor cortex at relative interstimulus intervals (ISIs) (-10 ms to 11 ms), centered on the ISI when TSS and TMS inputs simultaneously activated VM motoneurons. Doublet TSS was delivered at 80-ms ISI. For VM, the area of the combined response evoked by paired TMS and TSS was not facilitated at any ISI. For TA and MG, combined responses were facilitated by similar to 40-100% when TMS activated the motoneurons before or at a similar time as TSS, particularly with suprathreshold TSS. Additionally, for TA, there was greater suppression of the second sEMR evoked by TSS doublets using suprathreshold conventional TSS compared to high-frequency burst TSS (P < 0.001). The results suggest that for VM TSS activated predominantly motor axons, but for TA and MG facilitation of the sEMR by TMS suggests that TSS activated sensory axons. Stimulation waveforms had similar outcomes in most conditions.

Transcutaneous spinal cord stimulation, as used for rehabilitation of impaired motor function after spinal cord injury, often involves a 10-kHz waveform modulated to produce repetitive bursts of stimulation. Kilohertz-frequency waveforms may facilitate the summation of subthreshold depolarisations, but the optimal burst duration for nerve stimulation has not been systematically investigated. In 11 adults, the ulnar nerve was stimulated transcutaneously with a 10-kHz waveform that contained 1, 2, 4, 6, 8 or 10 pulses, in random order. Compound muscle action potentials (CMAPs) and sensory nerve action potentials (SNAPs) were measured from motor threshold up to the maximal CMAP (M-max). The efficacy of each waveform was determined at M-max as CMAP amplitude divided by total phase charge. For CMAPs and SNAPs, increasing the number of pulses shifted the stimulus-response curves to the left for current and to the right for total charge. Accordingly, an increase in the number of pulses decreased the current but increased the total charge at sensory and motor thresholds and M-max. Efficacy decreased as the number of pulses increased. Onset latencies were delayed for waveforms with six or more pulses compared to a single pulse. These findings provide evidence of the summation of subthreshold depolarisations in sensory and motor axons in humans. However, the optimal number of pulses for summation remains unclear due to the opposing changes in current and total charge. It is clear, though, that more than six pulses is suboptimal, as there were no further decreases in threshold current while total charge continued to increase.

Letter to the EditorProprioception: Clarification of low-level and high-level—Response to Wali and Block 2024Martin E. Héroux and Simon C. GandeviaMartin E. HérouxNeuroscience Research Australia, Sydney, New South Wales, AustraliaSchool of Biomedical Sciences, University of New South Wales, Sydney, New South Wales, Australia, andSimon C. GandeviaNeuroscience Research Australia, Sydney, New South Wales, AustraliaSchool of Clinical Medicine, University of New South Wales, Sydney, New South Wales, AustraliaPublished Online:29 Feb 2024https://doi.org/10.1152/japplphysiol.00088.2024MoreSectionsPDF (262 KB)Download PDF ToolsExport citationAdd to favoritesGet permissionsTrack citations ShareShare onFacebookTwitterLinkedInWeChat to the editor: In a recent Perspective, we introduced a framework of human proprioceptive assessment based on the concept of low-level and high-level proprioception (1). Low-level proprioceptive judgments are made in a single proprioceptive frame of reference and require a person to detect, discriminate, or match proprioceptive stimuli. For example, a person might detect the start of a movement, discriminate between two lifted weights, or match joint angles on either side of their body. High-level proprioceptive judgments are made across different frames of reference. For example, a person might report the size of a grasped object (proprioceptive frame of reference) by selecting from visually presented objects of different widths (visual frame of reference). Our Perspective sought to encourage open discussion and dispel misconceptions (2). Therefore, we welcome the Letter by Wali and Block (3) as it provides an opportunity to clarify aspects of our framework.Wali and Block (3) agree with us that different proprioceptive tests have different computational requirements and highlight the neural complexity of sensing the position of "end point effectors (hand or finger)." While elbow angle is directly encoded by proprioceptive receptors, namely muscle spindles and cutaneous receptors, index finger position is computed centrally based on proprioceptive signals from the whole upper limb and a central representation of the body. Wali and Block (3) suggest that "including end point effector localization in the framework may help researchers clarify how this computation is related to other proprioceptive computations, and how it may differ."To justify this suggestion, Wali and Block (3) summarize a study by Fuentes and Bastian (4): "[…] people estimated their elbow angle more precisely when asked to match the finger position1 rather than the elbow angle itself. This could suggest the brain has better access to end point position than individual joint angles." Unfortunately, this conclusion, that the brain has better access to end point position, is not well supported by the study's results.Both tests used by Fuentes and Bastian (4) involved high-level proprioceptive judgments: with their upper limb hidden from view, participants aligned visually presented stimuli, a line or a dot, to the actual angle of their forearm (line) or the location of the tip of their index finger (dot). On inspection, the difference in precision between the two tasks was small and fickle. On average, measures of elbow angle were more variable when participants (n = 10) indicated the location of their index finger [4.2° SD (1.5)] compared with when they reported the angle of their elbow [5.6° SD (1.5), P = 0.046]. We note that a result associated with a P value close to 0.05 has only about a 50% chance of being reproduced in a replication study (5). Importantly, Wali and Block (3) fail to mention there was no difference in accuracy between tasks [location of index finger: 1.8° SD (8.3); angle of elbow: −0.6° SD (5.9); P = 0.66]. Moreover, the large between-participant variability reveals that errors in perceived index finger location were ∼12 cm (or larger) in some participants, in line with our work (6). Overall, the evidence used by Wali and Block (3) to argue the brain is more attuned to the location of the hands and fingers is not compelling.Wali and Block (3) go on to discuss two proprioceptive tasks: hand position discrimination and fingertip matching. In hand position discrimination, a low-level proprioceptive task, the hand is passively moved to a reference position, briefly moved away, and then returned to a position close to the reference position. Participants are then asked to indicate whether their hand is located to the left or the right of the reference position. As highlighted in our Perspective, people are good at this task and, on average, can discriminate index finger positions that differ by as little as 1 cm (7).In one of the studies cited by Wali and Block (3), Wilson et al. (7) discuss this test as follows:"Importantly, this procedure avoids non-proprioceptive modalities, such as vision, motor responses and inter-hemispheric transfer of information. Intermodal performance is less accurate than intra-modal performance, and multiple modalities introduce additional sources of error that are not easily distinguished from proprioceptive errors. By limiting our procedure to proprioceptive stimuli, we avoided such influences."Here, intermodal, more commonly termed cross modal (8), refers to proprioceptive judgments that involve more than one modality. Although we agree with Wilson et al. (7) that vision is a modality, we do not consider the interhemispheric transfer of information a modality. In our framework, a proprioceptive test that requires the interhemispheric transfer of information (e.g., left-right matching) is simply a test that requires more complex neural computations.Similarly, we do not consider motor responses a modality. Rather, in some proprioceptive tasks, motor commands constitute a proprioceptive signal. For example, controlled experiments involving muscle fatigue or experimentally paralyzed muscles demonstrate that centrally generated motor commands, in and of themselves, contribute to low-level proprioceptive judgments of joint position (9–11). In other proprioceptive tasks, for example, when reporting the perceived width of a grasped object, motor commands are present but do not influence proprioceptive judgments (12). Finally, there are tasks where motor commands are present and bias proprioceptive judgments. One such example is the fingertip matching task highlighted by Wali and Block (3, 13, 14), where participants actively position and hold the tip of one index finger in contact with the underside of a flat horizontal surface, then move the tip of their other index finger on top of the surface to align the tips of their index fingers. In a study cited by Wali and Block (3), Van Beers et al. (14) alert the reader to the bias introduced by motor commands in this task:"Figure 1 shows a representative example of the positions subjects indicated in the experiment. The systematic errors are striking, but we do not study them here. We simply mention that subjects tended to point too far to the left. This tendency for an indicating hand to pass beyond the real target position is known as the 'overlap effect', and has been observed in similar experiments."The task of fingertip matching is further complicated by its asymmetry. While traditional proprioceptive matching tasks require a person to match joint angles or upper limb configurations on either side of their body (15–17), fingertip matching requires a person to match—a better term might be "align"—the physical location of the tip of one index finger to the physical location of the tip of the other index finger. The added complexity and functional relevance of this task are one of the reasons it is used to investigate aspects of human sensorimotor function (13, 14). However, the confound introduced by motor commands renders fingertip matching a less than ideal test of proprioception.To conclude their Letter, Wali and Block (3) reiterate that, to increase the relevance of our proprioceptive framework, we should include a new class of proprioceptive judgments termed "midlevel" proprioception that focuses on hand and finger position. We are not persuaded by the arguments put forth by Wali and Block (3). Our simple two-level framework is based on the premise that proprioceptive tests should not be viewed as interchangeable but rather complimentary, with different tests having different degrees of neural complexity. As such, our framework already covers proprioceptive judgments of hand and finger position and does not need expansion.We also have a more fundamental objection to the suggestion by Wali and Block (3). The addition of midlevel proprioception, focused solely on hand and finger position, would cause our framework to no longer apply to other aspects of proprioception, for example, position sense of the lower limbs and trunk, the sense of movement, the sense of force and effort, and the sense of weight. As highlighted in our Perspective, our two-level proprioceptive framework is, and should remain, valid for all aspects of proprioception.GRANTSS. C. Gandevia was supported by National Health and Medical Research Council (NHMRC) Grant 195699.DISCLOSURESNo conflicts of interest, financial or otherwise, are declared by the authors.AUTHOR CONTRIBUTIONSM.E.H drafted manuscript; M.E.H and S.C.G revised manuscript; M.E.H and S.C.G approved final version of manuscript.REFERENCES1. Héroux ME, Butler AA, Robertson LS, Fisher G, Gandevia SC. Proprioception: a new look at an old concept. J Appl Physiol (1985) 132: 811–814, 2022. doi:10.1152/japplphysiol.00809.2021. Link | ISI | Google Scholar2. Héroux ME, Butler AA, Robertson LS, Fisher G, Blouin JS, Diong J, Krewer C, Tremblay F, Gandevia SC. Proprioception: fallacies and misconceptions - response to Han et al. 2022. J Appl Physiol (1985) 133: 608–610, 2022. doi:10.1152/japplphysiol.00409.2022. Link | ISI | Google Scholar3. Wali M, Block HJ. Expanding the framework of proprioception – comment on Héroux et al. 2022. J Appl Physiol (1985). 2024. doi:10.1152/japplphysiol.00880.2023. Link | Google Scholar4. Fuentes CT, Bastian AJ. Where is your arm? Variations in proprioception across space and tasks. J Neurophysiol 103: 164–171, 2010. doi:10.1152/jn.00494.2009. Link | ISI | Google Scholar5. Gandevia S, Cumming G, Amrhein V, Butler A. Replication: do not trust your p-value, be it small or large. J Physiol 599: 1719–1721, 2021. Crossref | PubMed | ISI | Google Scholar6. Qureshi HG, Butler AA, Kerr GK, Gandevia SC, Héroux ME. The hidden hand is perceived closer to midline. Exp Brain Res 237: 1773–1779, 2019. doi:10.1007/s00221-019-05546-7. Crossref | PubMed | ISI | Google Scholar7. Wilson ET, Wong J, Gribble PL. Mapping proprioception across a 2d horizontal workspace. PLoS One 5: e11851, 2010. [Erratum in PLoS One 5, 2010]. doi:10.1371/journal.pone.0011851. Crossref | PubMed | ISI | Google Scholar8. Heller J. Internal references in cross-modal judgments: a global psychophysical perspective. Psychol Rev 128: 509–524, 2021. doi:10.1037/rev0000280. Crossref | PubMed | ISI | Google Scholar9. Gandevia SC, Smith JL, Crawford M, Proske U, Taylor JL. Motor commands contribute to human position sense. J Physiol 571: 703–710, 2006. doi:10.1113/jphysiol.2005.103093. Crossref | PubMed | ISI | Google Scholar10. Walsh LD, Proske U, Allen TJ, Gandevia SC. The contribution of motor commands to position sense differs between elbow and wrist. J Physiol 591: 6103–6114, 2013. doi:10.1113/jphysiol.2013.259127. Crossref | PubMed | ISI | Google Scholar11. Givoni NJ, Pham T, Allen TJ, Proske U. The effect of quadriceps muscle fatigue on position matching at the knee. J Physiol 584: 111–119, 2007. doi:10.1113/jphysiol.2007.134411. Crossref | PubMed | ISI | Google Scholar12. Butler AA, Héroux ME, van Eijk T, Gandevia SC. Stability of perception of the hand's aperture in a grasp. J Physiol 597: 5973–5984, 2019. doi:10.1113/JP278630. Crossref | PubMed | ISI | Google Scholar13. Babu R, Lee-Miller T, Wali M, Block HJ. Effect of visuo-proprioceptive mismatch rate on recalibration in hand perception. Exp Brain Res 241: 2299–2309, 2023. doi:10.1007/s00221-023-06685-8. Crossref | PubMed | ISI | Google Scholar14. van Beers RJ, Sittig AC, Denier van der Gon JJ. How humans combine simultaneous proprioceptive and visual position information. Exp Brain Res 111: 253–261, 1996. doi:10.1007/BF00227302. Crossref | PubMed | ISI | Google Scholar15. Dukelow SP, Herter TM, Moore KD, Demers MJ, Glasgow JI, Bagg SD, Norman KE, Scott SH. Quantitative assessment of limb position sense following stroke. Neurorehabil Neural Repair 24: 178–187, 2010. doi:10.1177/1545968309345267. Crossref | PubMed | ISI | Google Scholar16. Djajadikarta ZJ, Gandevia SC, Taylor JL. Age has no effect on ankle proprioception when movement history is controlled. J Appl Physiol (1985) 128: 1365–1372, 2020. doi:10.1152/japplphysiol.00741.2019. Link | ISI | Google Scholar17. Walsh LD, Allen TJ, Gandevia SC, Proske U. Effect of eccentric exercise on position sense at the human forearm in different postures. J Appl Physiol (1985) 100: 1109–1116, 2006. doi:10.1152/japplphysiol.01303.2005. Link | ISI | Google ScholarFOOTNOTES1Participants did not actually estimate their elbow angle in this task. Elbow angle was computed post-hoc by the investigators.AUTHOR NOTESCorrespondence: M. E. Héroux (m.heroux@neura.edu.au); S. C. Gandevia (s.gandevia@neura.edu.au). Download PDF Previous Back to Top FiguresReferencesRelatedInformation Related ArticlesExpanding the framework of proprioception: a comment on Héroux et al. 29 Feb 2024Journal of Applied Physiology More from this issue > Volume 136Issue 3March 2024Pages 511-513 Crossmark Copyright & PermissionsCopyright © 2024 the American Physiological Society.https://doi.org/10.1152/japplphysiol.00088.2024PubMed38423517History Received 1 February 2024 Accepted 1 February 2024 Published online 29 February 2024 Published in print 1 March 2024 Keywordsclarificationlow levelhigh level Metrics

Transcutaneous electrical stimulation with repetitive bursts of a kilohertz carrier frequency is thought to be less painful than conventional pulsed currents by reducing the sensitivity of pain receptors. However, no purported benefit has been shown unequivocally. We compared the effects of carrier-frequency stimulation and conventional stimulation on pain tolerance and the thresholds for sensory and motor axons in twelve participants. The ulnar nerve was stimulated transcutaneously with a conventional single pulse and 5 and 10 kHz carrier-frequency waveforms that had 5 and 10 pulses, respectively, when delivered in bursts of ∼1 ms duration. Phase durations were adjusted across waveform types to match the total charge for a given current amplitude. Single bursts of stimulation were delivered from 1 mA up until no longer tolerable. This was repeated with repetitive bursts of stimulation at 20 Hz for 1 s. Participants tolerated higher current amplitudes with both carrier-frequency waveforms than conventional stimulation, with repetitive bursts more painful than single bursts. However, compared to conventional stimulation, carrier-frequency waveforms required more current to produce sensory and motor-threshold responses and to obtain a maximal motor response (Mmax). When the current at pain tolerance was normalised to the current at Mmax, participants tolerated lower stimulus intensities with carrier-frequency waveforms than conventional stimulation. These findings indicate that there is little to no benefit in using carrier-frequency waveforms to minimise the discomfort from electrical stimulation as the increase in stimulus intensity at pain tolerance is more than offset by reduced effectiveness in the activation of sensory and motor axons. KEY POINTS: Transcutaneous electrical stimulation with repetitive bursts of a kilohertz carrier-frequency waveform is thought to be less painful than conventional pulsed currents. For ulnar nerve stimulation, when stimulus waveforms were matched for total phase charge, participants tolerated higher current amplitudes with carrier-frequency stimulation than conventional stimulation. However, compared to conventional stimulation, carrier-frequency waveforms required more current to produce a threshold response in both sensory and motor axons and to produce a maximal motor response (Mmax). When current at pain tolerance was normalised to current at Mmax, participants tolerated lower stimulus intensities with carrier-frequency waveforms than conventional stimulation. Carrier-frequency waveforms provide little to no benefit in minimising the discomfort from transcutaneous electrical stimulation as the increase in stimulus intensity at pain tolerance is more than offset by reduced effectiveness in activating sensory and motor axons.

Low-level proprioceptive judgements involve a single frame of reference, whereas high-level proprioceptive judgements are made across different frames of reference. The present study systematically compared low-level (grasp → $\rightarrow$ grasp) and high-level (vision → $\rightarrow$ grasp, grasp → $\rightarrow$ vision) proprioceptive tasks, and quantified the consistency of grasp → $\rightarrow$ vision and possible reciprocal nature of related high-level proprioceptive tasks. Experiment 1 (n = 30) compared performance across vision → $\rightarrow$ grasp, a grasp → $\rightarrow$ vision and a grasp → $\rightarrow$ grasp tasks. Experiment 2 (n = 30) compared performance on the grasp → $\rightarrow$ vision task between hands and over time. Participants were accurate (mean absolute error 0.27 cm [0.20 to 0.34]; mean [95% CI]) and precise ( R 2 $R^2$ = 0.95 [0.93 to 0.96]) for grasp → $\rightarrow$ grasp judgements, with a strong correlation between outcomes (r = -0.85 [-0.93 to -0.70]). Accuracy and precision decreased in the two high-level tasks ( R 2 $R^2$ = 0.86 and 0.89; mean absolute error = 1.34 and 1.41 cm), with most participants overestimating perceived width for the vision → $\rightarrow$ grasp task and underestimating it for grasp → $\rightarrow$ vision task. There was minimal correlation between accuracy and precision for these two tasks. Converging evidence indicated performance was largely reciprocal (inverse) between the vision → $\rightarrow$ grasp and grasp → $\rightarrow$ vision tasks. Performance on the grasp → $\rightarrow$ vision task was consistent between dominant and non-dominant hands, and across repeated sessions a day or week apart. Overall, there are fundamental differences between low- and high-level proprioceptive judgements that reflect fundamental differences in the cortical processes that underpin these perceptions. Moreover, the central transformations that govern high-level proprioceptive judgements of grasp are personalised, stable and reciprocal for reciprocal tasks. KEY POINTS: Low-level proprioceptive judgements involve a single frame of reference (e.g. indicating the width of a grasped object by selecting from a series of objects of different width), whereas high-level proprioceptive judgements are made across different frames of reference (e.g. indicating the width of a grasped object by selecting from a series of visible lines of different length). We highlight fundamental differences in the precision and accuracy of low- and high-level proprioceptive judgements. We provide converging evidence that the neural transformations between frames of reference that govern high-level proprioceptive judgements of grasp are personalised, stable and reciprocal for reciprocal tasks. This stability is likely key to precise judgements and accurate predictions in high-level proprioception.

Sound reporting of research results is fundamental to good science. Unfortunately, poor reporting is common and does not improve with editorial educational strategies. We investigated whether publicly highlighting poor reporting at a journal can lead to improved reporting practices. We also investigated whether reporting practices that are required or strongly encouraged in journal Information for Authors are enforced by journal editors and staff. A 2016 audit highlighted poor reporting practices in the Journal of Neurophysiology. In August 2016 and 2018, the American Physiological Society updated the Information for Authors, which included the introduction of several required or strongly encouraged reporting practices. We audited Journal of Neurophysiology papers published in 2019 and 2020 (downloaded through the library of the University of New South Wales) on reporting items selected from the 2016 audit, the newly introduced reporting practices, and items from previous audits. Summary statistics (means, counts) were used to summarize audit results. In total, 580 papers were audited. Compared to results from the 2016 audit, several reporting practices remained unchanged or worsened. For example, 60% of papers erroneously reported standard errors of the mean, 23% of papers included undefined measures of variability, 40% of papers failed to define a statistical threshold for their tests, and when present, 64% of papers with p-values between 0.05 and 0.1 misinterpreted them as statistical trends. As for the newly introduced reporting practices, required practices were consistently adhered to by 34 to 37% of papers, while strongly encouraged practices were consistently adhered to by 9 to 26% of papers. Adherence to the other audited reporting practices was comparable to our previous audits. Publicly highlighting poor reporting practices did little to improve research reporting. Similarly, requiring or strongly encouraging reporting practices was only partly effective. Although the present audit focused on a single journal, this is likely not an isolated case. Stronger, more strategic measures are required to improve poor research reporting.

Background: Essential tremor (ET) is characterized by abnormal oscillatory muscle activity and cerebellar involvement, factors that can lead to proprioceptive deficits, especially in active tasks. The present study aimed to quantify the severity of proprioceptive deficits in people with ET and estimate how these contribute to functional impairments.Methods: Upper limb sensory, proprioceptive and motor function was assessed in individualswith ET (n = 20) and healthy individuals (n = 22). To measure proprioceptive ability, participants discriminated the width of grasped objects and the weight of objects lifted with the wrist extensors. Causal mediation analysis was used to estimate the extent that impairments in upper limb function in ET was mediated by proprioceptive ability.Results: Participants with ET had impaired upper limb function in all outcomes, and had greater postural and kinetic tremor. There were no differences between groups in proprioceptive discrimination of width (between-group mean difference [95% CI]: 0.32 mm [-0.23 to 0.87 mm]) or weight (-1.12 g [-7.31 to 5.07 g]). Causal mediation analysis showed the effect of ET on upper limb function was not mediated by proprioceptive ability.Conclusions: Upper limb function but not proprioception was impaired in ET. The effect of ET on motor function was not mediated by proprioception. These results indicate that the central nervous system of people with ET is able to accommodate mild to moderate tremor in active proprioceptive tasks that rely primarily on afferent signals from muscle spindles.

"Effect of muscle fatigue on metabolic cost in running and implications for footwear design." Footwear Science, 15(sup1), pp. S132–S133Keywords: Fatiguemetabolic costmuscle activation patternsperformancefatigue effectsrunning Disclosure statementNo potential conflict of interest was reported by the author(s).

AbstractTranscutaneous spinal cord stimulation (TSS) is purported to improve motor function in people after spinal cord injury (SCI). However, several methodology aspects are yet to be explored. We investigated whether stimulation configuration affected the intensity needed to elicit spinally evoked motor responses (sEMR) in four lower limb muscles bilaterally. Also, since stimulation intensity for therapeutic TSS (i.e., trains of stimulation, typically delivered at 15–50 Hz) is sometimes based on the single‐pulse threshold intensity, we compared these two stimulation types. In non‐SCI participants (n = 9) and participants with a SCI (n = 9), three different electrode configurations (cathode–anode); L1‐midline (below the umbilicus), T11‐midline and L1‐ASIS (anterior superior iliac spine; non‐SCI only) were compared for the sEMR threshold intensity using single pulses or trains of stimulation which were recorded in the vastus medialis, medial hamstring, tibialis anterior, medial gastrocnemius muscles. In non‐SCI participants, the L1‐midline configuration showed lower sEMR thresholds compared to T11‐midline (p = 0.002) and L1‐ASIS (p < 0.001). There was no difference between T11‐midline and L1‐midline for participants with SCI (p = 0.245). Spinally evoked motor response thresholds were ~13% lower during trains of stimulation compared to single pulses in non‐SCI participants (p < 0.001), but not in participants with SCI (p = 0.101). With trains of stimulation, threshold intensities were slightly lower and the incidence of sEMR was considerably lower. Overall, stimulation threshold intensities were generally lower with the L1‐midline electrode configuration and is therefore preferred. While single‐pulse threshold intensities may overestimate threshold intensities for therapeutic TSS, tolerance to trains of stimulation will be the limiting factor in most cases.

Journals can substantially influence the quality of research reports by including responsible reporting practices in their Instructions to Authors. We assessed the extent to which 100 journals in neuroscience and physiology required authors to report methods and results in a rigorous and transparent way. For each journal, Instructions to Authors and any referenced reporting guideline or checklist were downloaded from journal websites. Twenty-two questions were developed to assess how journal Instructions to Authors address fundamental aspects of rigor and transparency in five key reporting areas. Journal Instructions to Authors and all referenced external guidelines and checklists were audited against these 22 questions. Of the full sample of 100 Instructions to Authors, 34 did not reference any external reporting guideline or checklist. Reporting whether clinical trial protocols were pre-registered was required by 49 journals and encouraged by 7 others. Making data publicly available was encouraged by 64 journals; making (processing or statistical) code publicly available was encouraged by ∼30 of the journals. Other responsible reporting practices were mentioned by less than 20 of the journals. Journals can improve the quality of research reports by mandating, or at least encouraging, the responsible reporting practices highlighted here.

Proprioception, which can be defined as the awareness of the mechanical and spatial state of the body and its musculoskeletal parts, is critical to motor actions and contributes to our sense of body ownership. To date, clinical proprioceptive tests have focused on a person’s ability to detect, discriminate, or match limb positions or movements, and reveal that the strength of the relationship between deficits in proprioception and physical function varies widely. Unfortunately, these tests fail to assess higher-level proprioceptive abilities. In this Perspective, we propose that to understand fully the link between proprioception and function, we need to look beyond traditional clinical tests of proprioception. Specifically, we present a novel framework for human proprioception assessment that is divided into two categories: low-level and high-level proprioceptive judgments. Low-level judgments are those made in a single frame of reference and are the types of judgments made in traditional proprioceptive tests (i.e., detect, discriminate or match). High-level proprioceptive abilities involve proprioceptive judgments made in a different frame of reference. For example, when a person indicates where their hand is located in space. This framework acknowledges that proprioception is complex and multifaceted and that tests of proprioception should not be viewed as interchangeable, but rather as complimentary. Crucially, it provides structure to the way researchers and clinicians can approach proprioception and its assessment. We hope this Perspective serves as the catalyst for discussion and new lines of investigation.

Letter to the EditorProprioception: fallacies and misconceptions – response to Han et al. 2022Martin E. Héroux, Annie A. Butler, Lucy S. Robertson, Georgia Fisher, Jean-Sébastien Blouin, Joanna Diong, Carmen Krewer, François Tremblay, and Simon C. GandeviaMartin E. HérouxNeuroscience Research Australia, Sydney, New South Wales, AustraliaSchool of Medical Sciences, University of New South Wales, Sydney, New South Wales, Australia, Annie A. ButlerNeuroscience Research Australia, Sydney, New South Wales, AustraliaSchool of Medical Sciences, University of New South Wales, Sydney, New South Wales, Australia, Lucy S. RobertsonNeuroscience Research Australia, Sydney, New South Wales, AustraliaSchool of Medical Sciences, University of New South Wales, Sydney, New South Wales, Australia, Georgia FisherNeuroscience Research Australia, Sydney, New South Wales, Australia, Jean-Sébastien BlouinSchool of Kinesiology, University of British Columbia, Vancouver, British Columbia, Canada, Joanna DiongFaculty of Medicine and Health, School of Medical Sciences, The University of Sydney, Sydney, New South Wales, Australia, Carmen KrewerSchoen Clinic Bad Aibling, Bad Aibling, GermanyDepartment of Sports and Health Sciences, Human Movement Science, Technical University Munich, Munich, Germany, François TremblaySchool of Rehabilitation Sciences, University of Ottawa, Ottawa, Ontario, Canada, and Simon C. GandeviaNeuroscience Research Australia, Sydney, New South Wales, AustraliaClinical School, University of New South Wales, Sydney, New South Wales, AustraliaPublished Online:30 Aug 2022https://doi.org/10.1152/japplphysiol.00409.2022MoreSectionsPDF (288 KB)Download PDF ToolsExport citationAdd to favoritesGet permissionsTrack citations ShareShare onFacebookTwitterLinkedInWeChat TO THE EDITOR: In our Perspective entitled “Proprioception: a new look at an old concept”, we proposed that proprioceptive tests could be placed along a continuum of increasing neural complexity and separated into those which were low-level and those which were high-level (1). A primary objective of our perspective was to spark discussion. Thus, we welcome the Letter by Han et al. (2), as it provides an opportunity to elaborate on key concepts and clarify certain misconceptions. To this end, we invited colleagues from the fields of motor control, rehabilitation, and statistics to join our response.Han et al. (2) indicate that they reviewed and classified methods to assess proprioception. In their view, “There are three main testing techniques for assessing proprioception—threshold detection of passive movement (TTDPM), joint position reproduction (JPR), also known as joint position matching, and active movement extent discrimination assessment (AMEDA)” (3). Passive TTDPM and JPR methods assess passively imposed proprioception, whereas the AMEDA test, which involves voluntary muscle contraction and may depend more on central processing, assesses actively obtained proprioception (4). Unfortunately, this classification, derived from Gibson (5), an ecological psychologist whose work focused on vision, fails to accommodate even the simplest proprioceptive tests. For example, in a common test of position sense, one limb is positioned passively, whereas the other limb matches actively. What is assessed: passively imposed or actively obtained proprioception?Han et al. (2) also argue that “it is an oversimplification to classify the three current proprioceptive testing methods as low-level.” This criticism is unjustified. We present low-level proprioception tests along a continuum (i.e., detect, discriminate, and match) and identify additional ways to differentiate low-level proprioceptive tests. For example, are they unilateral or bilateral, do they involve one joint or multiple joints, and do they involve the upper limbs, lower limbs, trunk, or neck? Although it was beyond the scope of our perspective, the comment by Han et al. (2) highlights the need for an improved taxonomy for proprioceptive tests that are based on expert consensus and physiological concepts.Another criticism by Han et al. (2) is that our perspective failed to consider “how closely proprioceptive tests reflect how the proprioceptive system works in real life”, which they consider to reflect ecological validity. First, the authors take issue with proprioceptive tests performed in absence of vision due to Bayes-optimal (or nearly optimal) sensory integration. However, probabilistic models of multisensory integration require careful estimates of bias and variability for each sensory modality encoding a variable of interest (6, 7), which requires selective evaluation of each sensory modality. The objection from Han et al. (2) may be better framed as a Bayesian prior regarding whole body orientation in space (also originating from a multisensory integration process). The potential influence of this prior information on the performance of proprioceptive tests presents a potential avenue for future research. Second, among the three types of proprioceptive tests considered by Han et al. (3), only the AMEDA test was considered ecologically valid. This test, created by Han et al. (2), is ill-named. In the original version of the test, a “central (standard) position was presented on each trial randomly as the first or second of the two movements being compared” (8). However, the same year, the authors published a different version of the AMEDA test (9), which Han et al. (3) describe as follows:“AMEDA tests are conducted using active movements. Each participant is given a familiarization session using an AMEDA apparatus before data collection commences, during which they are informed that they will experience, for example, five movement displacement distances, in order, from the smallest (moving to position 1) to the largest (moving to position 5), three times: 15 movements in total. Participants thereafter (typically) undertake 50 trials of testing, in which all five positions are presented 10 times, in a random order. On each trial in the AMEDA test protocol, only one movement out to the stop at a steady pace is allowed, followed by return to the start position. After experiencing a position and returning to the start position, participants are asked to make a judgement as to the position number (1, 2, 3, 4, or 5) of each test movement, without feedback being given as to the correctness to the judgement they make for each trial. That is, participants must use their memory of the five movement extents from the familiarization trials to enable them to identify each stimulus and thus make a numerical judgement (1, 2, 3, 4, or 5) identifying each perceived stimulus after it is presented. This task is thus a single stimulus or absolute judgement task, wherein a single stimulus is presented and single response is made on each trial. The time required to undertake one joint proprioception test is ∼10 min.”Based on this narrative, the AMEDA test is no longer a simple discrimination test but is now a complex test that requires people to learn the amplitude of a series of discrete, actively produced movements, which must be remembered and matched to other actively produced movements, some of which occur minutes later. Although Tremblay (10) previously emphasized the high memory requirements of the AMEDA test, Han et al. (3) conclude that, compared with joint repositioning tests, their test had low memory requirements. Moreover, Krewer et al. (11) highlighted that ecological validity does not supercede construct validity (i.e., how well a test measures the variable of interest). Referring to the version of the AMEDA test intended to assess ankle joint proprioception, Krewer et al. (11) wrote:“What the authors specify as strength for ecological validity can also be considered to be a critical concern for construct validity. In our opinion, the results obtained by AMEDA are not indicative of the proprioceptive function of a specific joint. They are more representative of a multi-modal, multi-joint measure of a multi-segment posture.”Other joints and senses (e.g., visual, vestibular, and auditory) likely encode motion associated with performance using this version of the AMEDA test (see Refs. 12, 13). However, we would go one step further and argue that a person could perform the AMEDA test without ankle proprioception. Similar to the strategy used by a deafferented individual (14), a person could send the same voluntary command and, based on when the movement ends, signaled either by cutaneous feedback from the foot sole or auditory cues from the device contacting the rigid stop, estimate the amplitude of the ankle movement. Even with intact proprioception, a person could focus on the time taken to reach the end of the movement rather than the actual angle of the ankle joint. Thus, performance on the AMEDA test may not reflect proprioceptive ability about the ankle joint. To measure ankle proprioception in an upright posture, other tests should be used (15, 16).Although no rationale is provided, Han et al. (2) proposed all tests need to be assessed for predictive validity, i.e., accurately predicting future outcomes from baseline time. They cite 10 of their own AMEDA papers to assert its predictive ability. However, all referenced studies bar one, a small longitudinal study (17), were cross-sectional. By design, these studies cannot determine predictive validity over time, as acknowledged by the authors (18). Moreover, the low number of events to potential predictors in their longitudinal study and the lack of external model validation undercut the authors’ own emphasis on predictive validity (17). Thus, it appears the authors confuse prediction with any form of association, regardless of whether the association is longitudinal or cross-sectional (19).Despite these and other criticisms (e.g., Refs. 10, 11), the associations found between AMEDA tests and functional performance are likely genuine. However, it is important to make clear that AMEDA tests are multijoint and multisensory, have high memory requirements, and can be completed with alternative performance strategies.In summary, the perspective by Héroux et al. (1) and the Letter by Han et al. (2) highlight various fallacies and misconceptions that persist in the field of proprioception. It is also clear that we need to formalize the terminology used to describe and categorize proprioceptive tests. This classification should be founded in common sense and, in our opinion, underlying physiological processes. Importantly, it should be practical for both clinicians and researchers.DISCLOSURESNo conflicts of interest, financial or otherwise, are declared by the authors.Simon Gandevia is an editor of Journal of Applied Physiology and was not involved and did not have access to information regarding the peer-review process or final disposition of this article. An alternate editor oversaw the peer-review and decision-making process for this article.AUTHOR CONTRIBUTIONSM.E.H., A.A.B., and S.C.G. drafted manuscript; M.E.H., A.A.B., L.S.R., G.F., J.-S.B., J.D., C.K., F.T., and S.C.G. edited and revised manuscript; M.E.H., A.A.B., L.S.R., G.F., J.-S.B., J.D., C.K., F.T., and S.C.G. approved final version of manuscript.REFERENCES1. Héroux ME, Butler AA, Robertson LS, Fisher G, Gandevia SC. Proprioception: a new look at an old concept. J Appl Physiol (1985) 132: 811–814, 2022. doi:10.1152/japplphysiol.00809.2021.Link | ISI | Google Scholar2. Han J, Adams R, Yang N, Waddington G. 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Spinal Cord 50: 579–584, 2012. doi:10.1038/sc.2012.25. Crossref | PubMed | ISI | Google ScholarAUTHOR NOTESCorrespondence: M. E. Héroux (m.[email protected]edu.au); S. C. Gandevia (s.[email protected]edu.au). Download PDF Previous Back to Top FiguresReferencesRelatedInformationRelated ArticlesProprioception: a different look at the same concept—Comment on Heroux et al. 30 Aug 2022Journal of Applied Physiology More from this issue > Volume 133Issue 3September 2022Pages 608-610 Crossmark Copyright & PermissionsCopyright © 2022 the American Physiological Society.https://doi.org/10.1152/japplphysiol.00409.2022PubMed36041481History Received 12 July 2022 Accepted 15 July 2022 Published online 30 August 2022 Published in print 1 September 2022 Keywordsproprioception Metrics

STUDY DESIGN:An international multi-centred, double-blinded, randomised sham-controlled trial (eWALK). OBJECTIVE:To determine the effect of 12 weeks of transcutaneous spinal stimulation (TSS) combined with locomotor training on walking ability in people with spinal cord injury (SCI). SETTING:Dedicated SCI research centres in Australia, Spain, USA and Scotland. METHODS:Fifty community-dwelling individuals with chronic SCI will be recruited. Participants will be eligible if they have bilateral motor levels between T1 and T11, a reproducible lower limb muscle contraction in at least one muscle group, and a Walking Index for SCI II (WISCI II) between 1 and 6. Eligible participants will be randomised to one of two groups, either the active stimulation group or the sham stimulation group. Participants allocated to the stimulation group will receive TSS combined with locomotor training for three 30-min sessions a week for 12 weeks. The locomotor sessions will include walking on a treadmill and overground. Participants allocated to the sham stimulation group will receive the same locomotor training combined with sham stimulation. The primary outcome will be walking ability with stimulation using the WISCI II. Secondary outcomes will record sensation, strength, spasticity, bowel function and quality of life. TRIAL REGISTRATION:ANZCTR.org.au identifier ACTRN12620001241921.