Nicole Wenderoth

Pupil size has been shown to reflect physical effort during brief, discrete motor tasks. It remains unknown whether pupil size similarly scales with effort during sustained repetitive movement, or whether it also reflects the accumulation of motor fatigability, a reduction in motor performance during prolonged movements. In our previous work, sustained maximal tapping induced motor slowing, a subtype of motor fatigability, characterized by decreasing movement speed and associated with increased antagonistic muscle coactivation. Next to these behavioural effects, pupil initially dilated and then gradually decreased over time. Whether this temporal change in pupil size is shaped by physical effort alone or also by motor fatigability remains unclear. Here, we combined a repetitive wrist tapping paradigm with force measurement, electromyography, and pupillometry, and paced participants at three different tapping speeds to dissociate physical effort from motor slowing, which has been shown to be speed-dependent. Fatigability-related motor slowing emerged selectively at the fastest speed. Moreover, we showed that antagonistic muscle coactivation increased more steeply at faster speeds, even in the absence of motor slowing, suggesting it may reflect an early change in motor control. While we found clear evidence that pupil size scaled with overall tapping speed, we did not find evidence that the temporal change of the pupil was pacing-dependent. These findings extend the pupil effort relationship to sustained, dynamic motor tasks and suggest that pupil size is a marker of physical effort but not motor fatigability during sustained repetitive movement.

The early somatosensory brainstem and thalamic nuclei are classically viewed as relays of peripheral input, yet research in animal models indicates they also receive top-down cortical signals. Whether such processing exists in humans remains unknown. Using cervical spinal cord injury (SCI), in which peripheral somatosensory input is reduced or absent while cortical processing is preserved, we tested whether top-down processing can elicit activation across the somatosensory nuclei. We combined 3 Tesla functional and quantitative MRI data to assess activity and structural properties along the somatosensory hand pathway in a cross-sectional study of 16 individuals with chronic cervical SCI (mean age ± s.e.m.=52.4 ± 3.5 years) and 20 age-, sex-, and handedness-matched able-bodied control subjects (mean age=50.8 ± 3.5 years). Participants were visually cued to make overt or, in cases of hand paralysis, attempted right- and left-hand movements. Activation was quantified across the cuneate nucleus, ventroposterior lateral thalamus, and primary somatosensory hand cortex, while structural properties were assessed using quantitative MRI measures sensitive to myelin and tissue integrity, including magnetisation transfer saturation (MTsat) and effective transverse relaxation rate (R2*), alongside morphometric measures. Despite reduced or absent peripheral input, SCI participants exhibited robust and lateralised activation across all levels of the somatosensory pathway. This pattern persisted even in a participant with complete hand paralysis who lacked bottom-up afferent input during the fMRI task, indicating that top-down processing alone is sufficient to drive activity in early somatosensory relays. We simultaneously observed structural degeneration in the cuneate nucleus of SCI participants, marked by reduced volume and myelin-sensitive metrics (MTsat and R2*), consistent with secondary degeneration. The extent of atrophy was related to time since injury and reduced sensorimotor hand function, but showed no significant relationship with functional activation, suggesting that preserved corticocuneate signalling is not dependent on the degree of structural degeneration. This provides the first evidence that the cuneate nuclei in humans are subject to both bottom- up and top-down somatosensory processing. Although these nuclei are vulnerable to structural atrophy following dorsal column injury, our results suggest that top-down processing remains intact decades after SCI. This may have implications for the development of rehabilitation treatments targeting preserved somatosensory processing after injury.

Background: Stroke is a leading cause of long-term disability worldwide, and with rising incidence and a global shortage of rehabilitation professionals, there is a growing need for scalable methods to assess motor impairment. Surface electromyography (sEMG) has emerged as a promising modality for capturing motor function. Despite its potential, sEMG remains underused in clinical practice and has been predominantly studied in chronic stroke populations, leaving the subacute phase largely unexplored. Its ability to complement standardized assessments is not yet well established. Methods: Bilateral sEMG was recorded from 23 subacute stroke participants performing four standardized wrist and hand tasks. Task-level features were extracted to train machine learning models to classify the presence of an impairment (affected or less-affected) and the level of impairment, as measured by the Upper Extremity Fugl-Meyer Assessment (FMA-UE) and its wrist and hand subsections (FMA-WH). Models were evaluated using leave-one-subject-out cross-validation (LOSO-CV). Benchmark regression models used therapist-rated subscores as inputs and paired t-tests compared their absolute errors against those of the sEMG-based models. Model interpretability was examined using SHapley Additive exPlanations values (SHAP) to identify sEMG features contributing most strongly to predicted impairment levels. Results: For impairment classification, Wrist Extension yielded the highest performance in classifying impairment (Accuracy 0.87 ± 0.16; Area Under the Receiver Operating Characteristic [AUC-ROC] 0.96 ± 0.07). An evaluation of all binary and triple task combinations revealed that Wrist Extension combined with Pincer Grasp achieved the best overall classification (Accuracy 0.92 ± 0.12; AUC-ROC 0.99 ± 0.03). For impairment level estimation, the sEMG-based predictions reached a Root Mean Squared Error (RMSE) of 3.12 for FMA-WH and 6.68 for FMA-UE. SHAP analysis with the sEMG-based model revealed that higher extensor activation strongly drove higher predicted scores. Conclusions: Using sEMG signals obtained from a consumer-grade armband during hand and wrist tasks enabled estimation of partial and full FMA-UE scores, achieving prediction errors below the minimally clinically important difference (MCID) of the full FMA-UE. Furthermore, a two-task protocol (Wrist Extension + Pincer Grasp) achieved the highest classification accuracy, demonstrating that clinical assessment burden could be reduced without compromising performance. This highlights the potential for scalable and portable assessment solutions, though larger longitudinal validation is required.

Reward can enhance motor performance. However, its potential to counteract motor fatigability, a reduction in motor performance during sustained movements, remains underinvestigated. This could be relevant in neurological conditions such as multiple sclerosis, where increased motor fatigability is a prominent symptom. One form of motor fatigability is motor slowing, a decline in movement speed over time evoked by fast, repetitive movements. In this study, we investigated whether the possibility to earn reward attenuates motor slowing, and examined associated changes in muscle activity and pupil size, a putative marker of physical effort. Participants performed a wrist tapping task at maximal voluntary speed with or without the possibility of earning a reward. We found that wrist tapping induced motor slowing and that slowing was significantly reduced by reward. Over time, tapping became more costly as indicated by higher muscle activity and coactivation per tap. This was accompanied by a sustained pupil dilation, which could not solely be explained by tapping speed. These findings suggest that, rather than restoring efficient motor control, reward attenuates motor slowing by allowing participants to access a performance reserve and invest more resources into the task, reflected by increased muscle activation per tap and sustained pupil dilation.

Introduction: In recent years, the growing demand for cost-effective rehabilitation after stroke has motivated the development of novel technologies to support high-intensity rehabilitation. However, available knowledge on the economic benefits of stroke technology-assisted rehabilitation (TAR) is relatively scarce and fragmented. Therefore, this scoping review aimed to review evidence on the economic benefits of TAR in laboratory, clinical, and home settings, as well as the methodologies used to evaluate these outcomes. Methods: A systematic search of four electronic bibliographic databases and two additional grey literature/ economic evidence sources (until 03 June 2026) identified 6469 records. Following predefined inclusion and exclusion criteria, 44 records were considered for further analysis. Additionally, 21 records were identified through a citation search. Results: In total, 65 articles reporting TAR-related costs were included, but only a few of these studies reported cost analyses (mostly cost comparisons). Firstly, of the 38 studies conducted in laboratory settings, only one reported a formal TAR-related cost analysis. Secondly, out of 16 studies reporting costs, 11 studies performed cost analysis for TAR in clinical settings. Of these, the majority (six) estimated TAR to be equally effective or even superior (one) and cheaper than conventional therapy (CT) in the clinic, but only when TAR enabled the therapist to treat several stroke survivors in parallel. This was captured using the relative therapist-to-patient ratio (rT/P), indicating that staffing and supervision models were more important than device cost. Lastly, seven of 13 studies conducted TAR-related cost analysis in a home setting. Three studies suggested that TAR may be economically beneficial compared with CT in the clinic. Conclusion: Empirical findings suggest that TAR may generate cost savings compared to CT in the clinic, particularly when rT/P is < 0.5. However, the current evidence is sparse, with limited comparability and generalisability due to heterogeneous TAR modalities, comparators and cost-calculation methods. Clinical trial number: Not applicable.

Spinal cord injury (SCI) leads to profound disruptions in sensorimotor processing. Seminal research in nonhuman primates suggests this sensory deprivation causes functional remapping in the primary somatosensory cortex (S1), where somatotopic representations of deprived body parts, such as the hand in cervical SCI, become responsive to touch on intact body parts, such as the face. However, evidence for such remapping in humans remains inconclusive. We investigated face-to-hand remapping in 16 chronic cervical SCI patients (15 male, 1 female) and 21 able-bodied controls (19 male, 2 female) using two fMRI experiments. Experiment 1 employed a lip movement task, while Experiment 2 investigated the full architecture of S1 face reorganization through vibrotactile stimulation of the forehead, lips, and chin. We assessed (1) the level of face activity in the anatomical S1 hand area, (2) cortical shifts in peak face activity, (3) face-part separability in the S1 hand area, and (4) correlations with clinical characteristics that may drive face-to-hand area remapping. Our results revealed no significant evidence in favor of face-to-hand area remapping in tetraplegic patients across markers of face-to-hand remapping during either lip movement or vibrotactile stimulation of face parts. Furthermore, our markers of remapping did not correlate with clinical characteristics. Together, these findings indicate that cortical face-to-hand remapping could not be demonstrated in our cohort of chronic cervical SCI patients, highlighting the need to revisit assumptions of large-scale face-to-hand reorganization after SCI.

Study Objectives: To quantify high-resolution video-based eye kinematics across sleep macro- and microstructure and determine their coupling with pupil-based and cortical arousal markers. Methods: We recorded polysomnography and utilized infrared video-based eye-tracking in 17 healthy adults. Computer vision was employed to extract eye position and speed, which were related to pupil size (subcortical arousal marker) and EEG spectral slope (cortical arousal marker) across sleep stages, rapid eye movement (REM) substates, and K-complexes. Results: Eye kinematics varied significantly across sleep stages (p<0.001), except for horizontal pupil position (p=0.192). Video-based eye position and speed are sufficient to classify stages with above chance level accuracy (47%). Eye movement speed positively correlated with pupil size during non-REM sleep (R≥0.21, p<0.001) and with spectral slope during wakefulness and REM sleep (R≥0.11, p<0.018). These strengths of the correlations differ depending on the direction of the eye movement. Phasic REM exhibited faster eye movements, larger pupil size (p<0.001), and a flatter spectral slope (p=0.014) compared to tonic REM, indicating elevated subcortical and cortical arousal. K-complexes were accompanied by increased eye movement speed (p<0.05) and a steeper spectral slope (p≤0.010), suggesting a transient shift toward a sleep-protective cortical state despite concurrent oculomotor activation. Conclusions: Video-based eye-tracking reveals that eye movements are quantitatively coupled to brain-wide arousal fluctuations in a state-dependent manner. This methodology provides a ground-truth framework for resolving fine-grained eye dynamics during sleep, offering a high-fidelity tool for sleep phenotyping and clinical assessment. Statement of significance: Traditional sleep monitoring relies on low-resolution electrical signals that often confound true eye movements with brain or muscle activity. This study uses high-resolution video tracking to establish a physical ground truth for eye kinematics across human sleep. We demonstrate that eye movements are coupled with both cortical and subcortical arousal levels in a state-dependent manner, providing a clearer neurophysiological distinction between, for example, sleep substates like tonic and phasic REM. This framework reveals how the eyes serve as a non-invasive window into the brain’s internal arousal state. Such insights address critical gaps in understanding sleep microarchitecture and offer a novel pathway for developing high-fidelity biomarkers for neurological disorders, such as Parkinson’s disease, characterized by disrupted sleep-related arousal.

The importance of sleep as a key component of cardiovascular health has been increasingly recognized. Our previous research demonstrated that auditory‐enhanced slow waves increase cardiac function, but the underlying mechanisms behind these beneficial effects remain uncertain. In this study, we examined the influence of two types of slow waves on cardiovascular functions. 18 healthy middle‐aged men participated in a three‐night sleep lab experiment under three conditions: two auditory slow wave enhancement conditions and one SHAM control. We found that the strength of heart rate and blood pressure responses occurring concurrently with slow waves predicts post‐sleep cardiac function in men as measured through transthoracic echocardiography. Furthermore, we observed that highly synchronized type I slow waves, compared to lower‐amplitude type II slow waves, are primarily associated with increased cardiovascular responses (transient increase in heart rate and blood pressure). While auditory stimulation enhances both types of slow waves, they display distinct temporal dynamics, suggesting different underlying brain and body microstates. These distinct slow wave types may affect cardiovascular function differently, indicating that targeted slow wave stimulation could be a strategic approach to enhancing cardiac function. Trial Registration: This study was registered under clinicaltrials.gov (NCT04166916)

Transcutaneous auricular vagus nerve stimulation (taVNS) is a promising noninvasive neuromodulation technique with growing therapeutic relevance. Although increasingly combined with physical therapy in neurorehabilitation, its mechanistic effects during active movement remain poorly understood, as most physiology studies examine taVNS at rest, overlooking the dynamic neural activity engaged during movement. This study aimed to determine the neurophysiological basis for pairing taVNS bursts with movement. Thirty-six healthy adults (10 females, 26 males) completed two experiments where 2 s taVNS bursts were delivered. The first experiment assessed autonomic [heart rate (HR), galvanic skin response (GSR)], neuromodulatory (pupil diameter), and cortical [electroencephalography (EEG) spectral slope] responses during a randomized trial design involving three stimulation conditions (taVNS, earlobe sham, no stimulation) and two behavioral contexts [movement (go) vs still (no-go)]. The second experiment evaluated corticospinal excitability by measuring transcranial magnetic stimulation (TMS)-induced motor evoked potentials (MEPs) during taVNS. taVNS increased TMS-induced MEP amplitudes, indicating transient facilitation of corticospinal output when stimulation coincides with an engaged motor system. Concordantly, EEG sensorimotor activity was enhanced by taVNS during movement but not during stillness. In contrast, pupil diameter showed a clear phasic response to stimulation in both movement and still conditions, consistent with state-independent neuromodulatory engagement. Autonomic indices were not additionally modulated by phasic taVNS beyond movement-related changes. These findings identify a state-dependent window in which taVNS preferentially boosts task-engaged motor circuitry rather than producing nonspecific autonomic activation, providing mechanistic support for movement-paired stimulation protocols and highlighting pupil, EEG, and MEPs as sensitive biomarkers of phasic taVNS effects.

The early somatosensory brainstem and thalamic nuclei are classically viewed as relays of peripheral input, yet research in animal models indicates they also receive top-down cortical signals. Whether such processing exists in humans remains unknown. Using cervical spinal cord injury (SCI), in which peripheral somatosensory input is reduced or absent while cortical processing is preserved, we tested whether top-down processing can elicit activation across the somatosensory nuclei. We combined 3 Tesla functional and quantitative MRI data to assess activity and structural properties along the somatosensory hand pathway in a cross-sectional study of 16 individuals with chronic cervical SCI (mean age ± s.e.m.=52.4 ± 3.5 years) and 20 age-, sex-, and handedness-matched able-bodied control subjects (mean age=50.8 ± 3.5 years). Participants were visually cued to make overt or, in cases of hand paralysis, attempted right- and left-hand movements. Activation was quantified across the cuneate nucleus, ventroposterior lateral thalamus, and primary somatosensory hand cortex, while structural properties were assessed using quantitative MRI measures sensitive to myelin and tissue integrity, including magnetisation transfer saturation (MTsat) and effective transverse relaxation rate (R2*), alongside morphometric measures. Despite reduced or absent peripheral input, SCI participants exhibited robust and lateralised activation across all levels of the somatosensory pathway. This pattern persisted even in a participant with complete hand paralysis who lacked bottom-up afferent input during the fMRI task, indicating that top-down processing alone is sufficient to drive activity in early somatosensory relays. We simultaneously observed structural degeneration in the cuneate nucleus of SCI participants, marked by reduced volume and myelin-sensitive metrics (MTsat and R2*), consistent with secondary degeneration. The extent of atrophy was related to time since injury and reduced sensorimotor hand function, but showed no significant relationship with functional activation, suggesting that preserved corticocuneate signalling is not dependent on the degree of structural degeneration. This provides the first evidence that the cuneate nuclei in humans are subject to both bottom- up and top-down somatosensory processing. Although these nuclei are vulnerable to structural atrophy following dorsal column injury, our results suggest that top-down processing remains intact decades after SCI. This may have implications for the development of rehabilitation treatments targeting preserved somatosensory processing after injury.