ISEK Around the World

Synaptic inputs to motoneurones will typically activate two classes of receptors: ionotropic and neuromodulatory. In a general sense, inputs to ionotropic receptors are command signals to activate the motoneurone, whereas neuromodulatory receptors modify the motoneurone’s responsiveness to ionotropic input. This presentation will focus on the role that serotonin has as a neuromodulator, where data from cellular and animal studies have revealed the importance that serotonin has for regulating motoneurone discharge. Findings from our human experiments will be discussed, where drug interventions have been used to safely study how serotonin activity in the CNS influences motor function. In these experiments, we reveal that descending drive is critical for serotonin to exert effects on motoneurones, with the 5-HT2 receptor playing a significant role in regulating motoneurone excitability. We demonstrate that blocking 5-HT2 receptor activity can suppress motor unit discharge rates, persistent inward currents, and self-sustained firing, which ultimately leads to reduction in muscle force. Since many clinical populations experience muscle weakness, neuromodulatory receptors may be a potential avenue for therapeutic development to support muscle activation through central excitability modulation.

Skeletal muscles driving animal movements show a wide variety of architecture in terms of the geometric arrangement of fascicles (bundles of muscle fibers), which largely determine how muscles act on the crossing joint. While muscle architecture has been extensively examined in living human experiments, our understanding is limited to certain small muscles located in the superficial sites due to the limitations of conventional ultrasound imaging. As a promising alternative to ultrasonography, diffusion tensor imaging (DTI), one of the MRI techniques, and related fiber tracking have emerged, enabling visualization and quantification of muscle fascicles over a large area of interest in 3D space. In this symposium, I will introduce recent works including our studies that utilized DTI to unveil how “giant” muscles, such as the gluteus maximus and adductor magnus, form and act in living human bodies. Our results provide novel insights into the functional role of each muscle beyond the current understanding, which strongly relied on anatomical studies. This potentially contributes to understanding how individual muscles control bodily movements and hints at the design of training/rehabilitation for enhancing our motor performance.  

Neural adaptations in motor unit properties contribute to early strength gains from eccentric training, yet these mechanisms remain unexplored in the hamstrings. This study examined changes in biceps femoris long head (BFlh) motor unit recruitment threshold and discharge rate during submaximal isometric contractions after 3 and 9 weeks of eccentric training.
Nineteen recreationally active men completed a 9-week eccentric program, with assessments pre-training, at week 3, and post-training. High-density surface electromyography was recorded during submaximal isometric knee flexions, and motor units were decomposed and tracked across sessions by matching action potential waveforms. Linear mixed-effects models compared recruitment threshold and discharge rate of matched units across time.
A total of 660 motor units were identified, with 68 successfully tracked over the intervention. Knee flexor strength increased by 6% at week 3 and 17% at post-training. Recruitment threshold increased by 12% at week 3 and 18% at post-training. Discharge rate increased by 6% at week 3 but returned to baseline by post-training.
These findings indicate that early strength gains with eccentric are underpinned by increased motor unit discharge rate and recruitment threshold, whereas continued strength improvement beyond 3 weeks reflects a shift toward structural rather than neural adaptations.

Skeletal muscle is one of the most fascinating tissues of our body due to its capability to actively generate forces. Our current understanding of in vivo muscle behavior is largely based on observations from animal muscles, as direct muscle force measurements in humans are limited and highly invasive. Still, we know from decades of research that muscle geometry and architecture are closely tied to its function, and this relationship manifests as length- and activity-dependent nonlinear behavior. The advancement of medical imaging techniques provides a great opportunity to characterize this behavior non-invasively, in vivo, at the whole muscle level. Ultrasound-based techniques such as shear wave elastography (SWE) and MRI-based techniques such as diffusion-tensor imaging each give unique insights; however, their use and interpretation of the derived measures are still challenging.
In this presentation, we will explore what SWE experiments in passive and active muscle states can reveal, examine the current limitations to interpreting these data, and discuss how MRI-based models might help overcome these challenges in the future.

Surface Electromyography (sEMG) signals have become an essential modality for understanding neuromuscular dynamics in human movement analytics. With advancements in wearable sensors and signal acquisition systems, sEMG enables real-time assessment of muscle activation during functional tasks. Recent trends focus on integrating sEMG with motion capture systems, inertial sensors, and AI-based models to extract clinically relevant features. Novel approaches such as high density sEMG, machine learning classification, and EMG-driven musculoskeletal modelling have shown promising applications in sports performance and rehabilitation. However, challenges persist due to signal noise, motion artifacts, electrode placement variability, and inter-subject differences. The non-stationary nature of sEMG and the difficulty in standardizing signal preprocessing limit its widespread adoption in dynamic tasks. Additionally, interpreting sEMG in pathological conditions requires contextual biomechanical modelling. Addressing these challenges is key to developing reliable biofeedback systems and predictive analytics. This talk explores the state-of-the-art in sEMG processing and highlights the path forward for translational applications in human movement science.

Adolescent idiopathic scoliosis (AIS) is characterised by three-dimensional vertebral and disc wedging. It is well-known that muscle activity and morphology influence muscle force generation, and that the forces applied to bones and discs are substantial moderators of growth and adaptation. Evidence suggest that paraspinal muscle imbalances may contribute to curve progression in AIS. However, findings across studies remain inconsistent, partly due to methodological variations. This study investigated whether adolescents with AIS demonstrate greater asymmetry in paraspinal muscle activation compared to peers without scoliosis during a simple, symmetrical, submaximal trunk extension task.

Twenty-four females with right thoracic AIS (mean age 13.8 ± 1.5 years) and 20 age-matched controls (mean age 13.8 ± 1.8 years) were recruited. Surface electromyography recorded bilateral muscle activity at T9 and T12 during submaximal trunk extensions performed at 10–20% of each individual’s maximal voluntary contraction. Symmetry of muscle activation was quantified using a log-transformed right-to-left ratio, and linear mixed modelling assessed between-group differences.
Findings from this study highlight localised asymmetry in paraspinal muscle activation at the curve apex in AIS. Such imbalances may contribute to asymmetrical spinal loading and potentially influence curve progression during growth.

Muscle fatigue is a neuromuscular phenomenon characterized by a decline in the ability to generate force during sustained muscle contractions. Surface Electromyography (sEMG) offers a non invasive approach for monitoring the myoelectric activity associated with muscle fatigue. While traditional analyses focus on the electrical behaviour of muscles, recent advancements highlight the importance of integrating mechanical properties to gain a comprehensive understanding of fatigue. In this study, an isometric fatiguing protocol is employed using the biceps brachii muscle under a 3 kg load, with simultaneous acquisition of sEMG signals and myotonometric measurements. Mechanical parameters are recorded before and after the fatigue task. The acquired sEMG signals undergo preprocessing and are segmented into non-fatigue and fatigue phases. To capture transient spectral changes, the advanced time-frequency analysis technique is utilized. This approach facilitates the investigation of the interplay between fatigue-induced changes in the sEMG signal and the underlying mechanical properties of muscle tissue, contributing to a more holistic understanding of neuromuscular fatigue.

This study evaluated whether ultrasound-guided identification of residual muscle bellies enhances EMG electrode placement in transtibial amputees (TTAs), comparing relaxed versus contracted muscle thickness and EMG signal quality against traditional palpation. Nine TTAs attended two sessions. In session 1, ultrasound measured thickness of Tibialis Anterior (TA), Peroneus Longus (PL), and Gastrocnemius Lateral/Medial (GL/GM) in relaxed and contracted states, marking the thickest region for electrode placement. In session 2, a prosthetist located electrodes by palpation. Distances between ultrasound- and palpation- identified spots were documented, and EMG signals were collected from both locations during contraction. Muscle thickness increased significantly upon contraction (p < 0.001), with GM thickest and PL thinnest (p < 0.001). Palpation misidentified muscles in four cases. In 72.2% of cases, the distance between ultrasound- and palpation-identified spots was more than 10 mm. The mean distance was the greatest for PL and GL. Ultrasound-guided placement produced slightly higher, though non-significant, signal amplitudes (p = 0.06) and significantly higher SNR (p = 0.04). In conclusion, relying on palpation to identify muscles in TTAs may provide irrelevant EMG due to erroneous placement. Ultrasound improves EMG electrode placement and signal quality in TTAs, with potential benefits for prosthetic control.

Motor units (MUs), the fundamental functional units of the neuromuscular system, provide critical insight into neural codes that govern our skeletal muscles. Accurate identification of MU discharge patterns enables a deeper understanding of neuromuscular function and control. The high-density electromyography (hdEMG) processing pipeline comprises five essential steps: hdEMG acquisition, channel selection, blind source separation-based MU filter estimation, MU discharge segmentation, and assessment of physiological parameters, such as MU discharge rate, recruitment threshold, and motor excitability as assessed by the ∆F method.
This presentation will focus on the third and fourth steps, emphasizing the theory and implementation of MU filters in practice. Within a convolutive mixing model of hdEMG, motor unit action potentials (MUAPs) serve as mixing coefficients while MU discharges represent neural codes originating from the central nervous system. Summation of MUAPs, combined with noise, produces hdEMG signals. Decomposition algorithms invert this model, enabling extraction of MU discharges from hdEMG signals by applying MU filters.
We will present the mathematical foundations of MU filter estimation, strategies for their optimization, and methods to evaluate filter quality. Additionally, we will demonstrate the application of MU filters to hdEMG and EEG signals, highlighting typical use cases and addressing key concerns.
By bridging theoretical frameworks with practical applications, this talk aims to illustrate how MU filters can advance our understanding of neuromuscular systems and support future developments in neural interfacing and rehabilitation technologies.

The present study aimed to explore the influence of static stretching on maximal force, force steadiness, and motor unit (MU) discharge characteristics of the semitendinosus and biceps femoris. Fifteen young participants completed a randomized, counterbalanced, within-subject design. Before and after the passive static stretching (5 sets x 90-s trials), participants performed steady isometric contractions at 10% and 40% of maximum voluntary contraction force in two different tasks. The knee-flexion task was performed at a 30° knee joint angle with the hip in a neutral position, and the hip-extension task was conducted with the knee fully extended and the hip neutral. Four high-density EMG electrodes were placed along the two muscles. Static stretching reduced significantly (-18.9%) maximal force and impaired force steadiness in both target forces, with task-specific manner depending on the stretching maneuver. After static stretching, there were significant increases in mean discharge rate, coefficient of variation for interspike interval, and SD of the filtered cumulative spike train. Hip stretching primarily affected the biceps femoris, while knee stretching altered the semitendinosus muscle. Also, knee stretching influenced more the distal, while hip stretching affected the proximal regions. Static stretching impaired force profile and MU behavior in a task- and region-specific manner.

Understanding how the nervous system coordinates muscle activity during asymmetric locomotor tasks provides key insights into motor control strategies and their adaptability. Muscle synergies, or low-dimensional motor modules, are hypothesized to simplify movement control by recruiting groups of muscles in a coordinated fashion. In my research group studies, we explored the modular organization of muscle activity during asymmetric gaits, such as unilateral skipping, which decouple traditional gait parameters like stride frequency and duty factor, lateral walking and gait transitions. Using surface electromyography and non-negative matrix factorization, we extracted muscle synergies EMG recordings in healthy individuals under symmetric and asymmetric conditions. Our findings show that while the number of synergies remains relatively stable, the composition and timing of individual synergies are modulated by task asymmetry. These adaptations suggest that the central nervous system reconfigures muscle coordination strategies to accommodate altered mechanical demands. The results not only reinforce the flexibility of motor modules but also highlight the relevance of asymmetric paradigms to study gait robustness and neuroplasticity. These insights may inform the development of targeted interventions for populations with impaired gait symmetry, such as post-stroke individuals or amputees.

Maintaining stable foot placement during walking relies on the precise coordination of proactive and reactive control strategies. Proactive adjustments occur in the 200–300 ms window before heel strike, while reactive responses emerge within 100–150 ms after perturbation onset. With aging, these mechanisms may become compromised, contributing to falls, which are a leading cause of morbidity in older adults. This study investigates how aging influences the temporal balance between proactive and reactive locomotor adaptations and how individual differences in physiological, cognitive, and psychological function contribute to these strategies. We will recruit 150 adults (ages 18–90) to perform treadmill walking tasks on an instrumented split-belt system with projected stepping targets. Proactive adaptation will be tested with predictable target shifts, while reactive adaptation will be examined under unpredictable perturbations across different gait phases. Outcomes will include step length, step width, and margin of stability, analyzed relative to pre- and post-perturbation time windows. Cognitive (MoCA, TMT), physiological (PPA components), and psychological (FES-I) assessments will be used to identify predictors of adaptation performance. By quantifying age-related changes in proactive and reactive control, and linking them to specific functional domains, this study aims to establish evidence-based parameters for targeted interventions to enhance gait adaptability and fall prevention in older adults.

This talk will explore the relationship between muscle structure and function and the functionality of older adults. Within this line of research, we seek to understand which muscles and which parameters of muscle structure (such as muscle quality, muscle thickness, fascicle length, and pennation angle) and muscle function (such as isometric, concentric, and eccentric strength, power, and rate of force development) are associated with older adults’ functionality. The lecture will highlight findings from our ongoing research over the past years, as well as recent advances in this field.

Stroke survivors often exhibit impaired regulation of submaximal forces, which may be linked to disruptions in common synaptic drive (CSD) to motoneurons. This study quantified fluctuations in estimated CSD during a sustained, fatiguing knee extension contraction in chronic stroke survivors and neurologically intact controls. Surface EMG from the vastus lateralis was decomposed to extract motor unit discharge rates during the first and last 10% of a fatiguing contraction at 30% MVC. CSD fluctuations were estimated as the coefficient of variation of the first common component of smoothed discharge rates. Stroke survivors (n=19) had significantly greater fluctuations in CSD compared to controls (n=15) at baseline and during fatigue. Fatigue increased fluctuations in CSD in both groups. Additionally, greater fluctuations in CSD were associated with decreased force steadiness at both baseline and fatigue. Stroke survivors also showed higher variability in motor unit firing rates, reduced muscle activation during fatigue, and decreased force steadiness overall. These findings suggest that stroke-related disruptions in descending motor commands lead to greater variability in common input to motoneurons, which may impair force control. Quantifying fluctuations in CSD may provide a neural biomarker for motor impairment and offer a target for future rehabilitation strategies.