Biology subjects

Ting, L. H.

Publications and source records attributed to Ting, L. H..

At least 19 recordsLinked to original sources

bioRxiv2026

Higher cortical beta oscillatory power before balance perturbations is associated with worse balance in older adults with Parkinson's Disease, but not in age-matched older adults

Elevated beta activity is hypothesized to reflect reduced flexibility in updating motor and sensory states, which may impair the rapid integration of sensory information required for balance. Therefore, we predicted that higher cortical beta power immediately before balance perturbations would be associated with poorer clinical balance performance, particularly in individuals with Parkinson's Disease (PD). Seventeen individuals with PD (median Hoehn & Yahr = 2) and eighteen neurotypical older adults stood on a translating platform while 32-channel electroencephalography was recorded. For each participant, the cortical component contributing most strongly to the perturbation-evoked N1 response, a balance-related cortical response localized to the supplementary motor area, was identified. Oscillatory beta power (13-30 Hz) during the one-second period immediately preceding perturbation onset was extracted from this N1-related cortical source and parameterized using Fitting Oscillations and One-Over-F (FOOOF). Balance ability was assessed using the Mini-Balance Evaluation Systems Test (Mini-BESTest). Beta power derived from this N1-related source did not differ between groups; however, within individuals with PD, higher pre-perturbation beta power was associated with lower Mini-BESTest scores, a relationship not observed in neurotypical older adults. A subset of older adults exhibited an additional, higher-frequency beta peak absent in PD, suggesting heterogeneity in cortical beta dynamics with aging. These findings suggest that elevated cortical beta oscillations immediately preceding balance perturbations are linked to clinically meaningful balance impairment in PD, supporting beta activity as a potential cortical biomarker of balance dysfunction in this population.

neuroscience↗

bioRxiv2026

The mammalian muscle spindle as a tunable feedback controller in locomotion

Although muscle spindle sensory signals have been extensively studied, little is known about how and why muscle spindle firing is modulated by the central nervous system during movement. Specialized motor neurons to the muscle spindle, i.e. gamma motor neurons, can profoundly alter spindle firing during behavior, but technological limitations hinder our ability to record gamma motor and muscle spindle sensory signals during most behaviors. We used a biophysical model of a muscle spindle within a muscle-tendon unit to simulate how gamma drive may modulate muscle spindle Ia firing during locomotion. Based on a few available recordings from decerebrate animals, we demonstrate that our model, tuned to passive stretch conditions, can reproduce profound changes in muscle spindle firing in response to identical joint motions in locomotor vs. relaxed stretch conditions. Our model can discover phasic patterns of two types of gamma motor neuron drive based on recorded muscle spindle Ia firing and joint motion. By simulating perturbations, we conclude that: 1) sinusoidal activation of static gamma motor neurons during locomotion, encoding intended movement, modulates muscle spindle signals such that they act as sensorimotor feedback signals based on errors from the intended muscle fascicle length; 2) phasic on/off activation of dynamic gamma motor neurons during locomotion acts as an event detector, heightening muscle spindle Ia responses to discrete perturbations. As such, their muscle-within-muscle structure allows the muscle spindle to act as a highly tunable physical internal model of muscle state to guide movement. Our model supports proposed but as-yet-untested theories of muscle spindle function and offers a framework for extending the testing of muscle spindle function to active, behavioral conditions.

neuroscience↗

bioRxiv2026

More isn't always better: Too much exoskeleton torque can disrupt balance

Wearable exoskeletons are a promising tool for augmenting balance and reducing fall risk. Recent work suggests that active ankle exoskeletons need to act faster than the human to improve reactive balance control. However, the magnitude of exoskeleton torque that is best for improving reactive balance remains unknown. Drawing from the optimal torque for minimizing metabolic expenditure, we hypothesized that reactive balance would improve with increased exoskeleton torque. Participants wearing bilateral ankle exoskeletons were instructed to maintain standing balance during 15cm backward support-surface perturbations. Three exoskeleton plantarflexion torque conditions were tested: NO (Off), LOW (15Nm), or HIGH (30Nm). LOW torque improved balance performance compared to NO torque (p<0.001), with a 7{+/-}3% decrease in peak center of mass (CoM) displacement. Although HIGH torque caused a 9{+/-}11% decrease in peak CoM displacement compared to NO torque (p=0.12), it was not significant due to high intersubject variability. Whereas LOW torque decreased peak CoM displacement in all (range: -0.2 to -1.6cm), HIGH torque only decreased it in some (range = 1.2 to -2.6cm). The change in CoM displacement from LOW to HIGH torque was associated with balance ability, quantified by the narrowing beam test (R2=0.29, p=0.06), while this relationship didnt meet conventional statistical significance, likely due to the small sample size, it suggests that higher levels of exoskeleton torque may hinder balance performance in individuals with better balance ability. Taken together, more exoskeleton torque is not always better for balance, highlighting a potential need to personalize exoskeleton torque for balance augmentation.

bioengineering↗

bioRxiv2026

A Primary Central Source Determines Perturbation-Evoked N1 Amplitudes but not Latencies in Younger Adults

The balance perturbation-evoked N1 potential is a reliable cortical response during reactive balance control that is correlated to a variety of cognitive and motor functions. Although the supplementary motor area (SMA) has been identified as the primary source of the N1, it is less understood whether other brain regions contribute to N1 recorded at the scalp. We used source localization on electroencephalography (EEG) data from 25 younger adults recorded during backward whole-body perturbations during stance. We identified the sources that contribute to channel-based N1 recordings and quantified their impact on N1 amplitude and latency. In younger adults, N1 amplitudes can be explained by one single source in a central midline cortical region covering the SMA. When reconstructing N1 signals using backprojections with one versus all independent components (IC) identified as brain sources there was no difference in peak amplitudes and a small but significant difference in N1 peak latencies. Parallel brain sources thus deflect the time course of the N1, but not its magnitude. Brain areas associated with ICs contributing to the shift in N1 latency varied between participants. Our results emphasize the dominant influence of central cortical areas on the N1 response, informing hypothesizes regarding the nature of the signal and its functional role. Importantly, the extent and location of other cortical structures that influence N1 timing, such as parietal cortex areas and the anterior cingulate cortex, may further elucidate cortical contributions to balance. These markers could be crucial for the early detection of balance problems in clinical populations. NEW & NOTEWORTHYWe demonstrate that channel-level amplitudes of the balance perturbation-evoked N1 in younger adults primarily reflect neural activity originating from cortical central midline regions, particularly the SMA. In contrast, contributions from parallel active brain regions evoked by balance perturbations are indicated by an influence on N1 peak latencies. Our findings imply that the perturbation-evoked N1, unlike other evoked potentials, is not a mixture of multiple neural sources in younger adults.

neuroscience↗

bioRxiv2025

Improved Stability and Interpretability of Motor Modules Computed with an Autoencoder

Motor module analysis is an important tool in the study of movement, particularly in people with impaired neural control. The most common method for computing motor modules is non-negative matrix factorization (NMF), which identifies a matrix of motor modules and their corresponding time-series activity from electromyography data. NMF has several limitations, including dependence of the muscle weightings on the number of modules selected. Approaches for selecting the number of modules vary between studies, making it difficult to compare and reproduce results. Some metrics of motor control complexity use the variance accounted for when extracting a single motor module (VAF1), yet that modules structure offers little biomechanical interpretability. In this work, we present a method for computing motor modules using an autoencoder, a neural network architecture that can find latent representations of data. Using a single layer autoencoder, we extracted motor modules from data in able-bodied and individuals post-stroke. The structure of autoencoder-computed modules were significantly less sensitive to selected module number. With the autoencoder-computed modules, increasing the number of modules added new information, instead of splitting previous modules. Autoencoder-computed modules, especially at low module counts, had more distinct and interpretable biomechanical functions. Lastly, the autoencoder-computed modules are consistent with previous NMF studies in persons with stroke, which found fewer modules needed to explain the muscle activity of paretic limbs. Our autoencoder-based method offers a new approach for computing motor modules, with advantages of better stability in module structure across module counts, and a more biomechanically relevant interpretation of VAF1. NEW & NOTEWORTHYThis work presents an approach for computing motor modules using an autoencoder and comprehensively compares the in stability of motor module structure, functional significance at low module counts, and interpretation of VAF1 to the current state of the art. The AE-computed module structures were more stable at different module counts. The AE has the potential to improve confidence in module structure and make analysis less dependent on the specific number of modules selected.

physiology↗

bioRxiv2025

Cortical response to balance perturbation is more sensitive in modern dancers than nondancers during biomechanically similar balance recovery

Motor skill expertise can facilitate more automatic movement, engaging less cortical activity while producing appropriate motor output. Accordingly, cortical-evoked N1 responses to balance perturbation, assessed using electroencephalography (EEG), are smaller in young and older adults with better balance. These responses may thus reflect individual balance challenge versus functional, or objective, task difficulty. However, the effect of balance expertise on cortical responses to balance perturbation has not been studied. We hypothesized that balance ability gained though long-term training facilitates more automatic balance control. Using professional modern dancers as balance experts, we compared cortical-evoked responses and biomechanics of the balance-correcting response between modern dancers and nondancers. We predicted that modern dancers would have smaller cortical-evoked responses and better balance recovery at equivalent levels of balance challenge. Support-surface perturbations were normalized to individual challenge levels by delivering perturbations scaled to 60% and 140% of each individuals step threshold. In contrast to our prediction, dancers exhibited larger N1 responses compared to nondancers while demonstrating similar biomechanical responses. Our results suggest dancers have greater cortical sensitivity to balance perturbations than nondancers. Further, dancer N1 responses modulated across perturbation magnitudes according to differences in objective task difficulty. In contrast, nondancer N1 responses modulated as a function of individual challenge level. Our findings suggest dance training increases sensitivity of the initial, cortical N1 response to balance perturbation, supporting postural alignment to an objective reference. The N1 response may reflect differences in balance-error processing that are altered with specific long-term training and may have implications for rehabilitation. NEW & NOTEWORTHYModern dancers show larger cortical responses to balance perturbations than nondancers, suggesting a greater sensitivity to perturbations. These results contrast with evidence of larger cortical-evoked responses in young adults with poorer balance, consistent with the cortical N1 response being a balance error assessment signal. Whereas nondancers scaled cortical responses by individual differences in N1 amplitude, dancers cortical responses were scaled to objective differences in perturbation magnitude, suggesting increased postural awareness due to training.

neuroscience↗

bioRxiv2025

Influence of exoskeleton stiffness on primary afferent feedback during stretch perturbations of isolated muscle-tendon unit

Exoskeletons assist and augment movement, but their effects on proprioceptive feedback remain poorly understood due to challenges in making direct measures of sensory signals in humans. Here, we leveraged a benchtop animal model to begin to explore how mechanical context akin to an elastic exoskeleton operating on a human lower limb joint may influence primary muscle spindle firing. In an anesthetized rat preparation, we applied controlled stretches to the medial gastrocnemius with engineered springs (0-0.5 N/mm) attached in parallel to the muscle-tendon unit (MTU) while modulating muscle activation to maintain overall system stiffness. Fascicle length was measured with sonomicrometry, force and MTU length with a servo motor, and spindle instantaneous firing rate (IFR) using dorsal root recordings. Trading off increases in parallel exoskeleton stiffness with reductions in muscle activation decreased biological muscle force (3.1 {+/-} 0.6 N to 1.6 {+/-} 0.6 N, p < 0.001) and stiffness (4.4 {+/-} 1.5 N/mm to 2.3 {+/-} 1.3 N/mm, p < 0.01), and increased fascicle length (7.9 {+/-} 1.3 mm to 8.3 {+/-} 1.5 mm, p < 0.005). We found significant correlations between spindle firing and each independent muscle fascicle kinematic and kinetic factor we investigated (p < 0.005). Thus, parallel stiffness emulating a passive elastic exoskeleton modifies muscle fascicle dynamics but does not alter spindle firing, possibly due to internal trade-offs in the salient muscle fascicle kinetic and kinematic features that drive spindle behavior. Leveraging in situ experimental frameworks that enable monitoring of primary afferent feedback during active contractions in complex mechanical contexts such as added parallel stiffness can provide a window into the effects of wearable devices on underlying sensory systems.

neuroscience↗

bioRxiv2025

Biophysical model for predicting muscle short-range stiffness during movement

Musculoskeletal simulations can offer valuable insight into how the properties of our musculoskeletal system influence the biomechanics of our daily movements. One such property is muscles history-dependent initial resistance to stretch, also known as short-range stiffness, which is key to stabilizing movements in response to external perturbations. Short-range stiffness is poorly captured by existing musculoskeletal simulations since they employ phenomenological Hill-type muscle models that lack the mechanisms underlying short-range stiffness. While it has been previously shown that biophysical cross-bridge models can reproduce muscle short-range-stiffness, it is unclear which specific biophysical properties are necessary to capture history-dependent muscle force responses in behaviorally relevant conditions. Here, we tested the ability of various biophysical cross-bridge models to reproduce empirical short-range stiffness and its history-dependent changes across a broad range of behaviorally relevant length changes and activation levels, using an existing dataset on permeabilized rat soleus muscle fibers (N = 11). We found that a biophysical cross-bridge model with cooperative myofilament activation reproduced the effects of muscle activation (R2 = 0.86), stretch amplitude (R2 = 0.71) and isometric recovery time (R2 = 0.79) on history-dependent changes in short-range stiffness after shortening. Similar results were obtained when the cross-bridge distribution of the biophysical model was approximated by a Gaussian (R2 = 0.73 - 0.88), but at a 20 times lower computational cost. These effects could not be reproduced by either a biophysical cross-bridge model without cooperative myofilament activation or a Hill-type model (R2 < 0.5). The reduced computational demand of the Gaussian-approximated models facilitates implementing biophysical cross-bridge models with cooperative myofilament activation in musculoskeletal simulations to improve the prediction of short-range stiffness during movements.

physiology↗

bioRxiv2024

Cortically-mediated muscle responses to balance perturbations increase with perturbation magnitude in older adults with and without Parkinson's disease

We lack a clear understanding of how cortical contributions to balance are altered in aging and Parkinsons disease (PD), which limits development of rehabilitation strategies. Processes like balance control are typically mediated through brainstem circuits, with higher-order circuits becoming engaged as needed. Using reactive balance recovery, we investigated how hierarchical neural mechanisms shape balance- correcting muscle activity across task difficulty in older adults (OAs) with and without PD. We hypothesize that feedback loops involving brainstem and cortical circuits contribute to balance control, and cortical engagement increases with challenge, aging, and PD. We decomposed perturbation-evoked agonist and antagonist muscle activity into hierarchical components based on latency using neuromechanical models consisting of two feedback loops with different delays to reflect different neural conduction and processing times. Agonist muscle activity was decomposed into two components that both increased with balance challenge in both groups. The first component occurred [~]120ms and the second occurred [~]210ms, consistent with the latencies of brainstem and transcortical circuits, respectively. Exploratory comparisons to young adults revealed larger transcortical components in OA and PD groups at lower balance challenge levels, consistent with increased cortical involvement with aging. Antagonist muscle activity included destabilizing and stabilizing components, with the destabilizing component correlating to balance ability in OAs but not in PD. These findings demonstrate that neuromechanical models can identify changes in the hierarchical control of balance without direct brain measurements. Identifying cortical contributions during balance control may complement clinical measures of balance ability to inform balance rehabilitation and assistive devices. NEW & NOTEWORTHYA neuromechanical model can decompose perturbation evoked muscle activity into components attributed to brainstem and higher-order sensorimotor feedback based on latency. In older adults with and without PD contributions from higher-order neural circuits increase with balance challenge and are related to clinical measures of balance ability. Interpreting the neural substrates of motor output for balance may reveal individual differences in the hierarchical control of balance, that could inform rehabilitation.

neuroscience↗

bioRxiv2024

Test-retest reliability of perturbation-evoked cortical activity reflects stable individual differences in reactive balance control

There is a growing interest in measuring cortical activity during balance control for understanding mechanisms of impaired balance with aging and neurological dysfunction. The most well-characterized electrophysiological signal elicited by a balance disturbance is the perturbation-evoked N1 potential that peaks 100-200 msec post-perturbation and is thought to reflect error processing. We previously found associations between the N1 and individual differences in balance ability, suggesting it may be a potential biomarker of balance health. However, a potential biomarker of balance function will be limited by its reliability and clinical feasibility, which has yet to be established. Here, we characterized the reliability of the N1 elicited by standing balance perturbations within and between sessions over a one-week interval in 10 younger and 14 older adults. A subset of older adults (n=12) completed a session approximately one year prior to the main experiment. We extracted N1 amplitude and latency from the Cz electrode using an advanced, computationally-intensive approach that relies on large amounts of data (e.g., 64 channels, many trials), Test-retest reliability was assessed using the intra-class correlation coefficient (ICC). Internal consistency was quantified by split-half reliability using the Spearman correlation coefficient. N1s varied across individuals (amplitude:12-82{micro}V, latency: 142-282ms), yet within individuals, the N1 showed excellent test-retest reliability (ICC>0.9) across a one-week and one-year time span. N1 amplitude reached excellent internal reliability for each session and group (r>0.9), that generally plateaued within 6 trials, while more trials were needed to reliably measure N1 latency. Similar results were obtained when quantifying N1s using a minimal approach performed with only three electrodes and simple preprocessing. Overall, the N1 is stable within and across sessions, and is largely independent of approach suggesting it could be a clinically-feasible biomarker of balance function. Characterizing reliability in populations with neurologic dysfunction and in different environmental contexts will be necessary to enhance our understanding of the N1, optimize experimental design, and determine its predictive validity of clinical outcomes (e.g., falls risk).

neuroscience↗

bioRxiv2024

Center of mass states render multi-joint torques throughout standing balance recovery

Successful reactive balance control requires coordinated modulation of hip, knee, and ankle torques. Stabilizing joint torques arise from feedforward neural signals that modulate the musculoskeletal systems intrinsic mechanical properties, namely muscle short-range stiffness, and neural feedback pathways that activate muscles in response to sensory input. Although feedforward and feedback pathways are known to modulate the torque at each joint, the role of each pathway to the balance-correcting response across joints is poorly understood. Since the feedforward and feedback torque responses act at different delays following perturbations to balance, we modified the sensorimotor response model (SRM), previously used to analyze the muscle activation response to perturbations, to consist of parallel feedback loops with different delays. Each loop within the model is driven by the same information, center of mass (CoM) kinematics, but each loop has an independent delay. We evaluated if a parallel loop SRM could decompose the reactive torques into the feedforward and feedback contributions during balance-correcting responses to backward support surface translations at four magnitudes. The SRM accurately reconstructed reactive joint torques at the hip, knee, and ankle, across all perturbation magnitudes (R2>0.84 & VAF>0.83). Moreover, the hip and knee exhibited feedforward and feedback components, while the ankle only exhibited feedback components. The lack of a feedforward component at the ankle may occur because the compliance of the Achilles tendon attenuates muscle short-range stiffness. Our model may provide a framework for evaluating changes in the feedforward and feedback contributions to balance that occur due to aging, injury, or disease. NEWS AND NOTEWORTHYReactive balance control requires coordination of neurally-mediated feedforward and feedback pathways to generate stabilizing joint torques at the hip, knee, and ankle. Using a sensorimotor response model, we decomposed reactive joint torques into feedforward and feedback contributions based on delays relative to center of mass kinematics. Responses across joints were driven by the same signals, but contributions from feedforward versus feedback pathways differed, likely due to differences in musculotendon properties between proximal and distal muscles.

bioengineering↗

bioRxiv2024

Gait signature changes with walking speed are similar among able-bodied young adults despite persistent individual-specific differences

Understanding individuals distinct movement patterns is crucial for health, rehabilitation, and sports. Recently, we developed a machine learning-based framework to show that "gait signatures" describing the neuromechanical dynamics governing able-bodied and post-stroke gait kinematics remain individual-specific across speeds. However, we only evaluated gait signatures within a limited speed range and number of participants, using only sagittal plane (i.e., 2D) joint angles. Here we characterized changes in gait signatures across a wide range of speeds, from very slow (0.3 m/s) to exceptionally fast (above the walk-to-run transition speed) in 17 able-bodied young adults. We further assessed whether 3D kinematic and/or kinetic (ground reaction forces, joint moments, and powers) data would improve the discrimination of gait signatures. Our study showed that gait signatures remained individual-specific across walking speeds: Notably, 3D kinematic signatures achieved exceptional accuracy (99.8%, confidence interval (CI): 99.1-100%) in classifying individuals, surpassing both 2D kinematics and 3D kinetics. Moreover, participants exhibited consistent, predictable linear changes in their gait signatures across the entire speed range. These changes were associated with participants preferred walking speeds, balance ability, cadence, and step length. These findings support gait signatures as a tool to characterize individual differences in gait and predict speed-induced changes in gait dynamics.

systems biology↗

bioRxiv2023

Identification of neural and non-neural origins of joint hyper-resistance based on a novel neuromechanical model.

Joint hyper-resistance is a common symptom in neurological disorders. It has both neural and nonneural origins, but it has been challenging to distinguish different origins based on clinical tests alone. Combining instrumented tests with parameter identification based on a neuromechanical model may allow us to dissociate the different origins of joint hyper-resistance in individual patients. However, this requires that the model captures the underlying mechanisms. Here, we propose a neuromechanical model that, in contrast to previously proposed models, accounts for muscle shortrange stiffness and its interaction with muscle tone and reflex activity. We collected knee angle trajectories during the pendulum test in 15 children with cerebral palsy (CP) and 5 typically developing children. We did the test in two conditions - hold and pre-movement - that have been shown to alter knee movement. We modeled the lower leg as an inverted pendulum actuated by two antagonistic Hill-type muscles extended with SRS. Reflex activity was modeled as delayed, linear feedback from muscle force. We estimated neural and non-neural parameters by optimizing the fit between simulated and measured knee angle trajectories during the hold condition. The model could fit a wide range of knee angle trajectories in the hold condition. The model with personalized parameters predicted the effect of pre-movement demonstrating that the model captured the underlying mechanism and subject-specific deficits. Our model thus allows us to determine subject-specific origins of joint hyper-resistance and thereby opens perspectives for improved diagnosis and consequently treatment selection in children with spastic CP.

pathology↗

bioRxiv2023

Distinct cortical correlates of perception and motor function in balance control

Fluctuations in brain state alter how we perceive our body and generate movements but have not been investigated in functional whole-body behaviors. During reactive balance control, we recently showed that evoked brain activity is associated with balance ability in healthy young individuals. Further, in individuals with Parkinsons disease, impairments in whole-body motion perception in reactive balance are associated with clinical balance impairment. Here we investigated brain activity during whole-body motion perception in reactive balance in healthy young adults. We hypothesized that flexibility in brain states underlies successful perception and movement during whole-body movement. We characterized two cortical sensorimotor signals using electroencephalography localized to the supplementary motor area: 1) the "N1 response", a perturbation-evoked potential that decreases in amplitude with expectancy and is larger in individuals with lower balance function; and 2) pre-perturbation beta oscillatory activity, a rhythm that favors maintenance of the current sensorimotor state and is inversely associated with perception in seated somatosensory perceptual tasks. In a two-alternative forced choice task, participants judged whether pairs of backward support-surface perturbations during standing were in the "same" or "different" direction. As expected, lower whole-body perception was associated with lower balance ability. Within a perturbation pair, N1 attenuation was larger on correctly perceived trials and associated with better balance, but not perception. In contrast, pre-perturbation beta power was higher on incorrectly perceived trials and associated with poorer perception, but not balance. Taken together, flexibility in different cortical processes influences perceptual accuracy but have distinct associations with balance and perceptual ability.

neuroscience↗

bioRxiv2023

Attenuation of muscle spindle firing with artificially increased series compliance during stretch of relaxed muscle

Muscle spindles relay vital mechanosensory information for movement and posture, but muscle spindle feedback is coupled to skeletal motion by a compliant tendon. Little is known about the effects of tendon compliance on muscle spindle feedback during movement, and the complex firing of muscle spindles make these effects difficult to predict. Our goal was to investigate changes in muscle spindle firing using added series elastic elements (SEEs) to mimic a more compliant tendon, and to characterize the accompanying changes in firing with respect to muscle-tendon unit (MTU) and muscle fascicle displacements (recorded via sonomicrometry). Sinusoidal, ramp-hold-release, and triangular stretches were analyzed to examine potential changes in muscle spindle instantaneous firing rates (IFRs) in locomotor-and perturbation-like stretches as well as history dependence. Added SEEs effectively reduced overall MTU stiffness and generally reduced muscle spindle firing rates, but the effect differed across stretch types. During sinusoidal stretches, peak firing rates were reduced and IFR was strongly correlated with fascicle velocity. During ramp stretches, SEEs reduced the dynamic and static responses of the spindle during lengthening but had no effect on initial bursts at the onset of stretch. Notably, IFR was negatively related to fascicle displacement during the hold phase. During triangular stretches, SEEs reduced the mean IFR during the first and second stretches, affecting the history dependence of mean IFR. Overall, these results demonstrate that tendon compliance may attenuate muscle spindle feedback during movement, but these changes cannot be fully explained by reduced muscle fascicle length and velocity. New FindingsO_ST_ABSWhat is the central question of the study?C_ST_ABSLittle is known about the effects of tendon compliance on muscle spindle function. We asked whether increasing the series compliance the muscle-tendon unit muscle spindle Ia responses to stretch. We also test the relationship between muscle spindle firing rates and muscle fascicle biomechanics. What is the main finding and its importance?Muscle spindle firing was generally attenuated with added series compliance, with the exception of the initial burst at the onset of stretch. Overall, the changes depended upon stretch profiles, and could not be fully explained by muscle fascicle length and velocity.

physiology↗

bioRxiv2022

Discovering individual-specific gait signatures from data-driven models of neuromechanical dynamics

Locomotion results from the interactions of highly nonlinear neural and biomechanical dynamics. Accordingly, understanding gait dynamics across behavioral conditions and individuals based on detailed modeling of the underlying neuromechanical system has proven difficult. Here, we develop a data-driven and generative modeling approach that recapitulates the dynamical features of gait behaviors to enable more holistic and interpretable characterizations and comparisons of gait dynamics. Specifically, gait dynamics of multiple individuals are predicted by a dynamical model that defines a common, low-dimensional, latent space to compare group and individual differences. We find that highly individualized dynamics - i.e., gait signatures - for healthy older adults and stroke survivors during treadmill walking are conserved across gait speed. Gait signatures further reveal individual differences in gait dynamics, even in individuals with similar functional deficits. Moreover, components of gait signatures can be biomechanically interpreted and manipulated to reveal their relationships to observed spatiotemporal joint coordination patterns. Lastly, the gait dynamics model can predict the time evolution of joint coordination based on an initial static posture. Our gait signatures framework thus provides a generalizable, holistic method for characterizing and predicting cyclic, dynamical motor behavior that may generalize across species, pathologies, and gait perturbations. Author SummaryIn this manuscript, we introduce a novel, machine learning-based framework for quantifying, characterizing, and modifying the underlying neuromechanical dynamics that drive unique gait patterns. Standard methods for evaluating movement typically focus on extracting discrete gait variables ignoring the complex inter-limb and inter-joint spatiotemporal dependencies that occur during gait. Popular physiologically realistic modeling approaches encode these spatiotemporal dependencies but are too complex to characterize individual differences in the factors driving unique gait patterns or disorders. To circumvent these modeling complications, we develop a phenomenological model of gait that enables more holistic and interpretable characterizations of gait, encoding these complex spatiotemporal dependencies between humans joint angles arising from joint neural and biomechanical constraints. Our coined gait signature framework provides a path towards understanding the neuromechanics of locomotion. This framework has potential utility for clinical researchers prescribing individualized therapies for pathologies or biomechanists interested in animal locomotion or other periodic movements assessed across different pathologies, neural perturbations, and or conditions.

neuroscience↗

bioRxiv2022

History-dependent muscle resistance to stretch remains high after small, posturally-relevant pre-movements

The contributions of intrinsic muscle fiber resistance during mechanical perturbations to standing and other postural behaviors are unclear. Muscle stiffness, a traditional metric for estimating muscles intrinsic resistance to stretch, is known to vary depending on the current level and history of the muscles activation, as well as the muscles recent movement history; this property has been referred to as history dependence or muscle thixotropy. However, we currently lack sufficient data about the degree to which muscle stiffness is modulated across posturally-relevant characteristics of muscle stretch and activation. Here, we characterized the history dependence of muscles resistance to stretch in single, permeabilized, activated, muscle fibers in posturally-relevant stretch conditions and activation levels. We used a classic paired muscle stretch paradigm, varying the amplitude of a "conditioning" triangular stretch-shorten cycle followed by a "test" ramp-and-hold imposed after a variable inter-stretch interval. We tested low (<15%), intermediate (15-50%) and high (>50%) muscle fiber activation levels, evaluating short-range stiffness and total impulse in the test stretch. Muscle fiber resistance to stretch remained high at conditioning amplitudes of <1% L0 and inter-stretch intervals of >1 s, characteristic of healthy standing postural sway. A ~70% attenuation of muscle resistance to stretch was reached at conditioning amplitudes of >3% L0 and inter-stretch intervals of <0.1s, characteristic of larger, faster postural sway in balance-impaired individuals. Overall, amplitude and inter-stretch interval interact to disrupt myofilaments such that intrinsic resistance to stretch is attenuated if the stretch is large enough and/or frequent enough. Summary StatementIntrinsic muscle fiber resistance to stretch is preserved after small, slow pre-movements based on healthy postural sway, but markedly reduced as pre-movements increase to emulate abnormal postural sway.

physiology↗

bioRxiv2022

Disturbing standing balance evokes an error-related negativity

The error-related negativity (ERN) is a neural correlate of error monitoring often used to investigate individual differences in developmental, mental health, and adaptive contexts. However, limited experimental control over errors presents several confounds to its measurement. An experimentally controlled disturbance to standing balance evokes the balance N1, which we previously suggested may share underlying mechanisms with the ERN based on a number of shared features and factors. We now measure whether the balance N1 and ERN are correlated across individuals within two small groups (N=21 young adults and N=20 older adults). ERNs were measured in arrow flanker tasks using hand and foot response modalities (ERN-hand and ERN-foot). The balance N1 was evoked by sudden slip-like movements of the floor while standing. The ERNs and the balance N1 showed good and excellent internal consistency, respectively, and were correlated in amplitude in both groups. One principal component strongly loaded on all three evoked potentials, suggesting that the majority of individual differences are shared across the three ERPs. However, there remains a significant component of variance shared between the ERN-hand and ERN-foot beyond what they share with the balance N1. It is unclear whether this component of variance is specific to the arrow flanker task, or something fundamentally related to error processing that is not evoked by a sudden balance disturbance. If the balance N1 were to reflect error processing mechanisms indexed by the ERN, balance paradigms offer several advantages in terms of experimental control over errors.

neuroscience↗