Biology subjects

Gassner, H.

Publications and source records attributed to Gassner, H..

4 recordsLinked to original sources

bioRxiv2025

Does reduced reactivity explain altered postural control in Parkinson's disease? A predictive simulation study.

Postural instability represents one of the cardinal symptoms of Parkinsons disease (PD). Still, internal processes leading to this instability are not fully understood. Simulations using neuromusculoskeletal human models could help understand these internal processes leading to PD-associated postural deficits. In this paper, we investigated whether reduced reactivity amplitudes resulting from impairments due to PD can explain postural instability as well as increased muscle tone as often observed in individuals with PD. To simulate reduced reactivity, we gradually decreased previously optimized gain factors within the postural control circuitry of our model performing a quiet upright standing task. After each reduction step, the model was again optimized. Simulation results were compared to experimental data collected from 31 individuals with PD and 31 age- and sex-matched healthy control participants. Analyzing our simulation results, we showed that muscle activations increased with a models reduced reactivity, as well as joint angles ranges of motion (ROMs). However, sway parameters such as center of pressure (COP) path lengths and COP ranges did not increase as observed in our experimental data. These results suggest that a reduced reactivity does not directly lead to increased sway parameters, but could cause increased muscle tone leading to subsequent postural control alterations. To further investigate postural stability using neuromusculoskeletal models, analyzing additional internal model parameters and tasks such as perturbed upright standing requiring comparable reaction patterns could provide promising results. By enhancing such models and deepening the understanding of internal processes of postural control, these models may be used to assess and evaluate rehabilitation interventions in the future. Impact StatementAltered postural control in Parkinsons disease can be partly associated to reduced reactivity. Additional changes in the neural circuitry need to be further investigated to fully explain the observed differences.

bioengineering↗

bioRxiv2024

A sensorimotor enhanced neuromusculoskeletal model for simulating postural control of upright standing

The humans upright standing is a complex control process that is not yet fully understood. Postural control models can provide insights into the bodys internal control processes of balance behaviour. Using physiologically plausible models can also help explaining pathophysiological motion behaviour. In this paper, we introduce a neuromusculoskeletal postural control model using sensor feedback consisting of somatosensory, vestibular and visual information. The sagittal plane model was restricted to effectively six degrees of freedom and consisted of nine muscles per leg. Physiological plausible neural delays were considered for balance control. We applied forward dynamic simulations and a single shooting approach to generate healthy reactive balance behaviour during quiet and perturbed upright standing. Control parameters were optimized to minimize muscle effort. We showed that our model is capable of fulfilling the applied tasks successfully. We observed joint angles and ranges of motion in physiological plausible ranges and comparable to experimental data. This model represents the starting point for subsequent simulation of pathophysiological postural control behaviour.

bioengineering↗

bioRxiv2023

Comparing sparse inertial sensor setups for sagittal-plane walking and running reconstructions

Estimating spatiotemporal, kinematic, and kinetic movement variables with little obtrusion to the user is critical for clinical and sports applications. Previously, we developed an approach to estimate these variables from measurements with seven lower-body inertial sensors, i.e., the full setup, using optimal control simulations. Here, we investigated if this approach is similarly accurate when using sparse sensor setups with less inertial sensors. To estimate the movement variables, we solved optimal control problems on sagittal plane lower-body musculoskeletal models, in which an objective was optimized that combined tracking of accelerometer and gyroscope data with minimizing muscular effort. We created simulations for 10 participants at three walking and three running speeds, using seven sensor setups with between two and seven sensors located at the feet, shank, thighs, and/or pelvis. We calculated the correlation and root mean square deviations (RMSDs) between the estimated movement variables and those from inverse analysis using optical motion capture (OMC) and force plate data. We found that correlations between IMU- and OMC-based variables were high for all sensor setups, while including all sensors did not necessarily lead to the smallest RMSDs. Setups without a pelvis sensor led to too much forward trunk lean and inaccurate spatiotemporal variables. RMSDs were highest for the setup with two foot-worn IMUs. The smallest setup that estimated joint angles as accurately as the full setup (<1 degree difference in RMSD) was the setup with IMUs at the feet and thighs. The mean correlations for joint angles, moments, and ground reaction forces were at least 0.8 for walking and 0.9 for running when either a pelvic sensor or thigh sensors were included. Therefore, we conclude that we can accurately perform a comprehensive sagittal-plane motion analysis with sparse sensor setups when sensors are placed on the feet and on either the pelvis or the thighs.

bioengineering↗

bioRxiv2020

Acute Exercise Following Skill Practice Promotes Motor Memory Consolidation in Parkinson's Disease

Acute cardiovascular exercise has shown to promote neuroplastic processes, and thus to improve the consolidation of newly acquired motor skills in healthy adults. First results suggest that this concept may be transferred to populations with motor and cognitive dysfunctions. In this context, Parkinsons disease (PD) is highly relevant since patients demonstrate deficits in motor learning. Hence, in the present study we sought to explore the effect of a single post-practice exercise bout on motor memory consolidation in PD patients. For this purpose, 17 PD patients (Hoehn and Yahr: 1 - 2.5, age: 60.1 {+/-} 7.9 y) practiced a whole-body task followed by either (i) a moderate-intense bout of cycling, or (ii) seated rest for a total of 30 minutes. The motor task required the participants to balance on a tiltable platform (stabilometer) for 30 seconds. During skill practice, patients performed 15 trials followed by a retention test 1 day and 7 days later. We calculated time in balance (platform within {+/-} 5{degrees} from horizontal) for each trial and within- and between-group differences in memory consolidation (i.e. offline learning = skill change from last acquisition block to retention tests) were analyzed. Groups revealed similar improvements during skill practice (F4,60 = .316, p = .866), but showed differences in offline learning, which was only evident after 7 days (F1,14 = 5.602, p = .033). Our results suggest that a single post-practice exercise bout is effective in enhancing long-term motor memory consolidation in a population with motor learning impairments. This may point at unique promoting effects of exercise on dopamine neurotransmission involved in memory formation. Future studies should investigate the potential role of exercise-induced effects on the dopaminergic system. HighlightsO_LIAcute exercise enhanced motor memory consolidation in PD C_LIO_LIEffects were evident only at 7-day retention C_LIO_LIResults may indicate unique exercise-effects on the dopaminergic system C_LIO_LIFindings show promising potential of exercise for motor rehabilitation C_LI

neuroscience↗