Analysis of the Relationship Between Muscle Tones and Abnormal Postures in a Computational Model.

Patients with Parkinson's disease (PD), a neurodegenerative disorder, exhibit a characteristic posture known as a forward flexed posture. Increased muscle tone is suggested as a possible cause of this abnormal posture. For further analysis, it is necessary to measure muscle tone, but the experimental measurement of muscle tone during standing is challenging. The aim of this study was to examine the hypothesis that "In patients with PD, abnormal postures are those with a small sway at increased muscle tones" using a computational model. The muscle tones of various magnitudes were estimated using the computational model and standing data of patients with PD. The postures with small sway at the estimated muscle tones were then calculated through an optimization method. The postures and sway calculated using the computational model were compared to those of patients with PD. The results showed that the differences in posture and sway between the simulation and experimental results were small at higher muscle tones compared to those considered plausible in healthy subjects by the simulations. This simulation result indicates that the reproduced sway at high muscle tones is similar to that of actual patients with PD and that the reproduced postures with small sway locally at high muscle tones in the simulations are similar to those of patients with PD. The result is consistent with the hypothesis, reinforcing the hypothesis.Clinical relevance- This study implies that improving the increased muscle tone in patients with PD may lead to an improved abnormal posture.

Analysis of abnormal posture in patients with Parkinson's disease using a computational model considering muscle tones.

Patients with Parkinson's disease (PD) exhibit distinct abnormal postures, including neck-down, stooped postures, and Pisa syndrome, collectively termed "abnormal posture" henceforth. In the previous study, when assuming an upright stance, patients with PD exhibit heightened instability in contrast to healthy individuals with disturbance, implying that abnormal postures serve as compensatory mechanisms to mitigate sway during static standing. However, limited studies have explored the relationship between abnormal posture and sway in the context of static standing. Increased muscle tone (i.e., constant muscle activity against the gravity) has been proposed as an underlying reason for abnormal postures. Therefore, this study aimed to investigate the following hypothesis: abnormal posture with increased muscle tone leads to a smaller sway compared with that in other postures, including normal upright standing, under the sway minimization criterion. To investigate the hypothesis, we assessed the sway in multiple postures, which is determined by joint angles, including cases with bended hip joints. Our approach involved conducting forward dynamics simulations using a computational model comprising a musculoskeletal model and a neural controller model. The neural controller model proposed integrates two types of control mechanisms: feedforward control (representing muscle tone as a vector) and feedback control using proprioceptive and vestibular sensory information. An optimization was performed to determine the posture of the musculoskeletal model and the accompanied parameters of the neural controller model for each of the given muscle tone vector to minimize sway. The optimized postures to minimize sway for the optimal muscle tone vector of patients with PD were compared to the actual postures observed in these patients. The results revealed that on average, the joint-angle differences between these postures was <4°, which was less than one-tenth of the typical joint range of motion. These results suggest that patients with PD exhibit less sway in the abnormal posture than in other postures. Thus, adopting an abnormal posture with increased muscle tone can potentially serve as a valid strategy for minimizing sway in patients with PD.

A Neural Controller Model Considering the Vestibulospinal Tract in Human Postural Control.

Humans are able to control their posture in their daily lives. It is important to understand how this is achieved in order to understand the mechanisms that lead to impaired postural control in various diseases. The descending tracts play an important role in controlling posture, particularly the reticulospinal and the vestibulospinal tracts (VST), and there is evidence that the latter is impaired in various diseases. However, the contribution of the VST to human postural control remains unclear, despite extensive research using neuroscientific methods. One reason for this is that the neuroscientific approach limits our understanding of the relationship between an array of sensory information and the muscle outputs. This limitation can be addressed by carrying out studies using computational models, where it is possible to make and validate hypotheses about postural control. However, previous computational models have not considered the VST. In this study, we present a neural controller model that mimics the VST, which was constructed on the basis of physiological data. The computational model is composed of a musculoskeletal model and a neural controller model. The musculoskeletal model had 18 degrees of freedom and 94 muscles, including those of the neck related to the function of the VST. We used an optimization method to adjust the control parameters for different conditions of muscle tone and with/without the VST. We examined the postural sway for each condition. The validity of the neural controller model was evaluated by comparing the modeled postural control with (1) experimental results in human subjects, and (2) the results of a previous study that used a computational model. It was found that the pattern of results was similar for both. This therefore validated the neural controller model, and we could present the neural controller model that mimics the VST.