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Kouzaki, M.

Publications and source records attributed to Kouzaki, M..

2 recordsLinked to original sources

Choosing safety or success: Fall-avoidance preference limits goal achievement during whole-body movements

Human bipedal posture is inherently unstable, making even daily activities potentially lead to falls and serious injuries. Although prior studies have shown that appropriate postural control supports both task success and postural balance during quiet standing or under modest postural demands, it remains unclear how the central nervous system controls whole-body posture under high-demand, near-fall conditions. Here, we investigated how varying postural demands influence postural strategies using a whole-body task in which participants leaned their body mediolaterally to reach a target. We manipulated the required leaning angles and velocities by varying target positions and time constraints to reach a target, thereby introducing different levels of postural demand. The results demonstrated that target position, time constraint, and movement distance significantly affected task performance, defined as reaching accuracy. Specifically, participants could accurately reach targets requiring upright or moderately leaning postures. However, when targets required greater leaning postures, participants failed to reach them. Furthermore, the detrimental effects of shorter time constraints and longer movement distances on task performance became more pronounced when target positions required greater leaning postures. These findings suggest that the central nervous system tolerates low to moderate postural demands to achieve task goals. In contrast, when postural demands exceed a certain threshold, the central nervous system begins to prioritize postural safety over task success. This study highlights the nonlinear effect of postural demands on motor planning during whole-body movements.

neuroscience↗

Data-driven spectral analysis for coordinative structures in periodic systems with unknown and redundant dynamics

Living organisms dynamically and flexibly operate a great number of components. As one of such redundant control mechanisms, low-dimensional coordinative structures among multiple components have been investigated. However, structures extracted from the conventional statistical dimensionality reduction methods do not reflect dynamical properties in principle. Here we regard coordinative structures in biological periodic systems with unknown and redundant dynamics as a nonlinear limit-cycle oscillation, and apply a data-driven operator-theoretic spectral analysis, which obtains dynamical properties of coordinative structures such as frequency and phase from the estimated eigenvalues and eigenfunctions of a composition operator. First, from intersegmental angles during human walking, we extracted the speed-independent harmonics of gait frequency. Second, we discovered the speed-dependent time-evolving behaviors of the phase on the conventional low-dimensional structures by estimating the eigenfunctions. Our approach contributes to the understanding of biological periodic phenomena with unknown and redundant dynamics from the perspective of nonlinear dynamical systems.

neuroscience↗