发表机构
Rutgers the State University of New Jersey; Rutgers University Center for Cognitive Science; Rutgers University Center for Biomedicine Imaging and Modelling（新泽西州立罗格斯大学; 罗格斯大学认知科学中心; 罗格斯大学生物医学成像与建模中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究采用Fisher-Rao距离作为坐标无关度量，分析认知负荷下运动波动的变化，发现负荷使个体波动特征向共同状态收敛，而非均匀移动。
AI 中文摘要
运动控制研究涉及对复杂运动所描述的位置轨迹中提取的运动学特征的分析。在需要实时认知和记忆过程的自然、无约束运动中，时间速度曲线并非钟形，可能具有多个峰值，且峰值分布最适合用具有形状和尺度两个参数的连续伽马分布族来拟合。由于复杂运动轨迹所描述的随机过程是非平稳的，描述这些过程的伽马形状和尺度参数跨越随机轨迹。这些点位于弯曲表面上，其中欧氏距离取决于参数化的任意选择。我们采用Fisher-Rao距离（伽马流形上的测地线长度）作为运动波动特征的坐标无关度量，并提出一个稳健的数值求解器，该求解器能在经验观测到的全部参数范围内收敛。我们在基于平板电脑的数字版连线测试中，对健康成年人进行了该度量的验证，比较了低认知负荷和高认知负荷下的微运动波动。负荷改变了每位参与者的波动特征，但没有共同的方向。相反，参与者收敛到一个共同的操作状态，其中基线时距离该状态最远的参与者移动最多。因此，认知负荷收缩了运动波动的个体性，而非均匀地改变整个人群。
英文摘要
Motor control research involves the study of movement kinematics derived from the positional trajectories that complex motions describe. In natural, unconstrained motions requiring cognitive and memory processes in real time, the temporal speed profiles are not bell-shaped, may have multiple maxima and the peaks distribution is best fit by the continuous gamma family with two parameters, the shape and the scale. As the stochastic processes described by complex motion trajectories are non-stationary, the gamma shape and scale parameters describing them span stochastic trajectories. These points live on a curved surface where Euclidean distance depends on the arbitrary choice of parameterization. We adopt the Fisher-Rao distance (the geodesic length on the gamma manifold) as a coordinate-free metric for movement fluctuation signatures and present a robust numerical solver that converges across the full range of empirically observed parameters. We demonstrate the metric on a tablet-based digitized Trail Making Test in healthy adults, comparing micromovement fluctuations under low and high cognitive load. Load displaced every participant's fluctuation signature but with no shared direction. Instead, participants converged toward a common operating regime, with those farthest from it at baseline moving the most. Cognitive load thus contracts individuality in motor fluctuations rather than shifting the population uniformly.
