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几何相位可预测跨越多个尺度的波动生命系统的运动性能。

Geometric phase predicts locomotion performance in undulating living systems across scales.

机构信息

School of Physics, Georgia Institute of Technology, Atlanta, GA 30332.

Department of Physics, Emory University, Atlanta, GA 30322.

出版信息

Proc Natl Acad Sci U S A. 2024 Jun 11;121(24):e2320517121. doi: 10.1073/pnas.2320517121. Epub 2024 Jun 7.

DOI:10.1073/pnas.2320517121
PMID:38848301
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11181092/
Abstract

Self-propelling organisms locomote via generation of patterns of self-deformation. Despite the diversity of body plans, internal actuation schemes and environments in limbless vertebrates and invertebrates, such organisms often use similar traveling waves of axial body bending for movement. Delineating how self-deformation parameters lead to locomotor performance (e.g. speed, energy, turning capabilities) remains challenging. We show that a geometric framework, replacing laborious calculation with a diagrammatic scheme, is well-suited to discovery and comparison of effective patterns of wave dynamics in diverse living systems. We focus on a regime of undulatory locomotion, that of highly damped environments, which is applicable not only to small organisms in viscous fluids, but also larger animals in frictional fluids (sand) and on frictional ground. We find that the traveling wave dynamics used by mm-scale nematode worms and cm-scale desert dwelling snakes and lizards can be described by time series of weights associated with two principal modes. The approximately circular closed path trajectories of mode weights in a self-deformation space enclose near-maximal surface integral (geometric phase) for organisms spanning two decades in body length. We hypothesize that such trajectories are targets of control (which we refer to as "serpenoid templates"). Further, the geometric approach reveals how seemingly complex behaviors such as turning in worms and sidewinding snakes can be described as modulations of templates. Thus, the use of differential geometry in the locomotion of living systems generates a common description of locomotion across taxa and provides hypotheses for neuromechanical control schemes at lower levels of organization.

摘要

自主运动的生物通过自身变形模式的产生来进行运动。尽管在无肢脊椎动物和无脊椎动物中存在着身体结构、内部驱动方案和环境的多样性,但这些生物通常使用类似的轴向身体弯曲传播波来进行运动。阐明自身变形参数如何导致运动表现(例如速度、能量、转弯能力)仍然具有挑战性。我们表明,一个几何框架通过图表方案取代了繁琐的计算,非常适合发现和比较不同生物系统中有效波动力学模式。我们关注的是波动运动的一个状态,即高度阻尼的环境,这种环境不仅适用于粘性流体中的小生物体,也适用于摩擦流体(沙子)中和摩擦地面上的较大动物。我们发现,毫米级线虫蠕虫和厘米级沙漠栖居蛇和蜥蜴所使用的行波动力学可以用与两个主要模式相关的权重时间序列来描述。在自身变形空间中,模式权重的近似圆形封闭路径轨迹为跨越两个体长十年的生物体包围了最大表面积分(几何相位)。我们假设,这样的轨迹是控制的目标(我们称之为“蛇形模板”)。此外,几何方法揭示了蠕虫中的转弯和蛇类的侧身蜿蜒等看似复杂的行为如何可以被描述为模板的调制。因此,生命系统运动中的微分几何的使用为跨分类群的运动提供了共同描述,并为较低组织水平的神经机械控制方案提供了假设。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b669/11181092/5c3e62f48a52/pnas.2320517121fig10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b669/11181092/e35d5d1ee592/pnas.2320517121fig01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b669/11181092/5bc4d735c253/pnas.2320517121fig02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b669/11181092/7766844795ac/pnas.2320517121fig03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b669/11181092/72709dcb4deb/pnas.2320517121fig04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b669/11181092/ae99b191ce51/pnas.2320517121fig05.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b669/11181092/52a42f15fef4/pnas.2320517121fig06.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b669/11181092/3c97b9a5b13c/pnas.2320517121fig07.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b669/11181092/ae980df2588e/pnas.2320517121fig08.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b669/11181092/fb634e535cd2/pnas.2320517121fig09.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b669/11181092/5c3e62f48a52/pnas.2320517121fig10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b669/11181092/e35d5d1ee592/pnas.2320517121fig01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b669/11181092/5bc4d735c253/pnas.2320517121fig02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b669/11181092/7766844795ac/pnas.2320517121fig03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b669/11181092/72709dcb4deb/pnas.2320517121fig04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b669/11181092/ae99b191ce51/pnas.2320517121fig05.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b669/11181092/52a42f15fef4/pnas.2320517121fig06.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b669/11181092/3c97b9a5b13c/pnas.2320517121fig07.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b669/11181092/ae980df2588e/pnas.2320517121fig08.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b669/11181092/fb634e535cd2/pnas.2320517121fig09.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b669/11181092/5c3e62f48a52/pnas.2320517121fig10.jpg

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