School of Computing, University of Leeds, Leeds LS2 9JT, UK.
School of Computing, University of Leeds, Leeds LS2 9JT, UK
Philos Trans R Soc Lond B Biol Sci. 2018 Sep 10;373(1758):20180208. doi: 10.1098/rstb.2018.0208.
Animal neuromechanics describes the coordinated self-propelled movement of a body, subject to the combined effects of internal neural control and mechanical forces. Here we use a computational model to identify effects of neural and mechanical modulation on undulatory forward locomotion of , with a focus on proprioceptively driven neural control. We reveal a fundamental relationship between body elasticity and environmental drag in determining the dynamics of the body and demonstrate the manifestation of this relationship in the context of proprioceptively driven control. By considering characteristics unique to proprioceptive neurons, we predict the signatures of internal gait modulation that contrast with the known signatures of externally or biomechanically modulated gait. We further show that proprioceptive feedback can suppress neuromechanical phase lags during undulatory locomotion, contrasting with well studied advancing phase lags that have long been a signature of centrally generated, feed-forward control.This article is part of a discussion meeting issue 'Connectome to behaviour: modelling at cellular resolution'.
动物神经力学描述了身体的协调自推进运动，受到内部神经控制和机械力的综合影响。在这里，我们使用计算模型来识别神经和机械调制对 的波动前进运动的影响，重点是本体感受驱动的神经控制。我们揭示了身体弹性和环境阻力之间的基本关系，这决定了身体的动力学，并展示了这种关系在本体感受驱动控制背景下的表现。通过考虑本体感受神经元的独特特征，我们预测了内部步态调制的特征，这些特征与已知的外部或生物力学调制步态的特征形成对比。我们进一步表明，本体感受反馈可以抑制波动运动过程中的神经机械相位滞后，与长期以来一直是中央产生的、前馈控制的特征的研究深入的推进相位滞后形成对比。本文是“从连接组到行为：以细胞分辨率进行建模”讨论会议议题的一部分。
