Neuromechanical Control Architectures of Arthropod Locomotion
Neuromechanical Control Architectures of Arthropod Locomotion
复制标题
节肢动物运动的神经机械控制架构
DOI：
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发表时间：
2009
期刊：
影响因子：
--
通讯作者：
Shai Revzen
中科院分区：
文献类型：
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作者：
Shai Revzen
我们定义了一个理论框架的神经机械控制的动物实验研究，从动力系统理论的数学概念的基础上。这种方法允许生物学家，工程师和数学家之间共享实验，结果和理论模型，并适用于任何系统，生物，人工或模拟的控制研究，只要系统表现出稳定的节奏解决方案。这个框架的基础是这样一个概念，即节奏系统最好表示为其相位的周期函数。使用相位作为预测器，可以将未来动物运动的外推预测与施加扰动时发生的运动进行比较。相位也可以作为运动状态的简要概括，允许相位概括的预期状态与受干扰动物中发现的相位之间的差异-lresidual相位器。在第一章中，我们介绍了关键概念，并描述了如何剩余阶段可能被用来识别动物的神经机械控制架构。在接下来的两章中，我们使用剩余相位来分析受到扰动的运行节肢动物。在最后一章中，我们将基于运动相位的模型扩展到基于Floquet理论的动物动力学线性化近似的构建。Floquet模型使我们能够直接检验运动控制的lTemplates和Correlors假说，并描述一个lTemplater -一个低维的动物动力学模型。在第二章中，我们的剩余相位结果从运行蟑螂在一个障碍表明，运动相位被重置，而运行频率被密切保持在p5%以内。运动相位的变化分布双峰模式一步（半个周期）分开，这对应于身体的运动状态的左右反射。结果降低了前馈控制的不确定性，并支持使用神经反馈的这项任务。基于结果，我们提出了一个控制器，表示的两个腿三脚架的动物作为两个耦合的相位振荡器，这反过来，也可以耦合到一个主时钟的时间。在第三章中，我们分析了蟑螂跑到一个横向平移的移动推车上。对动物施加的比冲量为50 p4 cm/s（平均值，SD），几乎是其前进速度25 p6 cm/s的两倍。动物通过降低步频来纠正这些扰动，从而证明了神经反馈。试验分为两类，一类在一步（50 ms）后减慢，另一类在近三步（130 ms）后减慢。类预测的运动学阶段的动物在发病的扰动。我们假设，在响应时间的差异是一个结果的机械姿势的动物在扰动，所表示的相位，以及耦合的神经和机械control.In第4章中，我们试图使用运动相位方法来重建的线性（Floquet）结构运行蟑螂时，被视为非线性振荡器。这种方法的发展需要应用数学和统计学方面的一些创新。我们分析了34只动物在跑步机上跑步的脚和身体位置。结果表明，蟑螂的优势速度具有一个六维模板，每步各维恢复率均小于50%（P<0.05，11只动物，24次试验，532步）。
We define a theoretical framework for the experimental study of neuromechanical control in animals, based on mathematical concepts from dynamical systems theory. This approach allows experiments, results and theoretical models to be shared among biologists, engineers and mathematicians, and is applicable to the study of control in any system, biological, artificial or simulated, provided the system exhibits stable rhythmic solutions. The basis of this framework is the notion that rhythmic systems are best expressed as periodic functions of their phase. Using phase as a predictor, an extrapolated prediction of future animal motions can be compared with the motions that occur when a perturbation is applied. Phase also serves as a succinct summary of the kinematic state, allowing the difference between the expected state as summarized by phase and the phase found in the perturbed animal -- a lresidual phaser. In the first chapter we introduce the key concepts and describe how the residual phase may be used to identify the neuromechanical control architecture of an animal. In the following two chapters we use residual phase to analyze running arthropods subjected to perturbations. In the final chapter, we extend the kinematic phase based models to the construction of a linearized approximation of animal dynamics based on Floquet theory. The Floquet model allows us to directly test the lTemplates and Anchors Hypothesisr of motor control and to characterize a ltemplater -- a low dimensional model of the dynamics of the animal.In chapter 2, our residual phase results from running cockroaches over a hurdle show that kinematic phase was reset, while running frequency was closely maintained to within p5%. Kinematic phase changes were distributed bi-modally with modes one step (half a cycle) apart, which corresponds to a left-right reflection of the kinematic state of the body. The results decrease the plausibility of feedforward control and support the use of neural feedback for this task. Based on the results, we propose a controller that expresses the timing of the two leg tripods of the animals as two coupled phase oscillators, which in turn, may also be coupled to a master clock. In chapter 3, we analyze cockroaches which ran onto a movable cart that translated laterally. The specific impulse imposed on animals was 50p4 cm/s (mean,SD), nearly twice their forward speed 25p6 cm/s. Animals corrected for these perturbations by decreasing stride frequency, thereby demonstrating neural feedback. Trials fell into two classes, one class slowing down after a step (50 ms), the other after nearly three steps (130 ms). Classes were predicted by the kinematic phase of the animal at onset of perturbation. We hypothesize that the differences in response time is a consequence of the mechanical posture of the animal during perturbation, as expressed by the phase, and the coupling of neural and mechanical control.In chapter 4 we attempted to use kinematic phase methods to reconstruct the linearized (Floquet) structure of running cockroaches when viewed as nonlinear oscillators. The development of this approach required several innovations in applied mathematics and statistics. We analyzed foot and body positions of 34 animals running on a treadmill. Results showed that cockroaches running at preferred speed possess a six dimensional template with each dimension recovering by less than 50% in a stride (P<0.05, 11 animals, 24 trials, 532 strides).
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影响因子：
2.5
作者：
Tresch, MC;Cheung, VCK;d'Avella, A
通讯作者：
d'Avella, A
影响因子：
2.4
作者：
BLICKHAN, R
通讯作者：
BLICKHAN, R
影响因子：
56.9
作者：
DELCOMYN, F
通讯作者：
DELCOMYN, F
影响因子：
2.5
作者：
Ting, LH;Macpherson, JM
通讯作者：
Macpherson, JM
DOI：
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发表时间：
1993-12
期刊：
The Journal of experimental biology
影响因子：
--
作者：
C. T. Farley;James W. Glasheen;Thomas A Mcmahon
通讯作者：
C. T. Farley;James W. Glasheen;Thomas A Mcmahon