Tóth Tibor I, Berg Eva, Daun Silvia
Heisenberg Research Group of Computational Neuroscience - Modeling Neuronal Network Function, University of Cologne, Cologne, Germany
Karolinska Institute, University of Stockholm, Stockholm, Sweden.
Physiol Rep. 2017 Nov;5(22). doi: 10.14814/phy2.13489.
Beside locomotion, search movements are another important type of motor activity of insects. They are very often performed by the front legs of the animals. They consist of cyclic stereotypical leg movements that can be modified by sensory signals. The details of the local organization of these movements have however not yet been studied. In this paper, we, using an appropriate variant of our existing one-leg model, present a scheme of how these searching movements might be organized and performed on the level of local neuromuscular control networks. In the simulations with the model, we attempted to mimic the experimental results by Berg et al. (J. Exp. Biol. 216:1064-1074, 2013) in which an obstacle was put in the way of the search movements of the front leg for a very short while, and then the recovery to the usual search movements was observed and analyzed. Our simulation results suggest that the recruitment of the fast levator and depressor muscles play a crucial part in resuming the search movements after removal of the obstacle. The interplay between the levator and depressor, and the extensor and flexor local control networks can, according to the model, bring about a large variety of search movements upon removal of the obstacle. A number of these movements are comparable with those seen in the experiments.
除了移动，搜索运动是昆虫的另一种重要的运动活动类型。它们通常由动物的前腿执行。它们由周期性的刻板腿部运动组成，这些运动可以被感官信号改变。然而，这些运动的局部组织细节尚未得到研究。在本文中，我们使用现有单腿模型的适当变体，提出了一种关于这些搜索运动在局部神经肌肉控制网络层面可能如何组织和执行的方案。在使用该模型的模拟中，我们试图模仿Berg等人（《实验生物学杂志》216:1064 - 1074，2013年）的实验结果，在该实验中，在前腿的搜索运动路径上放置一个障碍物很短一段时间，然后观察并分析恢复到通常搜索运动的情况。我们的模拟结果表明，快速提肌和降肌的募集在移除障碍物后恢复搜索运动中起着关键作用。根据该模型，提肌和降肌以及伸肌和屈肌局部控制网络之间的相互作用在移除障碍物后可以产生各种各样的搜索运动。其中一些运动与实验中观察到的运动相当。
