论文标题

秀丽隐杆线虫的多层网络分析:研究机车电路

Multilayer network analysis of C. elegans: Looking into the locomotory circuitry

论文作者

Maertens, Thomas, Schöll, Eckehard, Ruiz, Jorge, Hövel, Philipp

论文摘要

我们研究了如何在大脑中产生运动行为,重点是线虫秀丽隐杆线虫(秀丽隐杆线虫)的范式连接组以及控制前进运动的神经元活动模式。我们将蠕虫的神经元网络映射为多层网络,该网络考虑了各种神经递质和神经肽。使用逻辑回归分析,我们预测了运动子网的神经元。将神经元活性的后部 - 摩西方程与用于肌肉活动的泄漏的积分模型相结合,我们研究了该子网中的动力学,并使用谐波波模型预测了蠕虫的正向运动。时间延迟的反馈控制的应用揭示了同步效应,这有助于秀丽隐杆线虫的协调运动。当某些神经元的活性沉默时,分析同步性会告诉我们它们对协调的运动行为的重要性。由于在人类和秀丽隐杆线虫中,信息处理是相同的,因此对运动电路的研究为了解大脑如何产生运动行为提供了新的见解。

We investigate how locomotory behavior is generated in the brain focusing on the paradigmatic connectome of nematode Caenorhabditis elegans (C. elegans) and on neuronal activity patterns that control forward locomotion. We map the neuronal network of the worm as a multilayer network that takes into account various neurotransmitters and neuropeptides. Using logistic regression analysis, we predict the neurons of the locomotory subnetwork. Combining Hindmarsh-Rose equations for neuronal activity with a leaky integrator model for muscular activity, we study the dynamics within this subnetwork and predict the forward locomotion of the worm using a harmonic wave model. The application of time-delayed feedback control reveals synchronization effects that contribute to a coordinated locomotion of C. elegans. Analyzing the synchronicity when the activity of certain neurons is silenced informs us about their significance for a coordinated locomotory behavior. Since the information processing is the same in humans and C. elegans, the study of the locomotory circuitry provides new insights for understanding how the brain generates motion behavior.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源