论文标题
将连接组链接到动作：秀丽隐杆线虫的机器人模型中的新兴动力学
Linking the connectome to action: Emergent dynamics in a robotic model of C. elegans
论文作者
论文摘要
我们分析了神经动力学及其与机器人车辆的紧急行为的关系，该行为由基于线虫秀丽隐杆线虫神经系统的神经网络数值模拟控制。机器人通过传感器与环境相互作用，该传感器将信息传输到感觉神经元，而运动神经元输出连接到车轮。这足以使机器人在复杂的环境中移动，避免与障碍物发生冲突。使用机器人模型可以同时保持所有神经元的详细微观动力学的跟踪，并实时注册机器人的动作。这使我们能够研究Connectome和复杂行为之间的相互作用。我们发现，全球神经动力学的一些基本特征及其与在蠕虫中观察到的行为的相关性在机器人中自发出现，这表明它们只是连接组的新兴特性。
We analyse the neural dynamics and its relation with the emergent behaviour of a robotic vehicle that is controlled by a neural network numerical simulation based on the nervous system of the nematode Caenorhabditis elegans. The robot interacts with the environment through a sensor, that transmits the information to sensory neurons, while motor neurons outputs are connected to wheels. This is enough to allow robot movement in complex environments, avoiding collisions with obstacles. Working with a robotic model makes it possible to keep track simultaneously of the detailed microscopic dynamics of all the neurons and also register the actions of the robot in the environment in real time. This allowed us to study the interplay between connectome and complex behaviors. We found that some basic features of the global neural dynamics and their correlation with behaviour observed in the worm appear spontaneously in the robot, suggesting they are just an emergent property of the connectome.
