Nakagaki Toshiyuki, Guy Robert D
Creative Research Initiative SOUSEI, Hokkaido University, 001-0021 Sapporo, Japan and Research Institute for Electronic Science, Hokkaido University, 060-0812 Sapporo, Japan.
Department of Mathematics, University of California Davis, Davis, CA, USA.
Soft Matter. 2007 Dec 11;4(1):57-67. doi: 10.1039/b706317m.
We review how soft matter is self-organized to perform information processing at the cell level by examining the model organism Physarum plasmodium. The amoeboid organism, Physarum polycephalum, in the class of true slime molds, exhibits the intelligent behavior of foraging in complex situations. When placed in a maze with food sources at two exits, the organism develops tubular structures with its body which connect the food sources along the shortest path so that the rates of nutrient absorption and intracellular communication are maximized. This intelligent behavior results from the organism's control of a dynamic network through which mechanical and chemical information is transmitted. We review experimental studies that explore the development and adaptation of structures that make up the network. Recently a model of the dynamic network has been developed, and we review the formulation of this model and present some key results. The model captures the dynamics of existing networks, but it does not answer the question of how such networks form initially. To address the development of cell shape, we review existing mechanochemical models of the protoplasm of Physarum, present more general models of motile cells, and discuss how to adapt existing models to explore the development of intelligent networks in Physarum.
我们通过研究模式生物多头绒泡菌，来探讨软物质如何在细胞层面进行自组织以执行信息处理。这种变形虫状生物，多头绒泡菌，属于真正的黏菌类别，在复杂环境中展现出觅食的智能行为。当被放置在一个两个出口处有食物源的迷宫中时，该生物会用其身体形成管状结构，沿着最短路径连接食物源，从而使营养吸收和细胞内通讯的速率最大化。这种智能行为源于该生物对一个动态网络的控制，通过这个网络机械和化学信息得以传递。我们回顾了探索构成该网络的结构的发育和适应性的实验研究。最近已经开发出了一个动态网络模型，我们回顾了这个模型的公式并展示了一些关键结果。该模型捕捉了现有网络的动态，但它没有回答这样的网络最初是如何形成的问题。为了解决细胞形状的发育问题，我们回顾了现有的多头绒泡菌原生质的机械化学模型，提出了更通用的运动细胞模型，并讨论了如何调整现有模型以探索多头绒泡菌中智能网络的发育。
