Slime mold grows in the form of an interconnected network as part of its normal strategy to explore new sources of food. When it encounters numerous food sources separated in space, the slime mold cell surrounds the food and creates tunnels to distribute the nutrients.
To test how efficient the mold could be, Toshiyuki Nakagaki’s team duplicated the layout of the area around Tokyo: They placed the slime mold in the position of the city, and dispersed bits of oat around the “map” in the locations of 36 surrounding towns. The mold explored slowly at first, but like any good transportation engineer it began to figure out traffic patterns. Those carrying a high volume of nutrients gradually expand, while those that are little used slowly contract and eventually disappear.
The mold is able to replicate the existing subway network of Tokyo and connect important nodes by growing on a flat moist surface. What could be of interest here is how the mold can navigate topography to reach certain nodes. This could be a useful city planning strategy or means of locating service trails through national parks. A digital mathematical model of this same process could be supplemental to GIS systems.
Another area of interest would be to investigate the limits of the mold in exploring its surroundings for new sources of food. For example, how far will the furthest reaching cells travel in search of nutrients. Can the mold travel vertically? Can the mold be trained to search in specific directions by repeatedly placing then removing a food source? What other processes can the mold simulate?
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