Slime Mold

Introduction to Slime Mold

The cellular slime molds spend most of their lives as separate single-celled organisms, but when starving, they release a chemical signal, and the individual cells aggregate into a great swarm. Cellular slime molds are thus of great interest to biologists, because they provide a comparatively simple system for understanding how cells interact to generate a multicellular organism. This is an excellent demonstration of bottom up thinking, as well as self organizing systems.

What is This Simulation?

This project is inspired by the aggregation behavior of slime mold. It shows how creatures can aggregate into clusters without the control of a "leader."

In this example, each slime mold cell drops a chemical pheromone (shown in green). The cells also "sniff" ahead, trying to follow the gradient of other cells' chemicals. Meanwhile, the patches diffuse and evaporate the pheromone. Following these simple, decentralized rules, the cells aggregate into clusters.

How to Use It

Click the setup button to set up a collection of slime mold cells. Click the go button to start the simulation.

The population slider controls the number of slime mold cells in the simulation. Changes in the population slider do not have any effect until the next setup command.

The other sliders affect the way slime mold cells move. Changes to them will immediately affect the runningmodel.

sniff-threshhold: The minimum amount of chemical that must be present in a cell's patch before the cell will look for a chemical gradient to follow. This parameter causes the cells to aggregate only when there are enough other cells nearby. The default value is 2.5.
sniff-angle: The amount, in degrees, that a cell turns to the left and right to check for greater chemical concentrations. The default value is 52.
wiggle-angle: The maximum amount, in degrees, that a cell will turn left or right in its random movements. When wiggle-angle is set to zero, the cell will remain at the same heading until it finds a chemical gradient to follow. The default value is 22.
left-right-bias: The bias of a cell's average wiggle. When wiggle-bias = 0, the cell's average movement is straight ahead. When left-right bias> 0, the cell will tend to move more right than left. When bias < 0, the cell will tend to move more left than right. The default value is 0.
evaporation: the rate of evaporation of the chemical. The default is 0.9
diffusion: the diffusion rate of the chemical. The default is 1.
chemical-drops: the amount of chemical deposited at each step. The default is 2.

Note: It may be helpful to slow the simulation down by moving the ticks slider to the left.

Things to Notice

With 100 slime mold cells, not much happens. The cells wander around dropping chemical, but the chemical evaporates and diffuses too quickly for the cells to aggregate.

With 400 cells, the result is quite different. When a few cells happen (by chance) to wander near one another, they create a small "puddle" of chemical that can attract any number of other cells in the vicinity. The puddle then becomes larger and more attractive as more cells enter it and deposit their own chemicals. This process is a good example of positive feedback: the more cells, the larger the puddle; and the larger the puddle, the more likely it is to attract more cells.

Things to Try

Try different values for the sniff-threshhold, sniff-angle, wiggle-angle, and wiggle-bias sliders. How do they affect the slime mold cells' movement and the formation of clumps?
Change the sniff-angle and wiggle-angle sliders after some clumps have formed. What happens to the clumps? Try the same with sniff-threshhold and wiggle-bias.
Modify the program so that the cells aggregate into a single large cluster.
How do the results change if there is more (or less) randomness (wiggle) in the cells' motion?
What "critical number" of cells is needed for the clusters to form? How does the critical number change if you modify the evaporation or diffusion rate?

The Next Step

Check out this video of slime mold in real life:

For more insight, read this article.
Consider: What current events mimic slime mold behavior?

Table of Contents

Credits and References

This model was developed at the MIT Media Lab using CM StarLogo. See Resnick, M. (1994) "Turtles, Termites and Traffic Jams: Explorations in Massively Parallel Microworlds." Cambridge, MA: MIT Press. Adapted to StarLogoT, 1997, as part of the Connected Mathematics Project. Adapted to NetLogo, 2000, as part of the Participatory Simulations Project.

To refer to this model in academic publications, please use: Wilensky, U. (1997). NetLogo Slime model. http://ccl.northwestern.edu/netlogo/models/Slime. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.