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slimemold.stationary

Please note

The simulation needs a Java-Plugin (1.3.x) installed for your internet browser. If you do not already have one installed, the browser will prompt you to download the Plugin from “Sun”, who is the inventor of Java. Please download the JRE (=Java runtime environment) into a directory on your computer (e.g. “c:\temp”), execute the downloaded file for installation on your system (double-click on the file). Afterwards you will be able to reload the simulation page. Maybe you will have to restart your browser to succeed.

Run the simulation

Please click here.

Description of the simulation

In contrast to the simple model, this model focuses entironly on the propagation of the cAMP waves. As these waves moves much faster than the amoebes could move, it assumes the amoebes to be stationary. It further assumes that a cell that encounters a cAMP concentration over a certain threshold releases additional cAMP (100 units) by herself. After that, the cells stays refractory for a while.

The released cAMP diffuses (spreads) a little in the environment and evaporates after some timesteps.

Parameters

  • The slider density sets the density of cells
  • The slider number sets how many cells initially release their cAMP (as a starting signal)
  • The sliders threshold and period set the reaction threshold and the length of the refractory period.
  • The slider view-mode allows to switch between a view that shows the cells’ states and a view that shows the local cAMP concentrations.

Experiments

  • Test for effects in changing the refractory period and in changing the threshold
  • Test for the minimum needed density to see waves propagating.

Pictures

This picture shows you the typical form of the cAMP waves, as they can be seen in laborytory:

Screenshot

This is how the simulation predicts the waves:

Implementation

The model was inspired from Scott Camazines StarLogo-Model, that can be downloaded from his site.

The simulation was written in NetLogo by: Thomas Schmickl, Department for Zoology, Karl-Franzens-University Graz, Austria (Europe),
schmickl@nextra.at (preferred adress), thomas.schmickl@uni-graz.at
http://members.nextra.at/hfbuch/edoc
http://zool33.uni-graz.at/schmickl

Further readings

  • Camazine S., Deneubourg J.-L., Franks N.R., Sneyd J., Theraulaz G. and Bonabeau E. (2001) Self-Organization in biological systems. Princeton University Press.

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