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. 2017 Aug 23;7:9237. doi: 10.1038/s41598-017-09300-3

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© The Author(s) 2017

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Migration plasticity can be advantageous under heterogeneous, highly structured ECM conditions. The figure shows the average migration distance d _p of switching and non-switching populations depending on the switch ratio α/β under heterogeneous ECM condition (modeled by equation (2) with θ = 0.5, see Fig. 3(e)) and with different migration rate ratios: (a) c _M/c _A = 0.75 and (b) c _M/c _A = 0.25. The blue line represents the switching populations, the black lines display non-switching populations with different M-cell fraction $γ \in {0,0.3,0.7,1}$ . Each simulation is run with 50 cells. Simulations are evaluated after 200 Monte Carlo steps, averaged over 50 independent simulations. The errorbars show the standard deviation of the average migration distance d _p between the simulations. The standard deviation within the simulations is shown in Supplementary Fig. S6. Simulation parameters are κ = 1, $δ =0.1$ . The red arrow indicates the difference Δd _p between the switching population with maximum average migration distance d _p with respect to varied α/β ratio and the non-switching population with maximum d _p with respect to varied γ fraction, which is the observable analyzed in Fig. 7.