Characteristics of pattern formation and evolution in approximations of physarum transport networks

Most studies of pattern formation place particular emphasis on its role in the development of complex multicellular body plans. In simpler organisms, however, pattern formation is intrinsic to growth and behavior. Inspired by one such organism, the true slime mold Physarum polycephalum, we present examples of complex emergent pattern formation and evolution formed by a population of simple particle-like agents. Using simple local behaviors based on Chemotaxis, the mobile agent population spontaneously forms complex and dynamic transport networks. By adjusting simple model parameters, maps of characteristic patterning are obtained. Certain areas of the parameter mapping yield particularly complex long term behaviors, including the circular contraction of network lacunae and bifurcation of network paths to maintain network connectivity. We demonstrate the formation of irregular spots and labyrinthine and reticulated patterns by chemoattraction. Other Turing-like patterning schemes were obtained by using chemorepulsion behaviors, including the self-organization of regular periodic arrays of spots, and striped patterns. We show that complex pattern types can be produced without resorting to the hierarchical coupling of reaction-diffusion mechanisms. We also present network behaviors arising from simple pre-patterning cues, giving simple examples of how the emergent pattern formation processes evolve into networks with functional and quasi-physical properties including tensionlike effects, network minimization behavior, and repair to network damage. The results are interpreted in relation to classical theories of biological pattern formation in natural systems, and we suggest mechanisms by which emergent pattern formation processes may be used as a method for spatially represented unconventional computation. © 2010 Massachusetts Institute of Technology

Robust formation of morphogen gradients

We discuss the formation of graded morphogen profiles in a cell layer by nonlinear transport phenomena, important for patterning developing organisms. We focus on a process termed transcytosis, where morphogen transport results from binding of ligands to receptors on the cell surface, incorporation into the cell and subsequent externalization. Starting from a microscopic model, we derive effective transport equations. We show that, in contrast to morphogen transport by extracellular diffusion, transcytosis leads to robust ligand profiles which are insensitive to the rate of ligand production

Surface structure of i-Al(68)Pd(23)Mn(9): An analysis based on the T*(2F) tiling decorated by Bergman polytopes

A Fibonacci-like terrace structure along a 5fold axis of i-Al(68)Pd(23)Mn(9) monograins has been observed by T.M. Schaub et al. with scanning tunnelling microscopy (STM). In the planes of the terraces they see patterns of dark pentagonal holes. These holes are well oriented both within and among terraces. In one of 11 planes Schaub et al. obtain the autocorrelation function of the hole pattern. We interpret these experimental findings in terms of the Katz-Gratias-de Boisseu-Elser model. Following the suggestion of Elser that the Bergman clusters are the dominant motive of this model, we decorate the tiling T*(2F) by the Bergman polytopes only. The tiling T*(2F) allows us to use the powerful tools of the projection techniques. The Bergman polytopes can be easily replaced by the Mackay polytopes as the decoration objects. We derive a picture of ``geared'' layers of Bergman polytopes from the projection techniques as well as from a huge patch. Under the assumption that no surface reconstruction takes place, this picture explains the Fibonacci-sequence of the step heights as well as the related structure in the terraces qualitatively and to certain extent even quantitatively. Furthermore, this layer-picture requires that the polytopes are cut in order to allow for the observed step heights. We conclude that Bergman or Mackay clusters have to be considered as geometric building blocks of the i-AlPdMn structure rather than as energetically stable entities

CELL CYCLE KINETICS AND DEVELOPMENT OF HYDRA ATTENUATA

The differentiation of nerve cells and nematocytes in Hydra attenuata has been investigated by labelling interstitial cell precursors with PHJthymidine and following by autoradiography the appearance of labelled, newly differentiated cells. Nematocyte differentiation occurs only in the gastric region where labelled nematoblasts appear 12 h and labelled nematocytes 72—96 h after addition of 2H thymidine. Labelled nerves appear in hypostome, gastric region, and basal disk about 18 h after addition of 3H thymidine. The lag in the appearance of labelled cells includes cell division of the precursor as well as differentiation since nerves and nematocytes have 2JI postmitotic nuclear DNA content. A cell flow model is proposed for interstitial cells and their differentiated products. Stem cells occur as single interstitial cells or in pairs. Per cell generation about 60 % of the daughter cells of stem cell divisions remain stem cells and about 40 % differentiate nerves and nematocytes. Nerves differentiate directly from stem cells in about 1 day. Nematocyte differentiation requires 5-7 days including proliferation of a cluster of 4, 8, 16 or 32 interstitial cells and differentiation of a nematocyst capsule in each cell. The numbers of interstitial cells and nematoblasts predicted by the cell flow model from the rates of nerve differentiation (900 nerves/day/ hydra), nematocyte differentiation (1760 nematocyte nests/day/hydia) and stem cell proliferation (stem cell cycle = 24 h), agree with the numbers of these cells observed in hydra. The number of stem cells per hydra is 3000-6000 depending on assumptions about the time of determination. The ratio of nematocyte to nerve differentiation averaged over the whole hydra is 3:1. In the hypostome and basal disk interstitial cell differentiation occurs exclusively to nerve cells while in the gastric region the ratio of nematocyte to nerve differentiation is about 7:1

On the Importance of Countergradients for the Development of Retinotopy: Insights from a Generalised Gierer Model

During the development of the topographic map from vertebrate retina to superior colliculus (SC), EphA receptors are expressed in a gradient along the nasotemporal retinal axis. Their ligands, ephrin-As, are expressed in a gradient along the rostrocaudal axis of the SC. Countergradients of ephrin-As in the retina and EphAs in the SC are also expressed. Disruption of any of these gradients leads to mapping errors. Gierer's (1981) model, which uses well-matched pairs of gradients and countergradients to establish the mapping, can account for the formation of wild type maps, but not the double maps found in EphA knock-in experiments. I show that these maps can be explained by models, such as Gierer's (1983), which have gradients and no countergradients, together with a powerful compensatory mechanism that helps to distribute connections evenly over the target region. However, this type of model cannot explain mapping errors found when the countergradients are knocked out partially. I examine the relative importance of countergradients as against compensatory mechanisms by generalising Gierer's (1983) model so that the strength of compensation is adjustable. Either matching gradients and countergradients alone or poorly matching gradients and countergradients together with a strong compensatory mechanism are sufficient to establish an ordered mapping. With a weaker compensatory mechanism, gradients without countergradients lead to a poorer map, but the addition of countergradients improves the mapping. This model produces the double maps in simulated EphA knock-in experiments and a map consistent with the Math5 knock-out phenotype. Simulations of a set of phenotypes from the literature substantiate the finding that countergradients and compensation can be traded off against each other to give similar maps. I conclude that a successful model of retinotopy should contain countergradients and some form of compensation mechanism, but not in the strong form put forward by Gierer

Spatial variation in boundary conditions can govern selection and location of eyespots in butterfly wings

Despite being the subject of widespread study, many aspects of the development of eyespot patterns in butterfly wings remain poorly understood. In this work, we examine, through numerical simulations, a mathematical model for eyespot focus point formation in which a reaction-diffusion system is assumed to play the role of the patterning mechanism. In the model, changes in the boundary conditions at the veins at the proximal boundary alone are capable of determining whether or not an eyespot focus forms in a given wing cell and the eventual position of focus points within the wing cell. Furthermore, an auxiliary surface reaction diffusion system posed along the entire proximal boundary of the wing cells is proposed as the mechanism that generates the necessary changes in the proximal boundary profiles. In order to illustrate the robustness of the model, we perform simulations on a curved wing geometry that is somewhat closer to a biological realistic domain than the rectangular wing cells previously considered, and we also illustrate the ability of the model to reproduce experimental results on artificial selection of eyespots.Publisher PD

Oxygen adsorption on the Ru (10 bar 1 0) surface: Anomalous coverage dependence

Oxygen adsorption onto Ru (10 bar 1 0) results in the formation of two ordered overlayers, i.e. a c(2 times 4)-2O and a (2 times 1)pg-2O phase, which were analyzed by low-energy electron diffraction (LEED) and density functional theory (DFT) calculation. In addition, the vibrational properties of these overlayers were studied by high-resolution electron loss spectroscopy. In both phases, oxygen occupies the threefold coordinated hcp site along the densely packed rows on an otherwise unreconstructed surface, i.e. the O atoms are attached to two atoms in the first Ru layer Ru(1) and to one Ru atom in the second layer Ru(2), forming zigzag chains along the troughs. While in the low-coverage c(2 times 4)-O phase, the bond lengths of O to Ru(1) and Ru(2) are 2.08 A and 2.03 A, respectively, corresponding bond lengths in the high-coverage (2 times 1)-2O phase are 2.01 A and 2.04 A (LEED). Although the adsorption energy decreases by 220 meV with O coverage (DFT calculations), we observe experimentally a shortening of the Ru(1)-O bond length with O coverage. This effect could not be reconciled with the present DFT-GGA calculations. The nu(Ru-O) stretch mode is found at 67 meV [c(2 times 4)-2O] and 64 meV [(2 times 1)pg-2O].Comment: 10 pages, figures are available as hardcopies on request by mailing [email protected], submitted to Phys. Rev. B (8. Aug. 97), other related publications can be found at http://www.rz-berlin.mpg.de/th/paper.htm

Effect of randomness and anisotropy on Turing patterns in reaction-diffusion systems

We study the effect of randomness and anisotropy on Turing patterns in reaction-diffusion systems. For this purpose, the Gierer-Meinhardt model of pattern formation is considered. The cases we study are: (i)randomness in the underlying lattice structure, (ii)the case in which there is a probablity p that at a lattice site both reaction and diffusion occur, otherwise there is only diffusion and lastly, the effect of (iii) anisotropic and (iv) random diffusion coefficients on the formation of Turing patterns. The general conclusion is that the Turing mechanism of pattern formation is fairly robust in the presence of randomness and anisotropy.Comment: 11 pages LaTeX, 14 postscript figures, accepted in Phys. Rev.

Implicit-explicit timestepping with finite element approximation of reaction-diffusion systems on evolving domains

We present and analyse an implicit-explicit timestepping procedure with finite element spatial approximation for a semilinear reaction-diffusion systems on evolving domains arising from biological models, such as Schnakenberg's (1979). We employ a Lagrangian formulation of the model equations which permits the error analysis for parabolic equations on a fixed domain but introduces technical difficulties, foremost the space-time dependent conductivity and diffusion. We prove optimal-order error estimates in the \Lp{\infty}(0,T;\Lp{2}(\W)) and \Lp{2}(0,T;\Hil{1}(\W)) norms, and a pointwise stability result. We remark that these apply to Eulerian solutions. Details on the implementation of the Lagrangian and the Eulerian scheme are provided. We also report on a numerical experiment for an application to pattern formation on an evolving domain