An Epigenetic Model for Pigment Patterning Based on Mechanical and Cellular Interactions LORENA CABALLERO1,2,3∗, MARIANA BEN´ITEZ3,4,5, ELENA R

Total Page:16

File Type:pdf, Size:1020Kb

An Epigenetic Model for Pigment Patterning Based on Mechanical and Cellular Interactions LORENA CABALLERO1,2,3∗, MARIANA BEN´ITEZ3,4,5, ELENA R RESEARCH ARTICLE An Epigenetic Model for Pigment Patterning Based on Mechanical and Cellular Interactions LORENA CABALLERO1,2,3∗, MARIANA BEN´ITEZ3,4,5, ELENA R. ALVAREZ-BUYLLA3,6, SERGIO HERNANDEZ´ 3, 7 1,3 ALEJANDRO V. ARZOLA , AND GERMINAL COCHO 1Departamento de Sistemas Complejos Instituto de F´ısica, Universidad Nacional Autonoma´ de Mexico,´ Ciudad de Mexico,´ DF, Mexico´ 2Posgrado en Ciencias Biologicas,´ Universidad Nacional Autonoma´ de Mexico,´ Ciudad de Mexico,´ DF, Mexico´ 3C3, Centro de Ciencias de la Complejidad, Universidad Nacional Autonoma´ de Mexico,´ Ciudad de Mexico,´ DF, Mexico´ 4Department of Functional Genomics and Proteomics, Masaryk University, Brno, Czech Republic 5CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic 6Laboratorio de Genetica´ Molecular Desarrollo y Evolucion´ en Plantas Instituto de Ecolog´ıa, Universidad Nacional Autonoma´ de Mexico,´ Ciudad de Mexico,´ DF, Mexico´ 7Institute of Scientific Instruments Academy of Sciences of the Czech Republic, Brno, Czech Republic ABSTRACT Pigment patterning in animals generally occurs during early developmental stages and has eco- logical, physiological, ethological, and evolutionary significance. Despite the relative simplicity of color patterns, their emergence depends upon multilevel complex processes. Thus, theoretical models have become necessary tools to further understand how such patterns emerge. Recent studies have reevaluated the importance of epigenetic, as well as genetic factors in developmen- tal pattern formation. Yet epigenetic phenomena, specially those related to physical constraints that might be involved in the emergence of color patterns, have not been fully studied. In this article, we propose a model of color patterning in which epigenetic aspects such as cell migra- tion, cell–tissue interactions, and physical and mechanical phenomena are central. This model considers that motile cells embedded in a fibrous, viscoelastic matrix—mesenchyme—can deform it in such a way that tension tracks are formed. We postulate that these tracks act, in turn, as guides for subsequent cell migration and establishment, generating long-range phenomenolog- ical interactions. We aim to describe some general aspects of this developmental phenomenon with a rather simple mathematical model. Then we discuss our model in the context of available experimental and morphological evidence for reptiles, amphibians, and fishes, and compare it with other patterning models. We also put forward novel testable predictions derived from our model, regarding, for instance, the localization of the postulated tension tracks, and we propose new experiments. Finally, we discuss how the proposed mechanism could constitute a dynamic patterning module accounting for pattern formation in many animal lineages. J. Exp. Zool. (Mol. Dev. Evol.) 318:209–223, 2012. © 2012 Wiley Periodicals, Inc. ´ ´ J. Exp. Zool. How to cite this article: Caballero L, Benıtez M, Alvarez-Buylla ER, Hernandez S, Arzola AV, (Mol. Dev. Evol.) Cocho G. 2012. An epigenetic model for pigment patterning based on mechanical and cellular 318:209–223, 2012 interactions. J. Exp. Zool. (Mol. Dev. Evol.) 318:209–223. © 2012 WILEY PERIODICALS, INC. 210 CABALLERO ET AL. Morphogenetic mechanisms and pattern formation have tradi- tion of organic organization in terms of internal dynamics and tionally been central topics in developmental biology, and more interaction, focusing on process and change” (Van Speybroeck recently in the search of explanations for pattern formation and et al., 2002: p. 33). The related term epigenetics, which combines evolution at the molecular genetic level (e.g., Parichy, 2006). epigenesis and genetics, was proposed by Waddington to rep- In this context, a valuable strategy for understanding the basic resent “a true synthesis between developmental processes and phenomena involved in the emergence, maintenance, and evolu- genetic action, which together bring the organism into being” tion of developmental patterns is to look for potentially generic (Van Speybroeck et al., 2002: p. 33). mechanisms by using modeling or other theoretical approaches. Based on this understanding of the epigenetic phenomena, we Color pattern formation has already been studied with generic analyze some physical mechanisms critical to the establishment dynamic reaction–diffusion (RD) models (Turing ’52; Gierer and of color patterns in the skin of reptiles, fishes, and amphibians, Meinhardt ’72). However, such models generally do not take and postulate them as potentially generic processes across evo- into account the cellular and tissue environments in which color lutionary lineages. These generic mechanisms could explain, at patterns arise (see, however, Cocho et al., ’87a,b; Moreira and least partially, some of the repeated patterns observed in ver- Deutsch, 2005; Deutsch and Dormann, 2005). In this article, we tebrates. In this case, we will consider the epigenetic processes postulate a simple mathematical model that considers that long- of pigment-cell migration and attraction, and the adhesive and range forces can emerge from viscoelastic and tensile properties mechanical interactions between pigments cells and the mes- of the mesenchymatic tissue, and that these forces, in conjunc- enchyme. tion with cell–cell interactions, may give rise to color patterns Pigment pattern formation can be traced to early stages in like those observed in different animal lineages. We, neverthe- the development of fishes, amphibians, and reptiles, and like less, do not argue that RD models and the model we postulate many key developmental processes, it involves the arrangement here necessarily exclude each other. of epithelial sheets and cells in relation with the mesenchyme Developmental biology recognizes that the emergence of new (Schock¨ and Perrimon, 2002). It is important to mention that patterns results from interactions among diverse molecular, cel- the mesenchyme, the embryonic tissue on which pigment cells lular, and environmental processes, and that epigenetic interac- (chromatophores) migrate during color patterning, is a fibrous tions play an essential role in development (Newman and Muller¨ tissue with few cells. This makes the mesenchyme a matrix 2000). It is important to note that in this work we use the term that is biphasic (consisting of both solid and uid fractions) and epigenetic to refer to a wide range of mechanisms, and not only viscoelastic (exhibiting both viscous and elastic characteristics to refer to heritable DNA modifications, such as methylation. We when deformed), which can show heterogeneous compression or regard as epigenetic mechanisms processes such as cell commu- tension patterns (Grinnell and Petroll, 2010). Given such prop- nication, cell–environment interactions, tensegrity, which gives erties of the mesenchymatic tissue, cells migrating and adhering structural stability to a system by means of tension–compression to it can reorient its fibers and deform the matrix in a way such or attraction–repulsion mechanisms, and other physicochemi- that tension lines are formed. This phenomenon has been ob- cal mechanisms (Waddington, ’62; Newman and Muller,¨ 2000; served in both in vivo and in vitro experimental setups (Table 1). Ingber, 2000, 2006, 2010). According to van Speybroeck and Moreover, it has been shown that such lines become guides for coauthors (2002) “epigenesis can be seen to approach the ques- subsequent cell migration and accumulation (Weiss, ’59; Grin- nell and Petroll, 2010; Fig. 1, Table 1). Contract grant sponsor: Posgrado en Ciencias Biologicas;´ Contract grant We hypothesize that the migration of chromatophores on the sponsor: Centro de Ciencias de la Complejidad, C3; Contract grant spon- mesenchyme, which is mediated by different types of junctions, sor: CONACyT, contract grant numbers: 81433, 81542, 90565; Contract such as the adherens junctions (Schock¨ and Perrimon 2002; Ya- grant sponsor: Red de CONACyT Complejidad, Ciencia y Sociedad; Contract mada et al., 2005), deforms the mesenchyme and gives rise to grant sponsor: PAPIIT, contract grant numbers: IN210408, IN229009-3, tension tracks to which chromatophores will tend to migrate and IN223607-3. where these cells will be more likely to establish. In a recent re- The present address of Mariana Ben´ıtez is Department of Functional Ge- view, Grinnell and Petroll (2010) offer a comprehensive account nomics and Proteomics, Institute of Experimental Biology, Faculty of Sci- ence, Masaryk University, CZ-625 00 Brno, Czech Republic of the mechanisms involved in the adhesion and migration of ∗Correspondence to: Lorena Caballero, Departamento de Sistemas Com- cells embedded in a viscoelastic matrix, and mention that cell plejos, Instituto de F´ısica, Universidad Nacional Autonoma´ de Mexico,´ traction and contraction can deform viscoelastic tissues by es- Posgrado en Ciencias Biologicas,´ Universidad Nacional Autonoma´ de tablishing adhesive interactions and locally contracting the ma- Mexico,´ Ciudad de Mexico,´ DF, Mexico,´ Mexico´ 04510 . E-mail: lrnca- trix. Importantly, this deformation results in long-range forces [email protected] Received 28 February 2011; Revised 2 August 2011; Accepted 2 Novem- regulating subsequent cell migration and establishment (Weiss, ber 2011 ’59; Fig. 1). Published online 4 December 2011 in Wiley Online Library (wileyonline Almost 30 years ago, Oster and Murray (Oster et al., ’83; Mur- library.com). DOI: 10.1002/jez.22007 ray et al., ’83; Murray et al., ’88)
Recommended publications
  • Self-Organization Principles of Intracellular Pattern Formation
    Self-organization principles of intracellular pattern formation J. Halatek. F. Brauns, and E. Frey∗ Arnold{Sommerfeld{Center for Theoretical Physics and Center for NanoScience, Department of Physics, Ludwig-Maximilians-Universit¨atM¨unchen, Theresienstraße 37, D-80333 M¨unchen,Germany (Dated: February 21, 2018) Abstract Dynamic patterning of specific proteins is essential for the spatiotemporal regulation of many important intracellular processes in procaryotes, eucaryotes, and multicellular organisms. The emergence of patterns generated by interactions of diffusing proteins is a paradigmatic example for self-organization. In this article we review quantitative models for intracellular Min protein patterns in E. coli, Cdc42 polarization in S. cerevisiae, and the bipolar PAR protein patterns found in C. elegans. By analyzing the molecular processes driving these systems we derive a theoretical perspective on general principles underlying self-organized pattern formation. We argue that intracellular pattern formation is not captured by concepts such as \activators", \inhibitors", or \substrate-depletion". Instead, intracellular pattern formation is based on the redistribution of proteins by cytosolic diffusion, and the cycling of proteins between distinct conformational states. Therefore, mass-conserving reaction-diffusion equations provide the most appropriate framework to study intracellular pattern formation. We conclude that directed transport, e.g. cytosolic diffusion along an actively maintained cytosolic gradient, is the key process underlying pattern formation. Thus the basic principle of self-organization is the establishment and maintenance of directed transport by intracellular protein dynamics. Keywords: self-organization; pattern formation; intracellular patterns; reaction-diffusion; cell polarity; arXiv:1802.07169v1 [physics.bio-ph] 20 Feb 2018 NTPases 1 INTRODUCTION In biological systems self-organization refers to the emergence of spatial and temporal structure.
    [Show full text]
  • Guiding Self-Organized Pattern Formation in Cell Polarity Establishment
    ARTICLES https://doi.org/10.1038/s41567-018-0358-7 Guiding self-organized pattern formation in cell polarity establishment Peter Gross1,2,3,8, K. Vijay Kumar" "3,4,8, Nathan W. Goehring" "5,6, Justin S. Bois" "7, Carsten Hoege2, Frank Jülicher3 and Stephan W. Grill" "1,2,3* Spontaneous pattern formation in Turing systems relies on feedback. But patterns in cells and tissues seldom form spontane- ously—instead they are controlled by regulatory biochemical interactions that provide molecular guiding cues. The relationship between these guiding cues and feedback in controlled biological pattern formation remains unclear. Here, we explore this relationship during cell-polarity establishment in the one-cell-stage Caenorhabditis elegans embryo. We quantify the strength of two feedback systems that operate during polarity establishment: feedback between polarity proteins and the actomyosin cortex, and mutual antagonism among polarity proteins. We characterize how these feedback systems are modulated by guid- ing cues from the centrosome, an organelle regulating cell cycle progression. By coupling a mass-conserved Turing-like reac- tion–diffusion system for polarity proteins to an active-gel description of the actomyosin cortex, we reveal a transition point beyond which feedback ensures self-organized polarization, even when cues are removed. Notably, the system switches from a guide-dominated to a feedback-dominated regime well beyond this transition point, which ensures robustness. Together, these results reveal a general criterion for controlling biological pattern-forming systems: feedback remains subcritical to avoid unstable behaviour, and molecular guiding cues drive the system beyond a transition point for pattern formation. ell polarity establishment in Caenorhabditis elegans zygotes phase where myosin appears to reach a steady state (Supplementary is a prototypical example for cellular pattern formation that Fig.
    [Show full text]
  • Pattern Formation, Social Forces, and Diffusion Instability in Games
    EPJ manuscript No. (will be inserted by the editor) Pattern Formation, Social Forces, and Diffusion Instability in Games with Success-Driven Motion Dirk Helbing ETH Zurich, UNO D11, Universit¨atstr.41, 8092 Zurich, Switzerland Received: date / Revised version: date Abstract. A local agglomeration of cooperators can support the survival or spreading of cooperation, even when cooperation is predicted to die out according to the replicator equation, which is often used in evolutionary game theory to study the spreading and disappearance of strategies. In this paper, it is shown that success-driven motion can trigger such local agglomeration and may, therefore, be used to supplement other mechanisms supporting cooperation, like reputation or punishment. Success-driven motion is formulated here as a function of the game-theoretical payoffs. It can change the outcome and dynamics of spatial games dramatically, in particular as it causes attractive or repulsive interaction forces. These forces act when the spatial distributions of strategies are inhomogeneous. However, even when starting with homogeneous initial conditions, small perturbations can trigger large inhomogeneities by a pattern-formation instability, when certain conditions are fulfilled. Here, these instability conditions are studied for the prisoner's dilemma and the snowdrift game. Furthermore, it is demonstrated that asymmetrical diffusion can drive social, economic, and biological systems into the unstable regime, if these would be stable without diffusion. PACS. 02.50.Le Decision theory and game theory { 87.23.Ge Dynamics of social systems { 82.40.Ck Pattern formation in reactions with diffusion, flow and heat transfer { 87.23.Cc Population dynamics and ecological pattern formation 1 Introduction tions [17,18], which agree with replicator equations for the fitness-dependent reproduction of individuals in biology Game theory is a well-established theory of individual [19,20,21].
    [Show full text]
  • Using Neural Networks for Pattern Association for the Online Purchase
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by AIS Electronic Library (AISeL) Association for Information Systems AIS Electronic Library (AISeL) All Sprouts Content Sprouts 7-26-2009 Using Neural Networks for Pattern Association for the Online Purchase of Products Arpan Kumar Kar XLRI School of Business & Human Resources, [email protected] Supriyo Kumar De XLRI School of Business & Human Resources, [email protected] Follow this and additional works at: http://aisel.aisnet.org/sprouts_all Recommended Citation Kar, Arpan Kumar and De, Supriyo Kumar, " Using Neural Networks for Pattern Association for the Online Purchase of Products" (2009). All Sprouts Content. 281. http://aisel.aisnet.org/sprouts_all/281 This material is brought to you by the Sprouts at AIS Electronic Library (AISeL). It has been accepted for inclusion in All Sprouts Content by an authorized administrator of AIS Electronic Library (AISeL). For more information, please contact [email protected]. Working Papers on Information Systems ISSN 1535-6078 Using Neural Networks for Pattern Association for the Online Purchase of Products Arpan Kumar Kar XLRI School of Business & Human Resources, India Supriyo Kumar De XLRI School of Business & Human Resources, India Abstract Abstract: Today, a huge percentage of all the business transactions that take place in the domain of e-commerce are dominated by online shopping after the "virtual market" conceptualization of the business. This paper focuses on how pattern association rules may be obtained from the dynamic databases generated during purchases in an e-Store to maximize the profit of the marketer.
    [Show full text]
  • Evolutionary Game Theory: Theoretical Concepts and Applications To
    Physica A 389 (2010) 4265–4298 Contents lists available at ScienceDirect Physica A journal homepage: www.elsevier.com/locate/physa Evolutionary game theory: Theoretical concepts and applications to microbial communities Erwin Frey ∗ Ludwig-Maximilians-Universität München, Arnold Sommerfeld Center for Theoretical Physics and Center for NanoScience, Theresienstrasse 37, D-80333 Munich, Germany article info a b s t r a c t Article history: Ecological systems are complex assemblies of large numbers of individuals, interacting Received 30 January 2010 competitively under multifaceted environmental conditions. Recent studies using Available online 4 March 2010 microbial laboratory communities have revealed some of the self-organization principles underneath the complexity of these systems. A major role of the inherent stochasticity of its Keywords: dynamics and the spatial segregation of different interacting species into distinct patterns Population dynamics has thereby been established. It ensures the viability of microbial colonies by allowing for Game theory species diversity, cooperative behavior and other kinds of ``social'' behavior. Evolution Stochastic processes A synthesis of evolutionary game theory, nonlinear dynamics, and the theory of Nonlinear dynamics stochastic processes provides the mathematical tools and a conceptual framework for a Pattern formation deeper understanding of these ecological systems. We give an introduction into the modern formulation of these theories and illustrate their effectiveness focussing on selected examples of microbial systems. Intrinsic fluctuations, stemming from the discreteness of individuals, are ubiquitous, and can have an important impact on the stability of ecosystems. In the absence of speciation, extinction of species is unavoidable. It may, however, take very long times. We provide a general concept for defining survival and extinction on ecological time-scales.
    [Show full text]
  • Exploring Reaction-Diffusion and Pattern Formation
    Exploring Reaction-Diffusion and Pattern Formation Ramona Behravan1, Peter J. Bentley1, Robin Carlisle2 1 Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, England 2 Glassworks Ltd., 34 Great Pulteney Street, London W1F 9NP, England Abstract. This article reviews the development of the concept of reaction- diffusion leading to pattern formation in living organisms. The article com- mences with an historical background and then describes biological develop- ment, and ideas of the formation of patterns using dynamic activator inhibitor systems. In addition to this, different models to represent such systems and their computer simulations are discussed. 1 Introduction The first steps toward the sciences arose out of the recognition of patterns and struc- tures. Patterns are all around us in the living and the non-living world. Formation of galaxies, mountains, rivers, crystals, zebra stripes, flower petals and butterfly wings are all examples of ordered structures and regular patterns. While it seems likely that evolution plays the major role in creating, selecting and exploiting features in living organisms, there can be no denying the role of physics in nature. Physical structures can emerge naturally without the selection pressure of natural evolution: sand dunes, snow flakes, clouds and cracks in the ground can all self-organise into ordered and re- petitive forms with clearly defined patterns. The existence of such natural pattern has led many researchers to hypothesise that in some of the features of life, natural evolution has exploited the automatic pattern- formation machinery provided by physics instead of creating her own from scratch. In this article we focus on this class of patterns, namely pattern formation of living or- ganisms.
    [Show full text]
  • Pattern Formation in Reaction-Diffusion System on Membrane with Mechanochemical Feedback
    Pattern Formation in Reaction-Diffusion System on Membrane with Mechanochemical Feedback Naoki Tamemoto and Hiroshi Noguchi* Institute for Solid State Physics, University of Tokyo, Kashiwa, Chiba 277-8581, Japan Correspondence and requests for materials should be addressed to H.N. ([email protected] tokyo.ac.jp). 1 ABSTRACT Shapes of biological membranes are dynamically regulated in living cells. Although membrane shape deformation by proteins at thermal equilibrium has been extensively studied, nonequilibrium dynamics have been much less explored. Recently, chemical reaction propagation has been experimentally observed in plasma membranes. Thus, it is important to understand how the reaction-diffusion dynamics are modified on deformable curved membranes. Here, we investigated nonequilibrium pattern formation on vesicles induced by mechanochemical feedback between membrane deformation and chemical reactions, using dynamically triangulated membrane simulations combined with the Brusselator model. We found that membrane deformation changes stable patterns relative to those that occur on a non- deformable curved surface, as determined by linear stability analysis. We further found that budding and multi-spindle shapes are induced by Turing patterns, and we also observed the transition from oscillation patterns to stable spot patterns. Our results demonstrate the importance of mechanochemical feedback in pattern formation on deforming membranes. 2 INTRODUCTION Membrane deformation is a fundamental biological process involved in many cellular functions such as vesicular transport1, cell division2, and cell motility3. To understand these phenomena, the mechanism of membrane deformation by intracellular proteins has been investigated in detail4–8. Recently, it has been shown that the deformation of biological membranes is not just a passive phenomenon but also plays physiological roles8–15.
    [Show full text]
  • A Review: Pattern Formation and Adaptation in Multi-Robot Systems
    A Review: Pattern Formation and Adaptation in Multi-Robot Systems Erkin Bahc¸eci, Onur Soysal and Erol S¸ahin CMU-RI-TR-03-43 October 2003 Robotics Institute Carnegie Mellon University Pittsburgh, Pennsylvania 15213 c Carnegie Mellon University Abstract Recent advances in robotics have started making it feasible to deploy large numbers of inexpensive robots for tasks such as surveillance and search. However, coordination of multiple robots to accomplish such tasks remains a challenging problem. This report reviews some of the recent literature in multi-robot systems. It consists of two parts. In the first part, we reviewed the studies on the pattern formation problem, that is how can a group of robots be controlled to get into and maintain a formation. The second part reviews the studies that used adaptation strategies in controlling multi- robot systems. Specifically we have investigated (1) how learning (life-long adaptation) is used to make multi-robot systems respond to changes in the environment as well in the capabilities of individual robots, and (2) how evolution is used to generate group behaviors. I Contents 1 Introduction 1 2 Pattern formation in multi-robot systems 1 2.1 Centralized pattern formation . 1 2.2 Decentralized pattern formation . 2 3 Adaptation in multi-robot systems 5 3.1 Individual level adaptation . 5 3.2 Group level adaptation . 7 4 Conclusion 9 5 Acknowledgements 9 III 1 Introduction Recent advances in robotics have started making it feasible to deploy large numbers of inexpensive robots for tasks such as surveillance and search. However, coordination of multiple robots to accomplish such tasks remains a challenging problem.
    [Show full text]
  • Pattern Formation Models and Developmental Constraints GEORGE F
    THE JOURNAL OF EXPERIMENTAL ZOOLOGY 251:186-202 (1989) Pattern Formation Models and Developmental Constraints GEORGE F. OSTER AND JAMES D. MURRAY Departments of Biophysics, Entomology, and Zoology, University of California, Berkeley, California 94720 (G.F.0.); Centre for Mathematical Biology, Mathematical Institute, Oxford, OX1 3LB, England (J.D.M.) ABSTRACT Most schemes for embryonic pattern formation are built around the notion of lateral inhibition. Models of this type arise in many settings, and all share some common character- istics. In this paper we examine a number of pattern formation models and show how the phenome- non of lateral inhibition constrains the possible geometries that can arise. Morphogenetic models have provided embry- how the chemical prepattern is laid down. This ologists with insight into how embryonic patterns can be modeled in one of two ways. 1) Simple may be laid down. In this chapter we shall illus- chemical gradients are established across tissues, trate the basic pattern-forming principles of these assuming that certain cells act as sources or sinks models using as an example the formation of for the chemicals, which diffuse from cell to cell bones in the vertebrate limb. The physics of the via junctions, or through the intercellular space. pattern forming process imposes constraints on 2) A chemical prepattern can arise by means of the possible cartilage patterns the limb may ex- “diffusion-driven instabilities,” a notion first pro- hibit. These constraints are reflected in the gen- posed by Turing (’52), and subsequently elabo- eral similarity one observes amongst all tretrapod rated and applied by numerous authors to a va- limbs.
    [Show full text]
  • Inductive Pattern Formation
    INDUCTIVE PATTERN FORMATION A Dissertation by RAYMOND CHARLES MULLICAN Submitted to the Office of Graduate and Professional Studies of Texas A&M University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Chair of the Committee, Gabriela Campagnol Co-Chair of the Committee, Mardelle M. Shepley Committee Members, Jay R. Walton Robert K. Popp Head of Department, Robert Warden December 2017 Major Subject: Architecture Copyright 2017 Raymond Charles Mullican ABSTRACT With the extended computational limits of algorithmic recursion, scientific investigation is transitioning away from computationally decidable problems and beginning to address computationally undecidable complexity. The analysis of deductive inference in structure-property models are yielding to the synthesis of inductive inference in process-structure simulations. Process-structure modeling has examined external order parameters of inductive pattern formation, but investigation of the internal order parameters of self-organization have been hampered by the lack of a mathematical formalism with the ability to quantitatively define a specific configuration of points. This investigation addressed this issue of quantitative synthesis. Local space was developed by the Poincare inflation of a set of points to construct neighborhood intersections, defining topological distance and introducing situated Boolean topology as a local replacement for point-set topology. Parallel development of the local semi-metric topological space, the local semi-metric
    [Show full text]
  • Exploring Aesthetic Pattern Formation
    Generative Art 2002 Exploring Aesthetic Pattern Formation Katie A Bentley Computer Science Department, University College London. Email: [email protected] Abstract This paper is an exploration of an interdisciplinary nature. Through studies in fine art, pattern formation in nature, and artificial life, a mechanism for the artistic process is presented. Asynchronous updating schemes implemented in cellular automata and pheromonal agent swarms were evolved to produce aesthetic patterns and compared favourably to non-evolved synchronous production methods. The curious adaptive properties of the resulting patterns were investigated. 1. Introduction “When we stand before great churches, temples, pyramids, and other works of architecture built hundreds, if not thousands of years ago, our minds are filled with awe and admiration. Yet there have been architects millions of years before that. Their work, it is true, owes its existence not to the inspired genius of great artists, but to the unconscious, unremitting activity of the force of life itself.” [1] Pp 2. There remains a great deal of mystery surrounding the processes involved in the generation of aesthetic and functional forms, as they occur in nature and as generated by humans. Many would still like to believe that both human and natural generation of aesthetic form, at some level at least, a conscious creative plan, some central idea, meaning or goal. Artificial life offers an alternative paradigm of thought, and it is the point of this paper to explore how the seemingly disparate domains of pattern formation, social insect communication and artistic processes can be linked. The aim of this paper is to show that the processes involved in the formation and generation of shapes and patterns, aesthetic or functional, are best viewed as evolved adaptive systems.
    [Show full text]
  • Texture Generation with Neural Cellular Automata
    Texture Generation with Neural Cellular Automata Alexander Mordvintsev* Eyvind Niklasson* Ettore Randazzo Google Research fmoralex, eyvind, [email protected] Abstract derlying state manifold. Furthermore, we investigate prop- erties of the learned models that are both useful and in- Neural Cellular Automata (NCA1) have shown a remark- teresting, such as non-stationary dynamics and an inherent able ability to learn the required rules to ”grow” images robustness to damage. Finally, we make qualitative claims [20], classify morphologies [26] and segment images [28], that the behaviour exhibited by the NCA model is a learned, as well as to do general computation such as path-finding distributed, local algorithm to generate a texture, setting [10]. We believe the inductive prior they introduce lends our method apart from existing work on texture generation. arXiv:2105.07299v1 [cs.AI] 15 May 2021 itself to the generation of textures. Textures in the natural We discuss the advantages of such a paradigm. world are often generated by variants of locally interact- ing reaction-diffusion systems. Human-made textures are likewise often generated in a local manner (textile weaving, 1. Introduction for instance) or using rules with local dependencies (reg- Texture synthesis is an actively studied problem of com- ular grids or geometric patterns). We demonstrate learn- puter graphics and image processing. Most of the work in ing a texture generator from a single template image, with this area is focused on creating new images of a texture the generation method being embarrassingly parallel, ex- specified by the provided image pattern [8, 17]. These im- hibiting quick convergence and high fidelity of output, and ages should give the impression, to a human observer, that requiring only some minimal assumptions around the un- they are generated by the same stochastic process that gen- erated the provided sample.
    [Show full text]