Relational Basis of the Organism's Self-organization A Philosophical Discussion

In this thesis, I discuss the organism’s self-organization from the perspective of relational ontology. I critically examine scientific and philosophical sources that appeal to the concept of self-organization. By doing this, I aim to carry out a thorough investigation into the underlying reasons of emergent order within the ontogeny of the organism. Moreover, I focus on the relation between universal dynamics of organization and the organization of living systems. I provide a historical review of the development of modern ideas related to self-organization. These ideas have been developed in relation to various research areas including thermodynamics, molecular biology, developmental biology, systems theory, and so on. In order to develop a systematic understanding of the concept, I propose a conceptual distinction between transitional self-organization and regulative self-organization. The former refers to the spontaneous emergence of order, whereas the latter refers to the self-maintaining characteristic of the living systems. I show the relation between these two types of organization within biological processes. I offer a critical analysis of various theories within the organizational approach. Several ideas and notions in these theories originate from the early studies in cybernetics. More recently, autopoiesis and the theory of biological autonomy asserted certain claims that were critical toward the ideas related to self-organization. I advocate a general theory of self-organization against these criticisms. I also examine the hierarchical nature of the organism’s organization, as this is essential to understand regulative self-organization. I consider the reciprocal relation between bottom-up and top-down dynamics of organization as the basis of the organism’s individuation. To prove this idea, I appeal to biological research on molecular self-assembly, pattern formation (including reaction-diffusion systems), and the self-organized characteristic of the immune system. Finally, I promote the idea of diachronic emergence by drawing support from biological self-organization. I discuss the ideas related to constraints, potentiality, and dynamic form in an attempt to reveal the emergent nature of the organism. To demonstrate the dynamicity of form, I examine research into biological oscillators. I draw the following conclusions: synchronic condition of the organism is irreducibly processual and relational, and this is the basis of the organism’s potentiality for various organizational states

Education and development as complex dynamic agent systems::how theory informs methodology

This chapter argues that the integrative theory that can serve as the basis of integrative methodology is the theory of complex dynamic agent systems. It explains this general theory by focusing on teaching–learning processes in the educational context, and on pedagogical actions and dynamic assessment in the classroom. A complex dynamic system can be defined as a network of components that interact with each other. Self-organization means that the network of components organizes itself into a particular pattern of temporarily self-sustaining relationships among components. “Self-sustaining” means that systems resist external perturbations, at least to a certain extent. External perturbations, when they occur, may function for the better or for the worse. Emergence means that the interactions between the components of a system lead to the origination of properties that are new, in the sense that they transcend the properties of the components taken separately

Self-organized stress patterns drive state transitions in actin cortices

Biological functions rely on ordered structures and intricately controlled collective dynamics. This order in living systems is typically established and sustained by continuous dissipation of energy. The emergence of collective patterns of motion is unique to nonequilibrium systems and is a manifestation of dynamic steady states. Mechanical resilience of animal cells is largely controlled by the actomyosin cortex. The cortex provides stability but is, at the same time, highly adaptable due to rapid turnover of its components. Dynamic functions involve regulated transitions between different steady states of the cortex. We find that model actomyosin cortices, constructed to maintain turnover, self-organize into distinct nonequilibrium steady states when we vary cross-link density. The feedback between actin network structure and organization of stress-generating myosin motors defines the symmetries of the dynamic steady states. A marginally cross-linked state displays divergence-free long-range flow patterns. Higher cross-link density causes structural symmetry breaking, resulting in a stationary converging flow pattern. We track the flow patterns in the model actomyosin cortices using fluorescent single-walled carbon nanotubes as novel probes. The self-organization of stress patterns we have observed in a model system can have direct implications for biological functions

Persistent fluid flows defined by active matter boundaries

Biological systems achieve precise control over ambient fluids through the self-organization of active protein structures including flagella, cilia, and cytoskeletal networks. In active structures individual proteins consume chemical energy to generate force and motion at molecular length scales. Self-organization of protein components enables the control and modulation of fluid flow fields on micron scales. The physical principles underlying the organization and control of active-matter driven fluid flows are poorly understood. Here, we apply an optically-controlled active-matter system composed of microtubule filaments and light-switchable kinesin motor proteins to analyze the emergence of persistent flow fields in a model active matter system. Using light, we form contractile microtubule networks of varying shape. We analyze the fluid flow fields generated by a wide range of microtubule network geometries and explain the resulting flow fields within a unified theoretical framework. We specifically demonstrate that the geometry of microtubule flux at the boundary of contracting microtubule networks predicts the steady-state fluid flow fields across polygonal network geometries through finite-element simulations. Our work provides a foundation for programming microscopic fluid-flows with controllable active matter and could enable the engineering of versatile and dynamic microfluidic devices

DynaMoVis: Visualization of dynamic models for urban modeling

In association with Urban modelers, we have created DynaMoVis, a system for the visualization of dynamic models. The prediction of the evolution of urban and ecological systems is difficult because they are complex nonlinear systems that exhibit self-organization, emergence and path dependence. Without a good understanding of the dynamics, interventions might have unintended side-effects. This study aims to make progress in the understanding of dynamic models in the application areas of urban modelling. Analyzing these simulations is challenging due to the large amount of data generated and the high-dimensional nature of the system. We present a visualization system for exploring the behavior of a simulation from many different points of view. The system contains a number of different modes which allow exploration of: the simulation parameter space, the introduction and effect of noise on the simulation and the basins of attraction in the phase space of the simulation. Through use of this system it has been possible to develop a deeper understanding of the inter-dependencies in the models, their parameter spaces and corresponding phase spaces