Complex Self-organizing System Research Articles

Functional aspects of the EGF-induced MAP kinase cascade: a complex self-organizing system approach.

The EGF-induced MAP kinase cascade is one of the most important and best characterized networks in intracellular signalling. It has a vital role in the development and maturation of living organisms. However, when deregulated, it is involved in the onset of a number of diseases. Based on a computational model describing a “surface” and an “internalized” parallel route, we use systems biology techniques to characterize aspects of the network’s functional organization. We examine the re-organization of protein groups from low to high external stimulation, define functional groups of proteins within the network, determine the parameter best encoding for input intensity and predict the effect of protein removal to the system’s output response. Extensive functional re-organization of proteins is observed in the lower end of stimulus concentrations. As we move to higher concentrations the variability is less pronounced. 6 functional groups have emerged from a consensus clustering approach, reflecting different dynamical aspects of the network. Mutual information investigation revealed that the maximum activation rate of the two output proteins best encodes for stimulus intensity. Removal of each protein of the network resulted in a range of graded effects, from complete silencing to intense activation. Our results provide a new “vista” of the EGF-induced MAP kinase cascade, from the perspective of complex self-organizing systems. Functional grouping of the proteins reveals an organizational scheme contrasting the current understanding of modular topology. The six identified groups may provide the means to experimentally follow the dynamics of this complex network. Also, the vulnerability analysis approach may be used for the development of novel therapeutic targets in the context of personalized medicine.

Transport processes and irreversible thermodynamics analysis in tumoral systems

Cells are chemical engines in which specific ordered chemical reactions occur. Cancer can be described as an open complex dynamic and self-organizing system. Entropy generation approach has been used to evaluate the biochemical and biophysical conditions of the stationary states for tumoral cells, in relation to the transport processes through their membrane. The tumoral systems can assume all the values of volume, temperature, chemical reaction rate and the time of chemical reaction, in the range of stationary conditions. This range can be evaluated by the principle of extrema variation of the entropy generation. Outside this range, cancer cannot develop and dies. The geometrical characteristics are fundamental in the growth of cancer. The fractal dimensions are discussed in this analysis and the geometry of cancer is related to the entropy generation. A possible anticancer thermodynamic approach has been suggested.

A learning heuristic for space mapping and searching self-organizing systems using adaptive mesh refinement

In a complex self-organizing system, small changes in the interactions between the system's components can result in different emergent macrostructures or macrobehavior. In chemical engineering and material science, such spontaneously self-assembling systems, using polymers, nanoscale or colloidal-scale particles, DNA, or other precursors, are an attractive way to create materials that are precisely engineered at a fine scale. Changes to the interactions can often be described by a set of parameters. Different contiguous regions in this parameter space correspond to different ordered states. Since these ordered states are emergent, often experiment, not analysis, is necessary to create a diagram of ordered states over the parameter space. By issuing queries to points in the parameter space (e.g., performing a computational or physical experiment), ordered states can be discovered and mapped. Queries can be costly in terms of resources or time, however. In general, one would like to learn the most information using the fewest queries. Here we introduce a learning heuristic for issuing queries to map and search a two-dimensional parameter space. Using a method inspired by adaptive mesh refinement, the heuristic iteratively issues batches of queries to be executed in parallel based on past information. By adjusting the search criteria, different types of searches (for example, a uniform search, exploring boundaries, sampling all regions equally) can be flexibly implemented. We show that this method will densely search the space, while preferentially targeting certain features. Using numerical examples, including a study simulating the self-assembly of complex crystals, we show how this heuristic can discover new regions and map boundaries more accurately than a uniformly distributed set of queries.

Some neuromyths concerning the effectiveness of cochlear implants: Inferring function from dysfunction

Cochlear implants provide profoundly deaf infants and young children with access to critical temporal and spectral patterns of speech needed for language development. Despite the enormous benefits of cochlear implants, many controversial questions remain. I will consider ten pressing issues that are the focus of current efforts in the field: (1) individual variability in speech and language outcomes, (2) neuroplasticity and early implantation, (3) learning and linguistic experience, (4) linguistic vs indexical channels in speech perception, (5) bilateral vs. unilateral implantation, (6) Contribution of other neural and cognitive systems, (7) early predictors of outcomes and risk factors, (8) workload and mental effort, (9) speech in noise, and (10) acoustic simulations in normal-hearing listeners. These issues raise important theoretical questions about basic processes in speech perception and spoken language processing. Cochlear implant research may be viewed as a “model system” enabling inferences about normal function from the study of dysfunction providing additional converging support for the proposal that the ear does not function in isolation from the rest of the brain; it is an inseparable component of a complex adaptive self-organizing system that evolved to support the perception and production of spoken language. [Work supported by NIH Grants: R01 DC-XYZ and DC-ABC to Indiana University.]

Entropy generation and cell growth with comments for a thermodynamic anticancer approach

The chemical–physical analysis of the DNA have pointed out the connections between forces, thermodynamics and kinetics. The entropy generation approach has been suggested as a thermodynamic approach to evaluate the accessible states for cancer systems, in relation to their thermodynamic characteristic quantities. Cancer can be described as an open complex dynamic and self-organizing system. The stationary states of tumour systems are analyzed by a thermodynamic approach by using the entropy generation. The aim of this paper is to improve the thermodynamic approach to cell systems, based on the entropy generation. The results obtained consist of the theoretical analysis of the lifetimes of the processes which occur in cells and the numerical evaluation of the theoretical model proposed. Some considerations on the interactions between external fields and cell systems are developed. A possible new anticancer therapy based on the entropy generation is proposed.

Beyond the family life cycle: Understanding family development in the twenty-first century through complexity theories

Perspectives on family development have been organized, mainly, around the idea of the family life cycle. However, a family life cycle approach is probably too simplistic and norm-oriented to understand family development, particularly in face of the diversity of family forms and challenges in the twenty-first century. In this article, we discuss how family science can borrow inspiration from concepts and methods of complexity sciences in order to (re)conceptualize family development as the time unfolding of a complex self-organizing system, in the direction of increasing differentiation and integration. We highlight some strategies to inspect developmental coordination dynamics at the level of the whole family, as a complex system. We hope this reflection opens a new space of debate and new avenues for theoretical development and research in the field of family science.

The diminishing role of hubs in dynamical processes on complex networks

It is notoriously difficult to predict the behaviour of a complex self-organizing system, where the interactions among dynamical units form a heterogeneous topology. Even if the dynamics of each microscopic unit is known, a real understanding of their contributions to the macroscopic system behaviour is still lacking. Here, we develop information-theoretical methods to distinguish the contribution of each individual unit to the collective out-of-equilibrium dynamics. We show that for a system of units connected by a network of interaction potentials with an arbitrary degree distribution, highly connected units have less impact on the system dynamics when compared with intermediately connected units. In an equilibrium setting, the hubs are often found to dictate the long-term behaviour. However, we find both analytically and experimentally that the instantaneous states of these units have a short-lasting effect on the state trajectory of the entire system. We present qualitative evidence of this phenomenon from empirical findings about a social network of product recommendations, a protein–protein interaction network and a neural network, suggesting that it might indeed be a widespread property in nature.

Transport processes in biological systems: Tumoral cells and human brain

The entropy generation approach has been developed for the analysis of complex systems, with particular regards to biological systems, in order to evaluate their stationary states. The entropy generation is related to the transport processes related to exergy flows. Moreover, cancer can be described as an open complex dynamic and self-organizing system. Consequently, it is used as an example useful to evaluate the different thermo-chemical quantities of the transport processes in normal and in tumoral cells systems.

Different chemical reaction times between normal and solid cancer cells

Entropy generation approach has been developed in order to use it for the analysis of complex systems with particular regards to biological systems in order to evaluate their stationary states. The entropy generation is related to the transport processes related to energy flows. Moreover, cancer can be described as an open complex dynamic and self-organizing system. Using the entropy generation approach it is possible to point out different chemical reaction time between normal and solid cancer cells.

Thermodynamics and cancer stationary states

Cancer can be described as an open complex dynamic and self-organizing system. The stationary states of the open systems are analysed in engineering thermodynamics by entropy generation. The recent results on entropy generation are suggested as the basis of a new approach to cancer analysis in order to study the cancer evolution and new possible anticancer therapies.

Evolution of dilatant fracture networks in a normal fault — Evidence from 4D model experiments

Dilatant fractures in normal fault zones are widely recognized as major pathways of fluid flow in the upper crust where the ratio of rock strength and effective stress is suitable for their formation, but the structure of these fracture networks in 3D, their connectivity and their temporal evolution is poorly known. Here we build on 2D studies of scaled models of fracture networks in dilatant normal fault zones, using a series of X-ray computer tomographic scans of a physical model. We show how the dilatant fracture network evolves in 3D, as a complex self-organizing system with self-similar geometry. We processed the CT-scan data using a threshold filter to identify the open fracture volume, to allow visual and quantitative analysis of the evolving fracture system in 3D. Dilatant jogs initiated along the evolving fault plane coalesce into a self-similar percolating volume (Fd = 1.91). The fracture volume increases non-linearly with progressive displacement as the velocity of the fault blocks diverges from the master fault orientation and we infer that the normal stress on the fault decreases correspondingly. This process continues until the system triggers the formation of antithetic faults, with a corresponding increase in normal stress on the master fault and a decrease in the rate of fracture volume creation. We infer that although parameters like the width of the fractures are not scaled with the same ratio as length and stress, the processes and evolution of fracture geometries in our model are robust and apply to a wide range of normal fault zones in nature. Since our physical model does not involve chemical processes such as cementation or fault healing, the experiment suggests that fault systems can show a non-linear change of fracture network properties caused by a geometric evolution only.

The Brain, a Complex Self-organizing System

Our intuition assumes that there is a centre in our brain in which all relevant information converges and where all decisions are reached. To neurobiologists, the brain presents itself as a highly distributed system in which a very large number of processes occur simultaneously and in parallel without requiring coordination by a central convergence centre. The specific architecture resembles, in many respects, small world networks and raises the question of how the multiple operations occurring in parallel are bound together in order to give rise to coherent perception and action. Based on data obtained with massive parallel recordings, the hypothesis will be forwarded that temporal coherence serves as an important organizing principle and that this coherence is achieved by the synchronization of oscillatory activity in distinct frequency bands.

Empirical Tests of Zipf’s Law Mechanism in Open Source Linux Distribution

Zipf's power law is a ubiquitous empirical regularity found in many systems, thought to result from proportional growth. Here, we establish empirically the usually assumed ingredients of stochastic growth models that have been previously conjectured to be at the origin of Zipf's law. We use exceptionally detailed data on the evolution of open source software projects in Linux distributions, which offer a remarkable example of a growing complex self-organizing adaptive system, exhibiting Zipf's law over four full decades.

Complexity, simplicity, and epidemiology

It should be stressed that although many phenomena are complex, 15 the concept of ‘complexity’ is more specific. Complexity is the study of complex adaptive systems. These have been defined as ‘a collection of individual agents with freedom to act in ways that are not always totally predictable, and whose actions are interconnected so that one agent’s actions changes the context for other agents’. 16 Such systems include living cells, the brain, the immune system, the financial markets, ecosystems, and human populations. They are complex in the sense that there are a great many apparently independent agents interacting with each other, but the richness of these interactions allows the system as a whole to undergo self-organization. 1 They are also characterized as involving non-linearity and feedback loops in which small changes can have striking effects that cannot be understood simply by analysing the individual components. 17 The whole is more than the sum of its (reductionist) parts. Such complex systems can exist on a number of different levels from the subatomic through to the individual level, the population level, and beyond. 18 The most striking example of a complex self-organizing system is life itself, not only in terms of individual organisms but also in evolutionary terms—organisms adapt to each other through evolution into a finely tuned ecosystem. Similarly, various populations have evolved traditional ways of life that are now responding to the changes brought by the industrial revolution, colonization, and globalization. 19

The production of bimanual percussion in 12- to 24-month-old children

Bimanual coordination represents a complex self-organizing system that is subject to both internal and contextual constraints. Although there has been interest in examining bimanual development throughout the lifespan, few data exist relative to the bimanual activity of children between 1 and 4 years of age. The study reported here represents an initial effort to address this gap. Twenty-seven children who were either 12, 18 or 24 months old were videotaped while drumming with sticks on a plastic drum. Two independent observers recorded bout length as well as number and phase relation of movement cycles within bouts. Kinematic analysis provided more detailed information about the timing and form of children's activity. Results indicate that bimanual drumming becomes preferred over unimanual drumming by 2 years of age, that the proportions of different phase relations exhibited by children change between 1 and 2 years of age, and that the behavior appears to go through periods of stability and variability within this age range. These results are discussed in the context of the child's physical development and interactions with the environment during this period.

Principles of brain functioning: a synergetic approach to brain activity, behavior and cognition

This book presents a new understanding of brain activity. Based on the general results of synergetics, the brain is conceived as a complex self-organizing system with emergent properties. This approach is elaborated upon by numerous explicit models that are based on and checked by detailed experiments on movement control, on various results on vision and on EEG and MEG analysis. The book provides newcomers to brain research with an introductory chapter on the experimental exploration of the brain and provides newcomers to synergetics with detailed and easy-to-read chapters on the basic concepts and theoretical tools of this field.