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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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VI. Earth Life Emergence: Development of Body, Brain, Selves and Societies

A. A Survey of Common Principles

Tauber, Uwe. Critical Dynamics: A Field Theory Approach to Equilibrium and Non-Equilibrium Scaling Behavior. Cambridge: Cambridge University Press, 2014. A Virginia Tech physicist contributes a technical text that well quantifies the latest and deepest theoretical basis for nature’s self-similar “scale invariance” from physical to planetary realms.

Introducing a unified framework for describing and understanding complex interacting systems common in physics, chemistry, biology, ecology, and the social sciences, this comprehensive overview of dynamic critical phenomena covers the description of systems at thermal equilibrium, quantum systems, and non-equilibrium systems. Powerful mathematical techniques for dealing with complex dynamic systems are carefully introduced, including field-theoretic tools and the perturbative dynamical renormalization group approach, rapidly building up a mathematical toolbox of relevant skills. Heuristic and qualitative arguments outlining the essential theory behind each type of system are introduced at the start of each chapter, alongside real-world numerical and experimental data, firmly linking new mathematical techniques to their practical applications.

Tero, Atsushi, et al. Rules for Biologically Inspired Adaptive Network Design. Science. 327/439, 2010. Along with a news note “Amoeba-Inspired Network Design” in the same issue, how such microbial colonies can be seen as exemplars of self-organizing systems, which are being found to recur throughout nature’s ascendant nest, especially for viable human societies. All of which it is said seems to spring from an independent, universal mathematical source.

Troisi, Alessandro, et al. An Agent-based Approach for Modeling Molecular Self-organization. Proceedings of the National Academy of Sciences. 102/255, 2010. In another example from the recent nonlinear dynamics shift in physics, University of Bologna and Northwestern University researchers search ways to independently articulate and define the universally prevalent, nested complexity that is being found everywhere to distinguish a genesis nature.

Self-organization is one of the most fascinating phenomena in nature. It appears in such apparently disparate arenas as crystal growth, the regulation of metabolism, and dynamics of animal and human behavior. One of the great challenges in the field of complexity is the definition of the common patterns that make possible the emergence of order from apparently disordered systems. One example is given by the scale invariant networks that appear to offer a good perspective for many complex systems. Another possibility is the study of emergent phenomena through agent-based (AB) modeling. In this paper, after defining briefly the principles of AB modeling, we explore the possibility that such a modeling paradigm could be useful for the study of self-organizing chemical systems, complementing the currently used stochastic (Monte Carlo) or deterministic (molecular dynamics) methods. (255)

Tsuchiya, Masa, et al. Local and Global Responses in Complex Gene Regulation Networks. Physica A. 388/1738, 2009. Keio University, Japan, and Istituto Superiore di Sanita, Italy, researchers, including Kumar Selvarajoo and Alessandro Giuliani, employ a statistical physics approach to reveal a network paradigm an intrinsic genome-wide dynamical essence.

One relevant feature of the high degree of connectivity of gene regulation networks is the emergence of collective ordered phenomena influencing the entire genome and not only a specific portion of transcripts. The great majority of existing gene regulation models give the impression of purely local ‘hard-wired’ mechanisms disregarding the emergence of global ordered behavior encompassing thousands of genes while the general, genome wide, aspects are less known. (Abstract)

Biological phenomena, at every scale of definition from protein folding to the structure of ecological systems passing through gene expression regulation and physiology, display two seemingly alternative functioning modes. The first mode can be called “hard wired,” for the possibility to be efficiently described by the node-arrow representation prevalent in modern biology and the second mode (statistical mechanics-like) in which collective phenomena are more important than the specific elements involved. This second (collective) mode, despite successful application in different fields of cell biology still appears under adopted by the scientific community. (1738)

The demonstration that within a clonal population of multipotent progenitor cells, spontaneous non-genetic population heterogeneity primes the cells for different lineage choices and that , in turn, the progression along the differentiation pathways happens in terms of a genome-wide transcriptome displacement asks for a complementation of the classical gene-specific approach to cellular biology with a much wider statistical-mechanics like perspective. (1745)

Valverde, Sergi and Ricard Sole. Self-Organization versus Hierarchy in Open-Source Networks. Physical Review E. 76/046118, 2007. Over the past few years, scale-free networks composed of elemental nodes, which themselves can be complex nets, and are joined in dynamic, interactive linkage, have been found to distinguish every natural and social plane. In this case, email exchanges on the Internet, in contrast to ‘bottom-up’ biologically self-organized systems, can be observed to exhibit a ‘top-down’ degree of centralized direction. Might we then be able to note, I add circa 2008, an evolutionary vector of increasing intention and guidance? Sole, Valverde and their colleagues, based at the Universitat Pompeu Fabra in Barcelona, with international collaboration such as the Santa Fe Institute, are making significant contributions toward the theoretical explanation of a natural genesis. (But in the Physics and Astronomy Classification Scheme (PACS) this journal employs, this work is tacked on to an alien cosmos at the very end as category ‘89.75.Hc.’)

Valverde, Sergi, et al. Structural Determinants of Criticality in Biological Networks. Frontiers of Physiology. May 8, 2015. Valverde and Jordi Garcia-Ojalvo, University of Pompeu Fabra, Barcelona, Sebastian Ohse, Albert-Ludwigs University, Freiburg, along with Malgorzata Turalska and Bruce West, Duke University, finesse these generic anatomical dynamics which seem to universally appear in every development phase of universe and human. Figure 3, Gene Network Evolution has this caption: Natural selection pushes gene regulatory networks toward the critical regime due to the opposing forces of conserving essential network function and allowing for the evolution of potentially beneficial modifications. A favored middle state is then shown as poised between Ordered and Chaotic, once more as a reciprocal, metastable reciprocity.

Many adaptive evolutionary systems display spatial and temporal features, such as long-range correlations, typically associated with the critical point of a phase transition in statistical physics. Empirical and theoretical studies suggest that operating near criticality enhances the functionality of biological networks, such as brain and gene networks, in terms for instance of information processing, robustness, and evolvability. While previous studies have explained criticality with specific system features, we still lack a general theory of critical behavior in biological systems. Here we look at this problem from the complex systems perspective, since in principle all critical biological circuits have in common the fact that their internal organization can be described as a complex network. An important question is how self-similar structure influences self-similar dynamics. We review and discuss recent studies on the criticality of neuronal and genetic networks, and discuss the implications of network theory when assessing the evolutionary features of criticality. (Abstract)

Visentin-Bugoni, Jeferson, et al. Structure, Spatial Dynamics and Stability of Novel Seed Dispersal Mutualistic Networks in Hawai’i. Science. 364/78, 2019. Eight systems ecologists posted in Illinois, Wyoming, New Hampshire, and Honolulu report the presence of common topological forms as alien fauna and flora proceed to invade complex ecosystems. We thus record the presence of an independent mathematical source in universal formative effect.

Increasing rates of human-caused species invasions and extinctions may reshape communities and modify the structure, dynamics, and stability of species interactions. To investigate how such changes affect communities, we performed multiscale analyses of seed dispersal networks on Oahu, Hawaii. Networks consisted exclusively of novel interactions, were largely dominated by introduced species, and exhibited specialized and modular structure at local and regional scales, despite high interaction dissimilarity across communities. Furthermore, the structure and stability of the novel networks were similar to native-dominated communities worldwide. Our findings suggest that the emergence of complex network structure, and interaction patterns may be highly conserved, regardless of species identity and environment. (Abstract)

Vitiello, Giuseppe. On the Isomorphism between Dissipative Systems, Fractal Self-Similarity and Electrodynamics: Toward an Integrated Vision of Nature. Systems. 2/203, 2014. In this online journal, the University of Salerno theoretical physicist summarizes two decades of studies, with colleagues, upon a universal form and theme that seems to be exemplified and repeated in kind everywhere. The project is to achieve a unified, viable “living matter physics” situated in and aligned with a conducive quantum cosmos. See also Fractals, Coherent States and Self-Similarity Induced Noncommutative Geometry by GV at arXiv:1206.1854.

One more aspect which is related with the discussion here presented concerns with the description of fractal-like structures with self-similarity properties in terms of non-homogeneous Bose condensation. Indeed, in the present scheme they appear to be generated by coherent SU(1; 1) quantum condensation processes at the microscopic level, similar to “extended objects” or macroscopic quantum systems. The macroscopic appearances (forms) of the fractals seems to emerge out of a process of morphogenesis as the macroscopic manifestation of the underlying dissipative, coherent quantum dynamics at the elementary level. An integrated vision of Nature resting, in its essence, on the paradigm of coherence and dissipation thus emerges. Nature appears to be modulated by coherence, rather than being hierarchically layered in isolated compartments, in multi-coded collections of isolated systems and phenomena. (213)

The DNA genetic code appears in conclusion to be the output of the coherent dynamics. In this way, it is subtracted from its purely phenomenological characterization, which is sometimes at the origin of dogmatic or even miraculous beliefs. In this view, DNA appears to be the vehicle through which the laws of form express themselves in living systems and coherence and its deformations propagate through duplication and multiplication processes. (214)

Walleczek, Jan, ed. Self-Organized Biological Dynamics and Nonlinear Control. Cambridge, UK: Cambridge University Press, 2000. A theoretical appreciation of organisms as energy-driven, open systems which gives rise to an emergent fractal organization and viability. For these reasons, a physical basis for evolving life is defined.

A revolution is underway in the physical sciences, based on insights from nonlinear dynamics, which includes the areas popularly known as chaos and complexity studies. As described in the previous chapters, this revolution is beginning to affect greatly the biological and medical sciences as well. (409) The nonlinear dynamical systems view, which I also referred to in the Introduction to this book as the paradigm of self-organization, thus provides biology with a theoretically sound approach toward a ‘holistic biology’ for the first time in the history of science. (417)

Watson, Richard A., et al. Global Adaptation in Networks of Selfish Components: Emergent Associative Memory at the System Scale. Artificial Life. Early View, May, 2011. Watson and Rob Mills, Natural Systems, University of Southampton, and Chris Buckley, Informatics, Sussex University, post an advanced, technical analysis of the presence and activity of dynamic network phenomena across life’s nested evolution. By this work, and many akin, a growing quantification and admission accrues that something much more creative is going on to drive and direct life’s historic development. A universal complementarity of semi-autonomous agents or entities and communicative interrelations that serves both self and society is described as it repeats from biomolecules to ecosystems. For a further take see also next Watson, Richard A., et al. “Adaptation Without Natural Selection.” Both articles are available on Watson’s web publication page. We offer extended quotes to convey the technical verbatim, which may suggest, in translation, a cosmic genetic code at work.

In some circumstances complex adaptive systems composed of numerous self-interested agents can self-organise into structures that enhance global adaptation, efficiency or function. However, the general conditions for such an outcome are poorly understood and present a fundamental open question for domains as varied as ecology, sociology, economics, organismic biology and technological infrastructure design. In contrast, sufficient conditions for artificial neural networks to form structures that perform collective computational processes such as associative memory/recall, classification, generalisation and optimisation, are well-understood. (Abstract, 1)

Specifically, the key to understanding this result is that selfish agents necessarily modify connections in a manner consistent with Hebb’s rule – a simple learning rule familiar in computational neuroscience (Methods). This means that a system of selfish agents, each modifying its connections with other agents selfishly and in a completely distributed manner, will produce dynamical consequences for the system as a whole that are functionally identical to a learning neural network. (3)

Conclusions: We have shown that organisational principles familiar in organismic learning occur implicitly in distributed complex adaptive systems. System-level ‘learning’ or associative induction happens as a direct consequence of the fact that selfish modifications to relationships between components are equivalent to Hebb’s rule. Thus networks of selfish agents self-organise the connection structure of a network in a manner that creates an associative memory of state configurations that the system experiences. (22) These findings suggest that distributed complex adaptive systems of self-interested components, such as individuals in a social network or species in an ecosystem, may exhibit organisational principles in common with those familiar in organismic learning, developing an associative memory of their past behaviour that enhances system-level efficiency in future. This work thereby demonstrates a completely distributed adaptive process that we view as a natural extension to the “emergent collective computational abilities” that come ‘for free’ in physical systems [22].

West, Geoffrey. The Surprising Math of Cities and Corporations. http://www.ted.com/talks/geoffrey_west_the_surprising_math_of_cities_and_corporations.html.. The physicist and philosopher, once president of Santa Fe Institute, describes in this July 2011, Edinburgh, TED video presentation, the remarkable findings of research teams he has mentored and contributed to over 15 years. In the later 1990s West joined with ecologists James Brown and Brian Enquist in an endeavor to quantify within creaturely anatomy and physiology from mice to elephants, and biota from leaves to a forest, a pervasive recurrence of the same pattern and process, such metabolic rate. This project met with much success (search names herein) so that West extended the effort in the 2000s with Luis Bettencourt, Deborah Strumsky, Jose Lobo, and other colleagues to human settlements and commercial institutions. The talk is mainly on this aspect, but covers the whole expanse over orders of magnitude from microbes to a metropolis.

A significant difference then arises. While flora and fauna are seen as “sublinear,” i.e., metabolisms slow down from voles to whales, for villages to megacities, energy usages, and all activities, become “superlinear” as they increase with urban size and density. But notably, as we know, business companies hold to the sublinear range. The bigger they get, the more bureaucracy sets in, and viability decreases. As a result of this grand scenario, “generic universal principles” of nested network geometries that repeat with fractal-like self-similarity become robustly evident. What accrues is an historic discovery of a constant, iterative recurrence, as if from a mathematical source, across nature and culture. Galileo would say tell me about it. Geoffrey West, of British birth, brings to mind William Blake: “To see a world in a grain of sand, And a heaven in a wild flower, Hold infinity in the palm of your hand, And eternity in an hour.”

“The same principles, the same dynamics, the same organization is at work in all of these, including us, and it can scale over a range of 100 million in size. And that is one of the main reasons life is so resilient and robust -- scalability.”

West, Geoffrey and James Brown. Life’s Universal Scaling Laws. Physics Today. September, 2004. A popular survey of the theory that common properties of biological networks can explain the structural organization and metabolic dynamics of living systems.

Among the many fundamental variables that obey such scaling laws….are metabolic rate, life span, growth rate, heart rate, lengths of aortas and genomes, tree height, mass of cerebral grey matter, density of mitochondria, and concentration of RNA. (36) The starting point was to recognize that highly complex, self-sustaining, reproducing, living structures require close integration of enormous numbers of localized microscopic units that need to be serviced in an approximately “democratic” and efficient fashion. (38) Thus, growth and life-history events are, in general, universal phenomena governed primarily be basic cellular properties and quarter-power scaling. (40)

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