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IV. Ecosmomics: Independent, UniVersal, Complex Network Systems and a Genetic Code-Script Source

Mora, Thierry and William Bialek. Are Biological Systems Poised at Criticality?. arXiv:1012.2242. Posted in November 2010, a Princeton University geneticist and a physicist contribute to the on-going, historic revision of the essential nature of informative “genetic” domains. Not only are discrete “genes” being subsumed into layers of relational webworks, these dynamic, creative dimensions ought to be seen as instantiations of a universal proclivity for self-organization. These findings of a natural presence of critically poised complex systems from galaxies to genomes to Gaia bode well for a profoundly new and different kind of genesis universe, and an obvious implication whereby such phenomena take on a “genetic” quality.

Many of life's most fascinating phenomena emerge from interactions among many elements – many amino acids determine the structure of a single protein, many genes determine the fate of a cell, many neurons are involved in shaping our thoughts and memories. Physicists have long hoped that these collective behaviors could be described using the ideas and methods of statistical mechanics. In the past few years, new, larger scale experiments have made it possible to construct statistical mechanics models of biological systems directly from real data. We review the surprising successes of this “inverse" approach, using examples form families of proteins, networks of neurons, and flocks of birds. Remarkably, in all these cases the models that emerge from the data are poised at a very special point in their parameter space - a critical point. This suggests there may be some deeper theoretical principle behind the behavior of these diverse systems. (Abstract, 1)

To summarize, we have discussed experimental evidence of criticality in a wide variety of systems, spanning all possible biological scales, from individual proteins to whole populations of animals with high cognitive capacity, in stationary as well as dynamical systems. The wide applicability of the concepts exposed here, fueled by an increasing amount of high quality data, makes for an exciting time. Ideas which once seemed tremendously speculative are now emerging, independently, from the analysis of real data on many different systems, and the common features seen across so many levels of biological organization encourage us to think that there really are general principles governing the function of these complex systems. (18)

Moreno, Alvaro, et al. The Impact of the Paradigm of Complexity on the Foundational Frameworks of Biology and Cognitive Science. Hooker, Cliff, ed. Philosophy of Complex Systems. Amsterdam: Elsevier, 2011. Alvaro Moreno and Kepa Ruiz-Mirazo, University of the Basque Country, and Xabier Barandiaran, University of Sussex, biophilosophers voice the theme of the volume by once more contrasting, as per the quotes, an older emphasis on physics and chemistry, whereof cosmos and creatures are determined, insensate mechanisms, and in actuality, a dynamic, quickening vitality, and vista just adawning. By this project, prior, reduced particles can be equitably joined in ubiquitous scale-free networks to illume a lively, processional, awakening emergence. Thus to properly study and understand body and brain, organic form and cerebral acumen, in the 21st century, it is essential to move from detailed analysis to an integral systems survey across these temporal and spatial expanses.

The study of networks with strongly and recurrently interacting components allowed scientists to deal with holistic systems, showing that, despite their variety, they share certain generic properties. For many, these advances seemed to reflect some common, universal architecture of complex systems (or, at least, the fact that they all belonged to a critical region ‘at the edge of chaos.’ So the blossoming of the sciences of complexity, among other important reasons, induced –and is still inducing– a profound change in biology and neuroscience toward less analytic and more synthetic-holistic views. (313)

Indeed, when we examine more carefully biological and cognitive systems, a much wider variety of interacting components and non-linear interaction modes are found (as compared with any physical or chemical complex system). More precisely, biological and cognitive systems show an intricate and rich functional diversity within a modular and hierarchical dynamic organization. This organization is endowed with global/collective properties, like highly robust self-maintenance, and shows singular patterns of behaviour in their environments, like agency, multiscale adaptive flexibility, etc. (313-314)

Acknowledging that new approaches and methodological tools are required to account for the specific types of organized complexity that generate biological or cognitive phenomena, we will discuss in what sense the ‘paradigm of complexity’ is deeply reframing our ways of conceiving science and philosophy of science itself. And, finally, we recapitulate on the role that complexity sciences have played in the opening of what will probably constitute a new scientific era, in which up to now almost exclusively descriptive-explanatory disciplines, like biology and cognitive science, will turn into much more predictive and technologically fruitful parts of human intellectual endeavour. (314)

Morin, Edgar. RE: From Prefix to Paradigm. World Futures. 61/4, 2005. This essay by the French polymath philosopher, (1921- ), was first published in La Methode II: La Vie de la Vie (Editions du Seuil, 1980), here translated by Frank Poletti and Sean Kelly. Please view Morin’s bio on Wikipedia for his activist life from the Spanish civil war to WW II resistance movements, Marxism and its rejection, and on to these nonlinear engagements. A crucial theme is how to convey the deep essence of our reality as a manifest repetition of a generative, complexifying agency, algorithm, or process. In its day, the theories seem as an independent version of Maturana and Varela’s autopoietic, self-referencing living systems. Morin goes on to advise that anything new “Meta” need be couched in familiar “Retro” terms, a good guide. And although cited as abstractions, could we appreciate one more valiant attempt to express the actual, constant presence and operation of a cosmos to child genetic code, as a grand revelatory secret?

This article is a translated chapter from a large study of the philosophy of ecology and biology. It looks at the vast array of reiterative processes in nature and culture and argues that continuous recursion is the core activity that sustains living processes at all levels. Therefore, the prefix “re,” which is central to the concepts of repetition, renewal, reinforcement, regeneration, reorganization, recursion, and religion, is a radical concept that should be considered at the paradigmatic level. The author shows that by working “revolutions into its revolutions” the process of RE complexly unifies and intermixes the past and future in order to generate the creative pulse of evolution. (Abstract, 254)

Morowitz, Harold and Jerome Singer, eds. The Mind, the Brain, and Complex Adaptive Systems. Reading, MA: Addison-Wesley, 1995. Explorations of the welling realization that dynamical theories offer an effective new way to theoretically understand what an evolving nature is about.

In the 1980s and 1990s we are witnesses to a new paradigmatic shift in science. Theorists in many fields are moving away from linear, reductionist, simple cause-effect models toward confronting the challenges of complex adaptive systems. Such systems are found in fields as diverse as astrophysics and economics, cerebral neurobiochemistry and cognitive psychology. (1)

Mumford, David, et al. Indra’s Pearls. Cambridge: Cambridge University Press, 2002. A visually impressive book to convey how fast computers can now give colorful exposition to the intricate mathematics of the early 20th century, especially those of Felix Klein. By these insights and methods, an intricate fractal self-similarity seems to pervade nature at every scale. These findings are next seen to affirm the ancient Buddhist vision of reality as a net or web of jewels whence the entire universe is reflected in each pearl. These equations and images convey a universally repeated interrelationship, a mutual identity, among every domain and member of the cosmos.

Making a statement equally faithful to both mathematics and religion, we can say that each part of our pictures contains within itself the essence of the whole. (xix)

Munoz, Miguel. Colloquium: Criticality and Dynamical Scaling in Living Systems.. Reviews of Modern Physics. 90/031001, 2018. After three decades of complexity studies since 1980s inklings, 1990s diversities, onto a 21st century expansive filling in from cosmos to culture, in these later 2010s we seem to be closing on the dream and goal of a common, iconic recurrence everywhere. Along with other entries herein, a University of Granada, Statistical Physics Group (ergodic.ugr.es for info and bio) theorist posts a 40 page, 700 reference tutorial which explains how nature self-organizes and emerges in a scale invariant way from phase transitions to genomes, cellular physiologies, animal groups, neural activity, and much more by a constant critical poise between order and disorder. By literary license, one could cite a cosmic, gender-like complementary criticality. For some 2017 comparisons see The Wisdom of Networks by Peter Csermely, Inequality in Nature and Society by Marten Steffen, et al, and Challenges in the Analysis of Complex Systems by Harold Hastings, Harold, et al. Altogether here is an epochal discovery by our intelligent humankinder in our midst which would serve us to recognize and implement. See also an editorial by Mark Buchanan in Nature Physics for February 2018 which cites this work as a significant exposition of this universal complementarity.

For later works see, for example, The excitatory-inhibitory branching process: cortical states, excitability, and criticality by M. Munoz and colleagues at arXiv:2203.16374, and his personal website.

A celebrated and controversial hypothesis conjectures that some biological systems - parts, aspects, or groups of them - may extract important functional benefits from operating at the edge of instability, halfway between order and disorder, i.e. in the vicinity of the critical point of a phase transition. Criticality has been argued to provide biological systems with an optimal balance between robustness against perturbations and flexibility to adapt to changing conditions, as well as to confer on them optimal computational capabilities, huge dynamical repertoires, unparalleled sensitivity to stimuli, etc. Criticality, with its concomitant scale invariance, can be conjectured to emerge in living systems as the result of adaptive and evolutionary processes that select for it as a template upon which higher layers of complexity can rest. (Abstract excerpt)

The hypothesis that living systems may operate in the vicinity of critical points, with concomitant scale-invariance, has long inspired scientists. From a theoretical viewpoint this conjecture is certainly appealing, as it suggests an overarching mechanism exploited by biological systems to derive important functional benefits essential in their strive to survive and proliferate. Throughout this essay we discussed dynamical aspects of criticality, meaning that in most of the discussed examples it is assumed – either directly or indirectly - that there is an underlying dynamical process at work, and that such a process – susceptible to be mathematically modeled – operates in the vicinity of a continuous phase transition, at the borderline between two alternative regimes. (27)

Nadeau, Robert and Menas Kafatos. The Non-Local Universe. New York: Oxford University Press, 1999. An innovative synthesis of physics and biology which describes the cosmos as a unified, organic whole. The results of sophisticated physical experiments where widely separated objects are in instant contact implies a seamless, holistic reality. Such a universe develops into levels of increasing complexity and sentience due to a complementary interplay of particle and wave, entity and relation, analysis and system, at each subsequent stage. These qualities then imply a reciprocity of the masculine and feminine principles. In its human phase the cosmos reaches self-awareness able to reflect on the primal consciousness it arose from.

….profound complementarities have been disclosed in the study of relationships between parts and wholes in biological reality that are analogous to those previously disclosed in the study of the relationship between parts and wholes in physical reality. This not only suggests that complementarity is the logic of nature in biological reality. It could also provide a basis for better understanding how increasing levels of complexity in both physical and biological reality result from the progressive emergence of collections of parts that constitute new wholes that display properties and behavior that cannot be explained in terms of the sum of the parts. (103)

Newman, Mark. Modularity and Community Structure in Networks. Proceedings of the National Academy of Sciences. 103/8577, 2006. The recent discovery of the same network pattern and process from genomes to computers is distinguished by a prevalence of communal modules. University of Michigan physicist Newman here describes an improved mathematical method for their recognition and activity.

Newman, Stuart. Complexity in Organismal Evolution. Hooker, Cliff, ed. Philosophy of Complex Systems. Amsterdam: Elsevier, 2011. The New York Medical College mathematician begins with Immanuel Kant to trace an array of historical attempts to explain the intricate lineaments of genotype and phenotype. While any evocation of “design” is gauche, we ought not to let a past fixation on mechanism alone to keep us from the possibility that something is really going on. An overdue shift from point genes to dynamical forms, molecules to morphodynamics, is much underway, which augurs for a 21st century evolutionary synthesis at last able to include nature’s creative spontaneity.

Niazi, Muaz, editor. Complex Adaptive Systems Modeling: A Multidisciplinary Roadmap. Complex Adaptive Systems Modeling. 1/1, 2013. A new periodical from the SpringerOpen Journal and BioMed Central project, which are all in full online. This posting is an initial, thorough overview of CAS features, along with guidance for paper writing and entries, by its editor who is a computer scientist at Bahria University, Islamabad with a doctorate from the University of Stirling, UK. See also by Niazi and Amir Hussain, University of Stirling, a 2013 Springer Briefs in Cognitive Computation volume Cognitive Agent-Based Computing: A Unified Framework for Modeling Complex Adaptive Systems.

Keywords: agent-based models, agent-based simulation, artificial life, biological networks, Boolean networks, citation networks, complex adaptive systems, complex networks, computer networks, emergence, epidemiological networks, gene expression networks, gene regulatory networks, individual-based modeling, metabolic networks, multiagent systems, network modeling, nucleic acid networks, protein interaction networks, self-adaptation, self-assembly, self-healing, self-organization, signaling pathway networks, social network analysis, social networks, social simulation, systems biology.

The CAS concept is married to the interaction of a set of perhaps simple but numerous entities, components or agents which interact and adapt on the basis of interactions. This interaction is known to give rise to interesting and emergent phenomena. While it is rather difficult to contain all aspects of CAS in a single definition, our current understanding is that CAS are often found in nature and in nature-inspired artificial systems in close relation with or inspired by life in some way. CAS concepts are tied to an abstract concept of a society. As such, it can be noted that typical research articles with a focus in modeling CAS are ornate with the following concepts: 1. A large number of agents (e.g. Genes, societies, humans, animals, insects, software agents, data packets etc.). 2. Focus on somewhat simpler individual agents. 3. Focus on the nonlinear interaction between agents and global phenomena resulting from these interactions. (6-7)

Nitzan, Mor, et al. Revealing Physical Interaction Networks from Statistics of Collective Dynamics. Science Advances. 3/e1600396, 2017. (arXiv:1801.05598) Mor Nitzan, Hebrew University of Jerusalem, with Jose Casadiego and Marc Timme, MPI Dynamics and Self-Organization contribute to deeper rootings of life’s interconnective propensities within nature’s active physical substrate (which in turn appears as increasingly animate and conducive).

Revealing physical interactions in complex systems from observed collective dynamics constitutes a fundamental inverse problem in science. Current reconstruction methods require access to a system's model or dynamical data at a level of detail often not available. We exploit changes in invariant measures, in particular distributions of sampled states of the system in response to driving signals, and use compressed sensing to reveal physical interaction networks. Testing various nonlinear dynamic processes emerging on artificial and real network topologies indicates high reconstruction quality for existence as well as type of interactions. These results advance our ability to reveal physical interaction networks in complex synthetic and natural systems. (Abstract)

Many complex systems in physics and biology constitute networks of dynamically interacting units. Examples range from gene regulatory networks in the cell and neural circuits in the brain to food webs in ecosystems and power grids, as well as other supply systems of engineering. These systems’ interaction networks fundamentally underlie their collective dynamics and function, thus rendering the knowledge of their interaction topology essential. For instance, identifying new pathways in gene regulatory networks and understanding long-range feedback in engineering systems require exact knowledge of their physical interaction networks. (1)

Nonnemacher, Marcel, et al. Signatures of Criticality Arise from Random Subsampling in Simple Populations Models. PLOS Computational Biology. Online October, 2017. MPI Biological Cybernetics and University of Tubingen integrative neuroscientists contribute new ways to understand cognitive performance as best served by critically balanced state between static and rigor. This significant appreciation which began hesitantly a decade ago (search Dante Chialvo), is now well evident.

The rise of large-scale recordings of neuronal activity has fueled the hope to gain new insights into the collective activity of neural ensembles. One attempt to interpret such data builds upon analogies to the behaviour of collective systems in statistical physics. Here, we connect “signatures of criticality”, and in particular the divergence of specific heat, back to statistics of neural population activity commonly studied in neural coding: firing rates and pairwise correlations. We show that the specific heat diverges whenever the average correlation strength does not depend on population size. To analyze these simulations, we develop efficient methods for characterizing large-scale neural population activity with maximum entropy models. Thus, previous reports of thermodynamical criticality in neural populations based on the analysis of specific heat can be explained by average firing rates and correlations. We conclude that a reliable interpretation of statistical tests for theories of neural coding is possible only in reference to relevant ground-truth models. (Abstract excerpts)

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