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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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IV. Ecosmomics: Independent, UniVersal, Complex Network Systems and a Generative Code-Script Source

5. Common Code: A Further Report of Reliable, Invariant Principles

Radicchi, Filippo, et al. Complex Networks Renormalisation. Physics Review Letters. 101/148701, 2008. In our midst today, if we might inquire, is an imminent discovery via the sum of myriad contributions such as this finding of an invariant resonance whose nested nets from universe to human repeat the same archetypal pattern and process. Renormalization group theory, from 1982 physics Nobel laurate Kenneth Wilson, is yet another window upon nature’s innate universality, but is said to need better terminologies that could aid such a translation.

Generally speaking, an object is self-similar if any part of it, however small, maintains the general properties of the whole object. Self-similarity is a characteristic feature of fractals and it expresses the invariance of a geometrical set under a length-scale transformation. Many complex systems such as the World-Wide-Web (WWW), the Internet, social and biological systems, have a natural representation in terms of graphs, which often display heterogeneous distributions of the number of links per node (the degree k). These distributions can be described by a power law decay, i.e. are scalefree: they remain invariant under a rescaling of the degree variable, suggesting that suitable transformations of the networks’ structure may leave their statistical properties invariant. (148701)

Ramstead, Maxwell, et al. Answering Shrodinger’s Question: A Free-Energy Formulation. Physics of Life Reviews. Online September, 2017. Canadian, Australian, and British neurosciences including lead author Karl Friston post a new response to the 1944 What is Life? book by the Nobel laureate Erwin Schrodinger which has inspired the scientific quest for an integral definition grounded in physical principles. While ranging over a wide area, there is a growing confidence in the later 2010s that this essential rooting and explanation is within reach. In this journal, papers come with peer reviews, we note Michael Levin, John O. Campbell, Leot Leydesdorff, and others (14 men). But the whole project might benefit, it seems, from a toning down and clarity of technical terms.

The free-energy principle (FEP) is a formal model of neuronal processes that is widely recognised in neuroscience as a unifying theory of the brain and biobehaviour. More recently, however, it has been extended beyond the brain to explain the dynamics of living systems, and their unique capacity to avoid decay. The aim of this review is to synthesise these advances with a meta-theoretical ontology of biological systems called variational neuroethology, which integrates the FEP with Tinbergen's four research questions to explain biological systems across spatial and temporal scales. We exemplify this framework by applying it to Homo sapiens, before translating variational neuroethology into a systematic research heuristic that supplies the biological, cognitive, and social sciences with a computationally tractable guide to discovery. (Abstract)

In other words, an organism does not just encode a model of the world, it is a model of the world – a physical transcription of causal regularities in its eco-niche that has been sculpted by reciprocal interactions between self-organization and selection over time. On the basis of these distinctions, we turn next to defining a fully generalizable ontology for biological systems based on a multiscale free energy formulation, which we call “variational neuroethology.” (5)

Ribeiro, Tiago, et al. Scale-Free Dynamics in Animal Groups and Brain Networks. Frontiers in Systems Neuroscience. January, 2021. Into the 2020s, TR and Dietmar Plenz, NIH Critical Dynamics Group and Dante Chialvo, Universidad Nacional de San Martin, Argentina are able to perceive and delineate strong similarities between these disparate phases. An especial quality is the spontaneous presence of a self-organized criticalities in both active instances. Here then is an excellent instance of our Earthuman acumen just now attaining such a convergent synthesi of universal recurrence in kind.

The collective emergence of order in myriad interactive entities occurs over a vast range of physical and biological systems. Their key feature is an adaptive behavior beyond individual components. This article focuses on recent insights for two seemingly disparate phenomena: flocking in animal groups and neuronal ensembles in the brain. We report upon the spontaneous organization in bird flocks and whole human brain activity utilizing correlation functions and critical dynamics. Scale-free correlation functions capture the collective organization of neuronal avalanches in nonhuman primates and between neurons during visual processing in rodents. We conclude that at or near a phase-transition, neuronal information can propagate in the brain with similar efficiency to the collective adaptive response observed in some animal groups. (Abstract excerpt)

Roehner, Bertrand. Driving Forces in Physical, Biological and Socio-Economic Phenomena. Cambridge: Cambridge University Press, 2007. A University of Paris physicist applies network principles to group bonding and pathologies. Somewhat narrow and technical, it is noted because it opens with the observation that both the widely separated early elemental universe and later Neolithic societies can be seen to form by the same aggregative dynamics.

Root-Bernstein, Robert. A Modular Hierarchy-based Theory of the Chemical Origins of Life Based on Molecular Complementarity. Accounts of Chemical Research. 45/12, 2012. The Michigan State University polymath physiologist stays on message with another exposition about nature’s constant propensity to create and evolve by way of reciprocal mating pairs. With a philosophy PhD with Thomas Kuhn and a postdoc with Jonas Salk, he has made contributions to AIDS and autoimmunity research, along with blending science and the arts. See also his The Ribosome as a Missing Link in the Evolution of Life in the Journal of Theoretical Biology (Online December 2014), and Molecular Complementarity Between Simple, Universal Molecules and Ions with Vic Norris, et al in Biology Direct (9/28, 2014).

Molecular complementarity plays critical roles in the evolution of chemical systems and resolves a significant number of outstanding problems in the emergence of complex systems. All physical and mathematical models of organization within complex systems rely upon nonrandom linkage between components. Molecular complementarity provides a naturally occurring nonrandom linker. More importantly, the formation of hierarchically organized stable modules vastly improves the probability of achieving self-organization, and molecular complementarity provides a mechanism by which hierarchically organized stable modules can form. In sum, I propose that molecular complementarity is ubiquitous in living systems because it provides the physicochemical basis for modular, hierarchical ordering and replication necessary for the evolution of the chemical systems upon which life is based. I conjecture that complementarity more generally is an essential agent that mediates evolution at every level of organization. (Abstract)

Understanding the principles of evolution by modular complementarity suggests mechanism by which natural selection prunes away huge numbers of possibilities to direct evolution toward the increasingly integrated system. This pruning process transforms evolution from a probabilistic near-impossibility into an almost certain consequence of our Earthly chemistry. Complementarity principles may be “scale-free,” applicable to every level of organization from molecular to societal. (2170)

Rosas, Fernando. Quantifying High-Order Interdependencies via Multivariate Extensions of the Mutual Information. Physical Review E. 100/032305, 2019. Imperial College London mathematicians including Henrik Jensen report a technical exercise about ways to perceive and express nature’s emergent, animate scales. A prime feature seems to be an intrinsic synergy between all manner of entities and their informed, cooperative behaviors. A similar motif in musical compositions is offered as an example, indeed a true music and harmony of the spheres, and oour creaturely lives does play. See also Tangled Worldview Model of Opinion Dynamics by this group at arXiv:1901.06372 and Allometric Scaling of Mutual Information in Complex Networks in Entropy (22/206, 2020).

This article introduces a model-agnostic approach to study statistical synergy, a form of emergence in which patterns at large scales are not traceable from lower scales. Our framework leverages various multivariate extensions of Shannon's mutual information, and introduces the O-information as a metric capable of representing synergy- and redundancy-dominated systems. We develop key analytical properties of the O-information, and study how it relates to other metrics of high-order interactions from the statistical mechanics and neuroscience literature. Finally, as a proof of concept, we use the proposed framework to explore the relevance of statistical synergy in Baroque music scores. (Abstract)

A unique opportunity in the era of “big data” is to make use of the abundant data to deepen our understanding of the high-order interdependencies that are at the core of complex systems. Plentiful data is nowadays available about e.g. the orchestrated activity of multiple brain areas, the relationship between various econometric indices, or the interactions between different genes. What allows these systems to be more than the sum of their parts is not in the nature of the parts, but in the structure of their interdependencies. (1)

Synergy: the interaction or cooperation of two or more organizations, substances, or other agents to produce a combined effect greater than the sum of their separate effects.

Saavedra, Serguei, et al. Common Organizing Mechanisms in Ecological and Socio-economic Networks. arXiv:1110.0376. With coauthors Felix Reed-Tsochas and Brian Uzzi, in a paper to appear in World Scientific’s Complex Systems and Interdisciplinary Sciences series, management theorists from Northwestern and Oxford University are able to discern implicate affinities between these disparate natural and human stages. Once again, as if a genetic program in effect, a constant anatomy and physiology accrues at each and every domain.

Previous work (Nature. 457/463, 2009) has shown that species interacting in an ecosystem and actors transacting in an economic context may have notable similarities in behavior. However, the specific mechanism that may underlie similarities in nature and human systems has not been analyzed. Building on stochastic food-web models, we propose a parsimonious bipartite-cooperation model that reproduces the key features of mutualistic networks - degree distribution, nestedness and modularity -- for both ecological networks and socio-economic networks. Our analysis uses two diverse networks: mutually-beneficial interactions between plants and their pollinators, and cooperative economic exchanges between designers and their contractors. We find that these mutualistic networks share a key hierarchical ordering of their members, along with an exponential constraint in the number and type of partners they can cooperate with. The surprising correspondence across mutualistic networks suggests their broadly representativeness and their potential role in the productive organization of exchange systems, both ecological and social. (Abstract)

The study of direct member-to-member interactions have allowed us to find that the structure of ecological and socio-economic networks generated by mutually-beneficial interactions exhibits remarkably similar features. This empirical finding motivates the proposed model for bipartite cooperation, starting from a generalization of the niche model, which can successfully reproduce the overall structure of pollination and NYGI networks using the number of members and the total number of links as the only input parameters. (11)

Sakata, Shuzo and Tetsuo Yamamori. Topological Relationships between Brain and Social Networks. Neural Networks. 20/1, 2007. Cerebral information processing and friendship associations are found to develop and evolve in the same way, which suggests a unified phenomenal basis.

These results also imply the existence of underlying common principles behind the organization of brain and social networks. (12) This analogy between the role of explicit social attitudes in the establishment of social ties and that of molecular functions in the development of neuronal circuits raises an intriguing hypothesis that brain and social networks might contain similar connected structures. (12)

Sales-Pardo, Marta, et al. Extracting the Hierarchical Organization of Complex Systems. Proceedings of the National Academy of Sciences. 104/15224, 2007. From Luis Amaral’s Complex Systems Institute at Northwestern University, a report on progress toward distilling a common, universal structure and dynamics of scale-free webs everywhere. The quote is from a caption.

Hierarchical structure of metabolic networks. (A) global-level affinity matrices and hierarchical trees for the USCD (Univ. Cal. San Diego) reconstruction of the metabolic network of E. coli. The overall organization of the network is similar and independent of the reconstruction used to build the network. (15229)

Salman, Hanna, et al. Universal Protein Fluctuations in Populations of Microorganisms. Physics Review Letters. 108/238105, 2012. Similar to Nacher and Ochiai above, University of Pittsburgh biophysicists detect a common explicate recurrence amongst life’s metabolisms of nature’s ubiquitous lineaments and vitality.

The copy number of any protein fluctuates among cells in a population; characterizing and understanding these fluctuations is a fundamental problem in biophysics. We show here that protein distributions measured under a broad range of biological realizations collapse to a single non-gaussian curve under scaling by the first two moments. Moreover, in all experiments the variance is found to depend quadratically on the mean, showing that a single degree of freedom determines the entire distribution. Our results imply that protein fluctuations do not reflect any specific molecular or cellular mechanism, and suggest that some buffering process masks these details and induces universality. (Abstract)

Sarpeshkar, Rahul. Analog Synthetic Biology. Philosophical Transactions of the Royal Society. Online March, 2014. Nature is not purely digital. While molecules are discrete and digital, all molecular interactions that lead to computation, e.g., association, transformation and dissociation chemical reactions, have a probabilistic analog nature to them. (2) A MIT bioelectrical engineer makes a strong claim that life does not evolve as isolate entities only, rather it is graced by equally real communicative interrelations. Thus a complementarity of analog and digital phase aspects would better distinguish organisms. It is also averred that Digital computation is a subset of analog computation, which we might note is akin to our own brains, especially a woman’s bicameral mind. Such insights and syntheses are then said to provide a better guide for palliative synthetic biology enhancements.

We analyse the pros and cons of analog versus digital computation in living cells. Our analysis is based on fundamental laws of noise in gene and protein expression, which set limits on the energy, time, space, molecular count and part-count resources needed to compute at a given level of precision. We conclude that analog computation is significantly more efficient in its use of resources than deterministic digital computation even at relatively high levels of precision in the cell. Based on this analysis, we conclude that synthetic biology must use analog, collective analog, probabilistic and hybrid analog–digital computational approaches; otherwise, even relatively simple synthetic computations in cells such as addition will exceed energy and molecular-count budgets.

We present schematics for efficiently representing analog DNA–protein computation in cells. Analog electronic flow in subthreshold transistors and analog molecular flux in chemical reactions obey Boltzmann exponential laws of thermodynamics and are described by astoundingly similar logarithmic electrochemical potentials. Therefore, cytomorphic circuits can help to map circuit designs between electronic and biochemical domains. We review recent work that uses positive-feedback linearization circuits to architect wide-dynamic-range logarithmic analog computation in Escherichia coli using three transcription factors, nearly two orders of magnitude more efficient in parts than prior digital implementations. (Abstract)

Schack, Carolann, et al. Modularity is the Mother of Invention: A Review of Polymorphism in Bryozoans. Biological Reviews. Online November, 2018. Victoria University of Wellington, New Zealand biologists post a 35 page study of how pervasive nature’s evolutionary and biological employ of semi-autonomous modular units within larger assemblies such as bodies and brains actually is. Some two decades after their initial view by Gunter Wagner and others, this efficient structural composition, famously noted by Herbert Simon (search) in the 1960s, can now be well affirmed across the Metazoan lineages.

Modularity is a fundamental concept in biology. Most taxa within the colonial invertebrate phylum Bryozoa have achieved division of labour through the development of specialized modules (polymorphs), and this group is well exemplifies this phenomenon. We provide a comprehensive description of the diversity, morphology and function of these polymorphs and the significance of modularity to the evolutionary success of the phylum, which has >21000 described fossil and living species. Modular diversity likely arose from heterogeneous microenvironmental conditions, and repeated module clusters are an emergent property of zooid plasticity. (Abstract excerpt)

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