VI. Earth Life Emergence: Development of Body, Brain, Selves and Societies
A. A Survey of Common Principles
Picoli, S., et al. Scale-Invariant Structure of Size Fluctuations in Plants. Scientific Reports. 2/Article 328, 2012. Universidade Estadual de Maringá, Brazil, physicists untangle nature’s floral profusion by way of complex systems science to lately decipher this recurrent, recursive, “analogy of proper proportion” (Aquinas) scripture. See also Picoli and Mendes in Religion and Science.
A wide range of physical and biological systems exhibit complex behaviours characterised by a scale-invariant structure of the fluctuations in their output signals. In the context of plant populations, scaling relationships are typically allometric. In this study, we analysed spatial variation in the size of maize plants (Zea Mays L.) grown in agricultural plots at constant densities and found evidence of scaling in the size fluctuations of plants. The findings indicate that the scaling of the probability distribution of spatial size fluctuation exhibits non-Gaussian behaviour compatible with a Lévy stable process. The scaling relationships were observed for spatial scales spanning three orders of magnitude. These findings should provide additional information for the selection and development of empirically accurate models of pattern formation in plant populations.
Potirakis, Stelios, et al. Dynamical Analogy between Economical Crisis and Earthquake Dynamics within the Nonextensive Statistical Mechanics Framework. Physica A. Online February, 2013. University of Athens physicists drawn upon these thermodynamic theories of Constantino Tsallis to discern across disparate realms the presence of deep similarities, which are extended to seizures, magnetic storms and solar flares. So are we closing on a great historic realization, as other ages and cultures long aver, of an infinitely recurrent natural creation which so springs as if by universally applicable, genetic-like code. See also in regard “The Earth as a Living Planet” at arXiv:1210.4804 (October 2012) by Y. Contoyiannis, with Potirakis, whence more analogies are noted between geological criticalities and human physiology.
The field of study of complex systems considers that the dynamics of complex systems are founded on universal principles that may be used to describe a great variety of scientific and technological approaches of different types of natural, artificial, and social systems. Several authors have suggested that earthquake dynamics and the dynamics of economic (financial) systems can be analyzed within similar mathematical frameworks. We apply concepts of the nonextensive statistical physics, on time-series data of observable manifestations of the underlying complex processes ending up to these different extreme events, in order to support the suggestion that a dynamical analogy exists between a financial crisis (in the form of share or index price collapse) and a single earthquake. (Abstract)
Proekt, Alex, et al. Scale Invariance in the Dynamics of Spontaneous Behavior. Proceedings of the National Academy of Sciences. 109/10564, 2012. Physician Proekt, physicists Jayanth Banavar and Amos Martin, and neurobiologist Donald Pfaff, find animal activities to exhibit the same nested recurrence of self-organized phenomena as everywhere else in nature and society, as this site documents, from galaxies to genomes, brains, language, and our noosphere.
Typically one expects that the intervals between consecutive occurrences of a particular behavior will have a characteristic time scale around which most observations are centered. Surprisingly, the timing of many diverse behaviors from human communication to animal foraging form complex self-similar temporal patterns reproduced on multiple time scales. We present a general framework for understanding how such scale invariance may arise in nonequilibrium systems, including those that regulate mammalian behaviors. Our analyses reveal that the specifics of the distribution of resources or competition among several tasks are not essential for the expression of scale-free dynamics. Rather, we show that scale invariance observed in the dynamics of behavior can arise from the dynamics intrinsic to the brain. (Abstract)
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)
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)
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)
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)
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)