I. Our Planatural Edition: A 21st Century PhiloSophia, Earthropo Ecosmic PediaVersion

C. An Earthumanity Era: A 2020s Cerebral Cyberspace Achieves a Worldwise Knowsphere Resource

Shettigar, Nandan, et al. On the Biophysicsl Complexity of Brain Dynamics. Dynamics. 2/2, 2022. Texas A & M University bioengineers led by Steve Suh (see website) post a 35 page, 245 reference latest review of our human cerebral faculty as it has now become quantified and understood by way of network multiplex topologies, information process capacities and a preferred self-organized criticality. A typical topic is Complex Global Multimodal Synchronization from Local Nonlinear Interactions. As the quotes allude, two decades into the 21st century, our personal cognitive endowment is found to organize itself so as to think and learn in a wild world. In regard, our emergent acumen (as well as our own selves) can be appreciated as an iconic exemplar of the whole genesis ecosmos from which it arose from.

By this stratified witness the same neural cognizance could be seen in effect as a global sapiensphere may just come to her/his own knowledge. For a current 2022 discovery event section, we pair this entry with Self-Organized Critical Dynamics as a Key to Fundamental Features of Complexity in Physical, Biological and Social Networks by B. Tadic and R. Melnik (herein) as prime, quantitative examples in our urgent midst.

The human brain is a complex network ensemble of the cumulative interactions of its cellular components by way of nonlinear multicellular higher-order collaborations. Thus, as a statistical physical system, complex global emergent network behaviors are produced which enable the highly dynamical, adaptive, and efficient response of a macroscopic brain network. These effects emerge in local synchronized clusters which altogether form a collective organization with hierarchical and self-similar structures. Here, we will provide an overview perspective from a biological and physical complex network basis along with their exemplary presence in all manner of cerebral forms and functions. and how these operate within the physical constraints of nature. (Abstract excerpt)

Thus, the brain can be conceptualized as a complex information processing unit, molding its neural physiology as an analog neural network. Processing information through a medium of intricately coupled local action potential interactions, neural circuitry orchestrates interactions across the hierarchical scales of the brain, which combine individual action into collective group order. The latter is typically seen in overall brain activities and behaviors and can be quantified by multiphase, multiscale structures. (19)

The brain refines a finite number of network configurations using a canonical, self-similar pattern and structure across its temporal and spatial scales. This directly corresponds to the statistically self-similar fractal nature of the brain. Self-similarity across the multivariate scales of the brain is therefore essential in supporting efficient dynamical transitions by directing chaotic bifurcations in its own hierarchical structure to effectively filter information throughout the scales of the brain while conserving resources through a self-similar organization. (26)

Global neural activity is not random but highly ordered due to hierarchical structures. Their recursive implementation from the micro to macro scales allows the brain to produce complex information representations via neural dynamics so to enable performan a wide range of activities. These forms entail self-similarity so to optimize energy consumption and maintain a balance between stable and flexible states. Moving towards a more general step, effectively administering control of the complexity present in the brain can also provide insights towards the nature of complexity in our universe. (27)

Sormunen, Silja, et al. Critical Drift in a Neuro-Inspired Adaptive Network. arXiv:2206.10315. After some years of worldwide study, SS and Jari Saramaki, Aalto University, Finland, along with Thilo Gross, University of Oldenburg, Germany agree, that cerebral activities do in fact seek and reside at a preferred self-organized poise. As the Abstract notes, it is now time to consider and explore the full operational, cognitive presence of this optimum feature. Our Universal Genesis view in mid 2022 might then report similar realizations from astrophysical realms to bicameral societies. A glimpse of an intrinsic self-organized criticality, aka nature’s complementary sweet spot, could begin to grace and advise these traumatic times.

It has been postulated that the brain operates in a self-organized critical state that brings multiple benefits, such as optimal sensitivity to input. Thus far, self-organized criticality has been depicted as a one-dimensional process, mainly with a single parameter tuned to a critical value. However, the number of adjustable facets in the brain is vast, and hence critical states can occupy a high-dimensional manifold inside a high-dimensional parameter space. Here, we show that adaptation rules inspired by homeostatic plasticity drive a neuro-inspired network to drift on a critical manifold, poised between inactivity and persistent activity. During the occasion, global network parameters continue to change while the system remains at criticality. (Abstract)

Tadic, Bosiljka and Roderick Melnik. Self-Organized Critical Dynamics as a Key to Fundamental Features of Complexity in Physical, Biological and Social Networks. Dynamics. 2/2, 2022. Senior theorists in Solvenia and Canada (see bio’s below and home websites) provide a select, consummate survey of 21st century worldwise multiplex non-equilibrium system studies as they may reach their current convergent, integrative syntheses across every spatial and temporal, uniVerse to humanVerse, domain. We pair the entry with On the Biological Complexity of Brain Dynamics by N. Shettigar, et al in this issue so as prime instances of a epochal discovery event in our midst. Herein the emphasis is on novel findings about nature’s consistent propensity to seek and reside at an optimum mid-point balance between more or less relative coherence. The paper reviews technical attributes such as self-similarity, power laws, multifractal landscapes, simplicial networks, collective behaviors and all else. As one reads along, the text reiterates the cerebral descriptions in the other paper. That is to say, our Earthropocene sapience, as it learns and thinks on its own, can has well found and defined the presence of a familial genetic-like code which universally recurs in kind everywhere.

Studies of many complex systems have revealed new collective behaviours that emerge through the mechanisms of self-organised critical fluctuations. These collective states with long-range spatial and temporal correlations often arise from an external dynamic drive with an intrinsic nonlinearity and geometric interactions. The self-similarity of critical fluctuations enables us to describe natural systems using fewer parameters and universal functions that can then simplify the computational and information complexity. Current research on self-organised critical systems across many scales strives to formulate a unifying mathematical framework by way of critical universal properties in information theory. Through physical, biological, and social network exemplars, we show how a constant self-organised criticality occurs at the interplay of the complex topology and driving mode. (Abstract excerpt)

This feature article has two goals. Firstly, we give a brief survey of a diversity of current research trends of SOC systems across different scales and types of interactions. Secondly, we present new results on the field-driven spin dynamics in complex nano-networks, an appearing prominent example of SOC behaviour induced by the substrate’s geometry. Using several representative examples of SOC systems of different nature and interaction patterns, we highlight some fundamental aspects of the dynamic complexity. (3)

The SOC occurs in many complex systems and networks at various scales, types of interactions, and intrinsic dynamics. They all obey some universal behaviours that can be captured by the properties of the emergent critical states. These are the long-range correlations, fractality, avalanching dynamics and scale invariance. It has been understood that these properties of the critical states can provide a deeper understanding of different aspects of complexity. In particular, recent research on various SPA models and real-world systems strives to underpin self-organised critical behaviour in the mechanisms underlying the emergence of new collective features, essential for the physical and biological complexity. They also provide a more transparent structure of information stored in the critical state and reduced computational complexity. In the context of complexity, understanding the role of various geometrical constraints in the critical dynamics and hidden geometry features that enable competing interactions at different scales are of paramount importance. (13-14)

Bosiljka Tadic is a theoretical physicist at the Jozef Stefan Institute, Ljubljana who researches the intrinsic nature of complex systems and networks. Her studies involve the statistical physics of cooperative phenomena from functional brain networks to emotional behaviors in Internet societies. In regard, she has published over 120 technical papers.

Roderick Melnik is internationally regarded for his work in applied mathematics, and numerical analysis and a Canada Research Chair in Mathematical Modeling and Professor at Wilfrid Laurier University. He was born in the Ukraine and earned his doctorate at the National University of Kyiv. (I was unaware of his bio as I chose to highlight the paper, which is so appropriate for this knowledge vs. madness moment.)

Teuscher, Christof. Revisiting the Edge of Chaos: Again?.. Biosystems. May, 2022. The veteran Portland State University systems theorist looks back over the course of this perception all the way to Stuart Kauffman’s autocatalysis whereof life prefers to seek and reside at an active poise between more or less order. Albeit along the way there were doubts, problems and variations, but it can indeed once more be affirmed that this optimum balance does seem to be in prevalent effect across much natural and social phenomena. Which into 2022, with L. da Costa and myriad other confirmations, would constitute an epochal, salutary discovery.

Does biological computation happen at some sort of “edge of chaos”, a dynamical regime somewhere between order and chaos? And if so, is this a fundamental principle that underlies self-organization, evolution, and complex natural and artificial systems that are subjected to adaptation? In this article, we will review the literature on the fundamental principles of computation in natural and artificial systems at the “edge of chaos”. The term was coined by Norman Packard in the late 1980s. Since then, the concept of “adaptation to the edge of chaos” was demonstrated and investigated in many fields where both simple and complex systems receive some sort of feedback. Besides reviewing both historic and recent literature, we will also review critical voices of the concept. (Excerpt)

Tononi, Giulio, et al.. Only What Exists can Cause: An Intrinsic View of Free Will. arXiv:2206.02069. premier team of GT, Larissa Albantakis, Chiara Cirelli, and Melanie Boly, University of Wisconsin, along with Christof Koch, Allen Institute for Brain Science continue to advance this Integrated Information Theory view as it gains a popular validity. In regard, a table of Axioms: the essential properties of phenomenal existence by way of Intrinsicality, Composition, Information, and Exclusion is entered. A table of Postulates: physical existence then shows how the same qualities can be traced to a deep natural basis. As this section reports, since circa 2008 these developments seem to well define a parallel ascent of informed complexity and knowing consciousness.

This essay addresses the implications of integrated information theory (IIT) for free will. IIT is about what consciousness is and how it occurs. According to IIT, the presence of aware sentience is accounted for by a maximum of cause-effect power in the brain. Thus the way specific experiences feel is due to how that cause-effect power is structured. If IIT is right, we do have free will in the fundamental sense: we have real alternatives, we make decisions, and we - not our neurons or atoms - are the cause of willed actions responsibilities. IIT's claim of true free will is based on the proper understanding of consciousness drawn from its intrinsic powers ontology: what truly exists, in physical terms, are intrinsic entities. (Abstract)

Udrescu, Silviu-Marian, et al. AI Feynman 2.0: Pareto Optimal Symbolic Regression Exploiting Graph Modularity. arXiv:2006,10762. MIT and Stanford physicists including Max Tegmark conceive and employ further effective techniques that can inform and serve this global computational ascent.

We present an improved method for symbolic regression that seeks to fit data to formulas that are Pareto-optimal and have the best accuracy for a given complexity. We develop a method for discovering generalized symmetries (arbitrary modularity in the computational graph of a formula) from gradient properties of a neural network fit. We use normalizing flows to generalize and aid probability distributions for which we only have samples, along with statistical hypothesis testing. (Excerpt)

Van der Kolk,, Jasper, et al. Emergence of Geometric Turing Patterns in Complex Networks. arXiv:2211.11311. In November 2022, five Spanish systems theorists including Angeles Serrano and Marian Boguna post an extensive study about how various spatial topologies and shape-shiftings can lead to a wide array of morphogenetic effects across physical, biological and neural phenomena. A further deep affirmation of nature’s invariant, connective vitalities is evidently achieved, once more to prove the independent, ubiquitous presence in kind of these genotype-like mathematics. See also Network Geometry at (2001.03241) and Network Cosmology (1310.6272) by this collegial group.

The Turing instability due competing species of diffusive particles is an important framework for describing non-equilibrium self-organization across chemical and biological systems. These patterns have recently been observed in large complex networks with scale-free degree distributions and the small world property. In this work we study geometric random graph models, where the network topology arises from the fact that nodes live in an underlying similarity space. These results indicate that there is a profound connection between network functions and its hidden reaction-diffusion processes. (Excerpt)

Vujovic, Filip, et al. Cellular Self-Organization: An Overdrive in Cambrian Diversity? BioEssays. July, 2022. University of Sydney system biophysicians contribute another frontier perception of life’s evolutionary motive occasion as more primarily due to these mathematic procreative agencies, rather than post-selection alone. Their certain subject area is this profuse emergence some 540 mys ago. Some sections are Self-Organization: A Decentralized Algorithm to Transform Chaos into Predictability, Self-Organization and Emergence of Morphological Patterns and Emergence of Form and Function in Cellular Self-Organization. Along with 135 references, graphic displays show how this deep drive (natural genesis) provides a formative, organismic effect prior to selection.

See also The Phanerozoic Aftermath of the Cambrian Information Revolution by Shannon Hsieh, et al in Paleobiology, (48/3, 2022) about a concurrent cerebral and cognitive florescence within this expansive era and Self-Organization as a New Paradigm in Evolutionary Biology, Anne Malasse, ed., for a 2022 book-length report of life’s innate creative source. (See V. Evolution for more.)

Webb, Richard, ed. Consciousness. New Scientist Essential Guide. Volume 12, 2022. The British science writer achieves a wide-ranging, update survey and synthesis as an Earthuman acumen presently traces and fills in a long continuity from an ecosmic realm to our nascent awakenings. Six sections - What is Consciousness, Conscious Minds, Your Conscious Self, Sleep and Dreaming, Altered States, and Consciousness and Reality – span vital aspects that they involve. A deeply physical rooting for knowing sentience is braced by vignettes of and essays by leading players such as David Chalmers, Christof Koch, Anil Seth, David Bor (Consciousness is About Combining Information) and others.

Throughout my quest (Christof Koch) to understand consciousness, have never lost sense of living in a magical universe. I do believe that some deep and organizing principle created the universe and set it in motion with a purpose. A pioneering generation of stars had to die in a spectacular supernova to seed space with the heavier elements needed for the rise of self-replicating chemicals on a rocky planet orbiting a young star at just the right distance. The competitive pressures of natural selection led to the accession of creatures with nervous systems. As their complexity grew to huge proportions, some of the entities evolved the ability to reflect on themselves, and to contemplate their beautiful but cruel world. But I do believe that the laws of physics favored the emergence of consciousness, and that these laws will lead us to a complete knowledge of it.

wood, Charlie. Starfish Whisperer Develops a Physical Language of Life. Quanta. January 11, 2023. A science writer provides a cogent profile of Nikta Fakhri, an award-winning Iranian-American MIT biophysicist, as she adapts and extends a conceptual physics basis as a deeper rooting to better describe how tiny active biological components proceed to give rise to living organisms. A MIT press release notes that her findings reveal “’Starfish embryos to swim in formation like a “living crystal.” Some collegial papers by Fakhri are A Hierarchy of Protein Patterns Robustly Decodes Cell Shape Information by Manon Wigbers, et al in Nature Physics (17/578, 2021) and Odd Dynamics of Living Chiral Crystals by Tan, Tzer Han Tan, et al in Nature (607/287, 2022).

In her work to learn how biological phenomena produces the hugely complex business of living, Fakhri turned to physics — a field that’s adept at linking microscopic and macroscopic phases. Physicists have learned that temperature emerges from the motions of molecules, magnetism from the orientations of atoms, and superconductivity from paired electrons. Perhaps life, too, can be elegantly described as a property that can emerge under the right circumstances. From starfish embryos, she notes that, like other states of matter, life “breaks symmetry” — the growth of an embryo from its past to its future.

Biology is a field that’s much defined by its molecules. Physics takes a somewhat different view and tries to explain things across various scales, from the very small to the very large, using a sort of universal language. In the case of life, we would like to know: How do you go from energy dissipation at a single-particle level all the way up to a flock of birds? In the past, physics has shown that this approach of trying to understand a unit as more than the sum of its parts is at the heart of many complex phenomena. I am optimistic that physical rules may allow us to understand what might be the ultimate complexity in the world.

Wuppuluri, Shyam and Ian Stewart, eds. Electrons to Elephants to Elections. International: Springer Frontiers, 2022. An Indian editorial philosopher and and the British mathematician and author here gather and arrange some 45 chapters so as to illustrate and flesh out that from our late vantage nature’s evident course from universe to human can be as some manner of emergence. This broad theme unites essays from physical and biological to personal and social phases. whereby we need take leave of a bottomed-out reduction method. The entries variously agree on a scalar, recurrent hierarchy which frames an oriented ascent from quantum realms through life’s long, sentient evolution onto cultural behaviors. By this view, some manner of self-similar recurrence in sequential kind can be perceived. A paper which richly evinced was Shared Mathematical Content in the Context of Complex Systems by the Jacobs University physicist Hildegard Meyer-Ortmanns (search), whose Abstract is next. Overall, these intellectual endeavors do seem closer to an encoded natural genesis of complexity, awareness and persons.

We pursue reduction to mathematics rather than materiality which seems more likely to underlie universal phenomena in different contexts. We illustrate with examples of increasing complexity. Firstly, by way of a set of differential equations which apply to pattern formation in biology and to classical mechanics. We then refer to the asymptotics of singular behavior at criticality between various substances. Thirdly, a set of stochastic reactions gives rise to emergent ecological phenomena which corresponds to a transition from species coexistence to extinction.. The fourth case is about Tracy-Widom probability distributions which observes universality classes in wide occurrence. (H. Meyer-Ortmanns excerpt)

Yang, Vicky Chuqiao, et al. Scaling and the Universality of Function Diversity across Human Organizations. arXiv:2208.06487. Senior system theorists VCY, MIT, Christopher Kempes, Geoffrey West, Sidney Redner, Santa Fe Institute and Hyejin Youn, Northwestern University (search each) continue to study and quantify our diverse array of social modern institutions from companies to colleges so as here to make a strong case for a commonly recurrent patterns and processes, an urban universality. A constant theme is that these diverse groupings can have cognitive abilities and achievements beyond individual members. In regard, the basic Natural Genesis premise from its early 2000s origins is that a emergent personsphere transition has become able to learn, think and gain revolutionary knowledge on her/his own. See also Worldwide Scaling of Waste Generation in Urban Systems by this team at 2208.07917.

Function diversity, namely the range of tasks individuals can perform, is essential to productive organizations. This concept has often been studied, but general patterns and mechanisms remain unclear. Here, we analyze over five thousand organizations such as US federal agencies, Norwegian companies, and US universities, and find that the number of distinct functions scales with their size as a power law with an exponent of 1/2. Further, we find common patterns in the distribution of function abundance within organizations. Thus we can observe and report an evident universality whereby human organizations share common features. for creating specializations. (Excerpt)

Human organizations allow a group of individuals to accomplish what disconnected individuals cannot. Function diversity reflects the skills and abilities that are brought together in these groups. Our finding suggests that for top-down organizations, often governed by specified goals and objectives, such as government agencies, companies, and universities, there is a common scaling relationship between the function diversity and organization size, namely, a power law with exponent close to 1/2. This empirical observation implies that a critical size is required to sustain a given level of function diversity in an organization. (9)

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