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

4. Universality Affirmations: A Critical Complementarity

Ossandon, Sebastian, et al. Neural Network Approach for the Calculation of Potential Coefficients in Quantum Mechanics. Computer Physics Communications. 214/31, 2017. We note this paper by Chilean scientists in Valparaiso, Santiago, and Chillan as an instance of 2017 integrative frontiers as cerebral dynamics gain an iconic utility and application from human to universe. In this instance, they serve to quantify quantum phenomena, as also for chemical, genetic, behavioral, and evolutionary realms. What might all this infer and portend, we wonder in April 2017, with everything so amenable to a neural, brainy essence? Who are we phenomenal interlocutors as if a procreative cosmos trying to accomplish its own self-cognizance?

A numerical method based on artificial neural networks is used to solve the inverse Schrödinger equation for a multi-parameter class of potentials. First, the finite element method was used to solve repeatedly the direct problem for different parametrizations of the chosen potential function. Then, using the attainable eigenvalues as a training set of the direct radial basis neural network a map of new eigenvalues was obtained. This relationship was later inverted and refined by training an inverse radial basis neural network, allowing the calculation of the unknown parameters and therefore estimating the potential function. Three numerical examples are presented in order to prove the effectiveness of the method. The results show that the method proposed has the advantage to use less computational resources without a significant accuracy loss. (Abstract)

Parastesh, Fatemeh, et al. Chimeras. Physics Reports. October, 2020. Amirkabir University of Technology, University of Western Australia, Northwestern Polytechnical University, Xi’an, China. CNR Institute of Complex Systems, Fiorentino, Italy (Stefano Boccaletti), and University of Maribor, Slovenia (Matjaz Perc) system theorists post a major 80 page, 324 reference review about this recently recognized condition. While its name is taken from organisms with a double genome, here it stands for a complex dynamism which actively resides in more or less orderly or coherent modes at the same time. The paper covers various occasions such as chemical or neural, their network topologies, and more. The import in later 2020 is to add a major explication that natural phenomena everywhere seeks and prefers a “middle way golden balance” optimum poise.

Chimeras are this year coming of age since they were first observed by Kuramoto and Battogtokh in 2002. What started as an observation of a coexistence of synchronized and desynchronized states turned out to be an important new paradigm of nonlinear dynamics at the interface of physical and life sciences. Here we present a major review of chimeras, dedicated to all aspects of their theoretical and practical existence. We cover different dynamical systems in which they have been observed along with network structure for the emergence of chimeras. (Abstract)

Pavithran, Induja, et al. Universality in Spectral Condensation. Nature Scientific Reports. 10/17405, 2020. As the Abstract says, by an advanced technical finesse nine scientists from the Indian Institute of Technology, Madras, UC San Diego, and the Potsdam Institute for Climate Impact Research including Jurgen Kurths uncover a constant presence of this manifest physical phenomena. The article number means that it is amongst thousands each year, millions more if eprint sites are added. Whenever might we be able to perceive our worldwise endeavor as a vital work of ecosmic self-quantification and ultimate discovery?

Self-organization is the spontaneous formation of spatial, temporal, or spatiotemporal patterns in complex systems far from equilibrium. During such self-organization, energy distributed in a broadband of frequencies gets condensed into a dominant mode, analogous to a condensation phenomenon. We call this phenomenon spectral condensation and study its occurrence in fluid mechanical, optical and electronic systems. We define a set of spectral measures to quantify this condensation spanning several dynamical systems. Further, we uncover an inverse power law behaviour of spectral measures with the power corresponding to the dominant peak in the power spectrum in all the aforementioned systems. (Abstract)

Persi, Erez, et al. Criticality in Tumor Evolution and Clinical Outcome. Proceedings of the National Academy of Sciences. 115/E11101, 2018. University of Maryland and National Center for Biotechnology Information researchers including Yuri Wolf and Eugene Koonin report findings across a wide range of cancer cases that a complex generative dynamics is in effect which arrays as a critically poised state. It is said that appreciations of this common tendency could well aid diagnostics and treatment.

How mutation and selection determine the fitness landscape of tumors and hence clinical outcome is an open fundamental question in cancer biology, crucial for the assessment of therapeutic strategies and resistance to treatment. Here we explore the mutation-selection phase diagram of 6,721 tumors representing 23 cancer types by quantifying the overall somatic point mutation load (ML) and selection (dN/dS) in the entire proteome of each tumor. We show that ML strongly correlates with patient survival, revealing two opposing regimes around a critical point. In low-ML cancers, a high number of mutations indicates poor prognosis, whereas high-ML cancers show the opposite trend, presumably due to mutational meltdown. (Abstract excerpt)

Peruzzo, Fabio, et al. Spatial Patterns Emerging from a Stochastic Process near Criticality. arXiv:1907.08852. Into the year 2019, University of Leeds mathematicians including Sandro Azaele (search), draw upon a wealth of 21st century science so as to assert that living systems across every natural and social phase can be seen to seek and reach a preferred state of critical balance. As many other entries prove, this finding bodes well for a discovery of the universal complex recurrence of a dynamic complementarity. This constant phenomena arises from “nonlinearities of interacting agents,” that is nodal, particulate entities and relational, wave-like links, which are rooted in the physical cosmos, as it come to life again.

There is mounting empirical evidence that many communities of living organisms display key features which closely resemble those of physical systems at criticality. We here introduce a model framework for the dynamics of a community of individuals which undergoes local birth-death, immigration and local jumps on a regular lattice. We study these properties when the system is close to its critical point. Within a physically relevant regime dominated by fluctuations, it is possible to calculate analytically the probability density function of the number of individuals living in a given volume, which captures the close-to-critical behavior of the community across spatial scales. We discuss how this model in the critical-like regime is in agreement with several biodiversity patterns observed in tropical rain forests. (Abstract)

Plenz, Dietmar, et al. Self-Organized Criticality in the Brain. . . Into the 2020s, National Institute of Mental Health, Critical Brain Dynamics Section (D. Plenz director, search) neuroscientists report on a decade and more of convergent research findings which now have reached a proven validity that human cerebral activity does indeed seek and reside at an optimum dynamic poise. In respect, one more robust exemplar, on the way to an invariant universality, is achieved by virtue of our own microcosmic cognizance. The paper also appears in Frontiers in Physics for July 2021.

Self-organized criticality (SOC) refers to the ability of complex systems to evolve towards a phase transition at which interactions between system components lead to scale-invariant events beneficial for overall performance. For the last two decades, considerable experimental evidence has accumulated that the mammalian cortex with its diversity in cell types, interconnectivity, and plasticity might exhibit SOC. Here we review experimental findings of isolated, layered cortex preparations to self-organize towards the four dynamical motifs of up-states, oscillations, neuronal avalanches, and coherence potentials. The precise interaction between up-states, nested oscillations and avalanches in layered cortex provides compelling evidence for SOC in the brain. (Abstract excerpt)

Poirot, Olivier and Youri Timsit. Neuron-Like Networks between Ribsomal Proteins within the Ribosome. Nature Scientific Reports. 6/26485, 2016. We report this entry by Information Génomique et Structurale CNRS, Aix-Marseille Université researchers as an example of the 2016 historic synthesis in our global collaborative midst. At once, it shows how the archetypal scale-free networks found from cosmic webs to literary classics also appears in protein phenomena. This iconic universality is then seen as akin to neural net node and link informational activities.

The Ribosome is a minute particle consisting of RNA and associated proteins, found in large numbers in the cytoplasm of living cells. They bind messenger RNA and transfer RNA to synthesize polypeptides and proteins.

From brain to the World Wide Web, information-processing networks share common scale invariant properties. Here, we reveal the existence of neural-like networks at a molecular scale within the ribosome. We show that with their extensions, ribosomal proteins form complex assortative interaction networks through which they communicate through tiny interfaces. The analysis of the crystal structures of 50S eubacterial particles reveals that most of these interfaces involve key phylogenetically conserved residues. The systematic observation of interactions between basic and aromatic amino acids at the interfaces and along the extension provides new structural insights that may contribute to decipher the molecular mechanisms of signal transmission within or between the ribosomal proteins.

Similar to neurons interacting through “molecular synapses”, ribosomal proteins form a network that suggest an analogy with a simple molecular brain in which the “sensory-proteins” innervate the functional ribosomal sites, while the “inter-proteins” interconnect them into circuits suitable to process the information flow that circulates during protein synthesis. It is likely that these circuits have evolved to coordinate both the complex macromolecular motions and the binding of the multiple factors during translation. This opens new perspectives on nanoscale information transfer and processing. (Abstract)

Qian, Xiao-Feng, et al. Bohr’s Complementarity: Completed with Entanglement. arXiv:1803.04611. University of Rochester physicists X-F Qian, A. Vamivakas, and Joseph Eberly arrive at a current mathematical resolve by way of a triune synthesis of mutual exclusivity and an integral composite. Octogenarian Eberly has been a lifetime theorist for optical quantum phenomena. See also Shifting the Quantum-Classical Boundary by this team in Optica (2/7, 2015).

Ninety years ago in 1927 at an international congress in Como, Italy, Niels Bohr gave an address which is recognized as the first instance in which the term "complementarity" was spoken publicly. Bohr had accepted duality as a principle of physics: close observation of any quantum object will reveal either wave-like or particle-like behavior, one or the other of two fundamental and complementary features. Some confusion followed his talk and complementarity has seen much discussion since but the concept retains a central place in quantum mechanics. Scholarly examinations provide speculations about the relevance of complementarity in fields as different from physics as biology, psychology and social anthropology. In regard, recent approaches by our group and others seem to show that entanglement is the ingredient needed to complete Bohr's formulation. (Abstract edits)

Reina, Andreagiovanni, et al. Psychophysical Laws and the Superorganism. Nature Scientific Reports. 8/4387, 2018. As a good instance for this section, University of Sheffield and ISTC, Italian National Research Council computational psychologists discern a consistence recurrence in kind across a wide array of creaturely phyla. Furthermore, a similar correspondence holds for both somatic physiologies and cerebral functions. By these lights, a common evolutionary track of individual organisms into viable communal forms becomes evident, as enhanced by intelligent capacities.

A large number of organisms at diverse levels of biological complexity, from humans to unicellular moulds, obey the same psychophysical laws that characterise the relationship between stimuli and the organism’s response. This study shows for the first time that groups of individuals, in our case honeybee colonies, considered as a single superorganism, might also be able to obey the same laws. Similarly to neurons, no individual explicitly encodes in its simple actions the dynamics determining the psychophysical laws; instead it is the group as a whole that displays such dynamics. The observed similarities in stimuli response between brain and superorganism motivate further investigations of collective behaviour through the lens of cognitive science and psychology. Research synergies between neuroscience and collective intelligence studies can highlight analogies that could
help better to understand both systems. (5)

Rocha, Rodrigo, et al. Homeostatic Plasticity and Emergence of Functional Networks in a Whole-Brain Model at Criticality. Nature Scientific Reports. 8/15682, 2018. After a decade of theory and test, University of Padova. Italy biophysicists including Samir Suweis and Amos Maritan contribute to current conclusions that dynamic cerebral network cognition does indeed reside in a self-organized, critically balanced state between control and creativity. See also Life at the Edge: Complexity and Criticality in Biological Function by Dante Chialvo at arXiv:1810.11737.

Understanding the relationship between large-scale structural and functional brain networks remains a crucial issue in modern neuroscience. Recently, there has been growing interest in investigating the role of homeostatic plasticity mechanisms in regulating network activity and brain functioning against a wide range of environmental conditions and brain states. In the present study, we investigate how the inclusion of homeostatic plasticity in a stochastic whole-brain model, implemented as a normalization of the incoming node’s excitatory input, affects the macroscopic activity during rest and the formation of functional networks. In this work, we show that normalization of the node’s excitatory input improves the correspondence between simulated neural patterns of the model and various brain functional data. Our results suggest that the inclusion of homeostatic principles lead to more realistic brain activity consistent with the hallmarks of criticality. (Abstract)

The emerging hypothesis is that living systems like the brain are spontaneously driven close to a critical phase transition thus conferring upon them the emergent features of critical systems. These characteristics would translate into the ability of the brain, through a large spatial and temporal scale activity, to promptly react to external stimuli by generating a coordinated global behavior, to maximize information transmission, sensitivity to sensory stimuli and storage of information. These ideas have been investigated in the last fifteen years in neuroscience and the hypothesis that the brain is poised near a critical state is gaining consensus. In brain systems, the concept of criticality is mainly supported by the following two experimental findings: the discovery of scale-free neural avalanches, as described by power-law distributions for the size and duration of the spontaneous bursts of activity in the cortex; and the presence of long-range temporal correlations in the amplitude fluctuations of neural oscillation. (2)

Roli, Andrea, et al. Dynamical Criticality. Journal of Systems Science and Complexity. 31/3, 2018. In this Springer journal, University of Bologna, University of Modena, and European Centre for Living Technology researchers including Marco Villani (search for more papers) contribute to realizations that nature’s persistently seems to seek and balance at an optimum complementary state between reliable stability and free creativity. See also Concepts in Boolean Network Modeling by Julian Schwab, et al (2020) in Universal Principles.

Systems that exhibit complex behaviours are often found in a particular dynamical condition, poised between order and disorder. This observation is at the core of the so-called criticality hypothesis, which states that systems in this dynamical regime attain the highest level of computational capabilities and achieve an optimal trade-off between robustness and flexibility. Recent results in cellular and evolutionary biology, neuroscience and computer science have strengthened the criticality hypothesis, and its role as a candidate general law in adaptive complex systems. We provide an overview of the works on dynamical criticality that are, to the best of our knowledge, particularly relevant for the criticality hypothesis, such as dynamics and information processing at the edge of chaos. In regard, we illustrate the main achievements in the study of critical dynamics in biological systems. (Abstract edits)

Rulands, Steffen, et al. Universality of Clone Dynamics during Tissue Development. Nature Physics. 14/5, 2018. We recall hardly a decade ago when cellular self-organization was just a glimmer. For this ten person team from Cambridge University and the Free University of Brussels, it has become a tacit, intrinsic paradigm of creative effect across life’s developmental physiology., to which they contribute. In regard, systemic tendencies to reach a critical poise are reported, akin to other fields such as neuroscience, which are then traced to condensed matter physical energies. The entry can stand as iconic evidence for an imminent 21st century consonant genesis synthesis.

The emergence of complex organs is driven by the coordinated proliferation, migration and differentiation of precursor cells. The fate behaviour of these cells is reflected in the time evolution of their progeny, termed clones, which serve as a key experimental observable. But what can be learnt from clonal dynamics in development, where the spatial cohesiveness of clones is impaired by tissue deformations during tissue growth? Drawing on the results of clonal tracing studies, we show that, despite the complexity of organ development, clonal dynamics may converge to a critical state characterized by universal scaling behaviour of clone sizes. Our study shows the emergence of core concepts of statistical physics in an unexpected context, identifying cellular systems as a laboratory to study non-equilibrium statistical physics. (Abstract)

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