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

4. Universality Affirmations: A Critical Complementarity

Shmulevich, Ilya, et al. Eukaryotic Cells are Dynamically Ordered or Critical but Not Chaotic. Proceedings of the National Academy of Sciences. 102/13439, 2005. We cite this entry with Stuart Kauffman as a coauthor as an early notice of the tendency for gene regulatory networks to arrive and perform at this critical cusp between stability and openness. The many 2018 – 2020 entries herein and throughout which robustly quantify this common state give proof to its prescience.

Sivaram, Chandra, et al. Bioenergetics and Stellar Luminosities. International Journal of Astrobiology. Online October, 2017. Bangalore based Indian Institute of Astrophysics, Christ Junior College, and St. Joseph Indian College researchers comment upon a curious affinity across these widest reaches between creaturely physiologies and cosmic dynamics.

We draw attention to a curious coincidence wherein the most (steadily emitting) luminous objects in the Universe from stellar X-ray sources to ultra-luminous quasars and Ultra Luminous Infrared Galaxies, steadily emit a power per unit mass, which is just the same value as the maximal metabolic rate in (warm-blooded) bio-organisms. (Abstract)

Sole, Ricard, et al. Synthetic Criticality in Cellular Brains. Journal of Physics: Complexity. 2/4 December, 2021. In a companion paper to Christopher Dunham, et al in this issue, seven Barcelona complexity scientists continue to show how this common, active optimum poise can find beneficial application to a range of novel neural designs.

Cognitive networks have evolved to cope with uncertain environments in order to make reliable responses. Such decision making circuits need adapt to the external world in efficient and flexible ways. Mounting evidence has shown that brains generally operate in a broad self-organized criticality (SOC) mode. We ask how might this phenomena occur in small-scale living systems such as cells? We explore a recent model of engineered gene networks that avail the feedback between order and control parameters to achieve a SOC state. We suggest that a dynamic criticality could serve novel adaptive synthetic cellular and multicellular organisms. (Abstract excerpt)

Sorbaro, Martino, et al. Statistical Models of Neural Activity, Criticality, and Zipf’s Law. arXiv:1612.09123. We note this contribution by University of Edinburgh, School of Informatics researchers MS, Michael Herrmann and Matthias Hennig because it draws parallel between cerebral dynamics, their critical attractor state, and G. K. Zipf’s (second quote) linguistic origin. See also Statistical Criticality Arises in Maximally Informative Samples by Ryan Cubero, et al (1808.0249) for another take upon this synthesis.

In this overview, we discuss the connections between the observations of critical dynamics in neuronal networks and maximum entropy models that are often used as models of neural activity, focusing on the relation between "statistical" and "dynamical" criticality. We then discuss the emergence of Zipf’s law in neural activity, verifying their presence in retinal activity under a number of conditions. In the second part we review statistical criticality and the structure of the parameter space, as described by Fisher information. (Abstract excerpt)

Zipf's law is an empirical law formulated using mathematical statistics named after the linguist George Kingsley Zipf, who first proposed it in 1932. It states that given a large sample of words used, the occurrence of any word is inversely proportional to its rank in the frequency table. The most common word will occur about twice as often as the second most frequent word, etc. The relationship occurs in many other rankings, unrelated to language, such as the population ranks of cities in various countries, corporation sizes, income rankings, etc. (Wikipedia)

Stanoev, Angel, et al. Organization at Criticality Enables Processing of Time-Varying Signals by Receptor Networks. Molecular Systems Biology. 16/2, 2020. As we cite many papers about self-organized criticalities in neural systems, here MPI Molecular Physiology cell biologists report the presence of nature’s optimum biochemical balance has similarly been found in cellular information processing. Circa 2020, increasingly across in every realm, a common, independent generative pattern seems to be in exemplary evidence.

How cells utilize surface receptors for chemoreception is an open issue spanning physics and biology. For example, the dynamical mechanism for processing time‐varying signals is still unclear. Using a dynamical formalism to describe criticality in non‐equilibrium systems, we propose a generic principle for temporal information processing through phase space trajectories with transient memory. In contrast to short‐term memory, dynamic memory generated via a “ghost” attractor enables signal integrations and interprets complex temporal growth factor signals. We propose how recycling provides self‐organized maintenance of the critical receptor concentration at the plasma membrane through a fluctuation‐sensing mechanism. Processing of non‐stationary signals, a feature previously attributed only to neural networks, thus uniquely emerges for receptor networks organized at criticality. (Abstract excerpt)

Tadic, Bosiljka. Self-Organized Criticality and Emergent Hyperbolic Networks: Blueprint for Complexity in Social Dynamics. European Journal of physics. 40/2, 2019. A Josef Stefan Institute, Slovenia physicist continues her technical studies (see arXiv and TB website) which articulate an exemplary presence of universal nonlinear dynamics across online communications. In a similar way to every other natural and neural domain, they tend to critically poised states, from which a collective knowledge arises. By way of (neural) network phenomena such as algebraic topologies, the Internet appears as a knowledge-gaining process going on by itself, which is a main premise of this website. See also, for example, The Mechanisms of Self-Organized Criticality in Social Processes of Knowledge Creation by B. Tadic, et al in Physical Review E (96/032307, 2017).

Online social dynamics based on human endeavours exhibit prominent complexity in the emergence of new features embodied in the appearance of collective social values. The vast amount of empirical data collected at various websites provides a unique opportunity to quantitative study of the underlying social dynamics in full analogy with complex systems in the physics laboratory. Here, we briefly describe the extent of these analogies and indicate the methods from other science disciplines that the physics theory can incorporate to provide the adequate description of human entities and principles of their self-organisation. We demonstrate the approach on two examples using the empirical data regarding the knowledge creation processes in online chats and questions-and-answers. Precisely, we describe the self-organised criticality as the acting mechanisms in the social knowledge-sharing dynamics and demonstrate the emergence of the hyperbolic geometry of the co-evolving networks that underlie these stochastic processes. (Abstract)

Tagliazucchi, Enzo, et al. Large-Scale Signatures of Unconsciousness are Consistent with a Departure from Critical Dynamics. arXiv:1506.04304. Neuroscientists from Germany, Argentina, and Belgium including Dante Chialvo and Steven Laureys describe sophisticated research results that serve to interpret brain state-change activity in terms of critical phase transitions from statistical physics and complex systems theory. Our interest is that once again neural phenomena can be an archetypal exemplar of a nonlinear nature, which is then importantly seen, as the Abstract notes, to imply a “universal, independent” source.

Loss of cortical integration and changes in the dynamics of electrophysiological brain signals characterize the transition from wakefulness towards unconsciousness. The common mechanism underlying these observations remains unknown. In this study we arrive at a basic model, which explains these empirical observations based on the theory of phase transitions in complex systems. We studied the link between spatial and temporal correlations of large-scale brain activity recorded with functional magnetic resonance imaging during wakefulness, propofol-induced sedation and loss of consciousness, as well as during the subsequent recovery. A model of a system exhibiting a phase transition reproduced our findings, as well as the diminished sensitivity of the cortex to external perturbations during unconsciousness. This theoretical framework unifies different empirical observations about brain activity during unconsciousness and predicts that the principles we identified are universal and independent of the causes behind loss of awareness. (Abstract)

Thurner, Stefan. Nonextensive Statistical Mechanics and Complex Scale-Free Networks. Europhysics News. 36/6, 2005. We note this entry in a special issue on the first title phrase from Constantino Tsallis for its anticipation in the mid 2000s of an intrinsic unity, as there naturally must be, between such disparate fields and approaches.

One explanation for the impressive recent boom in network theory might be that it provides a promising tool for an understanding of complex systems. Network theory is mainly focusing on discrete large-scale topological structures rather than on microscopic details of interactions of its elements. This viewpoint allows to naturally treat collective phenomena which are often an integral part of complex systems, such as biological or socio-economical phenomena. Much of the attraction of network theory arises from the discovery that many networks, natural or man-made, seem to exhibit some sort of universality, meaning that most of them belong to one of three classes: random, scale-free and small-world networks. Maybe most important however for the physics community is, that due to its conceptually intuitive nature, network theory seems to be within reach of a full and coherent understanding from first principles. (218)

Tkacik, Gasper, et al. Thermodynamics and Signatures of Criticality in a Network of Neurons. Proceedings of the National Academy of Sciences. 112/11508, 2015. Seven theorists posted in Austria, France and the USA (Princeton) including Thierry Mora and William Bialek describe deep commonalities between far removed realms of condensed matter and cerebral matters by way of their energetic activities.

The activity of a brain—or even a small region of a brain devoted to a particular task—cannot be just the summed activity of many independent neurons. Here we use methods from statistical physics to describe the collective activity in the retina as it responds to complex inputs such as those encountered in the natural environment. We find that the distribution of messages that the retina sends to the brain is very special, mathematically equivalent to the behavior of a material near a critical point in its phase diagram. (Significance)

Tsallis, Constantino. Inter-Occurrence Times and Universal laws in Finance, Earthquakes and Genomes. arXiv:1601.03688. The Greek-Brazilian scientist (search) is the founder of a well-received 21st century thermodynamic theory known as non-extensive statistics. If one types in his last name on this site you get: Your query resulted in too many hits, only 1,000 are displayed. We note in this new section because once again a universality is claimed by how the same phenomena is present in the three title realms. See also A New Entropy Based on a Group-Theoretical Structure by Tsallis and coauthors in the Annals of Physics (366/21, 2016).

vandermeer, John, et al. New Forms of Structure in Ecosystems Revealed with the Kuramoto Model. arXiv:2006.16006. Reviewed more in Dynamic Ecosystems, we make note here as an example of how chimeric effects can even be apparent in these natural environs.

Villani, Marco, et al. Dynamic Criticality in Gene Regulatory Networks. Complexity. October, 2018. University of Modena theorists, along with coauthor Stuart Kauffman, show how his original prescience (search Bornholdt) that living systems reside at an dynamic edge between order and chaos is currently being robustly verified, as this section reports. While other studies in neuroscience (see VI. G. 2) also confirm, here this optimum state is found to hold for genomes. Search Villani for much more about this long foreseen, often elusive, historic discovery of one uniVerse to human epitome creative code.

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