Natural Genesis

A. An Ecode Endowment: A Universal, Independent, Exemplary, Ecosmome to Geomome Complementarity

Almeira, Joaquin, et al. Tricritical Behavior in a Neural Model with Exitatory and Inhibitory Units. arXiv:2207.02320. Researchers in Argentina and Italy including Dante Chialvo add further evidence for nature’s wide preference to seek and reside at such a sweet poise state between more or less relative coherence.

While the support for the relevance of critical dynamics to brain function is increasing, there is less agreement on the exact nature of the advocated critical point. Thus, a considerable number of theoretical efforts address which mechanisms and what transitions can be exhibited by neuronal networks models. The present work describes the effect of incorporating a fraction of inhibitory neurons on the collective dynamics. As we show, this results in a tricritical point for highly connected networks.

Antonello, Priscella, et al. Self-organization of In Vitro Neuronal Assemblies Drives to Complexity Network Topology. eLife. 11/e74521, 2022. Federal University of Sao Paulo, and Indiana University neuroscientists including Olaf Sporns and John Beggs post a sophisticated technical and theoretic study about innate cerebral tendencies to preferentially give rise to an optimum intricacy of parts and wholes. Our cognitive abilities thus organize themselves from the earliest get go for learning, communication and sage integrity to our retrospect global facility.

Activity-dependent self-organization plays a vital role as it underlies connectivity patterns in neural circuits. By combining neuronal cultures, network neuroscience methods and information theory, we can study how complex network topologies emerge from local interactions. We found that the number of network links grew over the course of development, shifting from a segregated to a more integrated architecture. In agreement with previous in silico and in vitro studies, a small-world modular format was detected by way of strong clustering among neurons. These findings leverage new insights into how neuronal effective networks relate to how neuronal forms and functions organize themselves. (Abstract excerpt)

Our findings suggest that plasticity and homeostatic mechanisms drive the emergence of segregated and integrated architectures in developing effective networks by reinforcing synchronized spontaneous activity. These processes induce a predictive relationship between the spike trains of pre- and post-synaptic neurons that produces reliable effective network patterns, such as the clustering of low firing rate neurons, the formation of modules, and the connection of high firing rate neurons across modules, integrating them. Such mechanisms, despite being independent of the exact physical location of each neuron, showed to have a preference to link neurons that are closer to each other. Finally, this organization involves a level of randomness, but it is greatly dependent on the heterogeneity of the firing rate of neurons. (Conclusion)

Aschwanden, Markus and Manuel Guedel.. Self-Organized Criticality in Stellar Flares. arXiv:2106.06490. Solar and Stellar Astrophysics Laboratory, Palo Alto and University of Vienna (search MA) researchers report an even more robust propensity for all manner of natural phenomena such as active sunny stars to hold to scale-invariant self-similarities. Of especial note is a persistent arrival at this middle way balance. See also The Universality of Power Law Slopes in the Solar Photosphere by MA and Nived Nhalil at 2211.08323 for later work.

What does it mean when we say that stellar flares exhibit self-organized criticality? If stellar flares would occur by pure random processes, their size distribution would fit a Poissonian or Gaussian function. In contrast, the fact that stellar flares are consistent with power law functions strongly supports the evolution of nonlinear (exponential-growing) energy dissipation processes, triggered by local fluctuations that exceed a system-wide threshold. The statistics of physical parameters in such nonlinear energy dissipation processes can be expressed with volumetric scaling laws, characterized by the scale-free probability, the (spatial) fractal dimension, classical diffusion, and the flux-volume scaling. (11)

Autorino, Camilla and Nicoletta Petridou. Critical Phenomenon in Embryonic Organization. Current Opinion in Systems Biology. Vol. 31, September, 2022. European Molecular Biology Laboratory, Heidelberg University biochemists describe an historic conceptual advance in this regard by a novel ability to perceive and quantify self-organized criticalities in effect during prenatal development. As the quotes say, even life’s earliest formative phases can be traced to a deep physical source. See also Programmed and Self-Organized Flow of Information during Morphogenesis by Claudio Collinet and Thomas Lecuit in Nature Reviews Molecular Cell Biology (22/245, 2021).

For a concurrent paper (these insights seem just now possible) see Animal Synchrony and Agent’s Segregation by Laura Schaposnik, et al (arXiv:2212.07505). We also note a 1995 paper Evolution as a Self-Organized Critical Phenomena by Per Bak, et al (PNAS, 92/5219) in response to initial their notices of SOC theories. Some three decades later might it be again considerable, by way of our global collaborations, to understand how we all arose from a conducive ecosmos.

The physics of critical points lies behind the organization of various complex systems, from molecules to ecosystems. Several functional benefits emerge when operating at a “criticality” state. Here, we propose that introducing this dynamic concept in developmental biology may explain remarkable features of embryonic development, such as collective behavior and fitness. Recent interdisciplinary work has studied embryogenesis within statistical physics frameworks and found that biochemical and biomechanical processes do indeed resemble critical phenomena. In regard we discuss gene expression, cell differentiation, and tissue mechanics whereby a critical balance can foster an optimum organization. (Abstract)

Many natural phenomena are considered to operate via similar mechanisms. Evolutionary systems, bird flocks, epidemic spreading, immune systems, intelligent behavior, neuronal activity, and gene expression are only a subset of biological phenomena that although display differences in their physical characteristics, such as size, shape, and material composition, also express remarkable similarities in their mode of organization and function. A major commonality is that they can be described using general frameworks of statistical physics by way of critical points in phase transitions (PTs). Criticality is traced from unique mathematical traits using PTs theories which can be studied via dynamical systems frameworks or statistical mechanics. Given that these traits are universal and largely independent, it is considered that such a deep theoretical basis can somehow wholly serve to explain the behavior of various critical occasions across nature. (1)

This search for a unifying theory of natural complexity an active research direction in physics. Why are biologists becoming more and more interested in it? Living systems appear to “know” how to reproducibly develop, as well as evolve and adapt to environments. One hypothesis is that their fitness is gained at criticality, since operating close to a critical point can balancing between functional regimes, so the system may efficiently shift between them. (2) The natural physics to seek and reside at a critical juncture can even be seen, by our work, to underlie embryo development, ranging from gene expression and cell differentiation, to tissue mechanics and morphogenesis. (5)

In conclusion, the developing embryo exhibits complex physical traits, which biologists attribute to the numerous mechanochemical interactions. Biology, however, shows that development needs to be approached as a whole, as a critical system. By utilizing statistical physics, scientists will be able to bridge theory and experiments to address the functional role of criticality in embryo development. (6)

Barzon, Giacomo, et al. Criticality and Network Structure Drive Emergent Oscillations in a Stochastic Whole-Brain Model. Journal of Physics: Complexity. 3/3, 2022. After some years into the 21st century, and original notices in the 1980s and before, by these 2020s University of Padova systems theorists including Samir Suweis can now reach a deep theoretical and empirical quantification of a critically-poised universality across the ecosmos to cerebral capacities so to provide a dynamic middle-way optimum poise between more or less, closed and open coherence. See Heterogeneity Extends Criticality by Fernanda Sanchez-Puig, et al herein for another 2022 instance.

Overall, here we have shown in detail how network structure plays a fundamental, yet sometimes poorly understood, role. Therefore, we believe that our work will serve as a baseline for future analytical efforts in explaining the nature of the observed transition under more relaxed assumptions, e.g., in the presence of a non-trivial distribution of weights and different topologies, to further understand the influence of both in the emergence of critical features in the human brain. Possible approaches may include the use of heterogeneous mean-field methods as done in the study of epidemic spreading or annealed network approximations. All in all, we believe that our findings are a further contribution to the still puzzling ‘critical brain hypothesis’. (11)

Beggs, John. The Cortex and the Critical Point: Understanding the Power of Emergence.. Cambridge: MIT Press, 2022. The veteran Indiana University neurophysicist has been studying these cerebral propensities for some 15 years. As a lead authority, into the 2020s the evidence is strong enough that a collegial book length treatment is possible. As this section and site reports, it is now well founded in both theory and test that brains seek, prefer and reside at this locus of optimum performance. As the case broadly builds, this phenomenal principle can be seen as nature’s common choice from celestial, quantum and material realms, life’s genetic and organic development and onto human societies. The work has since become newsworthy such as When Does the Brain Operate at Peak Performance? by JB, see quote (Quanta, January 31, 2023) See also, e.g., Fosque, L., et al. Quasicriticality Explains Variability of Human Neural Dynamics across Life Span. arXiv:2209.02592 with JB as a coauthor.

But if I were to try to explain in a paragraph, I would say this - it is like when water, at just the right pressure, changes into steam. For a moment it is both a flowing liquid and individual molecules zipping around in the air. Neurons can act this way too, firing synchronously then breaking of to improvise by themselves. Just at this transition. They are both independent and interdependent with all other neurons. Right here at what we will call the critical point, information flows easily, computations are most facile, and the brain is very sensitive to inputs. Here intricate patterns of waves, oscillations, and avalanches of activity arise most readily. (1)

Most broadly, there are two main consequences for a neural network that operates near the critical point. First, it will have scale-free properties which are linked to optimal information processing. Second it will exhibit universality, as we explored in this chapter. (105)

Over the last few decades, an idea called the critical brain hypothesis has been helping neuroscientists understand how the human brain operates as an information-processing powerhouse. It posits that the brain always teeters between two phases of activity: a relative quiet, less orderly side, and a more active, attentive mode,. The hypothesis predicts that between these conditions, at a “sweet spot” known as the critical point, the brain has an ideal balance of variety and structure so as to produce the most complex and information-rich patterns. (Beggs, Quanta)

Beiro, Mariano, et al. Signs of Criticality in Social Explosions. arXiv:2305.01944. University of Buenos Aires, Singapore University of Social Sciences, Nanyang Technological University, Singapore, Complexity Science Hub Vienna (Stefan Thurner) and International Valencian University, Spain systems theorists describe a unique, extensive project which has found that even this hyper-active, multi-faceted public intensity tends toward, exhibits and is distinguished a self-organized ciriticalities which endow near-optimum communicative conditions.

The success of an on-line movement could be defined by a shift to off-line street actions of protests. One may view these macro-behaviors as spontaneous interactions, which will give rise to common simplifications on several statistics. Here, we go on to observe of signs of criticality in such dynamic public demonstrations. Namely, the same power-law exponents are found whenever the distributions are calculated, either due to the same windows-time or the number of hashtags. By means of network arrays, we show that the systems take on two correlations with high or low values of modularity. The importance of analysing systems near a critical point is that any small disturbance can escalate and induce large-scale -- nationwide -- chain reactions. (Abstract excerpt)

Butler, Travis and Georgi Georgiev. Self-Organization in Stellar Evolution: Size-Complexity Rule. arXiv:2202.02318. Assumption University, Worcester, MA physicists (search GG) post a strong notice to date of nature’s deep propensity to organize itself into dynamic, invariant states everywhere. In this astral case, how stars form is seen as an another exemplary result. An historic importance then becomes an implied mathematic source code which exists in generative effect independently of any certain scale or instance. In regard, such recurrent features in kind from celestial to cultural phases are cited as a 2022 presence and proof of a true universality. As our Earthuman epic reaches a consummate moment, this entry, A Physics Perspective on Collective Animal Behavior (N. Ouellette 2022), and many others are coming altogether so to reveal and discover a cocreative uniVerse to wumanVerse familial genesis.

Complexity Theory is highly interdisciplinary, therefore any regularities must hold on all levels of organization, independent on the nature of the system. An open question in science is how complex systems self-organize to produce emergent structures and properties by way of non-equilibrium thermodynamics. There is a quantity-quality transition which holds across natural systems, which is often known as the size-complexity rule. We apply this standard to stars to compare them with other complex systems so to find universal patterns of self-organization independent of the substrate. This rule goes under different names in different disciplines and systems of different nature, such as the area-speciation rule, economies of scale, scaling relations in biology and for cities, and many others. (Abstract excerpt)

Chen, Luyao, et al. AI of Brain and Cognitive Sciences: From the Perspective of First Principles. arXiv:2301.08382. Sixteen Chinese length scholars under the auspices of the AI of Brain and Cognitive Sciences Research Group, Beijing Academy of Artificial Intelligence, and Beijing University post an array of chapters, per the first quote, in an effort to advance AI abilities by better appreciations of how our own cerebral faculties have actually formed and well function. Our main interest is Criticality: Bringing New Perspectives to the Brain and AI, which gathers and presents an extensive, latest survey as this realization lately gains a wide, quantified acceptance. The two longer quotes are from this section.

This paper collects six such first principles summarized by the research team, “AI of Brain and Cognitive Sciences”, in the Beijing Academy of Artificial Intelligence (BAAI). They are attractor network, criticality, random network, sparse coding, relational memory, and perceptual learning. On each topic, we review its biological background, fundamental property, potential application to AI, and future development.

The framework of criticality is a powerful tool to understand and analyze complex systems because many systems in physics and nature are in a critical state. In the past 20 years, researchers found that biological neural networks in the brain operate close to a critical state, which provides a new perspective on studying brain dynamics. It is known that the critical state is important for brain activities/functions because it optimizes numerous aspects of information transmission, storage, and processing. In addition, some brain diseases are believed to be related to the deviation from the critical state, which also opens a new window for diagnosing and treating these diseases. In the field of artificial intelligence, the framework of the critical state is used to analyze and guide both the structural design and weight initialization of deep neural networks, suggesting that operating close to a critical state may be considered one of the fundamental principles governing computations in neural networks. (9)

The critical state gives us a new perspective to study biological and artificial neural networks. At present, the framework of criticality has not only been used to understand neural dynamics and brain diseases but also to analyze the operation of deep neural networks and guide the design for further improvement. Through theoretical analysis and numerical simulations, we know that the critical state of the network can be controlled by some simple control parameters, such as branching ratio, spectral radius, and input-output Jacobian singular values. This makes it possible to analyze or tune the overall behavior of complex networks through statistics that are easy to observe. We believe that the framework of criticality will play an even more important role in helping us better understand the constraints applied to artificial neural networks and to design better architectures as well as dynamical rules to improve its performance in complex information processing. (14)

Cheraghalizadeh, J., et al. Simulating Cumulus Clouds Based on Self-Organized Criticality. arXiv:2211.06111. University of Mohaghech Ardabili, Iran and ETH Zurich physicists advance recent findings that even such weather conditions can be found to take on and exhibit this intrinsic phenomenal preference. In regard, this widespread, exemplary occasion of a SOC viability strongly indicates an independent source which is universally inl manifest effect.

Recently it was shown that self-organized criticality is an important ingredient of the dynamics of cumulus clouds (Physical Review E, 103(5), 2021). Here we introduce a new algorithm to simulate cumulus clouds in two-dimensional square lattices, based on the cohesive energy of wet air parcels and a sandpile-type diffusion of cloud segments. We observed that the cloud fields that we obtain from our model are fractal, with the outer perimeter having a fractal dimension. (Excerpt)

Ciaunica, Anna, et al. Nested Selves: Self-Organization and Shared Markov Blankets in Prenatal Development in Humans.. PsyArixiv Preprints, May 2023. We review this post by AC, University of Lisbon, Michael Levin, Tufts University, Fernando Rosas, University of Sussex, and Karl Friston, University College London (search each) as they move on to a unique perception that life’s embryonic stage can be rightly viewed as a self-organizing process. Into 2023, this occasion becomes evident within a biological self-making milieu and a newly fertile physical basis. So once more, along with Autorino and Petridou, a true evolutionary gestation takes credence as a genesis synthesis.

The immune system is a central component of organismic function in humans. This paper addresses self-organisation of a biological system in relation to — and nested within — an other biological system in pregnancy. Indeed, the hierarchical relationship in pregnancy reflects an earlier autopoietic process in the embryo by which the number of individuals in a single blastoderm is determined by cell-cell interactions. Specifically, we consider the role of the immune system in biological self-organisation in addition to neural/brain systems that furnish us with a sense of self. In pregnancy, two immune systems need to exchange resources and information to maintain viable self-regulation of nested systems. We then propose mechanisms that scaffold tise complex relationship through the lens of the Active Inference, with a focus on shared Markov blankets. (Abstract excerpt))

Ciss, Mamadou, et al. Description of the Cattle and Small Ruminants Trade Network in Senegal.. arXiv:2301.11784. We cite as another instance by Senegalese, French and British system veterinaries of how a mature awareness of common, implicate nonlinear lineaments in universal effect can provide an implicate guidance even for the distribution and maintenance of indigenous herd animals.

Livestock mobility of small and large ruminants, is a main pillar of production and trade in West Africa. These movements cover several thousand kilometers and connect the whole West African region. But this activity also leads to the diffusion of many animal and zoonotic diseases. In this paper, we present a procedure based on temporal network theory to identify possible sentinel locations using two indicators: vulnerability (i.e. the probability of being reached by the disease) and time of infection (i.e. the time of first arrival of the disease). (Excerpt)

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