IV. Ecosmomics: Independent Complex Network Systems, Computational Programs, Genetic Ecode Scripts

A. A Procreative Ecode: An Ecosmome to Geonome Complementary Hereditary Endowment

, . Van Schependom, Jeroen, et al. Neurophysiological avenues to better conceptualizing adaptive cognition. Communications Biology. 7/626, 2024.. Communications Biology. 7/626, 2024. Vrije Universiteit Brussel, Oxford University, CNR Istituto dei Sistemi Complessi, Italy and Technical University Dresden neuroscientists achieve another deeply quantified notice and expression of a reciprocal balance between coincident opposites of more or less coherence, conservation or creativity. Once again a semblance of a critically organized “sweet spot” appears as a natural optimum preference. We write on June 28 and wonder how can these robust, universal scientific findings ever make it to an academe stuck in mechanist denials of anything going on at all. We respectfully offer herein a Planatural PhiloSophia family mind and a PediaPedia Earthica.

We delve into the human brain’s deep capacity for adaptability and cognitive functioning, which are often seen as an executive domain. In regard, the neural bases that enable the navigation between transient thoughts without detracting from overarching goals form our article. We discuss the concept of “metacontrol,” which proposes a dynamic balancing of core processes depending on situational demands. This approach leads to the role of oscillatory processes in electrophysiological activity at different phases of desynchronization and synchronization in supporting adaptive behavior. These cognitive and neurophysiological avenues can thereby contribute to a more nuanced comprehension and its neural basis in both health and disease. (Excerpt)

Our central focus lies in exploring cognitive processing along a continuum characterized by its two polar phases: “persistence” and “flexibility.” We propose to use signal-processing methods to characterize this continuum connecting neurophysiology, physics, and cognitive science. (2)

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)

Anwar, Sayeed, et al. Self-organized bistability on globally coupled higher-order networks.. arXiv:2401.02825. In these 2020s complex system studies proceed to delve deeper and uncover vital new features. Here Indian Statistical Institute, Kolkata, KU Leuven, Belgium and Immanuel Kant Baltic Federal University, Kaliningrad neuroscientists including Nikita Frolov add a significant notice of nature’s tendency to seek and reside at an optimum state between two opposite but reciprocal modes of being. This middle way poise achieves a bilateral resonance rather than a total fixation on one or the other poles.

Self-organized bistability (SOB) stands as a critical behavior for the systems adjusting themselves to this dynamic balance. Recently, SOB has been found in a scale-free network as a recurrent transition to a global synchronization. Here, we extend the theoretical boundaries to a higher-order network. We use statistical data from spontaneous synchronized events to demonstrate the crucial role SOB plays in initiating and terminating temporary synchronized events. (Excerpt)

Multistability is a prevalent phenomenon observed in both man-made and real-world systems, characterized by consistent stable states. This poise plays a crucial role in regulating processes in living systems operating on different scales, from organ system interactions to neural synchronization. Typically, in normal conditions, neural activity in the brain demonstrates distinct power-law (scale-free) distributed avalanches, which is indicative of underlying self-organized criticality. (1)

To summarize, here we have reported a theoretical investigation of SOB by a globally coupled Kuramoto network with higher-order interaction. Our study reveals that the interplay between consumption and recovery rates results in a region of critical bistable dynamics. Within this regime, the critical dynamics allow for a self-sustaining toggling from the state of incoherence to coherence. (8)

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)

Asllani, Malbor and Alex Arenas. Pattern formation framework for chimera states in complex networks.. Physical Review E.. 111/044306, 2025. Florida State University and Universitat Rovira i Virgili physicists (organicists) bring a novel perspective to study this phenomena which emphasizes geometric forms, which is seen as akin to Alan Turing’s morphogenesis. We also record in this year an increasing notice of chimera dynamics everywhere, search F. Orsucci.

Chimera states distinguished by the coexistence of order and disorder are a recent research interest but their occasion remains an issue. In regard, our work evokes a pattern formation theory to explain the emergence of chimera states in complex networks in a similar way to how Turing morphologies are produced. Our findings suggest that chimeras result from the interplay between local and global dynamics at different timescales. Validated through simulations and empirical network analyses, our method enriches the understanding of coupled oscillator dynamics.

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)

Barjuan, Laia, et al. The multiscale self-similarity of the weighted human brain connectome. PLoS Computational Biology. April, 2025. Universitat de Barcelona and Jiangsu University, China neuroscientists including M. Angeles Serrano describe their comprehensive theoretic and empirical findings to date of a cerebral faculty distinguished by local and global recurrent patterns and a best critical balance. This exemplary affirmation can now be traced to and grounded in major physical principles. We then want to highlight this report as a prime instance of the mid 2020s achievement of a universal synthesis.

Anatomical connectivity between brain regions can be mapped to a network representation known as the connectome by way of links, weights, resilience and functions. Yet, these features are not fully understood. In this paper, we elucidate the architecture of multiscale neural nets from empirical data sets to reveal a fractal-like self-similarity in every occasion. This commonality is based on a theoretical renormalization model across all geometric scales. The observed symmetry also represents a signature of criticality states. (Excerpts)

The multiscale self-similarity of human connectomes, along with their modular organization, ensures that spectra representing weak ties are invariant across scales. Critical systems often demonstrate such fractal behavior, reflecting their organization as poised between various phases. Self-organized criticality is seen in non-equilibrium systems with many degrees of freedom which leads us to an evolutionary criticality. (14)

Barjuan, Laia, et al, Laia. et al. Optimal navigability of weighted human brain connectomes in physical space. arXiv:2311.10669. University of Barcelona system physicists contribute a further finesse of cerebral interactions which are specifically seen to improve the clear conveyance of information. Their work proceeds on to the notice of a persistent tendency to reach a middle balance point for this optimum performance. So once again it seems this common propensity to attain a best situation this way indeed appears as nature’s universal poise from quanta to astral to neural realms.

The architecture of the human connectome supports communication protocols relying on distances between brain regions or on the intensities of connections. However, these modes do not combine information about the two or reaches full efficiency. Here, we introduce a spectrum of routing strategies that joins link weights and embedded connectomes to transmit signals. We found that there is an intermediate region, a sweet spot, in which navigation achieves maximum communication. This phenomenon is robust and independent of the configuration of weights. Our results indicate that the intensity and topology of neural connections and brain geometry interplay to boost communicability to best support responses to stimuli. (Abstract)


In this work, we introduce a theoretical framework for the interplay between spatial distances and link weights in neural communication processes, and apply it to human connectomes to identify the distinctive roles played by the hard and soft wirings. The former describes the spatial distances in geometric embeddings, and the latter entails the weights of links between connected brain regions. We found that there is an intermediate region in this spectrum, a sweet spot, in which connectomes become maximally navigable and achieve full communication efficiency. (1)

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)

Barzon, Giacomo, et al. Excitation-Inhibition Balance Controls Information Encoding in Neural Populations. Physics Review Letters. 134/068403, 2025. University of Padova, MPI Physics of Complex Systems, and École Polytechnique de Lausanne contribute more evidential proof of life’s ubiquitous preference to balance beam these coincident opposites for best behaviors. See also Quasiuniversal scaling in mouse-brain neuronal activity stems from edge-of-instability critical dynamics by Guillermo Morales, et al in PNAS (120/9, 2023).

Understanding how the complex connectivity structure of the brain shapes its information-processing capabilities is a work in process. Here we focus on a paradigmatic architecture to study how the neural activity of excitatory and inhibitory populations encodes information from external signals. We show that informative content is maximized at the edge of stability as inhibition balances excitation. Along with other recent findings, our results portend a deeper information-theoretic understanding of how the balance between excitation and inhibition controls optimal information-processing in neural populations. IAbstract)

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.