Making mind matter with irruption theory: Bridging end-directedness and entropy production by satisfying the participation criterion

Froese, Tom and Georgii, Karelin and Takashi, Ikegami

Biological processes are end-directed, that is, teleological. Explaining the physical efficacy of end-directedness continues to be a profound challenge for theoretical biology, especially given its unavoidable implications for our own self-understanding. For a comprehensive theory of life, it is pivotal to bridge our human-centric view of end-directedness, which the social sciences and humanities consider intrinsic to our actions, with the natural sciences’ view of actions’ in purely physiological terms, especially in terms of thermodynamic tendencies. A comprehensive theory should therefore provide an end-involving account, which illuminates how both physiology and teleology distinctly contribute to behavior generation. Here we introduce the “Participation Criterion”: End-involvement in a bodily process entails that, in principle, it is distinguishable from one without end-involvement, specifically in terms of physiologically unpredictable changes in unexplainable variability. To exemplify the difficulty of satisfying this criterion, we critically analyze two theories on the thermodynamic basis of end-directedness. We then propose that “Irruption Theory” points to a way forward because it predicts that bodily processes have an end-involvement-dependent increase in their entropy rate. This is consistent with evidence of an association between conscious intention and neural fluctuations, is open to further experimental verification, and provides a novel perspective on the role of thermodynamic entropy production in the organism.

Read the full article at: philsci-archive.pitt.edu

Multistable Protocells Can Aid the Evolution of Prebiotic Autocatalytic Sets

Angad Yuvraj Singh and Sanjay Jain

We present a simple mathematical model that captures the evolutionary capabilities of a prebiotic compartment or protocell. In the model, the protocell contains an autocatalytic set whose chemical dynamics is coupled to the growth–division dynamics of the compartment. Bistability in the dynamics of the autocatalytic set results in a protocell that can exist with two distinct growth rates. Stochasticity in chemical reactions plays the role of mutations and causes transitions from one growth regime to another. We show that the system exhibits ‘natural selection’, where a ‘mutant’ protocell in which the autocatalytic set is active arises by chance in a population of inactive protocells, and then takes over the population because of its higher growth rate or ‘fitness’. The work integrates three levels of dynamics: intracellular chemical, single protocell, and population (or ecosystem) of protocells.

Read the full article at: www.mdpi.com

The structure of segregation in co-authorship networks and its impact on scientific production

Ana Maria Jaramillo, Hywel T. P. Williams, Nicola Perra & Ronaldo Menezes 

EPJ Data Science volume 12, Article number: 47 (2023)

Co-authorship networks, where nodes represent authors and edges represent co-authorship relations, are key to understanding the production and diffusion of knowledge in academia. Social constructs, biases (implicit and explicit), and constraints (e.g. spatial, temporal) affect who works with whom and cause co-authorship networks to organise into tight communities with different levels of segregation. We aim to examine aspects of the co-authorship network structure that lead to segregation and its impact on scientific production. We measure segregation using the Spectral Segregation Index (SSI) and find four ordered categories: completely segregated, highly segregated, moderately segregated and non-segregated communities. We direct our attention to the non-segregated and highly segregated communities, quantifying and comparing their structural topologies and k-core positions. When considering communities of both categories (controlling for size), our results show no differences in density and clustering but substantial variability in the core position. Larger non-segregated communities are more likely to occupy cores near the network nucleus, while the highly segregated ones tend to be closer to the network periphery. Finally, we analyse differences in citations gained by researchers within communities of different segregation categories. Researchers in highly segregated communities get more citations from their community members in middle cores and gain more citations per publication in middle/periphery cores. Those in non-segregated communities get more citations per publication in the nucleus. To our knowledge, this work is the first to characterise community segregation in co-authorship networks and investigate the relationship between community segregation and author citations. Our results help study highly segregated communities of scientific co-authors and can pave the way for intervention strategies to improve the growth and dissemination of scientific knowledge.

Read the full article at: epjdatascience.springeropen.com

Mediterranean School of Complex Networks.  Grado, Italy 30 June – 5 July 2024

In the last decade, network theory has been revealed to be a perfect instrument to model the structure of complex systems and the dynamical process they are involved into. The wide variety of applications to social sciences, technological networks, biology, transportation and economic, to cite just only some of them, showed that network theory is suitable to provide new insights into many problems.
Given the success of the Eighth Edition in 2023 of the Mediterranean School of Complex Networks, we call for applications to the Ninth Edition in 2024.

More at: mediterraneanschoolcomplex.net

Models of Cell Processes are Far from the Edge of Chaos

Kyu Hyong Park, Felipe Xavier Costa, Luis M. Rocha, Réka Albert, and Jordan C. Rozum
PRX Life 1, 023009

Complex living systems are thought to exist at the “edge of chaos” separating the ordered dynamics of robust function from the disordered dynamics of rapid environmental adaptation. Here, a deeper inspection of 72 experimentally supported discrete dynamical models of cell processes reveals previously unobserved order on long time scales, suggesting greater rigidity in these systems than was previously conjectured. We find that propagation of internal perturbations is transient in most cases, and that even when large perturbation cascades persist, their phenotypic effects are often minimal. Moreover, we find evidence that stochasticity and desynchronization can lead to increased recovery from regulatory perturbation cascades. Our analysis relies on new measures that quantify the tendency of perturbations to spread through a discrete dynamical system. Computing these measures was not feasible using current methodology; thus, we developed a multipurpose CUDA-based simulation tool, which we have made available as the open-source Python library cubewalkers. Based on novel measures and simulations, our results suggest that—contrary to current theory—cell processes are ordered and far from the edge of chaos.

Read the full article at: link.aps.org