Srdjan Kesić

Systems 2024, 12(1), 29

This article argues that complexity scientists have been searching for a universal complexity in the form of a “theory of everything” since some important theoretical breakthroughs such as Bertalanffy’s general systems theory, Wiener’s cybernetics, chaos theory, synergetics, self-organization, self-organized criticality and complex adaptive systems, which brought the study of complex systems into mainstream science. In this respect, much attention has been paid to the importance of a “reductionist complexity science” or a “reductionist theory of everything”. Alternatively, many scholars strongly argue for a holistic or emergentist “theory of everything”. The unifying characteristic of both attempts to account for complexity is an insistence on one robust explanatory framework to describe almost all natural and socio-technical phenomena. Nevertheless, researchers need to understand the conceptual historical background of “complexity science” in order to understand these longstanding efforts to develop a single all-inclusive theory. In this theoretical overview, I address this underappreciated problem and argue that both accounts of the “theory of everything” seem problematic, as they do not seem to be able to capture the whole of reality. This realization could mean that the idea of a single omnipotent theory falls flat. However, the prospects for a “holistic theory of everything” are much better than a “reductionist theory of everything”. Nonetheless, various forms of contemporary systems thinking and conceptual tools could make the path to the “theory of everything” much more accessible. These new advances in thinking about complexity, such as “Bohr’s complementarity”, Morin’s Complex thinking, and Cabrera’s DSRP theory, might allow the theorists to abandon the EITHER/OR logical operators and start thinking about BOTH/AND operators to seek reconciliation between reductionism and holism, which might lead them to a new “theory of everything”.

Read the full article at: www.mdpi.com

Lei Dong, Fabio Duarte, Gilles Duranton, Paolo Santi, Marc Barthelemy, Michael Batty, Luís Bettencourt, Michael Goodchild, Gary Hack, Yu Liu, Denise Pumain, Wenzhong Shi, Vincent Verbavatz, Geoffrey B. West, Anthony G. O. Yeh & Carlo Ratti 
Nature Cities (2024)

What is a city? Researchers use different criteria and datasets to define it—from population density to traffic flows. We argue there is one dataset that could serve as a proxy of the temporal and spatial connections that make cities what they are: geolocated data from the world’s more than 7 billion cell-phone users. Cell-phone data are a proxy of people’s presence in a given area and of their movement between areas. Combined with computational methods, these data can support city delineations that are dynamic, responding to multiple statistical and administrative requirements, and tailored to different research needs, thus accelerating ongoing work in urban science.

Read the full article at: www.nature.com

Andrea I. Luppi, Fernando E. Rosas, Pedro A.M. Mediano, David K. Menon, Emmanuel A. Stamatakis

Trends in Cognitive Science

To explain how the brain orchestrates information-processing for cognition, we must understand information itself. Importantly, information is not a monolithic entity. Information decomposition techniques provide a way to split information into its constituent elements: unique, redundant, and synergistic information. We review how disentangling synergistic and redundant interactions is redefining our understanding of integrative brain function and its neural organisation. To explain how the brain navigates the trade-offs between redundancy and synergy, we review converging evidence integrating the structural, molecular, and functional underpinnings of synergy and redundancy; their roles in cognition and computation; and how they might arise over evolution and development. Overall, disentangling synergistic and redundant information provides a guiding principle for understanding the informational architecture of the brain and cognition.

Read the full article at: www.cell.com

I. Bonamassa, B. Ráth, M. Pósfai, M. Abért, D. Keliger, B. Szegedy, J. Kertész, L. Lovász, A.-L. Barabási

In physical networks, like the brain or metamaterials, we often observe local bundles, corresponding to locally aligned link configurations. Here we introduce a minimal model for bundle formation, modeling physical networks as non-equilibrium packings of hard-core 3D elongated links. We show that growth is logarithmic in time, in stark contrast with the algebraic behavior of lower dimensional random packing models. Equally important, we find that this slow kinetics is metastable, allowing us to analytically predict an algebraic growth due to the spontaneous formation of bundles. Our results offer a mechanism for bundle formation resulting purely from volume exclusion, and provide a benchmark for bundling activation and growth during the assembly of physical networks.

Read the full article at: arxiv.org

Joseph Lizier

Getting in sync can be exhilarating when you’re dancing in rhythm with other people or clapping along in an audience. Fireflies too know the joy of synchronisation, timing their flashes together to create a larger display to attract mates.

Synchronisation is important at a more basic level in our bodies, too. Our heart cells all beat together (at least when things are going well), and synchronised electrical waves can help coordinate brain regions – but too much synchronisation of brain cells is what happens in an epileptic seizure.

Sync most often emerges spontaneously rather than through following the lead of some central timekeeper. How does this happen? What is it about a system that determines whether sync will emerge, and how strong it will be?

Read the full article at: theconversation.com