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

Cristian Axenie, Oliver López-Corona, Michail A. Makridis, Meisam Akbarzadeh, Matteo Saveriano, Alexandru Stancu, Jeffrey West

Antifragility characterizes the benefit of a dynamical system derived from the variability in environmental perturbations. Antifragility carries a precise definition that quantifies a system’s output response to input variability. Systems may respond poorly to perturbations (fragile) or benefit from perturbations (antifragile). In this manuscript, we review a range of applications of antifragility theory in technical systems (e.g., traffic control, robotics) and natural systems (e.g., cancer therapy, antibiotics). While there is a broad overlap in methods used to quantify and apply antifragility across disciplines, there is a need for precisely defining the scales at which antifragility operates. Thus, we provide a brief general introduction to the properties of antifragility in applied systems and review relevant literature for both natural and technical systems’ antifragility. We frame this review within three scales common to technical systems: intrinsic (input-output nonlinearity), inherited (extrinsic environmental signals), and interventional (feedback control), with associated counterparts in biological systems: ecological (homogeneous systems), evolutionary (heterogeneous systems), and interventional (control). We use the common noun in designing systems that exhibit antifragile behavior across scales and guide the reader along the spectrum of fragility-adaptiveness-resilience-robustness-antifragility, the principles behind it, and its practical implications.

Read the full article at: arxiv.org

Egbert H. van Nes, Diego G. F. Pujoni, Sudarshan A. Shetty, Gerben Straatsma, Willem M. de Vos, Marten Scheffer

PNAS 121 (2) e2221791120

Data from the human microbiome as well as communities of flies, rodents, fish, trees, plankton, and fungi suggest that consistently a tiny fraction of the species accounts for most of the biomass. We suggest that this may be due to an overlooked phenomenon that we call “stickiness” of rarity. This can arise in groups of species that are equivalent in resource use but differ in their response to stochastic stressors such as weather extremes and disease outbreaks. Stickiness is not absolute though. In our simulations, as well as natural time series from microbial communities, rare species occasionally replace dominant ones that collapse, supporting the insurance theory of biodiversity. Rare species may play an important role as backups stabilizing ecosystem functioning.

Read the full article at: www.pnas.org