V. Life's Corporeal Evolution Develops, Encodes and Organizes Itself: An EarthWinian Genesis Synthesis

5. Cooperative Member/Group Societies

Sasaki, Takao and Dora Biro. Cumulative Culture can Emerge from Collective Intelligence in Animal Groups. Nature Communications. 8/15049, 2017. As studies of creature behavioral interactions grow in sophistication, Oxford University avian social zoologists quantify how bird flocks attain a working common knowledge as a vital resource. As researchers find similar instances for herds, pods, clans, and troops, through life’s emergent evolution, we really ought to expect and seek the same salutary faculty for our local and global repositories such as the worldwide Internet.

Studies of collective intelligence in animal groups typically overlook potential improvement through learning. Although knowledge accumulation is recognized as a major advantage of group living within the framework of Cumulative Cultural Evolution (CCE), the interplay between CCE and collective intelligence has remained unexplored. Here, we use homing pigeons to investigate whether the repeated removal and replacement of individuals in experimental groups (a key method in testing for CCE) alters the groups’ solution efficiency over successive generations. Homing performance improves continuously over generations, and later-generation groups eventually outperform both solo individuals and fixed-membership groups. Homing routes are more similar in consecutive generations within the same chains than between chains, indicating cross-generational knowledge transfer. Our findings thus show that collective intelligence in animal groups can accumulate progressive modifications over time. Furthermore, our results satisfy the main criteria for CCE and suggest potential mechanisms for CCE that do not rely on complex cognition. (Abstract)

Sasaki, Takao and Stephen Pratt. The Psychology of Superorganisms: Collective Decision Making by Insect Societies. Annual Review of Entomology. 63/259, 2018. An Oxford University zoologist and Arizona State University neurobiologist advance understandings of how such creaturely groupings can attain an overall cognitive faculty, which in turn serves their viable survival. We also cite because S. Pratt was an advisor to Paul Davies (ASU) for his 2019 book (search) about such common tendencies, aka The Logic of Life, of social communities to seek and reach a distributed intelligence, with allusions to our worldwide humanity.

Under the superorganism concept, insect societies are so tightly integrated that they possess features analogous to those of single organisms, including collective cognition. Here, we review research that uses psychological approaches to understand decision making by colonies. The application of neural models to collective choice shows basic similarities between how brains and colonies balance speed/accuracy trade-offs in decision making. Experimental analyses have explored collective rationality, cognitive capacity, and perceptual discrimination at both individual and colony levels. A major theme is the emergence of improved colony-level function from interactions among relatively less capable individuals. Collective learning is a nascent field for the further application of psychological methods to colonies. (Abstract)

Schneider, Jonathan, et al. One, Two, and Many — A Perspective on What Groups of Drosophila melanogaster Can Tell Us About Social Dynamics. Advances in Genetics. Volume 77, 2012. With coauthors Jade Atallah and Joel Levine, University of Toronto at Mississauga biologists bring a novel dimension to the expanded study of minimal, once isolate organisms. Professor Levine’s group combined clever experimental studies of fruit fly interactive behaviors such as mating strategies, aggression, learning and memory abilities, which were found to express generic complex network phenomena. In regard, these findings are seen to evince that even seemingly simple, seemingly chaotic insects actually exhibit intricate behaviors of similar group dynamics as all animal societies do. This unique realization that even rudimentary invertebrates manifest nature’s relational universality adds still further credence to this pervasive source.

In the natural world, interactions between individuals occur in groups: an individual must recognize others, identify social opportunities, and discriminate among these options to engage in an interactive behavior. The presence of the group is known to exert an influence on individual group members, and this influence may feed back through the individual to affect behavior across the group. Such feedback has been observed in Drosophila melanogaster, for example, when mating frequency increases in groups composed of mixed strains compared to homogenous groups. A working hypothesis is that social processes—to recognize, identify, discriminate, and engage—are innate. They rely on a combination of genetic inheritance, molecular interactions, and cell circuitry that produce neural and immunological responses. Here, we discuss studies that emphasize social interactions in four categories in Drosophila melanogaster: learning, circadian clocks, aggression, and mating. We also speculate that a systems-level network approach to the study of Drosophila groups will be instrumental in understanding the genetic basis of emergent group-level behavior. (Abstract)

In the first part of this perspective, we consider several broad behavioral categories and emphasize effects elicited by social context. We also present several cases of groups exhibiting emergent properties arising through the dynamic interactions of group members. In the second part, we advocate treating groups of flies as complex systems, with many interactions and feed back loops between individuals. These relationships may explain the emergence of group-level behavioral patterns and allow us to understand the mechanisms that generate them. We have begun to approach the biology of the fly at a group level using system-level tools from network theory. (61-62)

The emergent group-level phenotypes highlighted above suggest that groups of flies undergo dynamic organization. Such complex systems display qualities that are not present at the individual level but are the additive and nonadditive effects of individual interactions. Analogous to the current “systems approach” to cell and molecular processes, we have begun to study the biology of the fly at a group level using network theory. Network analysis may be used to study individuals and their interaction patterns within a group. (70)

Seeley, Thomas, et al. Group Decision Making in Honey Bee Swarms. American Scientist. May-June, 2006. When a swarm of 10,000 bees go hunting for a new nest site, how do they survey and decide? This study from Cornell University’s renowned entomology department finds it is achieved via a group intelligence based on autonomous inputs from several hundred scouts, which leads to a sensed quorum, rather than to consensus or compromise. Three organizational factors are involved: a diversity of inputs is allowed, a minimum of slavish conformity, and a tendency to swiftly aggregate independent reports to offset competition. The paper closes with a suggestion that such apian wisdom could much avail human groups to …achieve collective intelligence and thus avoid collective folly.

Seuront, Laurent. Behavioral Fractality in Marine Copepods: Endogenous Rhythms vs. Exogenous Stressors. Physica A. In Press, October, 2010. In the early reign of natural philosophy, it was believed that every species and realm exemplified each other and a deep design. In the 21st century, a Flinders University biologist finds these Arthropoda planktons to indeed embody a ubiquitous, dynamic scale-invariance.

The presence of endogenous rhythms in the swimming behavior of five common species of copepods (i.e. minute marine crustaceans) was investigated through comparisons of the scaling properties of their three-dimensional trajectories and cumulative probability distribution function of move lengths recorded during the day and at night. The low and high fractal dimensions respectively observed during daytime in the dark and during night-time under conditions of simulated daytime indicate that these organisms have the ability to adjust the complexity of their swimming path depending on exogenous factors, independent of their actual endogenous rhythms. (Abstract)

Behavioral time series, though they often appear erratic, reveal 1/f like spectra; they are fractal-like because they display self-similar fluctuations over a wide range of time scales. Long-rang correlation in biological systems is adaptive because it serves as an organizing principle for highly complex, nonlinear processes and it avoids restricting the functional response of an organism to highly periodic behavior. (1)

Shellard, Adam and Roberto Mayor. Rules of Collective Migration from the Wildebeest to the Neural Crest. Philosophical Transactions of the Royal Society B. July, 2020. In this Collective Migration in Biological Systems issue, University College London biologists go on to report, explain and depict life’s constant active groupings from self-propelled particles to bacteria, cancer and every Metazoan phylum. An especial point is the common affinity between early developmental processes and large herds on the move.

Collective migration, the movement of groups in which individuals affect the behaviour of one another, occurs at every scale from bacteria up to whole species' populations. Universal principles of collective movement can be applied at all levels. In this review, we describe the rules governing collective motility, with a specific focus on the neural crest, an embryonic stem cell population that undergoes extensive migration during development. We will discuss how the underlying principles of individual cell behaviour, and those that emerge from a supracellular scale, can explain collective migration. (Abstract)

Three rules of collective migration: Attraction: a behaviour that causes individuals to steer towards the centre of mass, which is the average position of individuals within a certain radius. Repulsion: a factor that causes individuals to steer away from all its neighbours. Alignment: a behaviour whence individuals line up with others close by, such that it moves with the averaged heading of the nearby individuals.

Shou, Wenying, et al. Synthetic Cooperation in Engineered Yeast Populations. Proceedings of the National Academy of Sciences. 104/1877, 2007. From the Computational Biology Program, Laboratory of Living Matter, and Center for Studies in Physics and Biology at Rockefeller University, how genetic modifications can give rise to a beneficial mutuality in yeast cultures.

Although the interplay between cooperative organisms in natural systems must be far richer and deeper, we show that even in a simplified synthetic cooperative system, novel properties such as an increased ability to stay alive could emerge. (1880)

Sinhuber, Michael and Nicholas Ouellette. Phase Coexistence in Insect Swarms. Physical Review Letters. 119/178003, 2017. Stanford University, Environmental Complexity Lab researchers (search Ouellette) contribute to realizations that such dynamic creaturely assemblies can be traced to and explained by physical phenomena. Here statistical and thermodynamic principles find application so as to reveal phase transition states. An avail is made of “persistent homology,” along with analytical Betti numbers (see below). Of interest within this website, one may find both these methods cited from interstellar media to neural networks to literary works. I heard Ouellette speak at UM Amherst in 2014 when at Yale where he said that he chose midges for his lab because wildebeest herds or bird flocks would not be practical in New Haven. But it occurred that he assumed, as now the common view, that it did not matter which animal for the same independent mathematics are in play in every case.

Animal aggregations are visually striking, and as such are popular examples of collective behavior in the natural world. Quantitatively demonstrating the collective nature of such groups, however, remains surprisingly difficult. Inspired by thermodynamics, we applied topological data analysis to laboratory insect swarms and found evidence for emergent, material-like states. We show that the swarms consist of a core “condensed” phase surrounded by a dilute “vapor” phase. These two phases coexist in equilibrium, and maintain their distinct macroscopic properties even though individual insects pass freely between them. We further define a pressure and chemical potential to describe these phases, extending theories of active matter to aggregations of macroscopic animals and laying the groundwork for a thermodynamic description of collective animal groups. (Abstract)

Persistent homology is a method for computing topological features of a space at different spatial resolutions. More persistent features are detected over a wide range of length and are deemed more likely to represent true features of the underlying space, rather than artifacts of sampling, noise, or particular choice of parameters. In algebraic topology, the Betti numbers are used to distinguish topological spaces based on the connectivity of n-dimensional simplicial complexes. (Wikipedia)

Sinhuber, Raphael, et al. Self-organization in Natural Swarms od Synchronous Fireflies. Science Advances. 7/28, 2021. Biofrontiers Institute, University of Colorado biobehavior researchers including Orit Peleg provide a further sophisticated analysis via 3D perceptions of this coordinated phenomena which natural mathematic interactive rules organize. See also An Equation of State for Insect Swarms by Michael Sinhuber, et al in Nature Scientific Reports (11/3773, 2021.)

Fireflies flashing is a sure sign of animal collective behavior and biological synchrony. To elucidate synchronization mechanisms and inform theoretical models, we recorded the collective display of thousands of Photinus carolinus fireflies in natural swarms. At low firefly density, flashes appear uncorrelated. At high density, the swarm produces synchronous flashes within periodic bursts. Our results suggest that fireflies interact through a dynamic network of visual connections defined by terrain and vegetation. This model illuminates how a certain environment shapes self-organization and collective behavior. (Sarfati abstract excerpt)

Collective behaviour in flocks, crowds, and swarms occurs throughout the biological world. Animal groups are generally assumed to be adapted by evolution to achieve vital functions, so there is much interest for bio-inspired usages. Here we show that collective groups can be described by a thermodynamic framework and define a set of state variables and an equation of state for midge swarms. Our findings provide a new way of quantifying collective groups so to serve future bio-engineering design. (Sinhuber abstract excerpt)

Sivaram, Abhishek and Venkat Venkatasubramanian. Arbitrage Equilibrium, Invariance, and the Emergence of Spontaneous Order in the Dynamics of Birds Flocking. arXiv:2207.13743. A Columbia University PhD student and a senior chemical engineering professor contribute systemic insights into the independent formative forces that engender these natural topologies. See also A Unified Theory of Emergent Equilibrium Phenomena in Active and Passive Matter by Venkat V., et al (2206.09096) which adds a “statistical teleodynamics” quality, and Dynamics of Swarmalators by Gourab Sar and Dibakar Ghosh (2206.09096) for a similar contribution.

Active biological matter, such as bacterial colonies and bird flocks, is being found to exhibit self-organized dynamical behavior via inputs from hydrodynamics, kinetic theory, and non-equilibrium statistical physics. But for biological agents, these methods do not recognize the vital feature of survival-driven purpose and the pursuit of maximum utility. Here, we propose a novel game-theoretic framework to find that the bird-like agents self-organize into flocks so to approach a stable arbitrage equilibrium of equal effective utilities. Our theory is not limited to just birds flocking but can be adapted for the self-organizing dynamics of other active matter systems. (Abstract excerpt)

This kind of universality is particularly striking, which prompts us to close with an apropos quote from the Richard Feynman: ”Nature uses only the longest threads to weave her patterns, so that each small piece of her fabric reveals the organization of the entire tapestry.” It appears that the emergence of spontaneous order via self-organizing stable arbitrage equilibria is such a thread. (8)

Sober, Elliott and David Sloan Wilson. Unto Others: The Evolution and Psychology of Unselfish Behavior. Cambridge, Harvard University Press, 1998. Carefully-reasoned philosophical and scientific arguments for reciprocal altruism among members of a society and a consequent group selection.

Solomatin, Sergey, et al. Implications of Molecular Heterogeneity for the Cooperativity of Biological Macromolecules. Nature Structural & Molecular Biology. 18/6, 2011. Stanford University biochemists seek to accord such molecular diversities with a perceived organismic penchant for mutual associations. An “atomic-level mechanistic understanding” of “cooperative behaviors” is advanced toward an explanation. Our interest is to note a perception even at this rudimentary phase of the presence of these reciprocal activities.

Cooperativity, a universal property of biological macromolecules, is typically characterized by a Hill slope, which can provide fundamental information about binding sites and interactions. We demonstrate, through simulations and single-molecule FRET (smFRET) experiments, that molecular heterogeneity lowers bulk cooperativity from the intrinsic value for the individual molecules. As heterogeneity is common in smFRET experiments, appreciation of its influence on fundamental measures of cooperativity is critical for deriving accurate molecular models. (Abstract) In conclusion, we have demonstrated, through simulation and the first reported experimental single-molecule titrations, how molecular hetrogeneity distorts cooperativity observed in ensemble measurements.

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