Bulletin of the American Physical Society
APS March Meeting 2022
Volume 67, Number 3
Monday–Friday, March 14–18, 2022; Chicago
Session M03: Physics of Social Interactions IFocus Recordings Available
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Sponsoring Units: DBIO Chair: Orit Peleg, University of Colorado Boulder Room: McCormick Place W-176A |
Wednesday, March 16, 2022 8:00AM - 8:12AM |
M03.00001: Collective sensing in the slime mold Physarum polycephalum Albert Kao, Andrew Berdahl Collective sensing (the enhanced ability of groups to track features of the environment) is one of the most common benefits of group living. Acting as a distributed sensing array, an animal group may access more information from the environment and therefore make improved decisions. While collective sensing has been observed in many social animal species, it is less well understood in non-animals, such as plant roots, fungal networks, and slime molds, where their physical structure and mechanism of information transfer may be quite different than in ‘classic’ collective systems, such as bird flocks and fish schools. Here, we test whether the slime mold Physarum polycephalum benefits from collective sensing by recording samples, varying in size, traveling across a surface containing a chemical gradient. We find that, indeed, the ability to detect and follow the environmental gradient improves with the size of the slime mold. A simulation model of slime mold behavior recapitulates our experimental results. Together, our results shed light on the robustness of collective benefits despite significant differences in the details of the collective systems themselves. |
Wednesday, March 16, 2022 8:12AM - 8:24AM |
M03.00002: Competition for fluctuating resources reproduces statistics of species abundance over time across wide-ranging microbiotas Kerwyn C Huang Across diverse microbiotas, species abundances vary in time with distinctive statistical behaviors that appear to generalize across hosts, but the origins and implications of these patterns remain unclear. Here, we show that many of these patterns can be quantitatively recapitulated by a simple class of consumer-resource models, in which the metabolic capabilities of different species are randomly drawn from a common statistical ensemble. Our coarse-grained model parametrizes the consumer-resource properties of a community using only a small number of macroscopic parameters, including the total number of resources, typical resource fluctuations over time, and the average overlap in resource-consumption profiles across species. We elucidate how variation in these parameters affects various time series statistics, enabling the estimation of macroscopic parameters and their comparison across wide-ranging microbiotas, including the human gut, saliva, and vagina, as well as mouse gut and rice. The successful recapitulation of time series statistics across microbiotas suggests that resource competition may be a dominant driver of community dynamics. Our work unifies numerous time series patterns under one model, clarifies their origins, and provides a framework to infer parameters of effective resource competition from longitudinal studies of microbial communities. |
Wednesday, March 16, 2022 8:24AM - 9:00AM |
M03.00003: Inside the Canine Mind Invited Speaker: Alexandra Horowitz Dog cognition research aims to look at behavior of this gregarious species Canis familiaris to understand something about their minds -- especially elements of their psychology analogous to our own. I will describe the arm of our Lab's research which looks at social interactions between dogs and others, such as conspecifics or humans. We examine rough-and-tumble dyadic dog play, a fertile context to consider social behavior, as it is ubiquitous, familiar, and spontaneously occurring. What might seem to be a continuous, unitary behavior is, upon examination, an elaborate dance between play partners. I discuss one way that ethologists have carved play -- intraspecific as well as interspecific -- at its joints, and propose it as a model for a computational approach. I also describe social behavioral tasks from our lab's research into the attributions of emotions that people make to dogs in interaction with them, such as of their "guilt" or "jealousy." I also touch on the relevance of physical processes in these social encounters. |
Wednesday, March 16, 2022 9:00AM - 9:12AM |
M03.00004: Weight distribution in honey bee swarms Olga Shishkov, Claudia Chen, Claire Madonna, Alexander Lawson, Kaushik Jayaram, Orit Peleg The western honey bee (Apis mellifera) is a domesticated pollinator famous for living in highly social colonies. In the spring, thousands of worker bees and a queen self-assemble into a swarm that hangs from a tree branch for several days while worker bees scout for a new hive location. How bees are arranged within the swarm to distribute forces and optimize internal conditions is, so far, not well understood, since the majority of bees are hidden within the swarm. We reconstruct the non-isotropic arrangement of worker bees inside swarms made up of 3000 - 10000 bees using x-ray computed tomography. We find that the structure of the swarm is non-homogeneous. Some bees form stationary layers near the attachment board and scaffold-like chains throughout the swarm. The cross-sectional area of the swarm and packing density of bees within it distributes the weight such that the top layer of bees supports the most weight without overloading individual bees. The remaining bees use the chains as pathways to walk around the swarm, potentially to feed the queen or communicate with one another. This internal structure allows the swarm to protect the queen and adapt to the changing environment, and leaves scout bees free to investigate potential new hives. |
Wednesday, March 16, 2022 9:12AM - 9:24AM |
M03.00005: Coordination Without Communication in Fire-Ant Excavation Ram Avinery, Kehinde Aina, Carl J Dyson, Hui-Shun Kuan, Meredith D Betterton, Michael A Goodisman, Daniel I Goldman Many social animals, such as ants, are millimeters in scale and collectively dig meter scale nests in diverse substrates. To discover principles by which fire ant [S. invicta] collectives self-organize to excavate their crowded narrow (body-length) self-generated tunnels, we recorded 48 hour videos of groups of 40-70 ants digging in a quasi-two-dimensional system 14×21×0.25 cm3 composed of slightly wet 700 um glass beads. Excavation proceeded in three stages: an initial constant rate lasting approximately an hour followed by a rapid decay in rate, and finally a slower decay scaling in time as t-1/2. To understand such scaling and motivate how such rate modulation emerges without global control avoiding deleterious traffic clogs, we use a cellular automata model with multiple tunnels. In the model ants can count collisions with other ants, but otherwise do not directly communicate; this minimal model reproduces the observed excavation stages. A scaling argument assuming a constant number of workers and no collisions rationalizes the final t-1/2 scaling. This study furthers our understanding of how insect societies work together to regulate the early stages of nest construction in which getting below ground quickly protects against challenging environments and predation. |
Wednesday, March 16, 2022 9:24AM - 9:36AM |
M03.00006: A deep learning approach to quantify aggression between competing ant colonies Kevin G Do, Amisha Jain, Robert Riehn A social insect colony can be viewed as a superorganism that collectively processes and responds to environmental stimuli and even other competing superorganisms, despite the limited access to information of individual workers. While the dynamic networks within superorganisms have received considerable attention, less is known about interacting superorganisms. A fascinating example of the latter can be seen in colonies of the red imported fire ant (S. invicta), one of the few highly invasive species known to harbor intraspecies aggression. Studies have suggested that inter-colony aggression can be particularly sensitive to factors such as colony size, nestmate density and environmental parameters. However, conventional aggression bioassays have typically been limited to small numbers of individuals. In this study, we assembled a deep learning pipeline to track posture sequences of individual ants and infer their behavioral ‘states’ through high-resolution video. We applied the pipeline to investigate the effects of inter-colony separation on the frequency of aggression between two competing fire ant colonies. Our results confirm that the modulation of aggression between ant societies is contextual and more nuanced than previously thought. |
Wednesday, March 16, 2022 9:36AM - 9:48AM |
M03.00007: Inferring collective dynamics in groups of social mice Xiaowen Chen, Maciej Winiarski, Alicja Puścian, Ewelina Knapska, Thierry Mora, Aleksandra M Walczak Social interactions are a crucial aspect of behavior in many animal species. Nonetheless, it is often difficult to distinguish the effect of interactions from independent animal behavior (e.g. non-Markovian dynamics, response to environmental cues, etc.). In this talk, I will address this question in social mice, where we infer statistical physics models for the collective dynamics for groups of 15 mice, housed and location-tracked over multiple days in a controlled environment (the Eco-HAB [Puścian et al. 2016]). We reproduce the distribution for the co-localization patterns using pairwise maximum entropy models, and find that the resulting local fields successfully predict the transition rates. I will also discuss progress towards developing novel inference methods with memory, which while giving consistent equilibrium distribution as the maximum entropy models, also capture dynamical observables, e.g. long-tailed waiting time distributions, and that mice actively follow each other. We show that in the case of social mice, both individuality and interaction with peers are essential to give the observed co-localization patterns. |
Wednesday, March 16, 2022 9:48AM - 10:00AM |
M03.00008: Signatures of irreversibility in microscopic models of flocking Federica Ferretti, Caroline Holmes, Jordan L Shivers, Simon B Grosse-Holz, Irene Giardina, Aleksandra M Walczak, Thierry Mora Flocking is one of the most startling collective behaviors in active matter. The emergence of collective motion in d=2 occurring in these systems is a genuine non-equilibrium feature. It marks a fundamental difference with classical passive models for ferromagnets and requires irreversibility. |
Wednesday, March 16, 2022 10:00AM - 10:12AM |
M03.00009: Synchronization dynamics of firefly-LED systems Owen Martin, Orit Peleg, Raphael Sarfati, Julie Hayes Firefly communication in mating swarms results in synchronized flash behavior for two North American species, Photinus carolinus and Photuris frontalis. This collective behavior produces characteristic flash patterns with continuous or intermittent structure, depending on the species. Understanding the interaction dynamics between small groups of individuals that yields this swarm-level emergent behavior may be important in designing systems of autonomous agents that communicate using low-cost light signals. Using controlled density experiments where small groups of fireflies are exposed to rhythmic, controlled LED flashes in dark tents, we examine the range of artificial flash frequencies that produce aligned phase responses from the fireflies. In both species, we unveil a specific and narrow range of flash frequencies to which individual and small groups of fireflies can successfully entrain. Finally, we demonstrate a minimal set of group conditions sufficient for synchrony at small densities. In both species, the characteristic synchronization patterns can be rapidly induced in individual fireflies by exposing them to artificial light patterns simulating a group of four individuals. |
Wednesday, March 16, 2022 10:12AM - 10:24AM |
M03.00010: The exploitative segregation of plant roots: a game-theoretical framework for belowground plant interactions. Ricardo Martinez Garcia, Ciro Cabal, Aurora de Castro, Fernando Valladares, Stephen W Pacala, Gabriel Andreguetto Maciel Plant roots determine carbon uptake, survivorship, and agricultural yield and represent a large proportion of the world’s vegetation carbon pool. The study of below-ground competition, unlike above-ground competition, is hampered by our inability to observe roots. We have few observations of intact root systems in soil and lack a comprehensive theory for root system responses to their environment and the presence of other individuals. In this presentation, I will first review previous efforts to explain plant below-ground interactions and discuss how they lead to seemingly contradictory predictions. Then, I will introduce our recent work and show how it resolves existing controversy and provides a unifying framework to study below-ground plant interactions. I will conclude by discussing future research lines that depart from our results, how they can be addressed with extensions of our original model, and how to test them experimentally. |
Wednesday, March 16, 2022 10:24AM - 10:36AM |
M03.00011: Identifying interaction epochs in social behavior: contest phases in pairwise zebrafish fights Liam G O'Shaughnessy, Tatsuo Izawa, Joshua W Shaevitz, Greg J Stephens Animals engage in pairwise fighting behavior to settle dominance disputes. As a model social behavior, fighting is of particular interest due to the strong interactions between individuals and the richness of the social tasks they are attempting to solve. Contests often contain discrete phases of escalating aggression, each of which contains a set of stereotyped dynamics. Fights start with non-physical displays, can proceed to physical attacks, and end with asymmetric dominance behaviors. Here we present our work in identifying these phases in adult zebrafish fights on multiple timescales. We track fish bodypoints in 3D and identify the three main phases of the contest. Within the physical attack phase, we uncover short-time multi-animal behavioral motifs that the fish use to establish dominance. |
Wednesday, March 16, 2022 10:36AM - 10:48AM |
M03.00012: SubCellular model to study Bacterial - Fungal interaction Alireza Ramezani, Jolene Britton, Francesco Pancaldi, Kevin Tsai, Dale Pelletier, Mark Alber, William Cannon Bacteria and complex fungal networks can interact beneficially with one another and create an environmental niche. The fungus Laccaria bicolor synthesizes trehalose which is a nutrient for the chemotactic bacteria Psuedomonas fluorescens. Trehalose can serve as an energy source to allow the bacteria to move and explore new environments using their flagella in the liquid medium surrounding the fungal network. P.flourescens provides L. Bicolor with thiamine that promotes fungal growth thereby increasing fungal mass. In this work, we focus on interactions between P.flourescens and the fungi L.bicolor. We used Sub-Cellular Element model to describe and simulate the motion of bacteria and the interactions between bacteria and the environment. The movement mechanics of the bacteria, including run-reverse, flick, and the frequency of reversals motion, are all influenced by a gradient of a chemoattractant. Each bacteria moves in a random direction after each reversal occurs. But the presence of fungal-secreted chemoattractants, especially from the tips of the hyphae, acts to direct the interaction between bacteria and fungi network. In this study, we observed that following the hyphae increases the efficiency of bacteria movement and aggregation toward the source of the chemoattractant. |
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