How does group composition influence collective sensing and decision making?
Decentralized systems are composed of individual units which must coordinate their behavior for the system to function as a whole. This can refer to many different levels of biological organization, from cellular to organismal, but also to human societies and technological systems. Two common aspects of decentralized systems are that individuals differ in their behavior, and that the group's response depends on efficient aggregation of many individual responses, each of which is made based only on locally available information.
Epithelial cells and honey bee colonies are two biological systems that use decentralized collective sensing algorithms. Epithelial cells are the cells that layer the body’s organs and must coordinate their behaviour to maintain healthy tissue. During wound healing, certain cells switch their phenotype to that of a "leader" cell, which differs from others in physical composition and morphology. These leader cells guide other cells to close a wound. Honey bees are eusocial insects that allocate tasks among different group members in response to current conditions and colony needs. For example, when nectar is plentiful in the surrounding environment, foragers must quickly capitalize on nectar collection, while middle aged bees in the hive must offload and process the incoming nectar.
In both cells and bees, individuals differ in their behavior, and alter their behavioral phenotype based on factors that are are beyond the scale of any single individual. How do cells sense the motion state of the group with respect to the wound geometry, to “decide” which cells will become leaders? How do bees inside the colony detect and respond to environmental changes that only the foragers have experienced directly? In this project we will use these two model experimental systems to make a comparison of collective sensing and group behavior mechanisms, with a focus on 3 main questions:
- how individuals in the group differ from each other,
- what factors drive task/type differentiation, and
- how group composition affects function and response to external perturbations.
M Vishwakarma, J Di Russo, D Probst, US Schwarz, T Das and JP Spatz (2018): Mechanical Interactions among Followers Determine the Emergence of Leaders in Migrating Epithelial Cell Collectives. Nature Communications 9(1): 3469. https://doi.org/10.1038/s41467-018-05927-6
JD Davidson and DM Gordon (2017): Spatial Organization and Interactions of Harvester Ants during Foraging Activity. Journal of The Royal Society Interface 14(135): 20170413. https://doi.org/10.1098/rsif.2017.0413
ML Smith, PA Koenig, and JM Peters (2017): The Cues of Colony Size: How Honey Bees Sense That Their Colony Is Large Enough to Begin to Invest in Reproduction. Journal of Experimental Biology 220(9), 1597–1605. https://doi.org/10.1242/jeb.150342
JD Davidson, RP Arauco-Aliaga, S Crow, DM Gordon, and MS Goldman (2016): Effect of Interactions between Harvester Ants on Forager Decisions. Frontiers in Ecology and Evolution 4(115). https://doi.org/10.3389/fevo.2016.00115
ML Smith, MM Ostwald, and TD Seeley (2016): Honey Bee Sociometry: Tracking Honey Bee Colonies and Their Nest Contents from Colony Founding until Death. Insectes Sociaux 63(4): 553–63. https://doi.org/10.1007/s00040-016-0499-6
Publications Funded by the Project
M Vishwakarma and J Di Russo (2019): Why Does Epithelia Display Heterogeneity? Bridging Physical and Biological Concepts. Biophysical Reviews 11(5): 683–87. https://doi.org/10.1007/s12551-019-00583-6
ML Smith, JD Davidson, B Wild, D Dormagen, T Landgraf, and ID Couzin (2019): Lifetime Tracking of Bees Reveals Individual-Level Variability in Nest Use with Age. Proceedings of the 3rd International Symposium on Swarm Behaviour and Bio-Inspired Robotics (Swarm 2019).
Michael L. Smith, PhD
Jacob D. Davidson, PhD
Dr. Medhavi Vishwakarma, PhD
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