Ethology and Cognition

Photo Credit: Jake Peters, Orit Peleg

We have a growing interest in exploring aspects of collective dynamics in extreme situations, e.g. collective dynamics of cell aggregates, and the behavior of super-organisms exemplified in the life of social insects.

A basic question here is not so much the plethora of patterns that they exhibit (which is not very surprising), but why they do so, and how they are regulated to achieve a modicum of functional efficiency. Patterns allow for the harnessing and control of matter, energy and information in space-time, and create micro-niches that are neither completely permeable nor completely insulated. Either extreme will not allow for function. Social insects are a great example to study these questions of homeorhesis because they occupy a range of ecological niches and are evolutionary experiments that work.  They also are not dissimilar to multicellular organisms with a division of labor, analogs of somatic and germlines, etc. And they can be studied in the lab and the field at multiple scales. We started with termite mounds in Namibia and India, and have since worked on bee clusters in our own Concord Field Station, and finally with ants and robots in the lab. By studying animals in their environment makes obvious the artificial nature of the arbitrary boundaries between the living and non-living – behavior changes the (micro)environment that then feeds back on the behavior … which we have measured and quantified in these different social insects.

Ethology and cognition at the individual and collective level has led us to start to study the mechanisms of information transmission via chemical, hydrodynamic and mechanical channels, while asking if we can build artificial analogs of these organisms, e.g. bristlebots and r(obotic) ants,  to understand what are the minimal rules that drive functional patterns that can sense, act, learn and adapt. At the level of individual organisms, we are interested in and have studied aspects of  object recognition via shape and size discrimination,  navigational tasks in insects, the statistical nature of geometric reasoning, detecting motion using the early warning signals embedded in fluctuating motion, etc.   A subject of particular interest is linking geometry, dynamics, and probability, in such humble examples as the coin toss and the ball throw, to such ethereal examples as the cognition of visual space and motion.


Related Publications

Collective mechanical adaptation of honeybee swarms O. Peleg, J. M. Peters, M. K. Salcedo and L. Mahadevan,  Nature Physics Letters , 2018. [View PDF] [Download PDF]
Collective ventilation in honeybee nests J.M. Peters, O. Peleg, L. Mahadevan, J. R. Soc, Interface 16: 20180561. 2019. [DOI] [View PDF] [Download PDF]
Collective thermoregulation in bee clusters S. Ocko and L. Mahadevan,  Journal of the Royal Society - Interface  11, 20131033, 2014. [View PDF] [Download PDF]
Morphogenesis of termite mounds S. A. Ocko , A. Heyde, and L. Mahadevan, PNAS 116(9) 3379-3384; published ahead of print February 11, 2019. [View PDF] [Download PDF]
Termite mounds harness diurnal temperature oscillations for ventilation
H. King, S. Ocko, and L. Mahadevan,  Proceedings of the National Academy of Sciences  112, 37, 11589–11593, 2015.  [View PDF] [Download PDF]
Feedback-nduced phase transitions in active heterogeneous conductors S.A. Ocko and L. Mahadevan,  Physical Review Letters  114, 134501, 2015. [View PDF] [Download PDF]
Swarming, swirling and stasis in sequestered bristle-bots. L. Giomi, N. Hawley-Weld and L. Mahadevan,  Proceedings of the Royal Society (A), (2012),  469, 20120637. [View PDF] [Download PDF]
A multiphase theory for spreading microbial swarms and films
S. Srinivasan, N.C. Kaplan, L. Mahadevan, eLife 8:e42697, 2019. [DOI] [View PDF] [Download PDF]
Early warning signals in motion inference. Y. Hart, M. Vaziri-Pashkam, and L. Mahadevan, PLOS Computational Biology, 16 (5), 2020. [DOI] [View PDF] [Download PDF]
The statistical shape of geometric reasoning Yuval Hart, Moira R. Dillon, Andrew Marantan, Anna L. Cardenas, Elizabeth Spelke & L. Mahadevan, Nature-Scientific Reports , 8:12906, 2018. [View PDF] [Download PDF]
Models for benthic bipedalism. F. Giardina and L. Mahadevan, Royal Society - Interface 18: 20200701, 2021. [ONLINE ARTICLE] [DOI] [View PDF] [Download PDF]
Self-organized biotectonics of termite nests. A. Heyde, L. Guo, C. Jost, G. Theraulaz and L. Mahadevan, Proceedings of the National Academy of Sciences, , 2021. [ONLINE ARTICLE] [DOI] [View PDF] [Download PDF]