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Current Research Projects

Complex decision making in the slime mould Physarum polycephalum

I am interested in the decision making capabilities of slime moulds. Slime moulds, which are unicellular, lack brains. Nevertheless, we have recently shown that these simple organisms are capable of  flexible and complex behaviours. 

For more information, please see:

Reid, C. R., Latty, T., Dussutour, A. & Beekman, M. 2012. Slime mold uses an externalized spatial “memory” to navigate in complex environments. Proceedings of the National Academy of Sciences. Early Edition

Latty, T.
& Beekman, M. 2010 Speed–accuracy trade-offs during foraging decisions in the acellular slime mould Physarum polycephalum. Proceedings of the Royal Society B: Biological Sciences.


Latty, T. & Beekman, M. 2010 Irrational decision-making in an amoeboid organism: transitivity and context-dependent preferences. Proceedings of the Royal Society B: Biological Sciences.

 Dussutour,A, Latty,TM, Beekman,M and Simpson SJ. Amoeboid organism solves complex nutritional challenges. In press, Proceedings of the National Academy of Sciences.

 Latty,TM and Beekman, M (2009). Food quality affects search strategy in the acellular slime mould, Physarum polycephalum. Behavioural Ecology 20: 1160 - 1167 :

 Latty, TM and Beekman, M (2009). Food quality, hunger and the risk of light exposure effect patch choice decisions in the acellular slime mould Physarum polycephalum  Ecology 91:22-27




Dynamic problem solving in self-organised biological systems

 The goal of this project is to understand how self-organized natural systems are able to solve problems in dynamic environments. For example, bee colonies can adapt to changes in nectar concentration by re-allocating their workforce. Amazingly, they do this without designated leaders.  I am investigating the mechanisms that underlie dynamic decision making in three different self-organised systems: ants, bees and slime moulds. This project is part of an international collaboration between the labs of Dr. Madeleine Beekman, Dr. Martin Middendorf, Dr. David Sumpter and Dr. Toshi Nakagaki.

For more more information see:

Latty, T and Beekman,M. Keeping track of changes: foraging performance of ant colonies in dynamic environments. Animal Behaviour, in press.

Reid, C.R., Latty,T. & Beekman, M.  Making a trail: Informed Argentine ants lead colony to the best food by U-turning coupled with enhanced pheromone-laying. Animal Behaviour , in press

Granovskiy,B, Latty,T; Duncan,M; Sumpter, D J.T,  Beekman, M 2012. How dancing honey bees keep track of changes: the role of inspector bees. Behavioural Ecology, 23, 588-596.




Self-organised transportation networks in ants

I am interested in the structure, function and development of ant transportation networks. Human engineers and urban planners face the task of designing efficient and cost effective networks. Since  building longer roads/tracks requires more resources  (and is therefore more costly), a challenge for engineers is to design transportation networks that minimise resource use while still maintaining connectivity between cities, stations etc.  Similar problems are faced by ant colonies which build trail networks to connect multiple nests to many food sources. How do ants 'design' transportation networks in the absence of centralised control? What, if anything, do ants optimise when building networks?   This work has been done in close collaboration with computer scientist Kai Ramsch at the University of Leipzig.

For more information, please see

Latty, T., Ramsch, K., Ito, K., Nakagaki, T., Sumpter, D. J. T., Middendorf, M. & Beekman, M. Structure and formation of ant transportation networks. Journal of The Royal Society Interface.



Picture of ant network between three nests. The inset shows the shortest possible network (Steiner tree). Way to go ants!
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