How ants move: individual and collective scaling properties

The behavior of social insects constitutes beautiful examples of adaptive collective dynamics born out of apparent purposeless individual behavior [1]. The richness of the phenomena offers plenty of opportunities to test theories dedicated to understand fascinating aspects of collective behavior.
An emergent issue is to dissect the dynamics that are routed on individual versus those explained by collective forces [2]. Recent work [3,4] found that ants' bursts of activity moving inside their colony's nest exhibit a power-law relation between the duration of the activity and its average speed. Successive motion events, defined as the segment of data between two consecutive motionless instances, was found to obey a universal speed shape profile. The authors concluded that this predictability implies that the duration of each ant movement is ``somehow determined before the movement itself'' [4] thus placing important weight into the individual ant's spontaneous behavior.
Here, we re-analyze data previously reported in [3], and reconsider the causation arrows, proposed at individual level, not finding any link between the duration of the ants’ activity and its moving speed. The observed scaling relation and universal speed profile is explained by a first-order Markov model taking into account of the fact that autocorrelation plays a strong role in animal movement processes. This model reproduces the observe patterns in synthetic trajectories where the observed “decisions” of individual ants at each time step are shuffled, thus deleting any predetermined individual plan about how long and fast it would be any given bout of motion.
Finally, we report a new observation in this type of data, dubbed here ``the more the faster'' effect; as more ants are in motion in the arena, the faster they move. This result is clearly a collective property, which is consistent with a number of theoretical ideas on trail formation. Overall these results provide a mechanistic explanation for the reported behavioral laws, and suggest a formal way to further study the collective properties in these scenarios.

Authors: 
Riccardo Gallotti and Dante Chialvo
Room: 
5
Date: 
Tuesday, September 25, 2018 - 17:45 to 18:00

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