Pheromone trails are of the most impressive and well known collective phenomena exhibited by ants. Such trails are the accumulated product of marking events by individual ants. In Paratrechina longicornis ants such events are easily recognizable using a side-view camera.

Fortunately, in this species the stereotypical pattern of motion that characterizes the deposition of a single scent mark could be identified using the ants speed profile as measured from a top-view.

This allowed is to achieve what might be the first, ever, depiction of the full dynamics of the formation of an ant pheromone trail. In the many years in which humans have been watching ant trails -  mainly a single kind of trail was observed – a long trail connecting two immobile points (typically the nest and the food source). Using our novel experimental methodologies for identifying pheromone laying we have discovered a new kind of ant trail. This trail connects the immobile nest and the mobile, carried food load. Correspondingly, this trail is very different from the classically described trails. Mainly, instead of designating the whole path between the food source and the nest this trail only marks the next short step in which the carrying team should move.

We further study the geometrical aspects of foraging trails in the ant Tapinoma Israeli.

Further reading:

  • Ehud Fonio, Yael Heyman, Lucas Boczkowski, Aviram Gelblum, Adrian Kosowski, Amos Korman and Ofer Feinerman. “A new kind of ant trail achieves efficient routing in error prone conditions.” eLife 5: e20185. (2016).


Ants’ nests are complex structures. While the exceptional navigation skills of ants have been (and still are) extensively studied, much less is known about the navigation inside the dark maze of their nests.


Combining individual tracking, chemical analysis, and machine learning we study how ants identify and maintain their preferred nest chambers. We find that chemical blends found on nest surfaces act as ‘road-signs’ that guide the ants’ movements within the dark nest. This stabilizes the ants’ spatial organization and facilitates colony coordination.


Using our dynamic nest-like setup, we create conflicting navigational cues and follow individual ants performing navigational tasks to unravel their intra-nest navigation strategy.


The ant nest is a pitch dark convoluted labyrinth. How do ants find their way around? We investigated this question in artificial lab nests by following ants returning brood items to the brood chamber under IR illumination. This video illustrates how, to decide, which turn she should take an ant uses her memory of the nest structure but later verifies her decision by relying on the scent marks adhered to her trail of choice.


Recruitment using unreliable interaction in the desert ant Cataglyphis niger. The ants employ early negative feedback on the group level to achieve reliable recruitment despite their low quality messaging abilities of these species.

Further Reading:

  • Heyman, Yael, Yael Vilk, and Ofer Feinerman. "Ants use multiple spatial memories and chemical pointers to navigate their nest." iScience 14 (2019): 264-276.
  • Yael Heyman, Noam Shental, Alexander Brandis, Abraham Hefetz, and Ofer Feinerman “Ants regulate colony spatial organization using multiple chemical road-signs”. Nature Communications. In press (2017).
  • Nitzan Razin, Jean-Pierre Eckmann, and Ofer Feinerman. "Desert ants achieve reliable recruitment across noisy interactions." Journal of the Royal Society Interface 10, no. 82 (2013): 20130079.


The vast majority of a colony, including the queen and brood, spend most of their time inside the nest, exclusively relying on food provided by a few workers who leave the nest to forage. Therefore, food-sharing between individuals is essential to ensure the colony’s survival.

Ants have a pre-digestive organ called the “crop” (often dubbed the “social stomach”), in which they can store food to later be regurgitated and shared with other ants through mouth-to-mouth feedings, termed “trophallaxis”.Thus, foragers bring liquid food in their crops, convey it to receiving colony-members in the nest, who further pass it on in an elaborate cascade of trophallactic events.

We study this process with a novel technique developed in our lab, which enables to link individual actions to collective outcomes. We visualize the food flow within colonies of individually barcoded ants that feed on fluorescently labeled food, simultaneously obtaining data on food loads of individual ants across time and space, interaction patterns between individuals, and the collective nutritional state of the colony.

From a biological perspective, we are interested in how collective food intake regulation emerges from individual behavior, how food distributes and mixes within the colony and how different food types can reach their appropriate destinations. From a functional perspective, we treat the ant trophallactic network as a natural distributed system, exploring its properties, functions and limitations.


Further reading:

  • Greenwald, Efrat, Jean-Pierre Eckmann, and Ofer Feinerman. "Colony entropy—Allocation of goods in ant colonies." PLoS computational biology 15.8 (2019).
  • Efrat Greenwald, Lior Baltiansky, and Ofer Feinerman "Individual crop loads provide local control for collective food intake in ant colonies." eLife 7 (2018): e31730.
  • Efrat Greenwald, Enrico Segre, and Ofer Feinerman. "Ant trophallactic networks: simultaneous measurement of interaction patterns and food dissemination." Scientific reports 5 (2015).





A prime example of ant coordination is known as Cooperative Transport: the carrying of a large food load by a group of foraging ants to the nest. This task is difficult as it requires the ants to coordinate their efforts, aligning the forces they apply so as to move the load in the direction of the nest.

Efficient carrying requires the ants to assume different roles during the carrying (pulling/lifting/pushing). Moreover, the ants need to be able to navigate while carrying despite suffering from impaired perception, as their antennae and vision are partially blocked.

A factor that helps the ants overcome these difficulties is the constant turnover of carrying ants at the load. While ants that have been carrying for a long time lose orientation those that have just attached to the load carry accurate information regarding the correct route to the nest. Indeed, informed individuals who join the carrying effort act as effective leaders and steer the entire group for a short periods of time.

Remarkably, the ant group can assimilate new incoming information even though the force a leader ant exerts is not particularly strong. We’ve further shown the ant-load system lies near a phase transition, balancing conformism and individuality; if the ants are over conformist and their pull efforts too aligned the resulting collective motion is smooth but the system remains unresponsive to new information. This scenario occurs if the ants carry unnaturally large items,On the other hand, excessive individuality, as happens for small load size, would result in a random-walk-like motion pattern.

Naturally sized loads exhibit a near optimal balance between coordinated forces and sensitivity to incoming information.

The conformism of cooperatively carrying ants imply that most ants do not pull the object towards the direction of the nest but, rather, in the direction in which it already happens to be moving. Tethering the load with a thin string this behavioral rule can result in a pendulum motion perpendicular to the direction to the nest.

Our model of this constrained system predicted another motion regime which consists of full rotations of the load. Surprisingly, experiments with a large number of ants verify the existence of this biologically counter-intuitive behavior.

In the 1970's Nobel prize Laureate Pierre-Gilles De Gennes suggested a conceptual model that describes particle transport through disordered systems. He named his model The "Ant-in-A-Labyrinth". Fifty years later we have realized this model using real ants. The X8 sped up video shows longhorn crazy ants (Paratrechina longicornis) that transport a large food item through a disordered cube array that mimics their natural stone-ridden environment. The ants cooperate to significantly outperform physical models of the kind originally described by De-Gennes.

For more details see:

  • Gelblum, Aviram, Ehud Fonio, Yoav Rodeh, Amos Korman, and Ofer Feinerman. "Ant collective cognition allows for efficient navigation through disordered environments." eLife 9 (2020): e55195
  • Ofer Feinerman, Itai Pinkoviezky, Aviram Gelblum, Ehud Fonio, and Nir S. Gov. "The Physics of Cooperative Transport In Groups of Ants". Nature Physics 14.7 (2018): 683-693.
  • Jonathan E. Ron, Itai Pinkoviezky, Ehud Fonio, Ofer Feinerman, and Nir S. Gov. "Bi-stability in cooperative transport by ants in the presence of obstacles". PLOS Computational Biology 14.5 (2018).
  • Aviram Gelblum, Itai Pinkoviezky, Ehud Fonio, Nir Gov, and Ofer Feinerman. “The Ant Pendulum: problem solving through an emergent oscillatory phase.” Proceedings of the National Academy of Sciences (PNAS). 113.51 (2016): 14615-14620 (2016).
  • Aviram Gelblum,Itai Pinkoviezky, Ehud Fonio, Abhijit Ghosh, Nir Gov, and Ofer Feinerman. "Ant groups optimally amplify the effect of transiently informed individuals." Nature communications 6 (2015).