anTraX: high throughput video tracking of color-tagged insects

Abstract

Recent years have seen a surge in methods to track and analyze animal behavior. Nevertheless, tracking individuals in closely interacting, group-living organisms remains a challenge. Here we present anTraX, an algorithm and software package for high-throughput video tracking of color-tagged insects. anTraX combines neural network classification of animals with a novel approach for representing tracking data as a graph, enabling individual tracking even in cases where it is difficult to segment animals from one another, or where tags are obscured. The use of color tags, a well-established and robust method for marking individual insects in groups, relaxes requirements for image size and quality, and makes the software broadly applicable. anTraX is readily integrated into existing tools and methods for automated image analysis of behavior to further augment its output. anTraX can handle large-scale experiments with minimal human involvement, allowing researchers to simultaneously monitor many social groups over long time periods.

Colony expansions underlie the evolution of army ant mass raiding

“…We therefore systematically studied foraging behavior in the clonal raider ant, Ooceraea biroi, the only non-army ant doryline that can be propagated in the laboratory. In our efforts to establish this species as an experimental model, we have developed high-throughput, automated tracking approaches to monitor individual and collective behavior (Gal et al, 2020;Ulrich et al, 2018). This created the unique opportunity to study doryline foraging behavior quantitatively and under controlled laboratory conditions.…”

“…Each colony consisted of 25 ants, and each ant was tagged with an ordered pair of color dots that was unique within the colony. Specifically, each ant was painted on her thorax and gaster with one of five colors of oil-paint markers (uni Paint Markers PX-20 and PX-21), a previously-used technique (Gal et al, 2020;Trible et al, 2017;Ulrich et al, 2018). At the end of the experiment, we counted all larvae, and found that each colony had between 20 and 25 larvae.…”

“…Videos from this experiment were processed using anTraX (Gal et al, 2020) to produce the spatial (xy) coordinates of each ant in the colony during each of the events. Tracking quality was quantified using the assignment error (see (Gal et al, 2020) for definition) for each colony and each event separately.…”

“…Videos from this experiment were processed using anTraX (Gal et al, 2020) to produce the spatial (xy) coordinates of each ant in the colony during each of the events. Tracking quality was quantified using the assignment error (see (Gal et al, 2020) for definition) for each colony and each event separately. As in the context of this paper we have used individual trajectories for the analysis of the recruitment and response phases, we have quantified the assignment error in the time period starting just before start of recruitment phase and ending just after the end of the response phase.…”

“…As tracking the ants in the dense chamber is impractical, we used an alternative approach to understand the recruitment dynamics in the nest. We subtracted each frame in the video from the background image (an image which includes all image features, but without the ants; see (Gal et al, 2020) for the procedure used to generate these images), and converted it to gray scale. As ants are darker than the background, the value of each pixel, * , in this image was taken as the probability that it contains an ant.…”