LAUSR

Animals navigate by making a series of decisions using external stimuli and any internal model (or map) of the world they may have formed. Many animals, including ants, dogs, and rodents, spontaneously track scent trails, which are chemical cues that form navigational guides that allow animals to locate food, mates, and landmarks like their homes (1–6). Tracking odor trails is a nontrivial problem since cues are detected intermittently due to potential complexity of the trail as well as the nature of the sensory apparatus. Importantly, future locations of the trail are “invisible” and must be predicted based on current and past information (unlike in vision, where one can simply see the future locations). In PNAS, Reddy et al. (7) present a general algorithmic framework to understand odor trail tracking. Previous work in a variety of organisms ranging from insects to humans points to a characteristic zigzag movement over a scent trail (1, 2, 5). Such zigzag movements, or casting, have been described extensively in flying insects (8) and are thought to be part of their search strategies to discover the source of an odor. Casting movements are complemented by upwind surges upon odor detection (8). While purely odor-guided navigation has been discussed extensively, other sensory modalities may also play fundamental roles—for example, optomotor anemotaxis (8). Walking insects also exhibit odor-guided anemotaxis toward attractive odors, and there is an exciting surge in research on this behavior (9, 10). Trail tracking occurs under different constraints compared to windborne odor tracking, where turbulence leads to highly dynamic odor landscapes, unlike the more stable odor distribution in trails— some exceptions include so-called plume tracking, where the plume can be thought of as a trail (11–14). Dogs and wolves can track trails with remarkable accuracy over long distances, perhaps even for miles (6, 15). Intuitively, tracking is composed of an initial A