A Comparison between Mouse,In Silico, and Robot Odor Plume Navigation Reveals Advantages of Mouse Odor Tracking

Abstract

Localization of odors is essential to animal survival, and thus animals are adept at odor navigation. In natural conditions animals encounter odor sources in which odor is carried by air flow varying in complexity. We sought to identify potential minimalist strategies that can effectively be used for odor-based navigation and asses their performance in an increasingly chaotic environment. To do so, we compared mouse, in silico model, and Arduino-based robot odor-localization behavior in a standardized odor landscape. Mouse performance remains robust in the presence of increased complexity, showing a shift in strategy towards faster movement with increased environmental complexity. Implementing simple binaral and temporal models of tropotaxis and klinotaxis, an in silico model and Arduino robot, in the same environment as the mice, are equally successful in locating the odor source within a plume of low complexity. However, performance of these algorithms significantly drops when the chaotic nature of the plume is increased. Additionally, both algorithm-driven systems show more successful performance when using a strictly binaral model at a larger sensor separation distance and more successful performance when using a temporal and binaral model when using a smaller sensor separation distance. This suggests that with an increasingly chaotic odor environment, mice rely on complex strategies that allow for robust odor localization that cannot be resolved by minimal algorithms that display robust performance at low levels of complexity. Thus, highlighting that an animal's ability to modulate behavior with environmental complexity is beneficial for odor localization.

Using Head-Mounted Ethanol Sensors to Monitor Olfactory Information and Determine Behavioral Changes Associated with Ethanol-Plume Contact during Mouse Odor-Guided Navigation

“…A growing body of literature has focused on understanding the behavioral strategies for odor-source localization in freely moving mammals (Findley et al, 2020;Gire et al, 2016;Gumaste et al, 2020;Liu et al, 2020). However, correlating real-time olfactory information with behavior and physiological recordings from freely moving animals has been a challenging avenue due to the dynamic nature of the olfactory stimulus.…”

Plume dynamics structure the spatiotemporal activity of glomerular networks in the mouse olfactory bulb

“…Although inter-sniff comparisons in mice show that MT cells can detect the sign and magnitude of changes in odor concentration (Parabucki et al, 2019), it is unknown whether they are able to resolve the dynamics of natural plumes, which span across a range of temporal scales. If odor concentration dynamics are resolved, computational work has shown that they are informative for olfactory search ( (Baker et al, 2018); (Gumaste et al, 2020)). To avoid the complexity of stochastic odor plumes, the averaging of odor concentration dynamics could be an alternative strategy to navigate olfactory environments.…”

“…Mean odor concentration levels are moderated both by the distance from an odor source and how close an animal is to the central stream of the plume (Crimaldi and Koseff, 2001). While this measure is potentially informative, it does not by itself sufficiently inform decision-making on the timescale observed in rodents (Gumaste et al, 2020). Therefore, it is likely that the mouse relies upon spatiotemporal features of the plume for olfactory search as information can be extracted from odor concentration dynamics (Baker et al, 2018).…”

“…Mice are adept at localizing odor sources ( (Gire et al, 2016); (Baker et al, 2018); (Liu et al, 2019); (Gumaste et al, 2020)), but the spatiotemporal information in olfactory environments that aids this search behavior is unknown. Odors travel in plumes which pull odor away from its source in filaments that are broken and distorted as they travel in air, creating complex odor environments.…”

Spatial information from the odour environment in mammalian olfaction

“…The animal is rewarded after successfully navigating towards the port releasing odour. Bottom right: Time averaged and normalised PID recordings of odour from port 1 and 2 across the flow chamber (from Gumaste et al 2020). c Top: Schematic of two-dimensional odour plume tracking behaviour.…”