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Odours released by objects in natural environments can contain information about their spatial locations. In particular, the correlation of odour concentration timeseries produced by two spatially separated sources contains information about the distance between the sources. For example, mice are able to distinguish correlated and anti-correlated odour fluctuations at frequencies up to 40 Hz, while insect olfactory receptor neurons can resolve fluctuations exceeding 100 Hz. Can this high-frequency acuity support odour source localization? Here we answer this question by quantifying the spatial information about source separation contained in the spectral constituents of correlations. We used computational fluid dynamics simulations of multisource plumes in two-dimensional chaotic flow environments to generate temporally complex, covarying odour concentration fields. By relating the correlation of these fields to the spectral decompositions of the associated odour concentration timeseries, and making simplifying assumptions about the statistics of these decompositions, we derived analytic expressions for the Fisher information contained in the spectral components of the correlations about source separation. We computed the Fisher information for a broad range of frequencies and source separations for three different source arrangements and found that high frequencies were more informative than low frequencies when sources were close relative to the sizes of the large eddies in the flow. We observed a qualitatively similar effect in an independent set of simulations with different geometry, but not for surrogate data with a similar power spectrum to our simulations but in which all frequencies werea prioriequally informative. Our work suggests that the high-frequency acuity of olfactory systems may support high-resolution spatial localization of odour sources. We also provide a model of the distribution of the spectral components of correlations that is accurate over a broad range of frequencies and source separations. More broadly, our work establishes an approach for the quantification of the spatial information in odour concentration timeseries. 

Mice navigate an odor plume with a complex spatiotemporal structure in the dark to find the source of odorants. This article describes a protocol to monitor behavior and record Ca2+ transients in dorsal CA1 stratum pyramidale neurons in hippocampus (dCA1) in mice navigating an odor plume in a 50 cm x 50 cm x 25 cm odor arena. An epifluorescence miniscope focused through a GRIN lens imaged Ca2+ transients in dCA1 neurons expressing the calcium sensor GCaMP6f in Thy1-GCaMP6f mice. The paper describes the behavioral protocol to train the mice to perform this odor plume navigation task in an automated odor arena. The methods include a step-by-step procedure for the surgery for GRIN lens implantation and baseplate placement for imaging GCaMP6f in CA1. The article provides information on real-time tracking of the mouse position to automate the start of the trials and delivery of a sugar water reward. In addition, the protocol includes information on using of an interface board to synchronize metadata describing the automation of the odor navigation task and frame times for the miniscope and a digital camera tracking mouse position. Moreover, the methods delineate the pipeline used to process GCaMP6f fluorescence movies by motion correction using NorMCorre followed by identification of regions of interest with EXTRACT. Finally, the paper describes an artificial neural network approach to decode spatial paths from CA1 neural ensemble activity to predict mouse navigation of the odor plume. 

In order to survive, animals often need to navigate a complex odor landscape where odors can exist in airborne plumes. Several odor plume properties change with distance from the odor source, providing potential navigational cues to searching animals. Here, we focus on odor intermittency, a temporal odor plume property that measures the fraction of time odor is above a threshold at a given point within the plume and decreases with increasing distance from the odor source. We sought to determine if mice can use changes in intermittency to locate an odor source. To do so, we trained mice on an intermittency discrimination task. We establish that mice can discriminate odor plume samples of low and high intermittency and that the neural responses in the olfactory bulb can account for task performance and support intermittency encoding. Modulation of sniffing, a behavioral parameter that is highly dynamic during odor-guided navigation, affects both behavioral outcome on the intermittency discrimination task and neural representation of intermittency. Together, this work demonstrates that intermittency is an odor plume property that can inform olfactory search and more broadly supports the notion that mammalian odor-based navigation can be guided by temporal odor plume properties. 

Insects rely on their olfactory system to forage, prey, and mate. They can sense odor emitted from sources of their interest, use their highly efficient flapping-wing mechanism to follow odor trails, and track down odor sources. During such an odor-guided navigation, flapping wings not only serve as propulsors for generating lift and maneuvering, but also actively draw odors to the antennae via wing-induced flow. This helps enhance olfactory detection by mimicking “sniffing” in mammals. However, due to a lack of quantitative measuring tools and empirical evidence, we have a poor understanding of how the induced flow generated by flapping kinematics affects the odor landscape. In the current study, we designed a canonical simulation to investigate the impact of flapping motion on the odor plume structures. A sphere was placed in the upstream and releases odor at the Schmidt number of 0.71 and Reynolds number of 200. In the downstream, an ellipsoidal airfoil underwent a pitch-plunge motion. Both two- and three-dimensional cases are simulated with Strouhal number of 0.9. An in-house immersed-boundary-method-based CFD solver was applied to investigate the effects of flapping locomotion on the wake topology and odor distribution. From our simulation results, remarkable resemblances were observed between the wake topology and odor landscape. For the 2D case, an inverse von Kármán vortex street was formed in the downstream. For the 3D case, the wake bifurcates and forms two branches of horseshoe-like vortices. The results revealed in this study have the potential to advance our understanding of the odor-tracking capability of insects navigation and lead to transformative advancements in unmanned aerial devices that will have the potential to greatly impact national security equipment and industrial applications for chemical disaster, drug trafficking detection, and GPS-denied indoor environment.