Mouse Navigation Strategies for Odor Source Localization

Uncertainty and anxiety: Evolution and neurobiology

Anxiety is a complex phenomenon: Its eliciting stimuli and circumstances, component behaviors, and functional consequences are only slowly coming to be understood. Here, we examine defense systems from field studies; laboratory studies focusing on experimental analyses of behavior; and, the fear conditioning literature, with a focus on the role of uncertainty in promoting an anxiety pattern that involves high rates of stimulus generalization and resistance to extinction. Respectively, these different areas provide information on evolved elicitors of defense (field studies); outline a defense system focused on obtaining information about uncertain threat (ethoexperimental analyses); and, provide a simple, well-researched, easily measured paradigm for analysis of nonassociative stress-enhanced fear conditioning (the SEFL). Results suggest that all of these-each of which is responsive to uncertainty-play multiple and interactive roles in anxiety. Brain system findings for some relevant models are reviewed, with suggestions that further analyses of current models may be capable of providing a great deal of additional information about these complex interactions and their underlying biology.

Miniscope Recording Calcium Signals at Hippocampus of Mice Navigating an Odor Plume

Mice are able to navigate an odor plume with a complex spatiotemporal structure in the dark to find the source of odorants. We developed a protocol to monitor behavior and record Ca 2+ transients in dorsal CA1 stratum pyramidale neurons at the hippocampus (dCA1) in mice navigating an odor plume in a 50 cm x 50 cm x 25 cm odor arena. Ca 2+ transients were imaged by an epifluorescence miniscope focused through a GRIN lens on dCA1 neurons expressing the calcium sensor GCaMP6f in Thy1-GCaMP6f mice. We describe the behavioral protocol to train the mice to perform this odor plume navigation task in an automated odor arena. We provide the step-by-step procedure for the surgery for GRIN lens implantation and baseplate placement for imaging GCaMP6f in CA1. We provide 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, we provide information on the use of an Intan board to synchronize metadata describing the automation of the odor navigation task and frame times for the miniscope and a FLIR camera tracking mouse position. Moreover, we delineate the pipeline used to process GCaMP6f fluorescence movies by motion correction using NorMCorre followed by identification of regions of interest (ROIs) with EXTRACT. Finally, we describe use of artificial neural network (ANN) machine learning to decode spatial paths from CA1 neural ensemble activity to predict mouse navigation of the odor plume.

SUMMARY

This protocol describes how to investigate the brain-behavior relationship in hippocampal CA1 in mice navigating an odor plume. We provide a step-by-step protocol including the surgery to access imaging of the hippocampus, behavioral training, miniscope GCaMP6f recording and processing of the brain and behavioral data to decode the mouse position from ROI neural activity.

Robotic Odor Source Localization via Vision and Olfaction Fusion Navigation Algorithm

Robotic odor source localization (OSL) is a technology that enables mobile robots or autonomous vehicles to find an odor source in unknown environments. An effective navigation algorithm that guides the robot to approach the odor source is the key to successfully locating the odor source. While traditional OSL approaches primarily utilize an olfaction-only strategy, guiding robots to find the odor source by tracing emitted odor plumes, our work introduces a fusion navigation algorithm that combines both vision and olfaction-based techniques. This hybrid approach addresses challenges such as turbulent airflow, which disrupts olfaction sensing, and physical obstacles inside the search area, which may impede vision detection. In this work, we propose a hierarchical control mechanism that dynamically shifts the robot's search behavior among four strategies: crosswind maneuver, Obstacle-Avoid Navigation, Vision-Based Navigation, and Olfaction-Based Navigation. Our methodology includes a custom-trained deep-learning model for visual target detection and a moth-inspired algorithm for Olfaction-Based Navigation. To assess the effectiveness of our approach, we implemented the proposed algorithm on a mobile robot in a search environment with obstacles. Experimental results demonstrate that our Vision and Olfaction Fusion algorithm significantly outperforms vision-only and olfaction-only methods, reducing average search time by 54% and 30%, respectively.

Physical properties of odorants affect behavior of trained detection dogs during close-quarters searches

Trained detection dogs have a unique ability to find the sources of target odors in complex fluid environments. How dogs derive information about the source of an odor from an odor plume comprised of odorants with different physical properties, such as diffusivity, is currently unknown. Two volatile chemicals associated with explosive detection, ammonia (NH3, derived from ammonium nitrate-based explosives) and 2-ethyl-1-hexanol (2E1H, associated with composition C4 plastic explosives) were used to ascertain the effects of the physical properties of odorants on the search behavior and motion of trained dogs. NH3 has a diffusivity 3.6 times that of 2E1H. Fourteen civilian detection dogs were recruited to train on each target odorant using controlled odor mimic permeation systems as training aids over 6 weeks and then tested in a controlled-environment search trial where behavior, motion, and search success were analyzed. Our results indicate the target-odorant influences search motion and time spent in the stages of searching, with dogs spending more time in larger areas while localizing NH3. This aligns with the greater diffusivity of NH3 driving diffusion-dominated odor transport when dogs are close to the odor source in contrast to the advection-driven transport of 2E1H at the same distances.

Olfactory search with finite-state controllers

Long-range olfactory search is an extremely difficult task in view of the sparsity of odor signals that are available to the searcher and the complex encoding of the information about the source location. Current algorithmic approaches typically require a continuous memory space, sometimes of large dimensionality, which may hamper their optimization and often obscure their interpretation. Here, we show how finite-state controllers with a small set of discrete memory states are expressive enough to display rich, time-extended behavioral modules that resemble the ones observed in living organisms. Finite-state controllers optimized for olfactory search have an immediate interpretation in terms of approximate clocks and coarse-grained spatial maps, suggesting connections with neural models of search behavior.

Continuous odor profile monitoring to study olfactory navigation in small animals

Olfactory navigation is observed across species and plays a crucial role in locating resources for survival. In the laboratory, understanding the behavioral strategies and neural circuits underlying odor-taxis requires a detailed understanding of the animal's sensory environment. For small model organisms like Caenorhabditis elegans and larval Drosophila melanogaster, controlling and measuring the odor environment experienced by the animal can be challenging, especially for airborne odors, which are subject to subtle effects from airflow, temperature variation, and from the odor's adhesion, adsorption, or reemission. Here, we present a method to control and measure airborne odor concentration in an arena compatible with an agar substrate. Our method allows continuous controlling and monitoring of the odor profile while imaging animal behavior. We construct stationary chemical landscapes in an odor flow chamber through spatially patterned odorized air. The odor concentration is measured with a spatially distributed array of digital gas sensors. Careful placement of the sensors allows the odor concentration across the arena to be continuously inferred in space and monitored through time. We use this approach to measure the odor concentration that each animal experiences as it undergoes chemotaxis behavior and report chemotaxis strategies for C. elegans and D. melanogaster larvae populations as they navigate spatial odor landscapes.

Artificial Olfactory Signal Modulation for Detection in Changing Environments

Animals have evolved to sense in complex environments through both modulation behavior including sniffing as well as sophisticated neural processing including memory and neuromodulation. Here, we explore thermal modulation of chemically diverse sensor arrays, where response patterns are based on partitioning of odorants across the array. The differential response patterns contain information about the chemical nature of the odorant for identification. By transitioning away from well-defined concentration modulation, traditionally used in the field, to thermal modulation, it is possible to capture both diagnostic patterns as well as intensity information in complex environments. This performance is demonstrated with carbon-black based, chemically diverse sensor arrays, that are thermally modulated with light at 25 mHz exposed to different analytes of varying concentrations.

An optofluidic platform for interrogating chemosensory behavior and brainwide neural representation in larval zebrafish

Studying chemosensory processing desires precise chemical cue presentation, behavioral response monitoring, and large-scale neuronal activity recording. Here we present Fish-on-Chips, a set of optofluidic tools for highly-controlled chemical delivery while simultaneously imaging behavioral outputs and whole-brain neuronal activities at cellular resolution in larval zebrafish. These include a fluidics-based swimming arena and an integrated microfluidics-light sheet fluorescence microscopy (µfluidics-LSFM) system, both of which utilize laminar fluid flows to achieve spatiotemporally precise chemical cue presentation. To demonstrate the strengths of the platform, we used the navigation arena to reveal binasal input-dependent behavioral strategies that larval zebrafish adopt to evade cadaverine, a death-associated odor. The µfluidics-LSFM system enables sequential presentation of odor stimuli to individual or both nasal cavities separated by only ~100 µm. This allowed us to uncover brainwide neural representations of cadaverine sensing and binasal input summation in the vertebrate model. Fish-on-Chips is readily generalizable and will empower the investigation of neural coding in the chemical senses.

Lessons from behavioral lateralization in olfaction

Sensory information, sampled by sensory organs positioned on each side of the body may play a crucial role in organizing brain lateralization. This question is of particular interest with regard to the growing evidence of alteration in lateralization in several psychiatric conditions. In this context, the olfactory system, an ancient, mostly ipsilateral and well-conserved system across phylogeny may prove an interesting model system to understand the behavioral significance of brain lateralization. Here, we focused on behavioral data in vertebrates and non-vertebrates, suggesting that the two hemispheres of the brain differentially processed olfactory cues to achieve diverse sensory operations, such as detection, discrimination, identification of behavioral valuable cues or learning. These include reports across different species on best performances with one nostril or the other or odorant active sampling by one nostril or the other, depending on odorants or contexts. In some species, hints from peripheral anatomical or functional asymmetry were proposed to explain these asymmetries in behavior. Instigations of brain activation or more rarely of brain connectivity evoked by odorants revealed a complex picture with regards to asymmetric patterns which is discussed with respect to behavioral data. Along the steps of the discussed literature, we propose avenues for future research.

Using your nose to find your way: Ethological comparisons between human and non-human species

Olfaction is arguably the least valued among our sensory systems, and its significance for human behavior is often neglected. Spatial navigation represents no exception to the rule: humans are often characterized as purely visual navigators, a view that undermines the contribution of olfactory cues. Accordingly, research investigating whether and how humans use olfaction to navigate space is rare. In comparison, research on olfactory navigation in non-human species is abundant, and identifies behavioral strategies along with neural mechanisms characterizing the use of olfactory cues during spatial tasks. Using an ethological approach, our review draws from studies on olfactory navigation across species to describe the adaptation of strategies under the influence of selective pressure. Mammals interact with spatial environments by abstracting multisensory information into cognitive maps. We thus argue that olfactory cues, alongside inputs from other sensory modalities, play a crucial role in spatial navigation for mammalian species, including humans; that is, odors constitute one of the many building blocks in the formation of cognitive maps.

Mice learn multi-step routes by memorizing subgoal locations

The behavioral strategies that mammals use to learn multi-step routes are unknown. In this study, we investigated how mice navigate to shelter in response to threats when the direct path is blocked. Initially, they fled toward the shelter and negotiated obstacles using sensory cues. Within 20 min, they spontaneously adopted a subgoal strategy, initiating escapes by running directly to the obstacle's edge. Mice continued to escape in this manner even after the obstacle had been removed, indicating use of spatial memory. However, standard models of spatial learning-habitual movement repetition and internal map building-did not explain how subgoal memories formed. Instead, mice used a hybrid approach: memorizing salient locations encountered during spontaneous 'practice runs' to the shelter. This strategy was also used during a geometrically identical food-seeking task. These results suggest that subgoal memorization is a fundamental strategy by which rodents learn efficient multi-step routes in new environments.

Sniff-synchronized, gradient-guided olfactory search by freely moving mice

For many organisms, searching for relevant targets such as food or mates entails active, strategic sampling of the environment. Finding odorous targets may be the most ancient search problem that motile organisms evolved to solve. While chemosensory navigation has been well characterized in microorganisms and invertebrates, spatial olfaction in vertebrates is poorly understood. We have established an olfactory search assay in which freely moving mice navigate noisy concentration gradients of airborne odor. Mice solve this task using concentration gradient cues and do not require stereo olfaction for performance. During task performance, respiration and nose movement are synchronized with tens of milliseconds precision. This synchrony is present during trials and largely absent during inter-trial intervals, suggesting that sniff-synchronized nose movement is a strategic behavioral state rather than simply a constant accompaniment to fast breathing. To reveal the spatiotemporal structure of these active sensing movements, we used machine learning methods to parse motion trajectories into elementary movement motifs. Motifs fall into two clusters, which correspond to investigation and approach states. Investigation motifs lock precisely to sniffing, such that the individual motifs preferentially occur at specific phases of the sniff cycle. The allocentric structure of investigation and approach indicates an advantage to sampling both sides of the sharpest part of the odor gradient, consistent with a serial-sniff strategy for gradient sensing. This work clarifies sensorimotor strategies for mouse olfactory search and guides ongoing work into the underlying neural mechanisms.

Plume Dynamics Structure the Spatiotemporal Activity of Mitral/Tufted Cell Networks in the Mouse Olfactory Bulb

Although mice locate resources using turbulent airborne odor plumes, the stochasticity and intermittency of fluctuating plumes create challenges for interpreting odor cues in natural environments. Population activity within the olfactory bulb (OB) is thought to process this complex spatial and temporal information, but how plume dynamics impact odor representation in this early stage of the mouse olfactory system is unknown. Limitations in odor detection technology have made it difficult to measure plume fluctuations while simultaneously recording from the mouse's brain. Thus, previous studies have measured OB activity following controlled odor pulses of varying profiles or frequencies, but this approach only captures a subset of features found within olfactory plumes. Adequately sampling this feature space is difficult given a lack of knowledge regarding which features the brain extracts during exposure to natural olfactory scenes. Here we measured OB responses to naturally fluctuating odor plumes using a miniature, adapted odor sensor combined with wide-field GCaMP6f signaling from the dendrites of mitral and tufted (MT) cells imaged in olfactory glomeruli of head-fixed mice. We precisely tracked plume dynamics and imaged glomerular responses to this fluctuating input, while varying flow conditions across a range of ethologically-relevant values. We found that a consistent portion of MT activity in glomeruli follows odor concentration dynamics, and the strongest responding glomeruli are the best at following fluctuations within odor plumes. Further, the reliability and average response magnitude of glomerular populations of MT cells are affected by the flow condition in which the animal samples the plume, with the fidelity of plume following by MT cells increasing in conditions of higher flow velocity where odor dynamics result in intermittent whiffs of stronger concentration. Thus, the flow environment in which an animal encounters an odor has a large-scale impact on the temporal representation of an odor plume in the OB. Additionally, across flow conditions odor dynamics are a major driver of activity in many glomerular networks. Taken together, these data demonstrate that plume dynamics structure olfactory representations in the first stage of odor processing in the mouse olfactory system.

Olfactory tracking strategies in a neotropical fruit bat

Many studies have characterized olfactory-tracking behaviors in animals, and it has been proposed that search strategies may be generalizable across a wide range of species. Olfaction is important for fruit- and nectar-feeding bats, but it is uncertain whether existing olfactory search models can predict the strategies of flying mammals that emit echolocation pulses through their nose. Quantitative assessments of how well echolocating bats track and localize odor sources are lacking, so we developed a behavioral assay to characterize the olfactory detection and tracking behavior of crawling northern yellow-shouldered bats (Sturnira parvidens), a common neotropical frugivore. Trained bats were presented with a choice between control and banana-odor-infused solutions in a series of experiments that confirmed that bats are able to locate a reward based on odor cues alone and examined the effect of odor concentration on olfactory search behaviors. Decision distance (the distance from which bats made their change in direction before directly approaching the target) was distinctly bimodal, with an observed peak that coincided with an inflection point in the odor concentration gradient. We observed two main search patterns that are consistent with both serial sampling and learned route-following strategies. These results support the hypothesis that bats can combine klinotaxis with spatial awareness of experimental conditions to locate odor sources, similar to terrestrial mammals. Contrary to existing models, bats did not display prominent head-scanning behaviors during their final approach, which may be due to constraints of nasal-emitted biosonar for orientation.

Olfactory navigation in the real world: Simple local search strategies for turbulent environments

Olfaction informs animal navigation for foraging, social interaction, and threat evasion. However, turbulent flow on the spatial scales of most animal navigation leads to intermittent odor information and presents a challenge to simple gradient-ascent navigation. Here we present two strategies for iterative gradient estimation and navigation via olfactory cues in 2D space: tropotaxis, spatial concentration comparison (i.e., instantaneous comparison between lateral olfactory sensors on a navigating animal) and klinotaxis, spatiotemporal concentration comparison (i.e., comparison between two subsequent concentration samples as the animal moves through space). We then construct a hybrid model that uses klinotaxis but utilizes tropotactic information to guide its spatial sampling strategy. We find that for certain body geometries in which bilateral sensors are closely-spaced (e.g., mammalian nares), klinotaxis outperforms tropotaxis; for widely-spaced sensors (e.g., arthropod antennae), tropotaxis outperforms klinotaxis. We find that both navigation strategies perform well on smooth odor gradients and are robust against noisy gradients represented by stochastic odor models and real turbulent flow data. In some parameter regimes, the hybrid model outperforms klinotaxis alone, but not tropotaxis.

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

Olfaction guides navigation and decision-making in organisms from multiple animal phyla. Understanding how animals use olfactory cues to guide navigation is a complicated problem for two main reasons. First, the sensory cues used to guide animals to the source of an odor consist of volatile molecules, which form plumes. These plumes are governed by turbulent air currents, resulting in an intermittent and spatiotemporally varying olfactory signal. A second problem is that the technologies for chemical quantification are cumbersome and cannot be used to detect what the freely moving animal senses in real time. Understanding how the olfactory system guides this behavior requires knowing the sensory cues and the accompanying brain signals during navigation. Here, we present a method for real-time monitoring of olfactory information using low-cost, lightweight sensors that robustly detect common solvent molecules, like alcohols, and can be easily mounted on the heads of freely behaving mice engaged in odor-guided navigation. To establish the accuracy and temporal response properties of these sensors we compared their responses with those of a photoionization detector (PID) to precisely controlled ethanol stimuli. Ethanol-sensor recordings, deconvolved using a difference-of-exponentials kernel, showed robust correlations with the PID signal at behaviorally relevant time, frequency, and spatial scales. Additionally, calcium imaging of odor responses from the olfactory bulbs (OBs) of awake, head-fixed mice showed strong correlations with ethanol plume contacts detected by these sensors. Finally, freely behaving mice engaged in odor-guided navigation showed robust behavioral changes such as speed reduction that corresponded to ethanol plume contacts.

Spatial information from the odour environment in mammalian olfaction

The sense of smell is an essential modality for many species, in particular nocturnal and crepuscular mammals, to gather information about their environment. Olfactory cues provide information over a large range of distances, allowing behaviours ranging from simple detection and recognition of objects, to tracking trails and navigating using odour plumes from afar. In this review, we discuss the features of the natural olfactory environment and provide a brief overview of how odour information can be sampled and might be represented and processed by the mammalian olfactory system. Finally, we discuss recent behavioural approaches that address how mammals extract spatial information from the environment in three different contexts: odour trail tracking, odour plume tracking and, more general, olfactory-guided navigation. Recent technological developments have seen the spatiotemporal aspect of mammalian olfaction gain significant attention, and we discuss both the promising aspects of rapidly developing paradigms and stimulus control technologies as well as their limitations. We conclude that, while still in its beginnings, research on the odour environment offers an entry point into understanding the mechanisms how mammals extract information about space.

Topographically Distinct Projection Patterns of Early-Generated and Late-Generated Projection Neurons in the Mouse Olfactory Bulb

In the mouse brain, olfactory information is transmitted to the olfactory cortex via olfactory bulb (OB) projection neurons known as mitral and tufted cells. Although mitral and tufted cells share many cellular characteristics, these cell types are distinct in their somata location and in their axonal and dendritic projection patterns. Moreover, mitral cells consist of heterogeneous subpopulations.

In the mouse brain, olfactory information is transmitted to the olfactory cortex via olfactory bulb (OB) projection neurons known as mitral and tufted cells. Although mitral and tufted cells share many cellular characteristics, these cell types are distinct in their somata location and in their axonal and dendritic projection patterns. Moreover, mitral cells consist of heterogeneous subpopulations. We have previously shown that mitral cells generated at different embryonic days differentially localize within the mitral cell layer (MCL) and extend their lateral dendrites to different sublayers of the external plexiform layer (EPL). Here, we examined the axonal projection patterns from the subpopulations of OB projection neurons that are determined by the timing of neurogenesis (neuronal birthdate) to understand the developmental origin of the diversity in olfactory pathways. We separately labeled early-generated and late-generated OB projection neurons using in utero electroporation performed at embryonic day (E)11 and E12, respectively, and quantitatively analyzed their axonal projection patterns in the whole mouse brain using high-resolution 3D imaging. In this study, we demonstrate that the axonal projection of late-generated OB projection neurons is restricted to the anterior portion of the olfactory cortex while those of the early-generated OB projection neurons innervate the entire olfactory cortex. Our results suggest that the late-generated mitral cells do not extend their axons to the posterior regions of the olfactory cortex. Therefore, the mitral cells having different birthdates differ, not only in cell body location and dendritic projections within the OB, but also in their axonal projection pattern to the olfactory cortex.

Subpopulations of Projection Neurons in the Olfactory Bulb

Generation of neuronal diversity is a biological strategy widely used in the brain to process complex information. The olfactory bulb is the first relay station of olfactory information in the vertebrate central nervous system. In the olfactory bulb, axons of the olfactory sensory neurons form synapses with dendrites of projection neurons that transmit the olfactory information to the olfactory cortex. Historically, the olfactory bulb projection neurons have been classified into two populations, mitral cells and tufted cells. The somata of these cells are distinctly segregated within the layers of the olfactory bulb; the mitral cells are located in the mitral cell layer while the tufted cells are found in the external plexiform layer. Although mitral and tufted cells share many morphological, biophysical, and molecular characteristics, they differ in soma size, projection patterns of their dendrites and axons, and odor responses. In addition, tufted cells are further subclassified based on the relative depth of their somata location in the external plexiform layer. Evidence suggests that different types of tufted cells have distinct cellular properties and play different roles in olfactory information processing. Therefore, mitral and different types of tufted cells are considered as starting points for parallel pathways of olfactory information processing in the brain. Moreover, recent studies suggest that mitral cells also consist of heterogeneous subpopulations with different cellular properties despite the fact that the mitral cell layer is a single-cell layer. In this review, we first compare the morphology of projection neurons in the olfactory bulb of different vertebrate species. Next, we explore the similarities and differences among subpopulations of projection neurons in the rodent olfactory bulb. We also discuss the timing of neurogenesis as a factor for the generation of projection neuron heterogeneity in the olfactory bulb. Knowledge about the subpopulations of olfactory bulb projection neurons will contribute to a better understanding of the complex olfactory information processing in higher brain regions.

Many Paths to the Same Goal: Balancing Exploration and Exploitation during Probabilistic Route Planning

During self-guided behaviors, animals identify constraints of the problems they face and adaptively employ appropriate strategies (Marsh, 2002). In the case of foraging, animals must balance sensory-guided exploration of an environment with memory-guided exploitation of known resource locations. Here, we show that animals adaptively shift cognitive resources between sensory and memory systems during foraging to optimize route planning under uncertainty. We demonstrate this using a new, laboratory-based discovery method to define the strategies used to solve a difficult route optimization scenario, the probabilistic “traveling salesman” problem (Raman and Gill, 2017; Fuentes et al., 2018; Mukherjee et al., 2019). Using this system, we precisely manipulated the strength of prior information as well as the complexity of the problem. We find that rats are capable of efficiently solving this route-planning problem, even under conditions with unreliable prior information and a large space of possible solutions. Through analysis of animals’ trajectories, we show that they shift the balance between exploiting known locations and searching for new locations of rewards based on the predictability of reward locations. When compared with a Bayesian search, we found that animal performance is consistent with an approach that adaptively allocates cognitive resources between sensory processing and memory, enhancing sensory acuity and reducing memory load under conditions in which prior information is unreliable. Our findings establish new approaches to understand neural substrates of natural behavior as well as the rational development of biologically inspired approaches for complex real-world optimization.

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

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.

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.