Robust odor identification in novel olfactory environments in mice

Li, Yan; Swerdloff, Mitchell; She, Tianyu; Rahman, Asiyah; Sharma, Naveen Kumar; Shah, Reema; Castellano, Michael A.; Mogel, Daniel; Wu, Jason; Ahmed, Asim A.; Miguel, James San; Cohn, Jared; Shah, N.A.; Ramos, Raddy L.; Otazu, Gonzalo H.

doi:10.1038/s41467-023-36346-x

Cited by 8 publications

(7 citation statements)

References 82 publications

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“…Correlating sporadic plume encounters to behavioral changes, and neural recordings during odor-guided navigation has remained an elusive goal [6,7] due to the constraints in real-time olfactory monitoring. We previously reported a method to record the odor information available to a freely moving mouse using head-mounted sensors [20] that has been adopted by other groups to fit their research goals [30,31]. Here we combined this method with head-motion tracking using accelerometers to study how plume encounters shape head motions during an odor-localization task.…”

Section: Discussionmentioning

confidence: 99%

Dynamics of odor-source localization: Insights from real-time odor plume recordings and head-motion tracking in freely moving mice

Tariq,

Sterrett,

Moore

et al. 2023

Preprint

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Animals navigating turbulent odor plumes exhibit a rich variety of behaviors, and employ efficient strategies to locate odor sources. A growing body of literature has started to probe this complex task of localizing airborne odor sources in walking mammals to further our understanding of neural encoding and decoding of naturalistic sensory stimuli. However, correlating the intermittent olfactory information with behavior has remained a long-standing challenge due to the stochastic nature of the odor stimulus. We recently reported a method to record real-time olfactory information available to freely moving mice during odor-guided navigation, hence overcoming that challenge. Here we combine our odor-recording method with head-motion tracking to establish correlations between plume encounters and head movements. We show that mice exhibit robust head-pitch motions in the 5-14Hz range during an odor-guided navigation task, and that these head motions are modulated by plume encounters. Furthermore, mice orient towards the odor source upon plume contact. Head motions may thus be an important part of the sensorimotor behavioral repertoire during naturalistic odor-source localization.

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Section: Discussionmentioning

confidence: 99%

Dynamics of odor-source localization: Insights from real-time odor plume recordings and head-motion tracking in freely moving mice

Tariq,

Sterrett,

Moore

et al. 2023

Preprint

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“…This computational problem differs from many experimental tasks focusing on discrimination between two odorants [60], which underlie most scientific work on rodent olfactory decision making [60][61][62]. Here, the goal is to identify the components of a complex olfactory scene [63][64][65][66]. Importantly, the limits of human performance in this setting remain to our knowledge unknown [67,68].…”

Section: Related Work and Review Of The Olfactory Sensing Problemmentioning

confidence: 99%

Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb

Zavatone-Veth

Masset

Zak

et al. 2023

Preprint

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Within a single sniff, the mammalian olfactory system can decode the identity and concentration of odorants wafted on turbulent plumes of air. Yet, it must do so given access only to the noisy, dimensionally-reduced representation of the odor world provided by olfactory receptor neurons. As a result, the olfactory system must solve a compressed sensing problem, relying on the fact that only a handful of the millions of possible odorants are present in a given scene. Inspired by this principle, past works have proposed normative compressed sensing models for olfactory decoding. However, these models have not captured the unique anatomy and physiology of the olfactory bulb, nor have they shown that sensing can be achieved within the 100-millisecond timescale of a single sniff. Here, we propose a rate-based Poisson compressed sensing circuit model for the olfactory bulb. This model maps onto the neuron classes of the olfactory bulb, and recapitulates salient features of their connectivity and physiology. For circuit sizes comparable to the human olfactory bulb, we show that this model can accurately detect tens of odors within the timescale of a single sniff. We also show that this model can perform Bayesian posterior sampling for accurate uncertainty estimation. Fast inference is possible only if the geometry of the neural code is chosen to match receptor properties, yielding a distributed neural code that is not axis-aligned to individual odor identities. Our results illustrate how normative modeling can help us map function onto specific neural circuits to generate new hypotheses.

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“…Monoterpenes are also commonly used in olfactory research to survey neural activity in a variety of olfactory regions, probe the behavioral limits of odor discrimination, and assess odor-structure activity relationships in mice [17,[25][26][27][28][29][30][31][32]. The stimulus intensities used in these studies vary widely as appropriate concentrations have yet to be defined.…”

Section: Introductionmentioning

confidence: 99%

The behavioral sensitivity of mice to acyclic, monocyclic, and bicyclic monoterpenes

Williams,

Pauley,

Dewan

2024

PLoS ONE

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Monoterpenes are a large class of naturally occurring fragrant molecules. These chemicals are commonly used in olfactory studies to survey neural activity and probe the behavioral limits of odor discrimination. Monoterpenes (typically in the form of essential oils) have been used for centuries for therapeutic purposes and have pivotal roles in various biological and medical applications. Despite their importance for multiple lines of research using rodent models and the role of the olfactory system in detecting these volatile chemicals, the murine sensitivity to monoterpenes remains mostly unexplored. We assayed the ability of C57BL/6J mice to detect nine different monoterpenes (the acyclic monoterpenes: geraniol, citral, and linalool; the monocyclic monoterpenes: r-limonene, s-limonene, and γ-terpinene; and the bicyclic monoterpenes: eucalyptol, α-pinene, and β-pinene) using a head-fixed Go / No-Go operant conditioning assay. We found that mice can reliably detect monoterpene concentrations in the low parts per billion (ppb) range. Specifically, mice were most sensitive to geraniol (threshold: 0.7 ppb) and least sensitive to γ-terpinene (threshold: 18.1 ppb). These estimations of sensitivity serve to set the lower limit of relevant monoterpene concentrations for functional experiments in mice. To define an upper limit, we estimated the maximum concentrations that a mouse may experience in nature by collating published headspace analyses of monoterpene concentrations emitted from natural sources. We found that natural monoterpenes concentrations typically ranged from ~1 to 1000 ppb. It is our hope that this dataset will help researchers use appropriate monoterpene concentrations for functional studies and provide context for the vapor-phase delivery of these chemicals in studies investigating their biological activity in mice.

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Robust odor identification in novel olfactory environments in mice

Cited by 8 publications

References 82 publications

Dynamics of odor-source localization: Insights from real-time odor plume recordings and head-motion tracking in freely moving mice

Dynamics of odor-source localization: Insights from real-time odor plume recordings and head-motion tracking in freely moving mice

Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb

The behavioral sensitivity of mice to acyclic, monocyclic, and bicyclic monoterpenes

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