1
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Nag A, van Breugel F. Odour source distance is predictable from a time history of odour statistics for large scale outdoor plumes. J R Soc Interface 2024; 21:20240169. [PMID: 39079675 PMCID: PMC11288670 DOI: 10.1098/rsif.2024.0169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Accepted: 05/23/2024] [Indexed: 08/02/2024] Open
Abstract
Odour plumes in turbulent environments are intermittent and sparse. Laboratory-scaled experiments suggest that information about the source distance may be encoded in odour signal statistics, yet it is unclear whether useful and continuous distance estimates can be made under real-world flow conditions. Here, we analyse odour signals from outdoor experiments with a sensor moving across large spatial scales in desert and forest environments to show that odour signal statistics can yield useful estimates of distance. We show that achieving accurate estimates of distance requires integrating statistics from 5 to 10 s, with a high temporal encoding of the olfactory signal of at least 20 Hz. By combining distance estimates from a linear model with wind-relative motion dynamics, we achieved source distance estimates in a 60 × 60 m2 search area with median errors of 3-8 m, a distance at which point odour sources are often within visual range for animals such as mosquitoes.
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Affiliation(s)
- Arunava Nag
- Computer Science Engineering Department, University of Nevada, Reno, NV, USA
| | - Floris van Breugel
- Integrative Neuroscience Program, University of Nevada, Reno, NV, USA
- Ecology Evolution and Conservation Biology Program, University of Nevada, Reno, NV, USA
- Department of Mechanical Engineering, University of Nevada, Reno, NV, USA
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2
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Choi K, Rosenbluth W, Graf IR, Kadakia N, Emonet T. Bifurcation enhances temporal information encoding in the olfactory periphery. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.27.596086. [PMID: 38853849 PMCID: PMC11160621 DOI: 10.1101/2024.05.27.596086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Living systems continually respond to signals from the surrounding environment. Survival requires that their responses adapt quickly and robustly to the changes in the environment. One particularly challenging example is olfactory navigation in turbulent plumes, where animals experience highly intermittent odor signals while odor concentration varies over many length- and timescales. Here, we show theoretically that Drosophila olfactory receptor neurons (ORNs) can exploit proximity to a bifurcation point of their firing dynamics to reliably extract information about the timing and intensity of fluctuations in the odor signal, which have been shown to be critical for odor-guided navigation. Close to the bifurcation, the system is intrinsically invariant to signal variance, and information about the timing, duration, and intensity of odor fluctuations is transferred efficiently. Importantly, we find that proximity to the bifurcation is maintained by mean adaptation alone and therefore does not require any additional feedback mechanism or fine-tuning. Using a biophysical model with calcium-based feedback, we demonstrate that this mechanism can explain the measured adaptation characteristics of Drosophila ORNs.
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3
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Choi K, Rosenbluth W, Graf IR, Kadakia N, Emonet T. Bifurcation enhances temporal information encoding in the olfactory periphery. ARXIV 2024:arXiv:2405.20135v2. [PMID: 38855541 PMCID: PMC11160886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Living systems continually respond to signals from the surrounding environment. Survival requires that their responses adapt quickly and robustly to the changes in the environment. One particularly challenging example is olfactory navigation in turbulent plumes, where animals experience highly intermittent odor signals while odor concentration varies over many length- and timescales. Here, we show theoretically that Drosophila olfactory receptor neurons (ORNs) can exploit proximity to a bifurcation point of their firing dynamics to reliably extract information about the timing and intensity of fluctuations in the odor signal, which have been shown to be critical for odor-guided navigation. Close to the bifurcation, the system is intrinsically invariant to signal variance, and information about the timing, duration, and intensity of odor fluctuations is transferred efficiently. Importantly, we find that proximity to the bifurcation is maintained by mean adaptation alone and therefore does not require any additional feedback mechanism or fine-tuning. Using a biophysical model with calcium-based feedback, we demonstrate that this mechanism can explain the measured adaptation characteristics of Drosophila ORNs.
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Affiliation(s)
- Kiri Choi
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut 06511, USA
- Quantitative Biology Institute, Yale University, New Haven, Connecticut 06511, USA
- Swartz Foundation for Theoretical Neuroscience, Yale University, New Haven, Connecticut 06511, USA
| | - Will Rosenbluth
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut 06511, USA
| | - Isabella R. Graf
- Quantitative Biology Institute, Yale University, New Haven, Connecticut 06511, USA
- Department of Physics, Yale University, New Haven, Connecticut 06511, USA
| | - Nirag Kadakia
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut 06511, USA
- Quantitative Biology Institute, Yale University, New Haven, Connecticut 06511, USA
- Swartz Foundation for Theoretical Neuroscience, Yale University, New Haven, Connecticut 06511, USA
| | - Thierry Emonet
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut 06511, USA
- Quantitative Biology Institute, Yale University, New Haven, Connecticut 06511, USA
- Department of Physics, Yale University, New Haven, Connecticut 06511, USA
- Interdepartmental Neuroscience Program, Yale University, New Haven, Connecticut 06511, USA
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4
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Gumaste A, Baker KL, Izydorczak M, True AC, Vasan G, Crimaldi JP, Verhagen J. Behavioral discrimination and olfactory bulb encoding of odor plume intermittency. eLife 2024; 13:e85303. [PMID: 38441541 PMCID: PMC11001298 DOI: 10.7554/elife.85303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 03/04/2024] [Indexed: 04/09/2024] Open
Abstract
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.
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Affiliation(s)
- Ankita Gumaste
- Interdepartmental Neuroscience Program, Yale UniversityNew HavenUnited States
- John B. Pierce LaboratoryNew HavenUnited States
- Department of Neuroscience, Yale School of MedicineNew HavenUnited States
| | - Keeley L Baker
- John B. Pierce LaboratoryNew HavenUnited States
- Department of Neuroscience, Yale School of MedicineNew HavenUnited States
| | | | - Aaron C True
- Department of Civil, Environmental and Architectural Engineering, University of ColoradoBoulderUnited States
| | | | - John P Crimaldi
- Department of Civil, Environmental and Architectural Engineering, University of ColoradoBoulderUnited States
| | - Justus Verhagen
- Interdepartmental Neuroscience Program, Yale UniversityNew HavenUnited States
- John B. Pierce LaboratoryNew HavenUnited States
- Department of Neuroscience, Yale School of MedicineNew HavenUnited States
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5
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Tao L, Wechsler SP, Bhandawat V. Sensorimotor transformation underlying odor-modulated locomotion in walking Drosophila. Nat Commun 2023; 14:6818. [PMID: 37884581 PMCID: PMC10603174 DOI: 10.1038/s41467-023-42613-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 10/17/2023] [Indexed: 10/28/2023] Open
Abstract
Most real-world behaviors - such as odor-guided locomotion - are performed with incomplete information. Activity in olfactory receptor neuron (ORN) classes provides information about odor identity but not the location of its source. In this study, we investigate the sensorimotor transformation that relates ORN activation to locomotion changes in Drosophila by optogenetically activating different combinations of ORN classes and measuring the resulting changes in locomotion. Three features describe this sensorimotor transformation: First, locomotion depends on both the instantaneous firing frequency (f) and its change (df); the two together serve as a short-term memory that allows the fly to adapt its motor program to sensory context automatically. Second, the mapping between (f, df) and locomotor parameters such as speed or curvature is distinct for each pattern of activated ORNs. Finally, the sensorimotor mapping changes with time after odor exposure, allowing information integration over a longer timescale.
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Affiliation(s)
- Liangyu Tao
- School of Biomedical Engineering and Health Sciences, Drexel University, Philadelphia, PA, USA
| | - Samuel P Wechsler
- School of Biomedical Engineering and Health Sciences, Drexel University, Philadelphia, PA, USA
- Department of Neurobiology and Anatomy, Drexel University, Philadelphia, PA, USA
| | - Vikas Bhandawat
- School of Biomedical Engineering and Health Sciences, Drexel University, Philadelphia, PA, USA.
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6
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Szyszka P, Emonet T, Edwards TL. Extracting spatial information from temporal odor patterns: insights from insects. CURRENT OPINION IN INSECT SCIENCE 2023; 59:101082. [PMID: 37419251 PMCID: PMC10878403 DOI: 10.1016/j.cois.2023.101082] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 06/26/2023] [Accepted: 06/27/2023] [Indexed: 07/09/2023]
Abstract
Extracting spatial information from temporal stimulus patterns is essential for sensory perception (e.g. visual motion direction detection or concurrent sound segregation), but this process remains understudied in olfaction. Animals rely on olfaction to locate resources and dangers. In open environments, where odors are dispersed by turbulent wind, detection of wind direction seems crucial for odor source localization. However, recent studies showed that insects can extract spatial information from the odor stimulus itself, independently from sensing wind direction. This remarkable ability is achieved by detecting the fine-scale temporal pattern of odor encounters, which contains information about the location and size of an odor source, and the distance between different odor sources.
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Affiliation(s)
- Paul Szyszka
- Department of Zoology, University of Otago, Dunedin, New Zealand.
| | - Thierry Emonet
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, USA
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7
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Verano KVB, Panizon E, Celani A. Olfactory search with finite-state controllers. Proc Natl Acad Sci U S A 2023; 120:e2304230120. [PMID: 37579168 PMCID: PMC10450675 DOI: 10.1073/pnas.2304230120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 06/22/2023] [Indexed: 08/16/2023] Open
Abstract
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.
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Affiliation(s)
- Kyrell Vann B. Verano
- Quantitative Life Sciences, The Abdus Salam International Center for Theoretical Physics, 34151Trieste, Italy
- Department of Physics, Università Degli Studi di Trieste, 34127Trieste, Italy
| | - Emanuele Panizon
- Quantitative Life Sciences, The Abdus Salam International Center for Theoretical Physics, 34151Trieste, Italy
| | - Antonio Celani
- Quantitative Life Sciences, The Abdus Salam International Center for Theoretical Physics, 34151Trieste, Italy
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8
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Tichy H, Hellwig M. Gain control in olfactory receptor neurons and the detection of temporal fluctuations in odor concentration. Front Physiol 2023; 14:1158855. [PMID: 37501922 PMCID: PMC10368873 DOI: 10.3389/fphys.2023.1158855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Accepted: 07/03/2023] [Indexed: 07/29/2023] Open
Abstract
The ability of the cockroach to locate an odor source in still air suggests that the temporal dynamic of odor concentration in the slowly expanding stationary plume alone is used to infer odor source distance and location. This contradicts with the well-established view that insects use the wind direction as the principle directional cue. This contribution highlights the evidence for, and likely functional relevance of, the capacity of the cockroach's olfactory receptor neurons to detect and process-from one moment to the next-not only a succession of odor concentrations but also the rates at which concentration changes. This presents a challenge for the olfactory system because it must detect and encode the temporal concentration dynamic in a manner that simultaneously allows invariant odor recognition. The challenge is met by a parallel representation of odor identity and concentration changes in a dual pathway that starts from olfactory receptor neurons located in two morphologically distinct types of olfactory sensilla. Parallel processing uses two types of gain control that simultaneously allocate different weight to the instantaneous odor concentration and its rate of change. Robust gain control provides a stable sensitivity for the instantaneous concentration by filtering the information on fluctuations in the rate of change. Variable gain control, in turn, enhances sensitivity for the concentration rate according to variations in the duration of the fluctuation period. This efficiently represents the fluctuation of concentration changes in the environmental context in which such changes occur.
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9
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Steele TJ, Lanz AJ, Nagel KI. Olfactory navigation in arthropods. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 2023; 209:467-488. [PMID: 36658447 PMCID: PMC10354148 DOI: 10.1007/s00359-022-01611-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Revised: 12/26/2022] [Accepted: 12/31/2022] [Indexed: 01/21/2023]
Abstract
Using odors to find food and mates is one of the most ancient and highly conserved behaviors. Arthropods from flies to moths to crabs use broadly similar strategies to navigate toward odor sources-such as integrating flow information with odor information, comparing odor concentration across sensors, and integrating odor information over time. Because arthropods share many homologous brain structures-antennal lobes for processing olfactory information, mechanosensors for processing flow, mushroom bodies (or hemi-ellipsoid bodies) for associative learning, and central complexes for navigation, it is likely that these closely related behaviors are mediated by conserved neural circuits. However, differences in the types of odors they seek, the physics of odor dispersal, and the physics of locomotion in water, air, and on substrates mean that these circuits must have adapted to generate a wide diversity of odor-seeking behaviors. In this review, we discuss common strategies and specializations observed in olfactory navigation behavior across arthropods, and review our current knowledge about the neural circuits subserving this behavior. We propose that a comparative study of arthropod nervous systems may provide insight into how a set of basic circuit structures has diversified to generate behavior adapted to different environments.
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Affiliation(s)
- Theresa J Steele
- Neuroscience Institute, NYU School of Medicine, 435 E 30th St., New York, NY, 10016, USA
| | - Aaron J Lanz
- Neuroscience Institute, NYU School of Medicine, 435 E 30th St., New York, NY, 10016, USA
| | - Katherine I Nagel
- Neuroscience Institute, NYU School of Medicine, 435 E 30th St., New York, NY, 10016, USA.
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10
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Kim B, Haney S, Milan AP, Joshi S, Aldworth Z, Rulkov N, Kim AT, Bazhenov M, Stopfer MA. Olfactory receptor neurons generate multiple response motifs, increasing coding space dimensionality. eLife 2023; 12:79152. [PMID: 36719272 PMCID: PMC9925048 DOI: 10.7554/elife.79152] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 01/31/2023] [Indexed: 02/01/2023] Open
Abstract
Odorants binding to olfactory receptor neurons (ORNs) trigger bursts of action potentials, providing the brain with its only experience of the olfactory environment. Our recordings made in vivo from locust ORNs showed that odor-elicited firing patterns comprise four distinct response motifs, each defined by a reliable temporal profile. Different odorants could elicit different response motifs from a given ORN, a property we term motif switching. Further, each motif undergoes its own form of sensory adaptation when activated by repeated plume-like odor pulses. A computational model constrained by our recordings revealed that organizing responses into multiple motifs provides substantial benefits for classifying odors and processing complex odor plumes: each motif contributes uniquely to encode the plume's composition and structure. Multiple motifs and motif switching further improve odor classification by expanding coding dimensionality. Our model demonstrated that these response features could provide benefits for olfactory navigation, including determining the distance to an odor source.
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Affiliation(s)
- Brian Kim
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH)BethesdaUnited States
- Brown University - National Institutes of Health Graduate Partnership ProgramProvidenceUnited States
| | - Seth Haney
- Department of Medicine, University of California, San DiegoSan DiegoUnited States
| | - Ana P Milan
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Shruti Joshi
- Department of Medicine, University of California, San DiegoSan DiegoUnited States
| | - Zane Aldworth
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH)BethesdaUnited States
| | - Nikolai Rulkov
- Biocircuits Institute, University of California, San DiegoLa JollaUnited States
| | - Alexander T Kim
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH)BethesdaUnited States
| | - Maxim Bazhenov
- Department of Medicine, University of California, San DiegoSan DiegoUnited States
| | - Mark A Stopfer
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH)BethesdaUnited States
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Kadakia N, Demir M, Michaelis BT, DeAngelis BD, Reidenbach MA, Clark DA, Emonet T. Odour motion sensing enhances navigation of complex plumes. Nature 2022; 611:754-761. [PMID: 36352224 PMCID: PMC10039482 DOI: 10.1038/s41586-022-05423-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 10/06/2022] [Indexed: 11/11/2022]
Abstract
Odour plumes in the wild are spatially complex and rapidly fluctuating structures carried by turbulent airflows1-4. To successfully navigate plumes in search of food and mates, insects must extract and integrate multiple features of the odour signal, including odour identity5, intensity6 and timing6-12. Effective navigation requires balancing these multiple streams of olfactory information and integrating them with other sensory inputs, including mechanosensory and visual cues9,12,13. Studies dating back a century have indicated that, of these many sensory inputs, the wind provides the main directional cue in turbulent plumes, leading to the longstanding model of insect odour navigation as odour-elicited upwind motion6,8-12,14,15. Here we show that Drosophila melanogaster shape their navigational decisions using an additional directional cue-the direction of motion of odours-which they detect using temporal correlations in the odour signal between their two antennae. Using a high-resolution virtual-reality paradigm to deliver spatiotemporally complex fictive odours to freely walking flies, we demonstrate that such odour-direction sensing involves algorithms analogous to those in visual-direction sensing16. Combining simulations, theory and experiments, we show that odour motion contains valuable directional information that is absent from the airflow alone, and that both Drosophila and virtual agents are aided by that information in navigating naturalistic plumes. The generality of our findings suggests that odour-direction sensing may exist throughout the animal kingdom and could improve olfactory robot navigation in uncertain environments.
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Affiliation(s)
- Nirag Kadakia
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA
- Quantitative Biology Institute, Yale University, New Haven, CT, USA
- Swartz Foundation for Theoretical Neuroscience, Yale University, New Haven, CT, USA
| | - Mahmut Demir
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA
- Quantitative Biology Institute, Yale University, New Haven, CT, USA
| | - Brenden T Michaelis
- Department of Environmental Sciences, University of Virginia, Charlottesville, VA, USA
| | - Brian D DeAngelis
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA
- Quantitative Biology Institute, Yale University, New Haven, CT, USA
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA
| | - Matthew A Reidenbach
- Department of Environmental Sciences, University of Virginia, Charlottesville, VA, USA
| | - Damon A Clark
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA.
- Quantitative Biology Institute, Yale University, New Haven, CT, USA.
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA.
- Department of Physics, Yale University, New Haven, CT, USA.
| | - Thierry Emonet
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA.
- Quantitative Biology Institute, Yale University, New Haven, CT, USA.
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA.
- Department of Physics, Yale University, New Haven, CT, USA.
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12
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Tao L, Bhandawat V. Mechanisms of Variability Underlying Odor-Guided Locomotion. Front Behav Neurosci 2022; 16:871884. [PMID: 35600988 PMCID: PMC9115574 DOI: 10.3389/fnbeh.2022.871884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 03/14/2022] [Indexed: 11/17/2022] Open
Abstract
Changes in locomotion mediated by odors (odor-guided locomotion) are an important mechanism by which animals discover resources important to their survival. Odor-guided locomotion, like most other behaviors, is highly variable. Variability in behavior can arise at many nodes along the circuit that performs sensorimotor transformation. We review these sources of variability in the context of the Drosophila olfactory system. While these sources of variability are important, using a model for locomotion, we show that another important contributor to behavioral variability is the stochastic nature of decision-making during locomotion as well as the persistence of these decisions: Flies choose the speed and curvature stochastically from a distribution and locomote with the same speed and curvature for extended periods. This stochasticity in locomotion will result in variability in behavior even if there is no noise in sensorimotor transformation. Overall, the noise in sensorimotor transformation is amplified by mechanisms of locomotion making odor-guided locomotion in flies highly variable.
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