IDEAS home Printed from https://ideas.repec.org/a/plo/pcbi00/1007718.html
   My bibliography  Save this article

Mechanisms underlying attraction to odors in walking Drosophila

Author

Listed:
  • Liangyu Tao
  • Siddhi Ozarkar
  • Vikas Bhandawat

Abstract

Mechanisms that control movements range from navigational mechanisms, in which the animal employs directional cues to reach a specific destination, to search movements during which there are little or no environmental cues. Even though most real-world movements result from an interplay between these mechanisms, an experimental system and theoretical framework for the study of interplay of these mechanisms is not available. Here, we rectify this deficit. We create a new method to stimulate the olfactory system in Drosophila or fruit flies. As flies explore a circular arena, their olfactory receptor neuron (ORNs) are optogenetically activated within a central region making this region attractive to the flies without emitting any clear directional signals outside this central region. In the absence of ORN activation, the fly’s locomotion can be described by a random walk model where a fly’s movement is described by its speed and turn-rate (or kinematics). Upon optogenetic stimulation, the fly’s behavior changes dramatically in two respects. First, there are large kinematic changes. Second, there are more turns at the border between light-zone and no-light-zone and these turns have an inward bias. Surprisingly, there is no increase in turn-rate, rather a large decrease in speed that makes it appear that the flies are turning at the border. Similarly, the inward bias of the turns is a result of the increase in turn angle. These two mechanisms entirely account for the change in a fly’s locomotion. No complex mechanisms such as path-integration or a careful evaluation of gradients are necessary.Author summary: The strategy an animal employs to explore the environment and to find and return to the location where it has previously found food or mates is an important part of its behavior. In nature, animals have incomplete information about their environment, and must use this incomplete information to navigate. In most laboratory experiments, there is usually clear directional information making it difficult to infer an animal’s real strategy from laboratory behavioral experiments. In this study, we devise a new behavioral task wherein we remotely activate olfactory neurons when fruit flies are in a given location. This activation makes a given location attractive to the flies without providing any directional information and allows us to assess how flies navigate under these conditions. We find that flies navigate towards the activated location using two simple mechanisms: First, its speed in the activated region and its turn rate is much lower than it is elsewhere. Second, at the boundary of the odor-zone, its speed decreases dramatically and its turns become much sharper. Essentially, these simple mechanisms appear to be extremely robust.

Suggested Citation

  • Liangyu Tao & Siddhi Ozarkar & Vikas Bhandawat, 2020. "Mechanisms underlying attraction to odors in walking Drosophila," PLOS Computational Biology, Public Library of Science, vol. 16(3), pages 1-26, March.
  • Handle: RePEc:plo:pcbi00:1007718
    DOI: 10.1371/journal.pcbi.1007718
    as

    Download full text from publisher

    File URL: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007718
    Download Restriction: no

    File URL: https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1007718&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pcbi.1007718?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Quentin Gaudry & Elizabeth J. Hong & Jamey Kain & Benjamin L. de Bivort & Rachel I. Wilson, 2013. "Asymmetric neurotransmitter release enables rapid odour lateralization in Drosophila," Nature, Nature, vol. 493(7432), pages 424-428, January.
    2. G. M. Viswanathan & Sergey V. Buldyrev & Shlomo Havlin & M. G. E. da Luz & E. P. Raposo & H. Eugene Stanley, 1999. "Optimizing the success of random searches," Nature, Nature, vol. 401(6756), pages 911-914, October.
    3. Alex Gomez-Marin & Greg J. Stephens & Matthieu Louis, 2011. "Active sampling and decision making in Drosophila chemotaxis," Nature Communications, Nature, vol. 2(1), pages 1-10, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liangyu Tao & Samuel P. Wechsler & Vikas Bhandawat, 2023. "Sensorimotor transformation underlying odor-modulated locomotion in walking Drosophila," Nature Communications, Nature, vol. 14(1), pages 1-22, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liangyu Tao & Samuel P. Wechsler & Vikas Bhandawat, 2023. "Sensorimotor transformation underlying odor-modulated locomotion in walking Drosophila," Nature Communications, Nature, vol. 14(1), pages 1-22, December.
    2. Ferreira, A.S. & Raposo, E.P. & Viswanathan, G.M. & da Luz, M.G.E., 2012. "The influence of the environment on Lévy random search efficiency: Fractality and memory effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3234-3246.
    3. Priscila C A da Silva & Tiago V Rosembach & Anésia A Santos & Márcio S Rocha & Marcelo L Martins, 2014. "Normal and Tumoral Melanocytes Exhibit q-Gaussian Random Search Patterns," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-13, September.
    4. Ma, Brian O. & Davis, Brad H. & Gillespie, David R. & VanLaerhoven, Sherah L., 2009. "Incorporating behaviour into simple models of dispersal using the biological control agent Dicyphus hesperus," Ecological Modelling, Elsevier, vol. 220(23), pages 3271-3279.
    5. Marina E Wosniack & Marcos C Santos & Ernesto P Raposo & Gandhi M Viswanathan & Marcos G E da Luz, 2017. "The evolutionary origins of Lévy walk foraging," PLOS Computational Biology, Public Library of Science, vol. 13(10), pages 1-31, October.
    6. Yang Qi & Pulin Gong, 2022. "Fractional neural sampling as a theory of spatiotemporal probabilistic computations in neural circuits," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    7. Cody T Ross & Bruce Winterhalder, 2018. "Evidence for encounter-conditional, area-restricted search in a preliminary study of Colombian blowgun hunters," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-13, December.
    8. Pascual López-López & José Benavent-Corai & Clara García-Ripollés & Vicente Urios, 2013. "Scavengers on the Move: Behavioural Changes in Foraging Search Patterns during the Annual Cycle," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-9, January.
    9. José Ignacio Santos & María Pereda & Débora Zurro & Myrian Álvarez & Jorge Caro & José Manuel Galán & Ivan Briz i Godino, 2015. "Effect of Resource Spatial Correlation and Hunter-Fisher-Gatherer Mobility on Social Cooperation in Tierra del Fuego," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-29, April.
    10. Pauline Formaglio & Marina E. Wosniack & Raphael M. Tromer & Jaderson G. Polli & Yuri B. Matos & Hang Zhong & Ernesto P. Raposo & Marcos G. E. Luz & Rogerio Amino, 2023. "Plasmodium sporozoite search strategy to locate hotspots of blood vessel invasion," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    11. Toru Nakamura & Toru Takumi & Atsuko Takano & Fumiyuki Hatanaka & Yoshiharu Yamamoto, 2013. "Characterization and Modeling of Intermittent Locomotor Dynamics in Clock Gene-Deficient Mice," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-8, March.
    12. Sophie Lardy & Daniel Fortin & Olivier Pays, 2016. "Increased Exploration Capacity Promotes Group Fission in Gregarious Foraging Herbivores," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-14, December.
    13. LaScala-Gruenewald, Diana E. & Mehta, Rohan S. & Liu, Yu & Denny, Mark W., 2019. "Sensory perception plays a larger role in foraging efficiency than heavy-tailed movement strategies," Ecological Modelling, Elsevier, vol. 404(C), pages 69-82.
    14. Toman, Kellan & Voulgarakis, Nikolaos K., 2022. "Stochastic pursuit-evasion curves for foraging dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 597(C).
    15. Cédric Sueur & Léa Briard & Odile Petit, 2011. "Individual Analyses of Lévy Walk in Semi-Free Ranging Tonkean Macaques (Macaca tonkeana)," PLOS ONE, Public Library of Science, vol. 6(10), pages 1-8, October.
    16. Qi, Jie & Rong, Zhihai, 2013. "The emergence of scaling laws search dynamics in a particle swarm optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1522-1531.
    17. Zhang, Jingjing & Dennis, Todd E. & Landers, Todd J. & Bell, Elizabeth & Perry, George L.W., 2017. "Linking individual-based and statistical inferential models in movement ecology: A case study with black petrels (Procellaria parkinsoni)," Ecological Modelling, Elsevier, vol. 360(C), pages 425-436.
    18. Peter J M Van Haastert & Leonard Bosgraaf, 2009. "Food Searching Strategy of Amoeboid Cells by Starvation Induced Run Length Extension," PLOS ONE, Public Library of Science, vol. 4(8), pages 1-7, August.
    19. Stefano Focardi & Paolo Montanaro & Elena Pecchioli, 2009. "Adaptive Lévy Walks in Foraging Fallow Deer," PLOS ONE, Public Library of Science, vol. 4(8), pages 1-6, August.
    20. Maria C. Mariani & William Kubin & Peter K. Asante & Osei K. Tweneboah & Maria P. Beccar-Varela & Sebastian Jaroszewicz & Hector Gonzalez-Huizar, 2020. "Self-Similar Models: Relationship between the Diffusion Entropy Analysis, Detrended Fluctuation Analysis and Lévy Models," Mathematics, MDPI, vol. 8(7), pages 1-20, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pcbi00:1007718. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ploscompbiol (email available below). General contact details of provider: https://journals.plos.org/ploscompbiol/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.