Olfactory Navigation: Tempo is the key
Tracking odors is a matter of life or death for most organisms, and insects are no exception (Baker et al., 2018). Male moths can track the pheromones of their potential mating partners from hundreds of meters away, and even fruit flies successfully engage in long-range searches for food using their sense of smell. However, this task is far from easy. This is because the molecules that carry the odorous message are transported by turbulent wind, where they get mixed with other molecules and form complex structures (Murlis et al., 1992; Crimaldi and Koseff, 2001). As a result, the information about the origin of a scent is seemingly lost, hidden in the intricacies of the intermittent odor signal. Insects appear to be able to overcome this problem, but it is unclear how they extract information about the origin of the odor and translate it into behaviors that allow them to find the source.
A major hurdle in the way of understanding how animals track smells is the need to visualize odors and behaviors simultaneously. While tracking insect behaviors in the wild remains a daunting task, wind-tunnel experiments provide a way to collect high-throughput data in controlled situations (Álvarez-Salvado et al., 2018). However, the artificial environment still poses several challenges: for example, it is unclear whether naturally occurring stimuli can be reproduced, or if it is possible to visualize odor concentrations with sufficient resolution.
Now, in eLife, Thierry Emonet and co-workers from Yale University – including Mahmut Demir and Nirag Kadakia as first authors – report how the fruit fly Drosophila melanogaster behaves in response to an attractive smell while walking (Demir et al., 2020). Quite serendipitously, they discovered that starved flies are attracted to smoke, which can be easily visualized. By manipulating the airflow in a wind tunnel with lateral jets, they generated a stream of smoke with properties similar to the odor signals that flies encounter in the wild (Celani et al., 2014). In agreement with theoretical expectations, they found that, within the smoke, flies have brief, frequent and unpredictable encounters with the odor. But how do these encounters modulate flies’ behavior?
Demir et al. observed that the rich variety of movements exhibited by walking Drosophila could be summarized into just a few behavioral states relevant to olfactory navigation, echoing previous findings (Tao et al., 2019). They found the search process was inherently stochastic: periods of walking in a straight line would randomly be interrupted by rapid turning events or by stopping for longer extents of time.
By comparing the trajectories recorded with or without smoke, but always in presence of turbulent airflow, Demir et al. were able to identify which features of the flies’ movements were affected by encountering the smell. They found that the walking pace, the frequency and speed at which the flies made a turn, and the sharpness of the turns were not affected by the smoke. Conversely, when the smoke was present walks were on average longer and stops shorter. Most importantly, when the flies were turning, they were more likely to reorient upwind against the direction of the wind if they had already encountered the odor. But what are the specific characteristics of the odor that the fly perceives and responds to?
Demir et al. found that neither the concentration of the odor nor the amount of times flies were exposed to it played a significant role in the search process. Instead, the tempo of the flies’ encounters with the odor appeared to be the key determinant of the decision-making process. In a stopped fly, a single encounter was sufficient to initiate a walk, and several encounters close together shortened the duration of the stops. Walking times increased after an encounter, but further exposure to the odor shortly after did not lead to a cumulative effect. This modulation of walks and stops produces a bias that results in the fly visiting regions of space where it is more likely to encounter the smell. Further experiments showed that above a certain frequency of encounters flies were more likely to re-orientate themselves upwind. In fact, the combined effect of the odor on the frequency of walks and stops, as well as the direction of the turns, proved to be fundamental for the flies to find the origin of a smell (Figure 1).
There are tantalizing similarities between the olfactory-search strategies of walking flies and other insects, but also significant differences (Mafra-Neto and Cardé, 1994; Budick and Dickinson, 2006). In any event, irrespective of their sizes and behaviors, different species must overcome the same challenges posed by the transport of odor molecules by the turbulent airflow, pointing to the existence of general underlying principles. Perhaps, in the future, more studies like this one will pave the way towards a more fundamental understanding of long-range olfactory navigation.
References
-
Algorithms for olfactory search across speciesThe Journal of Neuroscience 38:9383–9389.https://doi.org/10.1523/JNEUROSCI.1668-18.2018
-
Free-flight responses of Drosophila melanogaster to attractive odorsJournal of Experimental Biology 209:3001–3017.https://doi.org/10.1242/jeb.02305
-
Odor landscapes in turbulent environmentsPhysical Review X 4:041015.https://doi.org/10.1103/PhysRevX.4.041015
-
Odor plumes and how insects use themAnnual Review of Entomology 37:505–532.https://doi.org/10.1146/annurev.en.37.010192.002445
Article and author information
Author details
Publication history
Copyright
© 2020, Celani
This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 1,223
- views
-
- 101
- downloads
-
- 5
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Neuroscience
Brain water homeostasis not only provides a physical protection, but also determines the diffusion of chemical molecules key for information processing and metabolic stability. As a major type of glia in brain parenchyma, astrocytes are the dominant cell type expressing aquaporin water channel. How astrocyte aquaporin contributes to brain water homeostasis in basal physiology remains to be understood. We report that astrocyte aquaporin 4 (AQP4) mediates a tonic water efflux in basal conditions. Acute inhibition of astrocyte AQP4 leads to intracellular water accumulation as optically resolved by fluorescence-translated imaging in acute brain slices, and in vivo by fiber photometry in mobile mice. We then show that aquaporin-mediated constant water efflux maintains astrocyte volume and osmotic equilibrium, astrocyte and neuron Ca2+ signaling, and extracellular space remodeling during optogenetically induced cortical spreading depression. Using diffusion-weighted magnetic resonance imaging (DW-MRI), we observed that in vivo inhibition of AQP4 water efflux heterogeneously disturbs brain water homeostasis in a region-dependent manner. Our data suggest that astrocyte aquaporin, though bidirectional in nature, mediates a tonic water outflow to sustain cellular and environmental equilibrium in brain parenchyma.
-
- Neuroscience
Neural implants have the potential to restore lost sensory function by electrically evoking the complex naturalistic activity patterns of neural populations. However, it can be difficult to predict and control evoked neural responses to simultaneous multi-electrode stimulation due to nonlinearity of the responses. We present a solution to this problem and demonstrate its utility in the context of a bidirectional retinal implant for restoring vision. A dynamically optimized stimulation approach encodes incoming visual stimuli into a rapid, greedily chosen, temporally dithered and spatially multiplexed sequence of simple stimulation patterns. Stimuli are selected to optimize the reconstruction of the visual stimulus from the evoked responses. Temporal dithering exploits the slow time scales of downstream neural processing, and spatial multiplexing exploits the independence of responses generated by distant electrodes. The approach was evaluated using an experimental laboratory prototype of a retinal implant: large-scale, high-resolution multi-electrode stimulation and recording of macaque and rat retinal ganglion cells ex vivo. The dynamically optimized stimulation approach substantially enhanced performance compared to existing approaches based on static mapping between visual stimulus intensity and current amplitude. The modular framework enabled parallel extensions to naturalistic viewing conditions, incorporation of perceptual similarity measures, and efficient implementation for an implantable device. A direct closed-loop test of the approach supported its potential use in vision restoration.