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Published in final edited form as: Curr Opin Neurobiol. 2019 Dec 14;64:10–16. doi: 10.1016/j.conb.2019.11.017

Multisensory control of navigation in the fruit fly

Tim Currier 1, Katherine Nagel 1
PMCID: PMC7292770  NIHMSID: NIHMS1569597  PMID: 31841944

Introduction

A central role of the brain is to combine input from multiple sensory modalities to guide behavior. How, where, and why it does this is not clear for most organisms and behaviors. Because it is influenced by nearly every sensory modality, spatial navigation provides an excellent model to understand how the brain integrates diverse stimuli. In this review, we will focus mainly on recent discoveries in Drosophila melanogaster, an excellent model for detailed circuit dissection and precise genetic manipulations of behavior. We will review the different forms of multisensory integration that have been experimentally demonstrated in navigating flies, and consider the neural sites where this integration might occur. Finally, we will suggest possible topics for future study that might allow circuit analysis in the fly to inform our understanding of multisensory integration in larger animals.

A broad range of sensory modalities guides navigation in fruit flies

Insects are avid navigators, using cues from sun, sky, smell, wind, and self-motion to find their way through dense tropical forests and bleak desert pans. The navigational exploits of desert ants and foraging bees have been reviewed elsewhere (Webb 2016, Heinze, 2017). Here we will focus on the humble fruit fly, whose peregrinations are likewise influenced by nearly every sensory modality.

Vision

Because of their ability to provide spatial and directional information, visual cues play a central role in fly navigation. Flies can orient to a variety of visual landmarks. For example, flying flies will fixate a high contrast vertical stripe (perhaps reminiscent of a distant tree) but avoid shorter objects (Maimon 2008). Vision also plays a role in the selection of preferred perching sites (Robie 2010). Flies can select a stable orientation relative to a visual object, such as the sun (Giraldo 2018) or a stripe (Green 2019), allowing them to travel in straight lines over long distances. Larval flies have less developed visual systems than adults and have not been shown to navigate relative to visual objects. However, larvae can use illumination gradients to navigate, displaying robust taxis away from brighter areas (Kane 2013; Humberg 2018).

Mechanosensation

Flies use antennal mechanoreceptors to detect both wind and sound (Yorozu 2009, Kamikouchi 2009). Each of these cues can influence navigation. For example, high wind speeds cause freezing (Yorozu 2009), while gentler winds are used for olfactory orientation (Bell 2015, Alvarez-Salvado 2018). Sound sources can be localized by comparing the magnitude of vibrations across the two antennae (Batchelor 2019). Sound-driven movements also play a critical role in courtship, during which male flies vibrate their wings while trailing a female at a stereotyped distance and angle (Coen 2014). Finally, noxious mechanosensory stimuli can elicit escape behaviors in larvae (Ohyama 2015) and freezing in adults (Lehnert 2013).

Olfaction

Odors can signal the presence of food, conspecifics, predators, or harmful microbes. Many odors thus illicit innate attraction (Jung 2015) or avoidance (Chin 2018). Larvae move toward food odors by measuring changes in odor concentration over time — decreases in this signal regulate the transition from straight runs to turns (Gershow 2012, Gomez-Marin 2014). Active head movements allow larvae to make finer measurements of odor gradients, facilitating proper up-gradient orientation during turns (Gomez-Marin 2014, Schulze 2015). Similarly, adult flies use concentration differences across the two antennae to orient toward higher concentrations (Borst 1982, Gaudry 2013). However, directional information is difficult to derive from concentration gradients when odor is carried on a wind-borne plume. Instead, adult flies make their way up plumes by integrating odor signals with visual and mechanosensory cues about wind direction (van Breugel 2014, Wasserman 2015, Bell 2015, Alvarez-Salvado 2018). Odor can also gate attraction to visual objects, allowing flies to identify potential landing sites (Saxena 2018, Cheng 2019) and to orient toward a female during courtship (Ribeiro 2018, Bidaye 2019). Many odors drive diverse changes in locomotion that are not simply predicted by odor valence (Jung 2015).

Thermosensation

Thermal stimuli drive taxis in larvae and adults, both of which exhibit preferred temperatures. Larval thermotaxis resembles chemotaxis, with temperature changes over time modifying the probability of re-orienting (Klein 2015; Lahiri 2011). Adult flies similarly processes thermal stimuli on multiple timescales (Frank 2015, Liu 2015).

Path integration

A final source of directional information is the so-called path integration system, an internal sense of direction used by insects and crustaceans to return to their nests after foraging voyages (Müller…Wehner, 1988). While flies do not return to a nest, they will return to previously located food sources (Kim/Dickinson 2017, Corfas 2019), even when visual or olfactory cues are not present.

Distinct modes of sensory integration are observed in different behavioral contexts

Natural environments often generate cues across many sensory modalities. Given the wide array of stimuli that can influence navigation, simultaneous cues may not always promote similar behaviors. Navigation in natural environments therefore requires the combination or comparison of competing stimuli. How does the fly achieve cross-modal integration with sufficient flexibility? Four main strategies have been observed experimentally: suppression, gating, summation, and association (Fig. 1). Each of these forms of integration may be associated with different neural circuit mechanisms.

Figure 1. Modes of multisensory integration during navigation.

Figure 1.

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(A) Suppression occurs when two cues drive mutually exclusive behavioral states. A hungry fly will track odor in the absence of other cues. Activation of taste receptors reduces or halts locomotion, although odor is still present. Adapted from Sayin et al., 2019.

(B) Gating occurs when one cue modifies a fly’s response to a second cue. Flies orient downwind in the absence of odor. Addition of odor (orange) induces upwind orientation. Adapted from Alvarez-Salvado et al., 2018.

(C) Summation occurs when two cues influence the same navigation parameter. In this case, a strongly attractive visual stimulus (purple) and a weakly aversive wind stimulus (green) each bias turn rate and direction. The strong drive to turn toward the visual cue is summed with the weak drive to turn away from the wind cue. The result (gray) is a turn of intermediate angular velocity toward the stronger (visual) cue. Adapted from Currier & Nagel, 2018.

(D) Association occurs when a cue that promotes innate attraction or aversion is paired with an innocuous cue from another modality. Here, noxious heat (red) is paired with orientation toward a visual pattern. The visual stimulus becomes associated with heat avoidance, causing the fly to turn away from the visual cue presented alone. Adapted from Liu et al., 2006.

Suppression occurs most often when the addition of a cue drives a change in behavioral state. For example, activation of gustatory sugar-sensing neurons inhibits locomotion (Corrales-Carvajal 2016), including locomotion evoked by odor (Sayin 2019). Mechanical stimulation of bristles similarly suppresses locomotion and evokes grooming (Seeds 2014). Conversely, neurons that promote forward walking can inhibit proboscis extension, a component of feeding behavior (Mann 2013). Thus, feeding, grooming, and locomotion might be considered mutually exclusive behavioral states. Suppressive integration arises when these mutually exclusive behaviors are driven simultaneously.

A complementary mode of integration is gating, in which the presence of one stimulus releases or switches the orienting response toward another. For example, food odors can switch a fly’s preferred orientation from downwind to upwind (van Breugel 2014, Bell 2016, Alvarez-Salvado 2018), or trigger the investigation of small visual objects (Saxena 2018, Cheng 2019). Similarly, visual orientation to a female can be triggered by P1 neurons (Ribeiro 2018), which are activated by olfactory and gustatory cues (Clowney 2015).

Surprisingly, competing navigation cues simply sum in many circumstances, with multisensory behavior reflecting weighted contributions from each modality. For example, visually evoked turns towards a stripe are summed with mechanosensory turns away from an air source, producing faster or slower turns depending on the orientations of the two stimuli (Currier 2018). Similarly, turns evoked by visual and olfactory cues are well-described as a linear sum of the responses to each stimulus alone (Frye 2004). In larval flies, olfactory and visual cues both drive taxis by modulating turn rate. As in adults, turn probability here reflects a linear sum of the responses to the two cues alone (Gepner 2015). Thus, summation likely represents one of the main modes of integration for stimuli arriving from different modalities.

Finally, flies can learn to associate a variety of cues with visual stimuli to drive navigation. In a version of the mammalian Morris water maze, flies can associate visual scenes with the location of cool or non-electrified “safe spots” (Ofstad 2011, Vogt 2014). Similarly, flying flies can learn to avoid 2-dimensional patterns that have been paired with infrared laser stimulation (Liu 2006). Flies also show a preference for visual landmarks previously paired with optogenetic activation of gustatory receptors (Haberkern 2019).

Sensory modalities are integrated multiple times to guide navigation

Where is information from multiple modalities combined in the insect brain, and how do these circuits support the navigation behaviors discussed above? While the answer to this question is not yet known for many specific behaviors, existing data suggest that sensory modalities are integrated multiple times and in multiple locations.

The simpler nervous system of the Drosophila larva has prompted extensive studies of the circuit architecture underlying navigation. In a landmark paper, Ohyama and colleagues (Ohyama 2015) used EM reconstruction, along with behavioral experiments and calcium imaging, to reconstruct circuits that translate wasp attack cues — the sound of wingbeats and nociceptor activation — into an escape roll. They found that these cues are integrated multiple times. “Basin” interneurons in the ventral nerve cord first integrate both cues. By way of abdominal interneurons, basins converge onto command-like “Goro” neurons that trigger rolling. Ascending brain projection neurons also link basins with Goros in a three neuron arc. These two pathways work cooperatively to promote efficient escape behavior.

Multisensory integration has also been examined in the context of larval foraging. Using a silencing screen, Tastekin et al. (2015) identified descending neurons from the sub-esophageal zone (SEZ) that are required for chemotaxis. A detailed analysis demonstrated that this group of neurons is responsible for the transition from forward runs to turns, triggered by decreasing odor concentration. Silencing these neurons impaired both photo- and thermotaxis. These data suggest that navigational cues from different modalities have been integrated into motor-like commands at or before the SEZ.

In adults, integration of signals from different modalities similarly occurs at multiple levels of the nervous system (Fig. 2), and has been observed as early as the sensory periphery. Specific posterior antennal lobe projection neurons respond to both temperature changes and constant-temperature dry air (Frank 2017). As temperature and humidity are transduced and represented in a manner analogous to odorants, hygro-thermal integration might be compared to the melding of olfactory signals from different receptor channels that also occurs at the first synaptic relay.

Figure 2. Multiple sites of multisensory integration in the fly brain.

Figure 2.

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(A) Primary sensory regions in the adult fly brain. Visual information is processed by the optic lobes (purple), mechanosensory cues (such as wind and sound) by the antennal mechanosensory and motor center (AMMC, green), and taste stimuli by the sub-esophageal zone (SEZ, blue). Odor, temperature, and humidity signals are all processed in the antennal lobes (orange).

(B) Key sites of multisensory integration. Colored arrows (as in panel A) indicate the modalities integrated in each region. The mushroom body receives both olfactory and visual information at its input layer in the calyx (Vogt et al. 2016). Taste information provides valence input to dopamine neurons that control mushroom body output (Kim/Scott 2017). The ventral lateral horn receives input from olfactory, visual, mechanosensory, and taste regions (Dolan 2019). The posterior slope contains the post-synaptic compartments of many descending neurons (DNs, gray) that provide motor commands to the ventral nerve cord. Many DNs receive input from both mechanosensory regions and from lobula columnar cells carrying visual information (Namiki 2017). Finally, the central complex receives visual input through ring neurons of the ellipsoid body (Omoto 2017, Sun 2017). Mechanosensory signals have been observed in the fan-shaped body (Ritzmann 2008), and olfactory neurons have downstream partners there (Scalpen 2019).

The ventral portion of the lateral horn, a structure traditionally thought of as a higher-order olfactory center, has recently been identified as a hub for multisensory integration (Dolan 2019). Based on anatomy, this region receives input from visual, mechanosensory, olfactory, and gustatory regions. However, the behavioral function of ventral horn integration is not yet clear.

Significant multisensory integration also occurs in the learning centers of the fly brain. The mushroom body is required for olfactory associative learning, and receives olfactory inputs at the calyx (Aso 2014). However, portions of the mushroom body also receive visual input (Gronenberg 1999, Balkenius 2009, Kinoshita 2015), and in some insects input to the mushroom body is almost entirely visual (Lin 2012). Behavioral experiments suggest that the same mushroom body dopamine neurons are required for both visual and olfactory associative learning, but that visual information arrives via distinct input cells (Vogt et al. 2014, 2016). The mushroom body also receives input from gustatory systems (Kim/Scott 2017, Sayin 2019), and is required for learned taste aversion (Kim/Scott 2017). Thus, the mushroom body may serve as an all-purpose engine for associating sensory stimuli with reward or punishment.

The adult brain region most closely associated with navigation is the central complex (Cx). Inputs to the Cx relay visual navigation cues, such as the orientation of polarized light (Heinze 2007) or visual landmarks (Omoto 2017, Sun 2017), and Cx lesions disrupt vision-based navigation (Strauss 1993). Cx neurons also respond to mechanosensory cues, such as stimulation of the antennae (Ritzmann 2008, Phillips-Portillo 2012). The Cx additionally receives input from mushroom body output neurons known to be involved in olfactory processing (Scalpen 2019). Whether most Cx neurons are multisensory, and how sensory information from different modalities is organized within the central complex, is not known.

The central complex contains representations of self-motion, including heading (Seelig 2015), angular velocity (Martin 2015, Green 2017, Turner-Evans 2017), and forward velocity (Stone 2017). Each of these signals depends on both visual and proprioceptive cues. A representation of heading is required for fixed-angle orientation to a visual stimulus (Giraldo 2018, Green 2019), but how this representation of self-motion is integrated with external sensory cues to guide navigation is not yet clear. Some orienting behaviors, such as looming avoidance and male courtship, are supported by visual interneurons that synapse directly onto descending neurons (Wu 2015, Ribeiro 2018, Bidaye 2019), and do not appear to require the Cx. Larvae are able to perform taxis in response to heat, light, and odors — and can integrate these cues — without a Cx (Luo 2010, Gepner 2015, Humberg 2018, Tastekin 2018). Thus, a key open question in insect navigation is which forms of navigation require a Cx, and which do not.

Finally, sensory signals can be integrated by descending neurons that directly activate the ventral nerve cord. A prominent example is the escape-promoting giant fiber neuron, which receives visual input related to looming (von Reyn 2014, Ache 2019) and mechanosensory inputs representing vibration and wind (Lehnert 2013). Direct integration of this sort may facilitate the rapid takeoff maneuvers required for escape.

Synaptic and circuit motifs for multisensory integration

Navigation is influenced by many modalities. Here we have argued that modalities can be combined in many ways, depending on the behavioral needs of the animal. In specific situations, experimenters have observed suppression, summation, gating, and learned association between cues of different modalities. It is likely that each of these integration modes depend on different circuit organizations and biophysical mechanisms, which may help to explain why the relatively simple fly brain integrates multimodal cues in so many regions.

Moving forward, identifying the circuit and biophysical motifs that allow for these different modes of integration in the fly could provide templates for how similar computations occur in vertebrates (Fig. 3). For instance, when simultaneous cues drive mutually exclusive behaviors, such as grooming, feeding, and locomotion, integration will likely involve reciprocal inhibition (Mann 2013, Seeds 2014). Such circuits could facilitate cross-modal suppression, allowing one network state, and therefore one behavior, to be active at each moment.

Figure 3. Hypothesized circuit and synaptic mechanisms of integration.

Figure 3.

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(A) Cross-modal suppression through reciprocal inhibition. Networks driving feeding and locomotion are linked by mutual inhibition (barred connections). Sensory input that drives feeding (tastant, blue) or locomotion (odor, orange) evokes winner-take-all dynamics.

(B) Summation through convergent sensory input. Neurons carrying visual (purple) and wind (green) information both make excitatory synapses (arrows) onto a neuron that controls orientation (gray).

(C) Gating through presynaptic inhibition. Wind signals (green) provide input to a neuron that controls orientation (gray). Odor information (orange) presynaptically shunts wind input to the orientation control neuron through an inhibitory connection (bar).

(D) Cross-modal association through modulation. The simultaneous presentation of noxious heat (red) and a visual stimulus strengthens the synapse from the visual input neuron onto the orientation control neuron through release of a neuromodulator from the heat-sensitive neuron (circle). Subsequent presentations of the visual stimulus alone are sufficient to drive activity in the orientation control cell. Inset shows the strength (w) of the synapse before and after pairing.

In contrast, multimodal navigation cues that each influence the same locomotor parameter, such as angular velocity, can be more simply integrated via synaptic summation. Information from each sense could converge onto single neurons or networks that control angular velocity in a graded manner.

A number of circuit and synaptic mechanisms could support multisensory gating. For example, the “gating” modality could be represented in neurons that presynaptically inhibit (or dis-inhibit) responses to the “gated” modality (Olsen 2009). In this motif, downstream locomotor control cells receive one set of inputs in single-modality conditions, and qualitatively different input in multisensory conditions. Second, the gating modality could control the release of neuromodulators that alter the strength of synapses relaying information about the gated modality. Finally, circuit mechanisms could also alter the gain of gated synapses, perhaps through recurrent amplification or changes to background synaptic input (Chance 2002).

A circuit structure for associative learning has been described in the mushroom body, where dopamine neurons control the strength of synapses that link sensory representations to behavioral outcomes (Aso 2014, Hige 2015). Spike-timing dependent plasticity may generally facilitate the association of stimuli from different sensory modalities (Handler 2019).

Although the multisensory control of navigation can theoretically be studied in many organisms, the robust behaviors and expansive genetic tools offered by the fruit fly make it an excellent model to identify the circuit motifs that support integration. Successful future studies will combine cell-specific manipulations of neural activity or gene expression with electron microscopy-based circuit reconstructions to reveal how animals integrate multisensory navigation cues.

Highlights.

  • Spatial navigation in Drosophila relies on many sensory modalities

  • 4 modes of integration have been observed: suppression, gating, summation, and association

  • Multiple brain regions are involved in multisensory integration

  • Distinct circuit mechanisms may underlie different modes of integration

Acknowledgements

This work was funded by grants from NIH (R00 DC012065, R01MH109690, and R01DC017979), NSF (IOS-1555933), and by the Sloan, Klingenstein-Simons, and McKnight Foundations to KN. TC was supported by a Dean’s Dissertation Fellowship Award from NYU.

Footnotes

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Conflicts of interest

The authors declare no conflict of interest.

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