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date: 24 October 2020

Sensing Polarized Light in Insects

Abstract and Keywords

Evolution has produced vast morphological and behavioral diversity amongst insects, including very successful adaptations to a diverse range of ecological niches spanning the invasion of the sky by flying insects, the crawling lifestyle on (or below) the earth, and the (semi-)aquatic life on (or below) the water surface. Developing the ability to extract a maximal amount of useful information from their environment was crucial for ensuring the survival of many insect species. Navigating insects rely heavily on a combination of different visual and non-visual cues to reliably orient under a wide spectrum of environmental conditions while avoiding predators. The pattern of linearly polarized skylight that results from scattering of sunlight in the atmosphere is one important navigational cue that many insects can detect. Here we summarize progress made toward understanding how different insect species sense polarized light. First, we present behavioral studies with “true” insect navigators (central-place foragers, like honeybees or desert ants), as well as insects that rely on polarized light to improve more “basic” orientation skills (like dung beetles). Second, we provide an overview over the anatomical basis of the polarized light detection system that these insects use, as well as the underlying neural circuitry. Third, we emphasize the importance of physiological studies (electrophysiology, as well as genetically encoded activity indicators, in Drosophila) for understanding both the structure and function of polarized light circuitry in the insect brain. We also discuss the importance of an alternative source of polarized light that can be detected by many insects: linearly polarized light reflected off shiny surfaces like water represents an important environmental factor, yet the anatomy and physiology of underlying circuits remain incompletely understood.

Keywords: insect vision, polarized light, behavior, navigation, orientation, water detection, physiology, neuroethology, visual ecology, neural circuits, neuroanatomy


The periodic illumination by sunlight is essential for directly fueling plant life on the earth, which in turn serves as an indispensable food source for all animal life. Sunlight is also crucial for synchronizing circadian behaviors across the animal kingdom, but it also enabled the evolution of a variety of photosensitive eye structures crucial for the successful adaptation to both nocturnal and diurnal lifestyles across a wide range of light intensities (Land & Fernald, 1992). Just like all other senses, visual systems across phyla evolved the ability to extract, distinguish, and quantify different modalities of incident or reflected sunlight, like intensity (brightness) or wavelength composition (color). Complex neural circuits underlying these processes have been characterized using behavioral, anatomical, and physiological approaches. Across species, striking similarities exist between the neuronal arrangements processing a specific feature, such as the local intensity increments or decrements associated with the perception of moving objects. Recently, understanding the computations performed by these circuits down to a cellular level has started to come within reach (Borst, 2014).

Sensing Polarized Light in Insects

Figure 1: Polarized light sources in the environment. Direct sunlight is unpolarized, meaning all e-vector orientations are equally represented (symbolized by the white, double headed arrows. Depicted are four different sources of polarization (from left to right): (1) reflection off water, leading to linearly polarized light with a horizontally oriented e-vector; (2) reflection off of shiny leaves, can lead to an oblique e-vector orientation; (3) reflections off the body surface of a scarab beetle lead to circular polarization with a rotating e-vector; (4) celestial pattern of linearly polarized light is created by scattering of sunlight in the atmosphere, which is strongest at an angle of 90 degrees from the sun. Therefore, e-vector orientation and degree of polarization vary across the sky (symbolized by thickness and orientation of the bars) in a predictable pattern that is centered around the sun.

In order to maximize an animal’s chance of survival, its nervous system had to evolve the ability to constantly extract specific features from the visual world that are useful for its lifestyle, filter them for relevance, and then combine them in a meaningful way to ensure an optimal behavioral output. It is therefore no surprise that many animal species developed very specialized sensitivities to specific visual modalities. One specific example is the perception of linearly polarized light, an ability that can be found across a large number of species involving vertebrates (birds, fishes), as well as marine invertebrates (Cephalopods, Crustaceans), and many flying or crawling insects (Cronin et al., 2003; Nilsson & Warrant, 1999). Although many of these species may use the information encoded by a stimulus containing polarized light for different purposes, they all detect the same physical property— the e-vector orientation of incident light (Wehner, 2001). Normally, sunlight is unpolarized, meaning its e-vectors are distributed randomly. However, different phenomena can result in the overrepresentation of certain e-vector orientations (summarized in Figure 1). First, there is scattering of sunlight in the atmosphere, resulting in linearly polarized skylight. Interestingly, both degree of polarization as well as e-vector orientation vary across the sky, creating a celestial polarization pattern that is centered around the sun and therefore changes over time from an observer’s perspective. Second, reflection of sunlight off of shiny surfaces results in linearly polarized reflections with defined e-vector orientations (horizontal, in the case of water bodies). Ponds or lakes, as well as shiny leaves or even moist skin or fur can create such linearly polarized reflections. Third, reflection of sunlight from certain materials, like the body surface of certain invertebrates, can result in circular or elliptical polarization, meaning the e-vector orientation changes in a circular fashion as the light beam propagates. Therefore, all three sources of polarized light provide crucial cues to many animals, especially insects. Polarized light can serve as: (1) information about the position of the sun (which itself might be obstructed from view), providing an additional celestial orientation cue baring important information to facilitate navigational tasks; (2) a signal indicating the presence of water as a potentially attractive or repulsive surface (depending on the behavioral context); (3) polarized reflections off different objects that may encode attractiveness as a food source or as suitable substrate for egg laying; or (4) polarized reflections off the body surface a conspecific individual signalizing availability for mating or to signal competition.

In the following sections we will summarize the existing work covering the different roles polarized lights can play for different insects, focusing on progress from more recent studies. We group the text into three broad research areas, which, when taken together, form a synergistic picture of the neuroethology of e-vector detection: first, we focus on the lessons that can be learned from the careful quantitative description of an animal’s behavioral responses to celestial and reflected polarized light stimuli. Second, we describe the anatomical techniques used to characterize both polarization sensitive photoreceptor neurons, as well as their synaptic connectivity. Third, we describe how targeted and unbiased physiologic characterization of polarization-sensitive neurons from the retina to the central brain results in a growing cellular model of polarization circuitry in the insect brain.


The huge morphological and behavioral diversity within the insect world provides a wide range of stunning examples of how different insect species utilize polarized light stimuli in order to adapt to their environment. Classic examples are true point-to-point navigators like honeybees and desert ants as well as species that use polarized light to improve their orientation skills, especially dung beetles, crickets, desert locusts, butterflies, and flies. Behavioral responses to polarized reflections from water are less well understood, although a growing number of reports have described this behavior. However, the importance of polarized reflections off other substrates remains much less well understood.

Polarized Light and Navigation Behavior of Central Place Foragers

Sensing Polarized Light in Insects

Figure 2: Honeybees deduce solar position from perceived e-vector orientations. Summary of experiments where honeybees were trained to fly through a tunnel toward a feeder. A polarizing foil mounted onto the tunnel ceiling resulted in the bees experiencing exclusively axial vectors (A–C), orthogonal e-vectors (D–F), or one followed by the other (G–I). The sun was always blocked off and could not be used as a landmark by the animals. (B) During the consecutive waggle dance, the bees communicated the direction to the food source by dancing a straight line at a defined angle to the sun. Individual waggle dance traces (red) plotted after flights through a tunnel with axial e-vectors were directed predominantly at orthogonal angles to the solar meridian (mean axis in turquoise). (C) Schematic summarizes the natural relationship between axial e-vectors in the zenith and the solar position associated with it (solar meridian is orthogonal to the bees path). (E) Waggle dance traces (red) are oriented along the solar meridian when orthogonal e-vectors were perceived, which is in agreement with the natural relationship between these stimuli (see F). The perception of both axial and orthogonal e-vectors arranged consecutively within the same tunnel led to dance directions (mean axis in turquoise) along the four diagonal axes (dotted black lines). (H) The four dance directions observed under a natural sky, after training in atunnel with two e-vectors (G), can be explained by the summation of two vectors (I). (Adapted with permission from Evangelista et al., 2014.)

The importance of linearly polarized light as a guidance cue for navigating insects was first demonstrated in 1949, when Karl von Frisch was experimenting with honeybees, which need to reliably find their way from the hive to a food source and back (von Frisch, 1949). Therefore, they serve as an excellent insect model system for truly navigating “central place foragers.” In von Frisch’s experiments, honeybee workers were able to correctly indicate to their nestmates the angular direction toward a food source during the “waggle dance,” even when the sun was occluded from their field of view. Through a series of tests, von Frisch identified the celestial polarized light pattern (which is always centered around the sun) as the source of this behavior, a discovery that was later confirmed and elaborated on by Rossel and Wehner (1986; for review see Rossel, 1993). These experiments revealed that honeybees can deduce the position of the sun (which serves as the reference for the “waggle” dance) from the perceived polarization pattern. This is particularly useful in situations when the sun is not visible, for instance, when hidden behind a cloud. Hence, by using both solar position (if available) and the celestial polarization pattern, the honeybee internal compass becomes much more reliable. In a more recent reexamination of this topic, it was shown that honeybees indeed compute polarized light information during flight by extracting a heading angle from the perceived e-vectors (summarized in Figure 2). For these experiments, honeybees were trained to fly through a 12-m tunnel toward a feeder while experiencing either axial or perpendicular e-vectors from above (Evangelista, Kraft, Dacke, Labhart, & Srinivasan, 2014; Kraft, Evangelista, Dacke, Labhart, & Srinivasan, 2011). As expected, the resulting heading orientation encoded by the linear phase of the “waggle dances” differed by 90 degrees between the two experiments: an axial e-vector resulted in perpendicular dances (Figure 2A–C), while a perpendicular e-vector resulted in axial dance orientations (Figure 2D–F) (waggle dance directions are always mirror symmetric, due to the inherent directional ambiguity of a polarized light stimulus: 0 and 180 degrees are the same). These waggle dance orientations were in good agreement with the natural solar position under these conditions: perpendicular e-vectors in the zenith occur when the sun is behind or in front of the animal, and axial e-vectors in the sun coincide with solar positions toward +90 or −90 degrees. Interestingly, when the flight tunnel was divided into two consecutive halves of first axial and then perpendicular e-vectors, the resulting waggle dances pointed toward all four diagonal directions, which in fact is the sum of all possible directional vectors the animal could have deduced from summing the two orthogonal e-vector orientations it had experienced (Figure 2G–I). In the absence of a solar landmark, the honeybees therefore make correct decisions by using the celestial e-vector pattern, which heavily biases their navigational decisions.

Sensing Polarized Light in Insects

Figure 3: Integration of sun and polarized light information by desert ants. (A) Classic example for path integration of the desert ant Cataglyphis: after an unbiased exploration run (blue), the ant returns to the nest in a straight line (red). To achieve this goal, the ant must constantly update information segments traveled to determine the homing vector to the nest. (With permission from Wehner, 2003.) (B) Summary of experiments where the ant was walking through a tunnel toward a feeder, while experiencing defined e-vector orientations that were created by mounting a polarizing foil onto the tunnel. When presenting the animals only one of three different stimuli during training and test (solar position, single e-vector, or celestial polarization pattern), they could correctly deduce solar position from e-vectors and vice versa. The animal therefore has an innate prediction of the relationship between these stimuli, and information can be transferred between the sensory systems perceiving them. Homing responses after training with perpendicular e-vectors is less accurate due to interference from phototaxis. (Adapted from Lebhardt & Ronacher, 2015.) (C) Top: By allowing the ant to see the sun while traveling through the tunnel, stimulus combinations were produced where polarization pattern and solar positions were in conflict. Bottom: The ants appeared to consider both stimuli equally reliable, setting of an intermediate homing vector (red) through averaging the vectors suggested by solar position (yellow), and polarization pattern (purple). (Adapted from Lebhardt & Ronacher, 2014.)

These experiments raise exciting questions about the integration of solar and celestial compass information, for instance, in cases of apparent conflict between a solar positions with an “unnatural” e-vector orientation. These questions have been addressed using another central place forager model system, the desert ant Cataglyphis. Over the last decades, the work of Rüdiger Wehner and colleagues has demonstrated the ability of these desert ants to efficiently navigate in an arid environment mostly void of any visual landmarks, thereby relying heavily on the celestial pattern of polarized light (for review, see Wehner, 2003). After finding food during an unbiased exploration run, the desert ants return to their nest entrance in a straight line rather than retracing their steps (which would result in an unnecessary waste of energy) (Figure 3A). In order to achieve this task, the ant is constantly updating its homing vector as it proceeds by measuring the direction of individual path segments as well as the distances traveled. This sophisticated navigational process, which was termed “path integration,” therefore combines the internal compass and the odometer system of the ant. Previous work investigating the ant’s internal compass system demonstrated that the celestial polarized light information appeared to dominate over the perceived solar position when the two were in conflict (Wehner & Müller, 2006). More recently, a series of experiments by Lebhardt and colleagues added new insights to the computation of these cues (Lebhardt, Koch, & Ronacher, 2012; Lebhardt & Ronacher, 2014, 2015): similar to the honeybee experiments, desert ants were trained to walk toward a feeder through a tunnel covered with polarization filters while the sun was occluded from the field of view. In the following test runs, the ants were walking under the open sky, witnessing the entire celestial e-vector pattern as well as the position of the sun. In agreement with the honeybee experiments, the ants trained under a single e-vector orientation correctly associated the solar position with the e-vector orientation, leading to strongly directed homing vectors: perpendicular e-vectors during training signaled solar positions front or back, whereas axial e-vectors signaled solar positions at orthogonal angles (Lebhardt et al., 2012). Once again, linear summation of orthogonal e-vectors during training resulted in diagonal homeward trajectories. Interestingly, it was also shown that polarized light information dominates over idiothetic cues (e.g., proprioceptive signals from mechanoreceptors), since the change of direction enforced by orthogonal bends in the tunnel were ignored by the ant if the presented e-vectors signaled an invariant celestial pattern. Another study by the same authors investigated the transfer of information between the solar detection system and the sensory system for detecting celestial polarization. For these experiments, desert ants experienced only one stimulus—either solar position or single e-vectors—during their training runs through the tunnel (Lebhardt & Ronacher, 2015). For the consecutive homing runs, the ants then had to extract the correct heading vector exclusively from the cue they were not trained with (the celestial polarization pattern or solar position) (Figure 3B). In all cases, the ants made correct navigational decisions. It appears therefore that the ant brain is capable of integrating directional information from solar and polarization detection systems, although they depend on different retinal detectors. Finally, Lebhardt and colleagues investigated the navigational decisions of Cataglyphis when solar and compass information were in direct conflict. In these experiments, desert ants performed training runs while presented single e-vectors as before, but the animals could also see the sun at the same time (Lebhardt & Ronacher, 2014). In all cases where the directional information provided by the e-vector and the solar compass disagreed during training, the ants chose an intermediate homing vector during the consecutive test under the open sky (Figure 3C). It appears therefore that inputs from both compass systems are summed roughly equally, which is surprising given previous findings on the dominance of the sky compass. It is possible that this choice of a mean direction applies to situations where both solar and sky compass information are considered equally reliable, resulting in their summation, rather than hierarchical override by one system (Wehner, Hoinsville, Cruse, & Cheng, 2016). It remains to be seen which factors determine dominance versus summation. In summary, both honeybees and desert ants can extract navigational information from detecting linearly polarized light or the solar position, and they have an innate understanding of the geographical relationship between these stimuli as they occur in nature.

Spontaneous Behavioral Responses to Polarized Light Guiding Orientation Behavior

Most insects do not travel back and forth between food sources and a fixed location like a nest or a hive. Therefore, reproducing the navigational decisions of these animal becomes more difficult. In this case, the investigation of polarized light vision relies on spontaneous behavioral responses, like the setting of certain compass headings, the alignment of the body axis with respect to the incident e-vector, an increased turning tendency in response to a rotating polarization filter, or keeping a straight course over time. All these spontaneous responses can be summarized as “polarotactic” behaviors. In all cases mentioned above, the animal might use the celestial polarization pattern as an orientation cue to plan and execute certain short- or long-range migratory tasks by avoiding to walk or fly in circles. Some of these experiments can be performed in the wild. Alternatively, polarotactic responses are characterized in laboratory experiments where an insect is tethered either over an air-suspended ball or on a wire in a flight arena. By turning the polarization filter above the animal, changes in the angular velocity and heading can be measured. For instance, polarotactic responses of walking crickets were described (Brunner & Labhart, 1985), and behavioral performance under different stimulus conditions were measured, by simulating decreasing degrees of polarization using quarter wave plate, which produces elliptically polarized light with varying ellipticity (and which is perceived as unpolarized in the case of circular polarization, since all e-vectors are equally represented over time; Henze & Labhart, 2007). Interestingly, the behavioral response remained stable down to a (simulated) degree 5% polarization, after which the polarotactic response abruptly ceases, thereby demonstrating how stable this behavior is under natural conditions. The polarotactic responses of desert locusts in tethered flight were used in a similar way to demonstrate the importance of a prominent anatomical structure in the insect brain, the anterior optic tract (AOT), that connects the optic lobe with the anterior optic tubercle (AOTU), a more centrally located structure belonging to the optic glomeruli (Mappes & Homberg, 2004). Bilateral surgical lesion of the AOT completely abolishes polarotaxis in tethered desert locusts, thereby confirming its importance for polarization vision (Mappes & Homberg, 2007). One study on monarch butterflies suspended on a wire also found polarotactic responses (Reppert, Zhu, & White, 2004), which is important given that this species performs long distance migrations over several thousand kilometers across the North American continent, while another one disagreed (Stalleicken et al., 2005). Polarotactic responses are also common in flies (Musca, Drosophila), for which they were demonstrated both for single flies walking on a ball as well as for flies suspended in a flight arena (Vonphilipsborn & Labhart, 1990; Weir & Dickinson, 2012; Wolf, Gebhardt, Gademann, & Heisenberg. 1980). Additionally, using real-time computer tracking of walking populations of Drosophila further demonstrated their spontaneous tendency to align their body axis with the incident e-vector when no other visual stimuli were presented (Velez, Gohl, Clandinin, & Wernet, 2014; Velez, Wernet, Clark, & Clandinin, 2014; Wernet et al., 2012). In the latter case, polarotactic responses were described both for celestial stimuli as well as for linearly polarized stimuli presented to the ventral half of the eye.

Sensing Polarized Light in Insects

Figure 4: Dung beetles set a bearing based on a snapshot of the visual scenery. Summary of three experiments investigating the rolling direction of the diurnal dung beetle Scarabaeus lamarcki. A specific combination of visual cues (celestial body or “Ersatz sun,” green; polarization pattern, UV) was presented during initial dancing and/or ball rolling, followed by a second experiment with a different combination of stimuli. (A) When only the celestial body was presented during the first trial (dance and roll), polarized UV light did not orient the second run (right: circular plot of change in direction between consecutive runs is random). Hence, no internal matched filter exists for transferring orientation information between solar position and celestial polarization pattern. (B) Both cues were presented only during the first “dance” of the animal on top of the ball, yet only polarized UV light was presented during a second experiment (dance and roll). Clustering of changes in rolling direction around zero and 180 degrees suggests the position of the celestial body was remembered, albeit solar and antisolar orientation being indistinguishable, when using the polarized light pattern alone. (C) Only visual cues present during the first dance (in this case, the celestial body) can be used for orienting ball rolling during experiment 2. Taken together, the rolling performance of the dung beetle during experiment shows that a snapshot of the visual scenery can only be taken during the first dance period. (Adapted from el Jundi et al., 2016.)

Particularly powerful model systems for investigating polarotactic behaviors are nocturnal and diurnal dung beetles. In most cases, the dung beetle forms a ball of dung and rolls it away from the food source, usually following a straight line (Baird, Byrne, Scholtz, Warrant, & Dacke, 2010). To achieve this task, the beetles use a combination of visual cues. Amazingly, the nocturnal species Scarabaeus zambesianus uses the polarization pattern of the moonlit sky, which originates from reflection of sunlight off the moon and is one million times dimmer than the daylight pattern (Dacke, Nilsson, Scholtz, Byrne, & Warrant, 2003; Dacke, Nordstrom, & Scholtz, 2003). In addition, the beetle can also use the moon as a landmark to set a straight course (Dacke, Byrne, Scholtz, & Warrant, 2004), and even the Milky Way can be used as an orientation cue (Dacke, Baird, Byrne, Scholtz, & Warrant, 2013) in the case of Scarabaeus satyrus. Diurnal dung beetles like Scarabaeus lamarcki can use an even wider selection of visual cues for their orientation, including the solar position, spectral cues, intensity gradients, and the celestial polarization pattern, the latter being the dominant cue (Dacke, el Jundi, Smolka, Byrne, & Baird, 2014; el Jundi, Foster, Byrne, Baird, & Dacke, 2015; el Jundi, Smolka, Baird, Byrne, & Dacke, 2014). Interestingly, these beetles appear to ignore landmarks (Dacke, Byrne, Smolka, Warrant, & Baird, 2013). But how does the dung beetle process the mixture of visual cues? An important clue was provided by the beetle’s behavior: just prior to rolling the ball away from the dung pile, it climbs onto the ball and performs a characteristic “dance” during which it rotates around its vertical axis (Baird, Byrne, Smolka, Warrant, & Dacke, 2012). Interestingly, the dances also occur whenever the beetle loses control of the ball, after they lose contact with it, when deviations from the set course are induced, or when visual cues change. It was therefore proposed that the dance serves to establish a roll bearing and to return to this bearing once a disturbance has been experienced. One recent study tested this hypothesis, revealing the mechanism underlying these orientation dances (el Jundi et al., 2016). Using an experimental arena, in which artificial stimuli could be presented to the dung beetles (sun, polarization pattern, spectral cues), it was first revealed that unlike honeybees or desert ants, the dung beetle has no innate ability to correctly predict the natural relationship between these cues. Instead, it appears that the dance is used to take a “celestial snapshot” of the current stimulus ensemble, even if this combination of solar azimuth and e-vector orientation never occurs in a natural sky. This internal representation is then used to set a fixed bearing. Interestingly, the snapshot must be taken during the dance, since a specific visual cue that has been absent while dancing cannot be used for accurate ball rolling (Figure 4). This strikingly simple strategy serves as an efficient way to efficiently use available visual cues to walk in a straight line away from the dung pile where predators or competitors may aggregate.

The Detection of Polarized Reflections: Finding or Avoiding Water Surfaces?

When sunlight is reflected off a water surface, it becomes horizontally polarized, with a maximum degree of polarization (100%) at a particular angle of incidence known as Brewster’s angle (53° for an air/water interface). Some flying insects rely on it to identify bodies of water and many semi-aquatic and aquatic insects appear to detect water surfaces via polarized reflections (Wehner, 2001) (Figure 5A). In most cases, polarized reflections appear to be attractive, yet exceptions exist, for instance, flying locust swarms usually avoid flying over polarized surfaces, probably to avoid crashing into the sea—a fact that can be exploited to repel them (Shashar, Sabbah, & Aharoni, 2005). One classic example for insects attracted by polarized surfaces are dragonflies: male dragonflies approach polarized surfaces to establish an aquatic territory, whereas females will attempt oviposition on what they assume to be the water surface (Wildermuth, 1998). It has been proposed that different dragonfly species known to show a preference for dark versus bright ponds might use the degree of polarization to distinguish between these habitats, yet it remains to be shown how insects would be able to perform this computationally difficult task (Bernath, Szedenics, Wildermuth, & Horvath, 2002). Numerous accounts exist where female insects erroneously oviposit onto shiny surfaces they mistakenly take for water, like parked cars or black gravestones (Horvath, Bernath, & Molnar, 1998; Horvath, Malik, Kriska, & Wildermuth, 2007 Kriska, Horvath, & Andrikovics, 1998), while other insects are attracted by glass buildings (Kriska, Malik, Szivak, & Horvath, 2008). Many of the extremely short-lived mayflies (Ephemeropta) show strong attraction to water (Kriska, Bernath, & Horvath, 2007). The so-called compensatory upstream flights of female mayflies before oviposition appear to be guided by horizontally polarized reflections (Farkas et al., 2016). Interestingly, these important dispersion maneuvers are severely disrupted by unpolarized light pollution, like bridge lamps (Szaz et al., 2015). Another species for which the attraction to polarized surfaces has been demonstrated in great detail is the hemipteran back swimmer Notonecta glauca, a bug that spends a considerable portion of its life hanging under the water surface. However, during dispersal flights between water bodies, it also visually identifies water surfaces, resulting in a characteristic diving reaction (Figure 5B) (Schwind, 1984b). Providing horizontal platforms emitting linearly polarized UV light are sufficient to induce Notonecta’s diving reaction (Schwind, 1983a). It should be pointed out that the glare resulting from horizontally polarized reflections can be problematic for some aquatic insects, for instance, when observing underwater objects from above the water surface, or for contrast enhancement while living near or under water (Wehner, 2001). Specific behavioral adaptations could therefore also aim at avoiding this stimulus (Sharkey, Partridge, & Roberts, 2015). Finally, it should also be noted that some insect species for which one would intuitively expect a strong attraction to linearly polarized reflections, based on their visual ecology centered around aquatic habitats, fail to display clear signs of such behaviors. For instance, so far there is no evidence that those honeybee workers with the dedicated task of water collection use polarized reflections to detect water sources. Also, it remains unclear whether female mosquitoes use vision at all for identifying oviposition sites after a blood meal, since they seem to rely mostly on olfactory cues (Bernath, Horvath, Gal, Fekete, & Meyer-Rochow, 2008; Bernath, Horvath, & Meyer-Rochow, 2012). In contrast, non-biting midges (Chironomidae) with a similar lifestyle appear to rely heavily on visual cues for the detection of water surfaces, thereby revealing important differences in the behavioral strategies used by these related species (Horvath, Mora, Bernath, & Kriska, 2011; Lerner et al., 2008). Taken together, a growing number of reports strengthens the importance of linearly polarized water reflections as an important environmental cue for many insect species. However, further quantitative characterization of these responses is needed for a better understanding of the different behaviors elicited by this stimulus.

Communication via Polarized Light, False Colors, and Circular Polarization

Water bodies are not the only source of linearly polarized reflections in nature. Similar reflections off shiny leaves represent an attractive oviposition cue for certain butterflies (Kelber, 1999a, 1999b). Interestingly, information about e-vector orientation and wavelength composition appear to be mixed in this case, resulting in the perception of “false colors.” This system most likely enables the female butterfly to distinguish matte from shiny leaves by perceiving them as different colors while flying by (Kelber, Thunell, & Arikawa, 2001). This cue would be suitable to signal several important features, such as quality of the landing site (leaf orientation), food quality (for caterpillar offspring), or protection for the eggs. A more recent study on the Japanese swallowtail butterfly Papilio xuthus reported similar mixing of linear polarization and light intensity (Kinoshita, Yamazato, & Arikawa, 2011). Hence, some butterflies might also perceive differently polarized surfaces of having different brightness levels. The authors propose that this mixing of visual modalities dominates during foraging, hence equipping the butterflies with two modes of polarization vision (mixing with color versus brightness) that may be used depending on the behavioral context of the animal (oviposition versus foraging).

Sensing Polarized Light in Insects

Figure 5: Reflected polarized light as an important visual cue for insects. (A) Same visual scene photographed with (left) and without (right) a horizontally oriented UV polarizing filter. (With permission from Schwind, 1983a.) (B) The aquatic hemipteran Notonecta glauca identifies water bodies during flight, leading to a characteristic diving reaction. The visual fields of ventral photoreceptors scan the water surface, from which linearly polarized light is reflected most strongly at the angle θ‎ (Brewster’s angle). (Adapted with permission from Schwind, 1984a.) (C) Photographs documenting the change in appearance of the scarab beetle Chrysina gloriosa when using a leftward (left) or rightward (right) circular polarization filters. (With permission from Sharma et al., 2009.)

True flies (Diptera) show strong attraction to polarized surfaces, but not necessarily water, which was demonstrated for blood-sucking horse flies (Tabanidae) (Egri et al., 2013; Horvath, Majer, Horvath, Szivak, & Kriska, 2008). This behavior most likely serves prey detection since polarimetric imaging of horses and cattle reveals strong linearly polarized reflections off their fur (Horvath et al., 2010). Brown and black fur produces the strongest polarized reflections, while white fur appears to be the best protection against horse fly attacks. Interestingly, certain fur patterns like stripes (zebras) and spots (cows) appear to change angle and degree of polarized reflections, thereby reducing attractiveness for horse flies and might therefore serve as an additional advantage of these otherwise useful camouflage-type adaptations (Blaho, Egri, Bahidszki, et al., 2012; Egri et al., 2012). A more sophisticated ability to detect polarized light patterns was revealed in a recent study where bumblebees were successfully trained to distinguish between different linearly polarized patterns. It appears therefore that pollinators may also use polarized reflections to identify or evaluate floral targets (Foster et al., 2014).

The iridescent scales on the wings of many butterflies also produce linearly polarized reflections that can be perceived by conspecifics and therefore serve as mating signals (Stavenga, Matsushita, Arikawa, Leertouwer, & Wilts, 2012; Sweeney, Jiggins, & Johnsen, 2003; Yoshioka & Kinoshita, 2007). For instance, certain Heliconius butterflies use these reflections to increase their visibility in the midst of highly complex visual forest environment where an abundance color, detail, and great differences in light intensity makes it difficult to be seen (Douglas, Cronin, Chiou, & Dominy, 2007). In this case, the polarized reflections are therefore used to increase the perceived visual contrast independent of spectrum and intensity. Surprisingly, the body cuticle of some insects reflects circularly polarized light—i.e., the e-vector rotates clock- or counterclockwise as the light beam propagates. For most insects, such a stimulus would appear unpolarized, since all e-vector orientations are equally represented in the beam of light (Labhart, 1996; Henze & Labhart, 2007). For instance, several scarab beetles reflect circularly polarized light (Hegedus, Szel, & Horvath, 2006; Jewell, Vukusic, & Roberts, 2007; Sharma, Crne, Park, & Srinivasarao, 2009). Usually well camouflaged in their natural habitat, these animals exhibit stark black contrast when viewed through a circular polarization filter (Figure 5C). In one behavioral study using choice experiments, specific phototactic responses to circularly polarized light were reported for the scarab beetle Chrysina gloriosa, whose body surface produces strong circularly polarized reflections (Brady & Cummings, 2010). Interestingly, the closely related species Chrysina woodii, which manifests only weak circularly polarized reflections, exhibited no phototactic discrimination between linearly and circularly polarized stimuli. It must be noted that another study investigating four different scarab beetle species manifesting circularly polarized reflections off their exocuticle found no evidence for specific behavioral responses to circularly polarized light (Blaho, Egri, Hegedus, et al., 2012). Hence, more studies are needed to evaluate the importance of circularly polarized reflections. Taken together, polarized reflections from a wide variety of substrates serve many different, yet very specific purposes, thereby greatly increasing the visual ecology of different insect species across a wide range of habitats.


All insect retinas are composed of a varying number of repetitive unit eyes, or ommatidia, which usually contain eight or nine photoreceptor neurons (Wernet, Perry, & Desplan, 2015). In many cases, specialized ommatidia containing photoreceptors with increased polarization sensitivity can be found in the dorsal periphery, or the ventral periphery of the retina. The neural circuits underlying these specialized ommatidia are being investigated in many insect species via the combination of anatomical, physiological, and behavioral tests.

Localized Polarization-Sensitive Photoreceptors in the Dorsal Rim Area

Despite considerable morphological variations, specialized ommatidia at the dorsal rim of the adult eye containing polarization-sensitive photoreceptors have been identified in many insect species (for review, see Labhart & Meyer, 1999). In this dorsal rim area (DRA), the light-gathering structures called rhabdomeres of at least two photoreceptor cells always contain straight, untwisted membrane invaginations, or microvilli. The photosensitive rhodopsin molecules are aligned along the axis of these rhabdomeric membranes, leading to a preferential absorption of a certain e-vector orientation by the photoreceptor cell, sometimes referred to as its “analyzer direction” (Roberts, Porter, & Cronin, 2011). Throughout the rest of the retina, polarization sensitivity of photoreceptors is actively prevented through twisting of the rhabdomere membranes in different directions along the length of the rhabdomere, leading to no preferred e-vector tuning of the receptors (and therefore low polarization sensitivity) (Wehner & Bernard, 1993). Usually, two groups of untwisted, highly polarization-sensitive photoreceptors can be found in every DRA ommatidium, manifesting analyzer directions that are orthogonal to each other (Labhart & Meyer, 1999). Hence, if one channel is maximally excited, the other one is minimally active. This design appears to be crucial for the perception of polarized light. In all known cases, the two groups of untwisted, polarization-sensitive photoreceptors with orthogonal analyzers express the same rhodopsin molecules in order to avoid mixing between color and polarized light information. However, the wavelength sensitivity of the rhodopsins used in DRA ommatidia varies between insects: while UV-sensitive rhodopsins are always used by bees, ants, and flies (Fortini & Rubin, 1990; Labhart, 1986; Vonhelversen & Edrich, 1974), crickets and locusts express blue-sensitive rhodopsins in the DRA (Henze, Dannenhauer, Kohler, Labhart, & Gesemann, 2012; Schmeling et al., 2014), while some beetles (cockchafers) rely on green-sensitive polarization-sensitive DRA units (Labhart, Meyer, & Schenker, 1992) (Figure 6A). Hence, the detection of the celestial polarization pattern occurs at different wavelengths, depending on the species, the reasons for which are still being discussed (Barta & Horvath, 2004; Hegedus, Horvath, & Horvath, 2006). Interestingly, there also exists a great variety in the number and subtypes of photoreceptor cells contributing to the two orthogonal analyzer channels in the DRA. For instance, flies use only two photoreceptors with orthogonal microvilli called R7 and R8 (Wunderer, Seifert, Pilstl, Lange, & Smola, 1990; Wunderer & Smola, 1982a), while the remaining six photoreceptors are not involved in celestial polarization vision (Wernet et al., 2012). In contrast, all nine photoreceptors in DRA ommatidia are polarization-sensitive in some butterfly species, like the monarch (Sauman et al., 2005). The reasons for this diversity remain unclear.

Sensing Polarized Light in Insects

Figure 6: The anatomical basis for polarized light sensing in insects. (A) Top row: Four examples of polarization-sensitive ommatidia in the dorsal rim area (DRA) of crickets, beetles, honeybees, and flies (from left to right). Polarization-sensitive photoreceptors with untwisted rhabdomeres are shown in color. Different colors symbolize spectral sensitivities: green, blue, versus UV. Bottom row: morphology of ommatidia outside the DRA, for comparison. (Adapted with permission from Labhart & Meyer, 1999.) (B) Morphology of locust transmedullary neurons (shown in orange, via Dextran tracer application to the lower unit of the anterior optic tubercle), which are presumed to be specifically post-synaptic to DRA photoreceptors (shown in blue). Overlap between photoreceptors and transmedullary neurons is obvious in the dorsal rim medulla (DRMe). (Adapted from el Jundi, Pfeiffer, & Homberg, 2011.)

Across insect species, the orthogonal analyzer directions differ between neighboring DRA ommatidia, resulting in a fan-shaped array of analyzers, which together can detect any celestial e-vector orientation (Blum & Labhart, 2000; Homberg & Paech, 2002; Strausfeld & Wunderer, 1985; Weir et al., 2016). Due to the low light intensities at night, the number of DRA ommatidia in nocturnal dung beetles is increased when compared to their diurnal counterparts, whereas true flies set aside only one single row of DRA ommatidia for polarization vision, along the dorsal head cuticle (Dacke, Nodrstrom, Scholtz, & Warrant, 2002; Smolka et al., 2016). Interestingly, DRA ommatidia of some insect species can be identified with the naked eye due to darker pigmentation (Homberg & Paech, 2002). In some cases, corneal specializations serve to severely widen the optical axis of the photoreceptors, thereby allowing the DRA to cover a large portion of the sky at the expense of acuity in this part of the eye (Aepli, Labhart, & Meyer, 1985; Meyer & Labhart, 1981). Interestingly, there always exists a sharp boundary between morphologically specialized DRA and non-DRA ommatidia, rather than a gradual change between the two morphological types (Labhart & Meyer, 1999). In Drosophila, the molecular mechanisms governing this localized specification of DRA ommatidia have been described in detail: specific expression of the homeodomain transcription factor Homothorax (Hth) in DRA R7 and R8 cells is both necessary and sufficient to induce the DRA fate (Wernet & Desplan, 2014; Wernet et al., 2003); Hth is expressed in response to the morphogen Wingless (Wg) and dorsal selector genes of the Iro-C complex. Interestingly, Wg levels specify different cell types depending on their proximity to the dorsal head cuticle (Tomlinson, 2003), and secondary release of Wg is used to sharpen the boundary between the different ommatidial fates (Kumar, Patel, & Tomlinson, 2015). To date, it is not known whether this molecular mechanism is conserved beyond flies.

Morphological Specializations Leading to Polarization-Sensitivity in the Ventral Retina

There does not appear to exist a specialized type of ommatidia, common to all insects, which is localized at the ventral rim of the retina, harboring polarization-sensitive photoreceptors that could mediate the response to linearly polarized reflections, for example, from shiny surfaces. Despite the numerous reports of behavioral responses to such stimuli, it remains surprising that only a handful of neural correlates for such behaviors have so far been characterized for different insect eyes. Probably the best-characterized example is the zonation of the ventral retina of the hemipteran back swimmer Notonecta glauca. The identification of different ventral zones of ommatidia harboring untwisted photoreceptors of differing microvilli orientations represents an ideal adaptation to its very specialized aquatic lifestyle above and below the water surface. The most ventrally facing ommatidia containing two fused, untwisted rhabdomeres with orthogonally oriented microvilli represent a structure perfectly adapted for detecting polarized reflections like water surfaces (Schwind, 1983b). Interestingly, such specialized adaptations have not yet been described in such detail for any other insect. Other retinal substrates possibly related to polarized reflections off water have been described in another hemipteran, the water strider Gerris lacustris, the sunburst diving beetle larvae Thermonectus marmoratus, as well as for some fly species (Schneider & Langer, 1969; Stecher, Morgan, & Buschbeck, 2010; Trujillocenoz & Bernard, 1972). In Gerris, ventral ommatidia contain untwisted rhabdomeres, often with only one predominant analyzer direction. This could serve to filter out polarized reflections, most likely resulting in the animal’s improved ability to look deeper into the water, or to increase contrast when observing animals against the glare that results from polarized reflections (Schneider & Langer, 1969). Hence, retinal specializations in the ventral retina that are related to polarized reflections may serve opposite functions, depending on their ultrastructure and the lifestyle of the insect: attraction to water via detection of horizontal e-vectors or the specific screening of such surface-reflected light.

Reflections off leaves or off the body surface of other animals provide important cues for many insects, either for oviposition, intraspecific communication, or to detect prey. For instance, the “false color” detection system of the Australian orchard butterfly Papilio aegeus results from blue- and green-sensitive photoreceptors outside the DRA retaining polarization sensitivity due to insufficient rhabdomere twist (Arikawa & Uchiyama, 1996). More importantly, their analyzer directions are orthogonal to each other (vertical versus horizontal, respectively). Upon excitation of any of these photoreceptors, information about e-vector orientation and wavelength composition will therefore be mixed, resulting in the perception of “false colors.” Another well-characterized example for the existence of polarization-sensitive photoreceptors outside the DRA is from electron microscopy–based ultrastructure of blood-sucking horse flies (Tabanidae). These studies revealed that in the midregion of the retina, both R7 and R8 cell rhabdomeres are largely untwisted, providing a putative retinal substrate for host finding via the detection of polarized light (Smith & Butler, 1991; Wunderer & Smola, 1986). Interestingly, very similar studies also identified a subtype of untwisted R8 photoreceptor in blow flies, yet such cells could not be reliably identified in closely related Drosophila (Wunderer & Smola, 1982b). Instead, systematic analysis of rhabdomere twist in this species revealed a low number of untwisted, UV-sensitive R7 cells in the ventral fly retina (Wernet et al., 2012). Together with low twisting outer photoreceptors within the same ommatidia, these cells could provide the retinal substrate for Drosophila’s polarotactic responses to linearly polarized stimuli presented ventrally (Velez, Gohl et al., 2014; Velez, Wernet, et al., 2014; Wernet et al., 2012; Wolf et al., 1980).

The detection of circularly polarized light reflected off the exoskeleton of some scarab beetles also remains incompletely understood. The expected anatomical design of a hypothetical retinal detector has been proposed based on stomatopod crustacean examples: in their eyes, two orthogonally arranged detectors are joined by a third distal photoreceptor with a microvilli orientation of 45 degrees, which acts a quarter wave retarder (Chiou et al., 2008; Warrant, 2010). Nevertheless, such specializations have not yet been described in scarab beetles, whose body surfaces cause circularly polarized reflections, nor in any other insects.

Anatomical Characterization of Circuit Elements for Polarization Vision in the Insect Brain

Since the DRA photoreceptor input channels for celestial polarization vision can be identified unambiguously, their post-synaptic elements have also been the subject of several studies. Although electrophysiology has proven to be a much more effective technique for describing polarization-sensitive circuit elements throughout the insect brain, different anatomical techniques have also been used successfully to describe cell types that seem to specifically contact DRA photoreceptors. For instance, the injection of tracer molecules such as biotinylated dextran into the lower unit of the anterior optic tubercle (AOTU-LU, or AOTU-LUC in honeybees) in both locusts and bumblebees revealed transmedullary neurons with processes in the Dorsal Rim Medulla (MEDRA) and long projections into the AOTU-LU (Homberg, Hofer, Pfeiffer, & Gebhardt, 2003; Pfeiffer & Kinoshita, 2012; Zeller et al., 2015). Co-labeling of DRA photoreceptor terminals with another dextran probe confirmed very close contact between these cells (el Jundi, Pfeiffer, & Homberg, 2011) (Figure 6B). These transmedullary neurons therefore serve as excellent candidates for DRA input into the anterior optic tubercle that appear to be conserved between species. Another study using immunohistochemichal labeling of Cryptochrome-expressing cells in the monarch butterfly brain pointed toward connections between DRA photoreceptor terminals and the circadian clock (Sauman et al., 2005). Finally, cobalt injections into marginal ommatidia of the blowfly revealed columnar small field neurons connecting the MEDRA with distinct marginal regions of the deeper neuropils (lobula and lobula plate). From there, local assemblies of columnar neurons then connect to the same region in the optic lobe of the opposite eye, as well as to descending neurons terminating in the thoratic ganglia (Strausfeld & Wunderer, 1985).

Of course these morphological studies did not provide functional proof that the characterized cell types are involved in polarization vision, nor did they directly show that synaptic connections between them exist. Nevertheless, they provide the framework of a neural circuit for celestial polarization vision that includes the DRA, the AOTU, as well as central processing centers whose cellular organization has been described in detail using electrophysiology (see next section).


Functional methods for revealing the activity of identified neurons are crucial for understanding their role in the perception of specific visual stimuli. Since several excellent review articles on this topic already exist, this section only briefly introduces the characterization of polarization vision circuitry in insects using electrophysiology. The functional characterization of polarization-sensitive circuit elements includes photoreceptors, optic lobe cell types, and neurons in the central brain.

Polarization Sensitivity of Insect Photoreceptors

Sensing Polarized Light in Insects

Figure 7: Functionally characterized polarization-sensitive neurons in the insect brain. (A) Modulation of activity from polarization-sensitive photoreceptors in the Drosophila DRA expressing the genetically encoded calcium indicator GCamp6. Top: Orientation of the polarizer maximum response (preferred e-vector angle, in pseudocolor) in R7 and R8 terminals. Bottom: Preferred e-vector angle plotted against horizontal position (trend line shown in black). Responses R7 and R8 at any given position along the fan-shaped array of analyzers are approximately orthogonal of each other, in good agreement with photoreceptor morphology (rhabdomere orientation). (With permission from Weir et al., 2016.) (B) Fluorescence traces for R7 and R8 regions of interests during one full rotation of the polarizing filter. Note the negative signals of both photoreceptor at e-vector orientations when the orthogonal channel is maximally excited. (With permission from Weir et al., 2016.) (C) Two models for polarization processing in a medullar column receiving input from R7 and R8 from the same ommatidium. All connections between cells are inhibitory (R7 and R8 photoreceptors are histaminergic). Out = output neuron; Int = sign-inverting interneuron (Int). (With permission from Weir et al., 2016.) (D) Summary of the gradually changing compass-like representation of e-vector tunings (double arrows) in columnar CPU1 neurons of the protocerebral bridge and upper division of the central body (CBU) of the locust. LAL = lateral accessory lobe. (With permission from Homberg, 2015.) (E) Activity of a central body tangential neuron (lower division) with stimulation from above through a rotating polarizer. Spike frequency is modulated as a function of e-vector orientation (note how Φ‎max and Φ‎min spiking activity occur at orthogonal E-vectors). (With permission from Homberg, 2015.) (F) Anatomy of the polarization vision pathway in the locust, as deduced from single-unit electrophysiology recordings. Highlighted are the brain regions involved in processing sky compass cues (red), with an emphasis in the central body (gold). Abbreviations: La = lamina; LoX = lobula-complex; aMe = accessory medulla; DRLa = dorsal rim lamina; DRMe = dorsal rim medulla; MB = mushroom body; AL = antennal lobe; POTu = posterior optic tubercle; BU = bulb; ALo = anterior lobula; PB = protocerebral bridge; CBU = central body upper unit; CBL = central body lower unit; LAL = lateral accessory lobes. (With permission from el Jundi, Pfeiffer, et al., 2014.)

The high polarization sensitivity (PS) of photoreceptors in the DRA has been confirmed for many insect species using electrophysiology (Hardie, 1984; Labhart, 1980, 1986; Labhart, Hodel, & Valenzuela, 1984; Stalleicken, Labhart, & Mouritsen, 2006). In most species, photoreceptors outside the DRA have significantly low PS due to rhabdomere twist, yet exceptions exist (Bandai, Arikawa, & Eguchi, 1992). These experiments also confirmed the direct link between morphology and physiology of DRA input channels resulting in their orthogonal analyzer directions. They also unambiguously revealed the spectral sensitivity of the respective photoreceptors. However, in some species, photoreceptors are too small for electrophysiology, for instance, in Drosophila. Due to the molecular genetic toolkit available for this species, genetically encoded indicators of activity have become an attractive alternative to electrophysiology. One recent study used the genetically encoded calcium sensor GCamp6 to visualize the activity of DRA inner photoreceptors R7 and R8 in response to a polarizer illuminated by a UV LED (Weir et al., 2016). One attractive advantage of this technique is the possibility to simultaneously record the activity from many R7 and R8 terminals. The fan-shaped array of analyzer directions across the DRA was thus visualized, as well as the strictly orthogonal alignment of R7 versus R8 within the same ommatidium (Figure 7A). Surprisingly, this study also revealed clear direct inhibitory interactions between R7 and R8, which had previously been reported only from few electrophysiological recordings in the DRA of larger flies (Hardie, 1984) (Figure 7B). This inhibition could result from direct synaptic contacts between R7 and R8 photoreceptors. The existence of such inter-photoreceptor synapses was recently confirmed via 3D electron microscopic reconstruction of the Drosophila optic lobes (Takemura et al., 2013; Takemura, Lu, & Meinertzhagen, 2008). Hence, these reciprocal synaptic connections could increase polarization contrast at the level of R7 and R8 photoreceptors themselves (Figure 7C). It remains to be seen whether this retinal microcircuitry is a specialized adaptation of flies or whether it represents a broader concept present across insect species.

Electrophysiological Characterization of Circuit Elements in the Insect Optic Lobes

Insect photoreceptors can be grouped into two categories, depending on the length of their axons. Most have short visual fibers (svf) projecting into a neuropil called lamina, where usually one or two photoreceptors with long visual fibers (lvf) terminate in a deeper neuropil called the medulla. Together with the lobula complex, lamina and medulla form the optic lobes of insects. Several polarization-sensitive neuron types have been characterized by electrophysiology in the medulla of different insect species. One example from crickets are the so-called polarization-opponent (POL) interneurons, which are excited by one particular e-vector orientation while being inhibited by an orthogonal e-vector (Labhart, 1988). Such opponent microcircuitry is beneficial in several ways, since it makes the system insensitive to intensity modulations and therefore to celestial intensity gradients, but it also increases the amplitude of signal modulation, thereby increasing polarization contrast. To date, it is not known whether POL neurons receive direct input from photoreceptor cells, which, at least in Drosophila, could produce very similar signals. However, it was shown via recordings from cricket POL neurons that DRA ommatidia with similar analyzer directions but located in different regions of the DRA converge onto the same post-synaptic elements (Labhart, Petzold, & Helbling, 2001). Interestingly, only three groups of POL neurons with distinct analyzer preference were identified in crickets, leading to a model in which the relative excitation of these three population could be used to encode a specific compass heading (Labhart & Wehner, 2006). In locusts, one recent study characterized several polarization-sensitive neurons in the medulla, as potential neuronal elements intercalated between the DRA and AOTU, whose connectivity remains unclear: five cell types were described with wide arborizations in the same medulla layer as well as in the MEDRA and the “accessory medulla,” the presumed circadian clock of the locust (el Jundi et al., 2011). Such a potential interaction between the polarization-vision and circadian systems is particularly interesting, due to the fact that the celestial polarization pattern changes in a predictable way as the solar stimulus moves across the sky together with the solar cue. Similar to cricket POL neurons, the medulla neurons in the locust showed cell type-specific orientation tuning to zenithal polarized light, albeit without the characteristic binning into three specific categories (el Jundi et al., 2011). Furthermore, the polarization-sensitive medulla neurons from locusts did not show any color opponency or daytime specific adjustment of sky compass signals. Such characteristics are important for correcting for the change in solar elevation and have been demonstrated for neurons in the AOTU of the locust and therefore arise at a later processing stage, beyond the medulla (Homberg, 2004; Homberg, Heinze, Pfeiffer, Kinoshita, & el Jundi, 2011; Kinoshita et al., 2007; Pfeiffer & Homberg, 2007). Hence, these neuronal cell types represent good candidates for the neuronal substrate that integrates time-compensated sky compass information in a migratory insect. Despite their precise characterization, the exact synaptic connectivity between these individual elements, as well as the DRA and AOTU, remains to be worked out.

Electrophysiological Characterization of Circuit Elements in the Insect Central Brain

A major step toward understanding how discrete compass headings are extracted from the celestial pattern of polarized light was the description of polarization-sensitive neurons in a neural structure buried deep in the brain of the locust, called the central complex. In a conserved substructure known as the “protocerebral bridge,” the preferred e-vector orientation of polarization-sensitive neurons varies systematically from one columnar structure to the next, leading to a topographic representation of celestial e-vectors deep in the brain (Heinze & Homberg, 2007) (Figure 7D,E). A defined compass heading could therefore be encoded by the relative activity of the “compass neurons” forming this internal map. In the meantime, central complex neurons with very similar properties have been identified in crickets, monarch butterflies, and dung beetles (el Jundi, Warrant, et al., 2015; Heinze & Reppert, 2011; Sakura, Lambrinos, & Labhart, 2006). Interestingly, these central complex neurons also respond to unpolarized chromatic stimuli (which are not detected by DRA ommatidia), thereby acting as an integrator of different celestial cues (for review, see el Jundi, Pfeiffer, Heinze, & Homberg, 2014). Recently, one study comparing responses of compass neurons between nocturnal and diurnal dung beetle species shed more light on this integration: on the one hand, the compass neurons from diurnal beetles always show responses when an artificial celestial body is presented under experimental conditions. On the other hand, in the nocturnal species, compass neurons usually respond to the pattern of polarized skylight during night time, which would be the most reliable navigational cue in the night sky. However, when the nocturnal beetle is forced to roll its ball during the day, its compass neurons undergo a switch by responding to the solar position (el Jundi, Warrant, et al., 2015). These findings correlate well with the behavioral decisions of these animals when they switch to using the sun as a more reliable orientation cue when forced to roll their ball during the day. Hence, there exists a good correlation between visual cue preference (and reliability) during ball-rolling behavior and the weighing of different visual inputs in the central complex of these insects. Taken together, the use of different physiological techniques across species has resulted in a growing circuit diagram for polarization vision in insects (Homberg, 2015) (Figure 7F). While the details are being worked out, it remains interesting to see what similarities and differences exist between these circuits and those mediating visual responses to other cues, like motion and color.

Concluding Remarks

Not visible to the human eye, polarized light represents an important stimulus for many insects, including such ethologically important cues like linearly polarized skylight, linearly polarized reflections, and potentially also circularly polarized light. The study of navigating insects over the last few decades has resulted in a good understanding of their visual ecology, the underlying anatomical structures and the functional characterization of underlying circuit elements. Much less is known about the anatomical and physiological substrates for the detection of linearly polarized reflections. Insect models that rely on polarized reflections for tasks like oviposition, prey detection, or intraspecific communication should therefore become a priority. Just as for the detection of other visual cues like motion or color, understanding the functional connectivity of the vast number of neuronal elements involved in any of these processes remains a challenge. Further high-resolution reconstruction efforts are needed to reveal the exact synaptic connectivity between the described neuronal units. More sophisticated imaging techniques in combination with genetically encoded indicators of activity may also provide crucial information about sensory processing by visualizing many cells at once. Introducing these tools into non-genetic model organisms like locusts, dung beetles, or butterflies has now become possible, thanks to improved genome editing techniques like Crispr/Cas9 (Perry et al., 2016). Taken together, polarization vision serves a good example for a research field that successfully combines behavioral, anatomical, and physiological studies for understanding the relevance of certain visual cues to different animal species. It therefore combines the overlapping perspectives of such exciting fields as visual ecology, neuroethology, and modern circuit science.


The authors thank Fleur Lebhardt, Claude Desplan, and one anonymous reviewer for helpful comments on the manuscript’s text and figures. The authors also apologize for any work that could not be cited due to restrictions in length.


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