Long-timescale anti-directional rotation in Drosophila optomotor behavior

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    The present study provides a valuable new perspective on the optomotor response based on an inversion of the behavior under specific (non-natural) conditions that may help elucidate the principles of this specific behavior. The evidence provided is convincing.

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Abstract

Locomotor movements cause visual images to be displaced across the eye, a retinal slip that is counteracted by stabilizing reflexes in many animals. In insects, optomotor turning causes the animal to turn in the direction of rotating visual stimuli, thereby reducing retinal slip and stabilizing trajectories through the world. This behavior has formed the basis for extensive dissections of motion vision. Here, we report that under certain stimulus conditions, two Drosophila species, including the widely studied Drosophila melanogaster , can suppress and even reverse the optomotor turning response over several seconds. Such ‘anti-directional turning’ is most strongly evoked by long-lasting, high-contrast, slow-moving visual stimuli that are distinct from those that promote syn-directional optomotor turning. Anti-directional turning, like the syn-directional optomotor response, requires the local motion detecting neurons T4 and T5. A subset of lobula plate tangential cells, CH cells, show involvement in these responses. Imaging from a variety of direction-selective cells in the lobula plate shows no evidence of dynamics that match the behavior, suggesting that the observed inversion in turning direction emerges downstream of the lobula plate. Further, anti-directional turning declines with age and exposure to light. These results show that Drosophila optomotor turning behaviors contain rich, stimulus-dependent dynamics that are inconsistent with simple reflexive stabilization responses.

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  1. Author Response

    Reviewer #1 (Public Review):

    Mano et. al. use a combination of behavioral, genetic silencing, and functional imaging experiments to explore the temporal properties of the optomotor response in Drosophila. They find a previously unreported inversion of the behavior under high contrast and luminance conditions and identify potential pathways mediating the effect.

    Strengths:

    Quantifications of optomotor behavior have been performed for many decades. Despite a large number of previous studies, the authors still find something fundamentally novel: under high contrast conditions and extended stimulation periods, the behavior becomes dynamic over time. The turning response shows an initial transient positive following response. The amplitude of the behavior then decreases and even inverts such that animals show an anti-directional rotation response. The authors systematically explore the stimulation feature space, including large ranges of spatial and temporal frequencies and conditions with high and low contrast. They also test two wild-type fly species and even compare experiments across two different labs and setups. From these data, it seems clear that the behavior is robust and largely depends on the brightness of the stimulation, rearing conditions, and genetic background. The authors discuss that these effects have not clearly been reported elsewhere beforehand, and convincingly argue why this may be the case.

    In general, the presented behavioral quantifications illustrate the importance of further experimental studies of the temporal dynamics of behavior in response to dynamically varying stimulus features, across different stimulus types, genetic backgrounds, and model animal systems. It also illustrates the importance of relating the conditions that animals experience in the laboratory to the ones they would experience in the wild. As the authors mention, the brightness during a sunny day can reach values as high as 4000 cd/m2, while experimental stimulation in the lab has so far often been orders of magnitude below that.

    The study then systematically explores potential neural elements involved in the behavior. Through a set of silencing experiments, they find that T4 and T5 neurons, as expected, are required for motion behaviors. On the other hand, silencing HS cells largely abolishes the 'classical' syn-directional response but leaves anti-directional turning intact. On the other hand, silencing CH cells abolishes the anti-directional response but leaves the syn-directional behavior intact. Through functional imaging in T4, T5, HS, and CH neurons, the authors could show that none of these neurons shows a response inversion depending on contrast level. Together, these experiments nicely illustrate that the dynamics do not seem to be computed within the early parts of visual processing, but they must happen on the level of the lobula plate or further downstream.

    Weaknesses:

    While the authors have already explored various parameters of the experiment, it would have been nice to see additional experiments regarding the initial adaptation phase. The experiments in Figure 2e, where the authors show front-to-back or back-to-front gratings before the rotation phase, are a good start. What would the behavioral dynamics look like if they had exposed animals to long periods of static high or low contrast gratings, whole field brightness, or darkness? Such experiments would surely help to better understand the stimulus features on which the adaptation elements operate. It would be interesting to explore to what degree such static stimuli impact the subsequent behavioral dynamics.

    To address this question, we have added a new adaption condition, in which a high contrast, stationary sinusoidal grating is presented for 5 seconds before the high contrast rotational stimulus is presented (new Figure 2 – Supp. Fig. 1). We find that the turning looks identical to the case of a gray adapter. These results drive home the point that the direction of motion of the adapter is what matters most.

    Given the dynamics of the behavior, it would probably also be worth looking at the turning dynamics after the stimulus has stopped. If direction-selective adaptation mechanisms are regulating the turning response, one may find long-lasting biases even in the absence of stimulation. If the authors have more data after the stimulus end, it would be good to further expand the time range by a few seconds to show if this is the case or not (for example, in Figure 1b).

    We now show these dynamics in Figure 1. See Essential Revision #1.

    Another important experiment could be to initially perform experiments in a closed-loop configuration, and then quickly switch to open-loop. The closed-loop configuration should allow the motion computing circuitry to adapt to the chosen environmental conditions. Explorations of the changes in turning response dynamics after such treatments should then enable further dissections of the mechanisms of adaptation. Closed-loop experiments under different contrast conditions have already been performed (for example, Leonhardt et al. 2016), which also showed complex response dynamics after stimulus on- and offset. It would be great to discuss the current open-loop experiments, and maybe some new closed-loop results, in relation to the previous work.

    We have performed these suggested experiments; please see Essential Revision #2.

    The authors mention the different rearing conditions, and there is one experiment in Figure S2 which mentions running experiments at 25 deg C. But it is not clear from the Methods at which temperature all other experiments have been performed. It is also not clear at which temperature the shibire block experiments were performed. As such experiments require elevated temperatures, I assume that all behavioral experiments have been performed at such levels? How high were those?

    Our apologies for leaving out this important information. In DAC’s lab, behavioral experiments are run at 34-36ºC in a room maintaining ~50% relative humidity (this yields ~25% RH in the box with the experiment, as we now note in the methods). These conditions yield high quality, reproducible behavior, especially since this temperature elicits strong walking behavior. In TRC’s lab, behavioral experiments are similarly run at 34ºC in a room maintaining ~50% relative humidity (similarly with ~25% RH in the experimental box), for similar reasons. We have now added these details to the methods sections for each lab’s behavioral experiments.

    What does the fly see before and after the stimulus (i.e. the gray boxes in all figures)? Are these periods of homogenous gray levels or are these non-moving gratings with the luminance and contrast of the subsequent stimulus? It would be important to add this information to the methods and to the figure illustrations or legends.

    In the figures, gray is a uniform luminance screen that appears before and after the stimuli, with luminance matched to the mean stimulus luminance. We have now included this in the methods section where we describe how stimuli were generated in each lab.

    It would be nice to discuss the potential location where the motion adaptation may be implemented in the brain. A small model scheme as an additional figure could further help to discuss how such computations may be mechanistically implemented, helping readers to think about future experimental dissections of the behavior.

    Following this suggestion, we have created a diagram that shows a potential mechanistic implementation of the behavior observed, and summarizes our results (new Figure 6 – Supp. Fig. 2). There are many other possible alternatives that we do not show, including exactly how an opposing signal could ramp up under the conditions of these experiments. In the figure caption, we remind readers what locations have been excluded for this sort of computation. We reference this diagram where we discuss subtraction in the Discussion.

    For setting up similar experiments in other labs, the authors need to better describe how they measured the luminance of the arena. Do they simply report the brightness delivered by the Lightcrafter system, or did they measure this with a lux-meter? If so, at which distance was the measurement performed and with which device? Given that the behavior is sensitive to the specific properties of the stimulus, it will be important to report these numbers carefully to enable other groups to reproduce effects.

    In brief, since these are rear projection screens, we can easily measure light intensity by placing a power meter in front of the screen. This gives us the photon flux in watts, which can be converted to lumens by a standard conversion and then into candelas by making the approximation that our screen scatters into 2π steradians. Dividing by the sensor area gives us our desired candelas per square-meter. We have now added this methodology to the methods section.

  2. eLife assessment

    The present study provides a valuable new perspective on the optomotor response based on an inversion of the behavior under specific (non-natural) conditions that may help elucidate the principles of this specific behavior. The evidence provided is convincing.

  3. Reviewer #1 (Public Review):

    Mano et. al. use a combination of behavioral, genetic silencing, and functional imaging experiments to explore the temporal properties of the optomotor response in Drosophila. They find a previously unreported inversion of the behavior under high contrast and luminance conditions and identify potential pathways mediating the effect.

    Strengths:
    Quantifications of optomotor behavior have been performed for many decades. Despite a large number of previous studies, the authors still find something fundamentally novel: under high contrast conditions and extended stimulation periods, the behavior becomes dynamic over time. The turning response shows an initial transient positive following response. The amplitude of the behavior then decreases and even inverts such that animals show an anti-directional rotation response. The authors systematically explore the stimulation feature space, including large ranges of spatial and temporal frequencies and conditions with high and low contrast. They also test two wild-type fly species and even compare experiments across two different labs and setups. From these data, it seems clear that the behavior is robust and largely depends on the brightness of the stimulation, rearing conditions, and genetic background. The authors discuss that these effects have not clearly been reported elsewhere beforehand, and convincingly argue why this may be the case.

    In general, the presented behavioral quantifications illustrate the importance of further experimental studies of the temporal dynamics of behavior in response to dynamically varying stimulus features, across different stimulus types, genetic backgrounds, and model animal systems. It also illustrates the importance of relating the conditions that animals experience in the laboratory to the ones they would experience in the wild. As the authors mention, the brightness during a sunny day can reach values as high as 4000 cd/m2, while experimental stimulation in the lab has so far often been orders of magnitude below that.

    The study then systematically explores potential neural elements involved in the behavior. Through a set of silencing experiments, they find that T4 and T5 neurons, as expected, are required for motion behaviors. On the other hand, silencing HS cells largely abolishes the 'classical' syn-directional response but leaves anti-directional turning intact. On the other hand, silencing CH cells abolishes the anti-directional response but leaves the syn-directional behavior intact. Through functional imaging in T4, T5, HS, and CH neurons, the authors could show that none of these neurons shows a response inversion depending on contrast level. Together, these experiments nicely illustrate that the dynamics do not seem to be computed within the early parts of visual processing, but they must happen on the level of the lobula plate or further downstream.

    Weaknesses:
    While the authors have already explored various parameters of the experiment, it would have been nice to see additional experiments regarding the initial adaptation phase. The experiments in Figure 2e, where the authors show front-to-back or back-to-front gratings before the rotation phase, are a good start. What would the behavioral dynamics look like if they had exposed animals to long periods of static high or low contrast gratings, whole field brightness, or darkness? Such experiments would surely help to better understand the stimulus features on which the adaptation elements operate. It would be interesting to explore to what degree such static stimuli impact the subsequent behavioral dynamics.

    Given the dynamics of the behavior, it would probably also be worth looking at the turning dynamics after the stimulus has stopped. If direction-selective adaptation mechanisms are regulating the turning response, one may find long-lasting biases even in the absence of stimulation. If the authors have more data after the stimulus end, it would be good to further expand the time range by a few seconds to show if this is the case or not (for example, in Figure 1b).

    Another important experiment could be to initially perform experiments in a closed-loop configuration, and then quickly switch to open-loop. The closed-loop configuration should allow the motion computing circuitry to adapt to the chosen environmental conditions. Explorations of the changes in turning response dynamics after such treatments should then enable further dissections of the mechanisms of adaptation. Closed-loop experiments under different contrast conditions have already been performed (for example, Leonhardt et al. 2016), which also showed complex response dynamics after stimulus on- and offset. It would be great to discuss the current open-loop experiments, and maybe some new closed-loop results, in relation to the previous work.

    The authors mention the different rearing conditions, and there is one experiment in Figure S2 which mentions running experiments at 25 deg C. But it is not clear from the Methods at which temperature all other experiments have been performed. It is also not clear at which temperature the shibire block experiments were performed. As such experiments require elevated temperatures, I assume that all behavioral experiments have been performed at such levels? How high were those?

    What does the fly see before and after the stimulus (i.e. the gray boxes in all figures)? Are these periods of homogenous gray levels or are these non-moving gratings with the luminance and contrast of the subsequent stimulus? It would be important to add this information to the methods and to the figure illustrations or legends.

    It would be nice to discuss the potential location where the motion adaptation may be implemented in the brain. A small model scheme as an additional figure could further help to discuss how such computations may be mechanistically implemented, helping readers to think about future experimental dissections of the behavior.

    For setting up similar experiments in other labs, the authors need to better describe how they measured the luminance of the arena. Do they simply report the brightness delivered by the Lightcrafter system, or did they measure this with a lux-meter? If so, at which distance was the measurement performed and with which device? Given that the behavior is sensitive to the specific properties of the stimulus, it will be important to report these numbers carefully to enable other groups to reproduce effects.

  4. Reviewer #2 (Public Review):

    This study looks at how optomotor turning in fruit flies varies with stimulus conditions. Although the response has usually been observed in the same direction of rotation as the stimulus, they find that in many situations the flies turn strongly in the opposite direction to the stimulus. This 'anti-directional' turning increases with stimulus brightness, contrast, and duration of the stimulus, and also varies with many factors such as rearing temperature, lab, strain, and developmental stage. They show that the anti-directional response depends on neurons in the visual system that are also important for the more standard response, but they don't find clear changes in the activity of these neurons that could explain the directional switch. The main conclusion is that supposedly simple behaviors may be more complicated than they first appear, and careful consideration needs to be given to the precise stimulus conditions and the response dynamics when measuring such behaviors, and especially when comparing data across labs.