Author response:
eLife Assessment
Hoverflies are known for their sexually dimorphic visual systems and exquisite flight behaviors. This valuable study reports how two types of visual descending neurons differ between males and females in their motion- and speed-dependent responses, yet surprisingly, the behavior they control lacks any sexual dimorphism. The results convincingly support these findings, which will be of interest for studies of visuomotor transformations and network-level brain organization.
This statement perfectly recapitulates our findings.
Public Reviews:
Reviewer #1 (Public review):
Summary:
Hoverflies are known for a striking sexual dimorphism in eye morphology and early visual system physiology. Surprisingly, the male and female flight behaviors show only subtle differences. Nicholas et al. investigate the sensori-motor transformation of sexually dimorphic visual information to flight steering commands via descending neurons. The authors combined intra- and extracellular recordings, neuroanatomy, and behavioral analysis. They convincingly demonstrate that descending neurons show sexual dimorphisms - in particular at high optic flow velocities - while wing steering responses seem relatively monomorphic. The study highlights a very interesting discrepancy between neuronal and behavioral response properties.
Thank you for this summary. Most of the statement perfectly recapitulates the main findings of our paper. However, we want to emphasize that some hoverfly flight behaviors are strongly sexually dimorphic, especially those related to courtship and mating. Indeed, only male hoverflies pursue targets at high speed, chase away territorial intruders, and pursue females for mating. However, other flight behaviours, such as those related to optomotor responses and flights between flowers when feeding, are not sexually dimorphic. We will amend the Introduction to make the difference between flight behaviors clear.
More specifically, the authors focused on two types of descending neurons that receive inputs from well-characterized wide-field sensitive tangential cells: OFS DN1, which receives inputs from so-called HS cells, and OFS DN2, which receives input from a set of VS cells. Their likely counterparts in Drosophila connect to the neck, wing, and haltere neuropils. The authors characterized the visual response properties of these two neuronal classes in both male and female hoverflies and identified several interesting differences. They then presented the same set of stimuli, tracked wing beat amplitude, and analyzed the sum and the difference of right and left wing beat amplitude as a readout of lift or thrust, and yaw turning, respectively. Behavioral responses showed little to no sexual dimorphism, despite the observed neuronal differences.
Thank you for this very nice summary of our work. We want to clarify that LPTC input to DN1 and DN2 has not been shown directly in hoverflies using e.g. dye coupling, or dual recordings. Instead, the presumed HS and VS input is inferred from morphological and physiological DN evidence, and comparisons to similar data in Drosophila and blowflies. We will amend the Introduction to clarify this. The rest of the paragraph perfectly recapitulates the main findings of our paper.
Strengths:
I find the question very interesting and the results both convincing and intriguing. A fundamental goal in neuroscience is to link neuronal responses and behavior. The current study highlights that the transformations - even at the level of descending neurons to motoneurons - are complex and less straightforward than one might expect.
Thank you.
Weaknesses:
The authors investigated two types of descending neurons, but it was not clear to me how many other descending neurons are thought to be involved in wing steering responses to wide-field motion. I would suggest providing a more in-depth overview of what is known about hoverflies and Drosophila, since the conclusions drawn from the study would be different if these two types were the only descending neurons involved, as opposed to representing a subset of the neurons conveying visual information to the wing neuropil.
This is a great point. There are around 1000 fly DNs, of which many could respond to widefield motion, without being specifically tuned to widefield motion. For example, many looming sensitive neurons also respond to widefield motion, and could therefore be involved in the WBA movements that we measured here. In addition, there are many multimodal neurons that could be involved in optomotor responses in free flight, but these may not have been stimulated when we only provided visual input. Furthermore, many visual neurons are modulated by proprioceptive feedback, which is lacking in immobilized physiology preps. Finally, in blowflies, up to 5 optic flow sensitive DNs have been identified morphologically, and in Drosophila 3 have been identified morphologically and physiologically. In summary, it is more than likely that other neurons project visual widefield motion information to the wing neuropil. We will amend our Introduction and Discussion to make this important point clear to the readers.
Both neuronal classes have counterparts in Drosophila that also innervate neck motor regions. The authors filled the hoverfly DNs in intracellular recordings to characterize their arborization in the ventral nerve cord. In my opinion, these anatomical data could be further exploited and discussed a bit more: is the innervation in hoverflies also consistent with connecting to the neck and haltere motor regions? Are there any obvious differences and similarities to the Drosophila neurons mentioned by the authors? If the arborization also supports a role in neck movements, the authors could discuss whether they would expect any sexual dimorphism in head movements.
These are all great points. We did not see any clear arborizations to the frontal nerve, where we would expect to find the neck motor neurons (NMNs). In addition, while we did see fine arborizations throughout the length of the thoracic ganglion, we saw no strong outputs projecting directly to the haltere nerve (HN). In the revised version of the MS we will modify figure 4 (morphological characterization) to clarify.
There are important differences between the morphology of DN1 and DN2 in hoverflies and DNHS1 and DNOVS2 in Drosophila, in terms of their projections in the thoracic ganglion. For example, In Drosophila DNOVS2, there are several fine branches along the length of the neuron in the thoracic ganglia. Similarly, we found fine branches in Eristalis tenax DN2, however, in addition, we found a wide branch projecting to the area of the thoracic ganglion where the prothoracic and pterothoracic nerves likely get their inputs (Figure 4), suggesting that the neuron could contribute to controlling the wings and/or the forelegs (which is why we quantified the WBA). In Drosophila DNHS1, there is a similar fat branch to the prothoracic and pterothoracic nerves, which we also found in Eristalis tenax OFS DN1 (Figure 4). Indeed, while Drosophila DNHS1 and DNOVS2 have quite strikingly different morphology, DN1 and DN2 in Eristalis looked quite similar. We will modify the Results section to make this clear.
In addition, to investigate this further, in the revised version of the MS we will include analysis of the movement of different body parts (including the head) to investigate the presence of any potential sexual dimorphism. Unfortunately, however, this will not include the halteres, as they cannot be seen well in the videos.
Reviewer #2 (Public review):
Summary:
Many fly species exhibit male-specific visual behaviors during courtship, while little is known about the circuit underlying the dimorphic visuomotor transformations. Nicholas et al focus on two types of visual descending neurons (DNs) in hoverflies, a species in which only males exhibit high-speed pursuit of conspecifics. They combined electrophysiology and behavior analysis to identify these DNs and characterize their response to a variety of visual stimuli in both male and female flies. The results show that the neurons in both sexes have similar receptive fields but exhibit speed-dependent dimorphic responses to different optic flow stimuli.
This statement perfectly recapitulates the main findings of our paper. However, as mentioned above, while hoverfly flight behaviors related to courtship and mating are strongly sexually dimorphic, other flight behaviours, such as those related to optomotor responses and flights between flowers when feeding, are not. We will amend the Introduction to make the difference between flight behaviors clear.
Strengths:
Hoverflies, though not a common model system, show very interesting dimorphic behaviors and provide a unique and valuable entry point to explore the brain organization behind sexual dimorphism. The findings here are not only interesting on their own right but will also likely inspire those working in other systems, particularly Drosophila.
Thank you.
The authors employed rigorous morphology, electrophysiology, and behavior methods to deliver a comprehensive characterization of the neurons in question. The precision of the measurements allowed for identifying a subtle and nuanced neuronal dimorphism and set a standard for future work in this area.
Thank you.
Weaknesses:
Cell-typing using receptive field preferred directions (RFPDs): if I understood correctly, this classification method mostly relies on the LPDs near the center of the receptive field (median within the contour in Fig.1). I have two concerns here. First, this method is great if we are certain there are only two types of visual DNs as described in the manuscript. But how certain is this? Given the importance of vision in flight control, I would expect many DNs that transmit optic flow information to the motor center. I'd also like to point out that there are other lobula plate tangential cells (LPTCs) than HS and VS cells, which are much less studied and could potentially contribute to dimorphic behaviors.
This is very true, and an important point. As mentioned above, in blowflies, up to 5 optic flow sensitive DNs have been identified morphologically, however, if these correspond to 5 different physiological types remain unclear. In both blowflies and Drosophila 3 have been identified morphologically and physiologically (DNHS1, DNOVS1, DNOVS2). Importantly, in both blowflies and fruitflies DNOVS1 gives graded responses, and no action potentials, meaning that we would not be able to record from it using extracellular electrophysiology.
We previously used clustering techniques to show that in Eristalis, we can reliably distinguish two types of optic flow sensitive DNs from extracellular electrophysiological data, based on a range of receptive field parameters, and we think that these correspond to DNHS1 and DNOVS2 in Drosophila (Nicholas et al, J Comp Physiol A, 2020, cited in paper). As mentioned above in response to Reviewer 1, this does not mean that there are no other neurons that could respond to widefield optic flow, and which might be involved in the WBA we recorded in the paper. However, the point of this paper was not to conclusively show that there are only two optic flow sensitive descending neurons. The point was to say that there are two quite distinct optic flow sensitive neurons that have similar receptive fields in males and females, while the responses to widefield motion show differences between males and females.
We will modify the Introduction and Discussion to make these important points clear to the Reader, including the discussion of the 45-60 LPTCs that exist in the lobula plate, and what their role might be.
Second, this method feels somewhat impoverished given the richness of the data. The authors have nicely mapped out the directional tuning for almost the entire visual field. Instead of reducing this measurement to 2 values (center and direction), I was wondering if there is a better method to fully utilize the data at hand to get a better characterization of these DNs. As the authors are aware, local features alone can be ambiguous in characterizing optic flows. What's more, taking into account more global features can be useful for discovering potentially new cell types.
This is a great point, and we did an extensive analysis of other receptive field properties in this study (shown in supp fig 1). In addition, and as mentioned above, we have published a clustering analysis across receptive field properties of these neurons (Nicholas et al, J Comp Physiol A, 2020, cited in paper). The point that we attempted to make in this paper was that by using two strikingly simple metrics, we can reliably distinguish which of the two neuron types we are recording from (if we accept that there are two main types that we are likely to record from) simply based on location and overall directional preference. This makes automated analysis very easy and straightforward. Indeed, we now use this routinely to ID what neuron we are recording from, rather than making a human-based assumption.
However, we agree that further in depth analysis is warranted. Therefore, to address this, we will provide additional receptive field analysis and clustering in the revised version of the MS. In addition, we want to highlight that all data is uploaded to DataDryad for anyone interested in doing additional in-depth analyses.
Line 131, it wasn't clear to me why full-screen stimuli were used for comparison here, instead of the full receptive field maps. Male flies exhibit sexual dimorphic behaviors only during courtship, which would suggest that small-sized visual stimuli (mimicking an intruder or female conspecific) would be better suited to elicit dimorphic neuronal responses. A similar comment applies to the later results as well. Based on the receptive field mapping in Figure 1, I'm under the impression that these 2 DN types are more suited to detect wide-field optic flows, those induced by self-motion as mentioned in the manuscript. The results are still very interesting, but it's good to make this point clear early on to help set appropriate expectations. Conversely, this would also suggest that there are other visual DN types that are responsible for the courtship-related sexually dimorphic behaviors.
Thank you for mentioning these important points. Our reasoning for using full-screen stimuli for the analysis on line 131 was that since we used the small sinusoidal gratings for mapping the receptive fields, and to subsequently classify the neurons, it would be unfair to use the same data to investigate potential sexual dimorphism. I.e., we selected neurons that fulfilled certain criteria, and then we cannot rightfully use the same criteria to determine differences. This was not explicitly mentioned in the paper, so we will modify the text to make this clear to the Reader.
However, in Supp Figure 1d/e we show that there are no striking receptive field differences between males and females in terms of receptive field center nor directional preference. In Supp Figure 1f we show that there is no difference between male and female receptive field height and width. We will modify the text to draw the Reader’s attention to this figure, and also mention the additional analysis done in response to the comment above.
As a side note, I personally expected at least DNHS1 to have a smaller receptive field in males, as the hoverfly HSN is strikingly sexually dimorphic (Nordström et al, Curr Biol 2008), and also very sensitive to small objects. However, while optic flow sensitive DNs do respond to small objects (see e.g. the J Comp Physiol paper mentioned above) we did not detect any obvious sexual dimorphism in receptive field properties. Indeed, we think that a different subset of DNs control target pursuit behavior (target selective DNs (TSDNs)). This will be addressed in the modified version of the paper.
