B Flow Mosquito Mp3 Download =LINK=
Eden Kolander
Flight through cluttered environments, such as forests, poses great challenges for animals and machines alike because even small changes in flight path may lead to collisions with nearby obstacles. When flying along narrow corridors, insects use the magnitude of visual motion experienced in each eye to control their position, height, and speed but it is unclear how this strategy would work when the environment contains nearby obstacles against a distant background. To minimise the risk of collisions, we would expect animals to rely on the visual motion generated by only the nearby obstacles but is this the case? To answer this, we combine behavioural experiments with numerical simulations and provide the first evidence that bumblebees extract the maximum rate of image motion in the frontal visual field to steer away from obstacles. Our findings also suggest that bumblebees use different optic flow calculations to control lateral position, speed, and height.
Flying insects use the pattern of wide-field image motion on their retina - called optic flow - to control their flight. Optic flow is measured across the panoramic field of view of their compound eyes2,3 from the output of arrays of visual motion detection units that extract a motion estimate from neighbouring ommatidia4 over a small portion of the visual field. The outputs of these units are then pooled across larger parts of the visual field by integrating neurons5,6,7,8, which results in a wide-field representation of optic flow that can then be used to guide various aspects of flight behaviour such as lateral position, flight speed, and vertical position. What remains unclear is exactly how the pooling calculation that is being used to control flight is being performed and whether this is done across the entire visual field or in only select parts of it.
Bees routinely forage in cluttered natural environments, such as around bushes or in forests, where the risk of colliding with obstacles is high. The obstacles that pose the greatest collision risk in clutter are those in front. These would generate higher magnitudes of optic flow than the more distant background, but would subtend only a minor portion of the visual field. If the value for the magnitude of optic flow that is used for flight control is averaged across the output of motion detectors across a broad visual field, then information about the proximity of obstacles in front of the agent will be lost. Thus, how and where in the visual field optic flow is calculated will severely affect the performance of any vision-based flight control and collision avoidance strategies. Previous work provides little insight into how insects measure optic flow for flight control because the pattern of optic flow generated in the experimental corridors that are typically used in these studies is qualitatively independent of viewing angle and the nearest obstacles (the walls) occur only in the lateral visual field.
To investigate how insects control flight in cluttered environments and to identify the optic flow pooling strategies they use to do so, we recorded the trajectories of bumblebees flying through corridors in which the density and placement of obstacles were varied. We then calculated the response of different optic flow pooling methods to our different experimental environments and compared this to the measured data. We find that lateral position and speed control are being regulated by an optic flow pooling strategy that extracts optic flow from nearby obstacles in the frontal visual field but that height control is being regulated by a value of optic flow derived by averaging optic flow across a wide lateral field of view. Overall, our findings suggest that rather than calculating optic flow only across a wide visual field, bees selectively react to nearby obstacles for centring and speed control and that optic flow for different flight control behaviours may be mediated by parallel processing streams in the insect visual system.
The change in lateral position, flight speed, and vertical position in response to the density of nearby obstacles is likely a reflection of the way in which bumblebees pool optic flow from their panoramic field of view to control flight. Are they using a fixed spatial integration of optic flow across their entire visual field or are they selectively reacting to the nearby obstacles? To answer this question, we predict the lateral position, flight speed and vertical position in each of our experimental corridors for different methods of optic flow integration from different parts of the visual field. We then assess how well the results of each method agree with the experimental data from bumblebees to determine which method best explains the observed responses.
Our predictions of the lateral position are based on the optic flow balancing control strategy in which a sideways force is applied based on the difference between the optic flow on the left and right sides23 (for details, see equation [8]). Optic flow on the left and right side are pooled according to four of the most biologically plausible methods: average optic flow across lateral and fronto-lateral visual field (noted respectively avg and avgf), and maximum optic flow in lateral and fronto-lateral visual field (noted respectively max and maxf).
Although no pooling is performed on ventral flow, the predicted vertical position is affected by flight speed, which in turn is affected by the presence of obstacles and thus also the pooling method used. The predicted vertical position is lower when maximum pooling is used on the lateral optic flow than when average pooling is used (Fig. 3e) because the agent flies slower and must reduce its height to maintain ventral optic flow at the reference value.
The predictions that best match the experimental data are with average pooling, which yield prediction errors (Fig. 3f) that are approximately 5 times lower than with maximum pooling, suggesting that bees use average pooling of lateral optic flow to control their vertical position.
Our model predictions suggest that bumblebees use maximum optic flow pooling in the frontal visual field to control both their lateral position and flight speed but that vertical position is controlled by average optic flow pooling in the lateral visual field. An agent using only maxf would correctly replicate bumblebee lateral position and flight speed, but would not fly at the same vertical position and an agent using only average pooling would correctly replicate bumblebee vertical position, but would not fly at the same lateral position and flight speed. How can we reconcile this contradiction?
To test this hypothesis, we generated predictions using different optic flow pooling methods in parallel. Namely, in the formulation of the three forces driving the control of lateral position, flight speed and vertical position (equation [8]), we allowed different pooling methods to be used for each axis. While we applied the same control strategies for lateral position and flight speed as before, we modified the control strategy for vertical position. Instead of regulating the ventral optic flow so that it is equal to a fixed reference value, we regulate it according to a value generated from the lateral optic flow (and therefore coupled to flight speed, see equation [9]).
In this study, we investigate the effect of clutter on flight control in bumblebees and use mathematical models to understand how and where optic flow is being measured for this. We find that lateral position is controlled by balancing the maximum optic flow in the frontal visual field. This would ensure that even small obstacles in the flight path will be detected and used to control position, enabling rapid and effective collision avoidance responses. For speed control, the same pooling method is used to calculate the optic flow value that is then compared to a reference value, presumably set by the optimum sensitivity of specific speed-regulating neurons. Detecting the maximum optic flow output across an array of motion detectors is a biologically plausible operation which could easily be implemented in neural systems using a Winner-Take-All network30 or using differentiation and zero-crossing31, and is supported by previous behavioural32 and analytical33 studies. Interestingly, we find that bees are most likely using a different pooling method for controlling vertical position. Instead of adjusting their height to maintain the ventral optic flow at a fixed reference value, as suggested for honeybees21, we find that bumblebees regulate the ventral flow to a non-constant reference value equal to the average optic flow in the fronto-lateral visual field. It is possible that this finding is specifically related to our experimental situation, which contained vertical obstacles that could not be avoided by changing vertical position. It would be interesting for future investigations to examine the responses to horizontally-oriented obstacles and to model the pooling of lateral and ventral optic flow across varying azimuth and elevation angles. Taken together, our results suggest that bumblebees pool optic flow from the frontal visual field using two methods in parallel - averaging and maximum pooling - to control different aspects of flight. This has important implications for the design of flying robots because our findings suggest that a single forward pointed camera covering the frontal visual field is sufficient to replicate bumblebee behaviour.
In most insects, wing APOs are present in a location of the thorax that is medial to the wings and immediately ventral of the scutellar cuticle (Arnold, 1964; Pass et al., 2015). In general, these circulatory organs function by periodically increasing the volume of a sinus located between the scutellar cuticle and a pulsatile diaphragm, with each expansion aspirating hemolymph out of the wings via posterior wing veins. This, in turn, draws hemolymph into the wings via veins in the anterior of the appendage. Although this mode of action is fairly conserved across taxa, the kinetics of contractions are largely unknown and the structure of these organs varies significantly (Krenn and Pass, 1994a,b; Pass et al., 2015). Some wing circulatory organs are extensions of the dorsal vessel. Others are structurally independent of the dorsal vessel and are called wing hearts. When independent from the dorsal vessel, wing hearts can be paired organs, in which case each wing has its own pulsatile diaphragm, or an unpaired organ, in which case a single pulsatile diaphragm circulates hemolymph in both wings. Within the order Diptera, which encompasses the flies, wing circulatory organs are structurally independent of the dorsal vessel, and can be either paired, as in Drosophila sp. and Ceratitis capitata, or unpaired, as in Tipula sp. and Haematopoda pluvialis (Krenn and Pass, 1994a). The functional mechanics of the wing heart of mosquitoes remains unknown. In the present study, we scrutinized the circulatory physiology of the wing of the malaria mosquito Anopheles gambiae. We describe an unpaired wing heart, demonstrate that it contracts independently from the dorsal vessel, and uncover the trajectory and velocity of hemolymph within the wing space.
df19127ead