The correlation between wing kinematics and steering muscle activity in the blowfly Calliphora vicina
Department of Integrative Biology, University of California, Berkeley, CA 94720, USA
*e-mail: cnbalint{at}socrates.berkeley.edu
Accepted 5 October 2001
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Summary |
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Key words: insect flight, blowfly, Calliphora vicina, motor output, kinematics, steering.
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Introduction |
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Several studies have addressed aspects of motor encoding in insect flight by quantifying the muscle spiking patterns, largely in locusts (Möhl, 1985; Möhl and Zarnack, 1977
; Pearson and Wolf, 1987
; Schmidt and Zarnack, 1987
; Wendler, 1974
; Wilson and Weis-Fogh, 1962
; Zarnack and Möhl, 1977
), moths (Kammer, 1971
; Wendler et al., 1993
) and flies (Egelhaaf, 1989
; Götz, 1983
; Heide, 1983
; Nachtigall and Wilson, 1967
). Further, the coupling process linking changes in muscle activity to adjustments in wing kinematics has been studied through correlational studies in locusts and flies: Locusta (Dawson et al., 1997
; Thuring, 1986
; Zarnack, 1988
); Schistocerca (Fischer and Kutsch, 1999
; Waldman and Zarnack, 1988
); Drosophila (Heide and Götz, 1996
; Lehmann, 1994
; Lehmann and Götz, 1996
); Calliphora (Heide, 1983
; Tu and Dickinson, 1996
). However, given the potential non-linearities of muscle mechanics, the unknown nature of the coupling between muscles, joint morphology and the wing, as well as the highly variable motor responses to open-loop sensory conditions, our understanding of the transfer functions between motor patterns and wing movement is quite simplistic. In addition, information regarding the full extent of variation in wing kinematics has lagged behind the analysis of firing patterns in flight muscles.
Although flies are among the most aerodynamically sophisticated fliers, certain features of their flight control system are relatively simple and amenable to experimental studies. Flies use a single pair of wings and the muscles are segregated into distinct functional groups (for a review, see Dickinson and Tu, 1997). Many of the subtle alterations in wing kinematics that allow flies to execute fast changes in flight trajectory are accomplished by the action of small steering muscles that insert directly onto the sclerites at the base of the wing. The differential responses of several of these steering muscles to the direction (Heide, 1968
, 1971b
, 1975
, 1983
; Heide and Götz, 1996
) and time course (Egelhaaf, 1989
) of visual stimuli have corroborated their presumed role in mediating certain flight behaviors. The 13 steering muscles are attached to four sclerites at the wing hinge: the basalar sclerite, the pterales I and III and the posterior notal wing process. Five additional synchronous muscles thought to be involved in flight control are not directly attached to the sclerites of the wing hinge.
Inferences from the morphology of the hinge and its muscle attachments, together with the tonic firing patterns of their muscles, have given rise to several models of steering muscle function (Dickinson and Tu, 1997; Heide, 1968
, 1971a
,b
; Miyan and Ewing, 1985
; Nachtigall and Wilson, 1967
; Wisser, 1987
; Wisser and Nachtigall, 1984
). Because of their similar response properties, Heide (1975
, 1983
) proposed synergistic effects among muscles. Specifically, the second muscle of the basalare (b2) and the first muscle of pterale III (III1) act together to increase stroke amplitude, whereas the first muscle of pterale I (I1) and the third muscle of the posterior notal wing process (hg3) act to decrease stroke amplitude. In the fruitfly Drosophila melanogaster, the bursting activity in various individually recorded steering muscles is correlated with changes in stroke amplitude over many wingbeat cycles (Heide and Götz, 1996
). In the blowfly Calliphora vicina, the timing of individual basalare muscle spikes within a single wingbeat cycle can have clear cycle-by-cycle effects on wingbeat kinematics (Tu and Dickinson, 1996
). Lehmann and Götz (1996
) confirmed the influence of firing phase on stroke kinematics by stimulating b2 at various points within the stroke cycle. In addition to the effects of individual muscles on wingbeat kinematics, the analysis of Tu and Dickinson (1996
) also suggested the existence of functional synergies within the population of steering muscles. However, these muscles have not previously been recorded in concert, nor in combination with high-speed video.
To quantify the contribution of multiple muscle groups to kinematic variation, we extend the methodology of Tu and Dickinson (1996) to include multiple, simultaneous steering muscle recordings combined with high-speed videography. We correlate kinematic changes with the temporal and spatial activity patterns of steering muscles on a cycle-by-cycle basis. The results extend the work of previous studies and provide some new hypotheses concerning the processes linking motor activity and flight behavior.
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Materials and methods |
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Tethering procedure
We anesthetized each fly by placing it in a freezer at 4°C for 34 min. The fly was then immediately tethered at the dorsal midline of the mesopraescutum to a modified no. 0 insect pin as described by Tu and Dickinson (1996). As a modification to the earlier procedure, we soldered short lengths of 0.025 mm diameter nickel chromium (NiChr) wire with formvar insulation (A-M Systems) to the terminals of five pairs of 28 gauge wires glued to the tether. We implanted the tips of a pair of the NiChr wires into each of 45 steering muscles on the left side of the animal through holes in the cuticle made with an etched tungsten needle. In all nine animals used in the electrophysiological analysis, paired electrodes were implanted into muscles b2, b1, III1 and I1. In six of these animals, electrodes were also implanted in the vicinity of muscles III2III4. Correct implantation of each pair of electrodes was verified by qualitative differences in firing rate (e.g. high rates in b1 relative to b2) and the extent of cross-talk with nearby muscles (e.g. I1 recordings include cross-talk from b2, while III1 recordings include cross-talk from I1 but not from b2).
To create markers for digitization, we used a sharpened wooden applicator stick to place a small dot of silver (Palmer Prism Acrylic) or iridescent pearl (Golden Acrylics) paint on the basicosta (wing base) and at the distal tip of the wing posterior to the junction of vein R4+5. Each fly was allowed to recover for 1 day following initial electrode implantation before filming began, but we often made adjustments in electrode placement between filming sequences. Data were collected for 24 consecutive days following initial electrode implantation. When flies were not being used in experiments, they were suspended over a polypropylene ball floating in a beaker of water. The flies drank water ad libitum from the ball and were fed sugar water twice daily via a hand-held syringe.
Filming
Flies were kept under fully lit laboratory conditions (500 lx) starting at least 1 h prior to and during filming. We secured the free end of the tether onto a piezoelectric crystal attached to a rigid acrylic rod. The end of the rod was aligned using an adjustable manipulator, so that the flys longitudinal body axis was between 0° and 15° relative to horizontal and its sagittal plane was parallel to the cameras focal plane. The video camera lens was 4245 cm from the midline of the fly. A polypropylene ball floating within a beaker of water was placed under the fly to allow it to stand or walk between flight bouts.
We filmed the flies at a rate of 3000 frames s1 using a Kodak Ektapro equipped with an Intensified Imager and a 90 mm macro lens (Tamron). The video camera was tilted 30° relative to the ground to capture the wingbeat trajectory optimally within the 192x80 pixel field of view. Extracellular potentials from the implanted electrodes were amplified using an a.c. amplifier (A-M Systems; model 1800) and digitized using a Digidata 1200 and Axoscope software (Axon Instruments). Wingbeat signals from the piezoelectric crystal and frame-mark signals from the EktaPro Hi-Spec Processor were also recorded. Acquisition rates were 29, 37, or 42 kHz per channel depending on the number of input signals. All three types of signal, the wingbeat signals, the electromyographic (EMG) signals and the framemark signals, were displayed along a common time base to allow for fine temporal correlation among channels.
Wind and visual stimuli were presented to the fly as described previously (Tu and Dickinson, 1996). The mouth of a small open-throated wind tunnel was positioned directly in front of the fly, approximately 5 cm from the front of its head. A 7.0 cmx0.8 cm black cylindrical brass rod was suspended between the fly and the wind tunnel, with the base of the rod level with the flys head (Fig. 1). This pendulum rod oscillated at a frequency of approximately 1 Hz. We increased the contrast between the black rod and the background by fitting the top of the wind tunnel with a white cardboard panel. In a few cases, the position of the pendulum was monitored by placing the rods upper end between a light-emitting diode (LED) and an opto-electronic position sensor (UDT). In these cases, the output of the light sensor was recorded concurrently with the other signals.
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Data were collected from a total of 11 animals. Five animals with implanted electrodes were also filmed without the visual stimulus. Two animals were filmed prior to and following electrode implantation, and two animals were filmed solely without implanted electrodes.
Kinematic data analysis
All recorded video images were transferred from the EktaPro Hi-Spec Processor onto VHS videotape, and selected sequences were downloaded onto computer. For each sequence analyzed, we used Scion Image software to digitize the wingtip once per frame and the basicosta once per sequence. We manually digitized wingtip coordinates from a total of 144 150 frames taken from 21 selected video sequences of 11 flies.
While it is most convenient to quantify wing motion relative to the stroke plane, we found that in Calliphora vicina the mean stroke plane varies from stroke to stroke and thus cannot serve as a straightforward reference frame. Therefore, we defined the wingtip coordinates morphologically relative to the body to facilitate comparisons within sequences and among individuals. First, the X and Y coordinates of the basicosta (x0,y0) were subtracted from each wingtip coordinate so that the basicosta acted as the origin. Second, the body axis was defined as the line connecting the top of the calipter and the mid-posterior border of the eye. We defined the inclination angle of the body () as the angle between this line and the horizontal axis of the video screen. To combine ease of inter-animal comparison with that of aerodynamic interpretation, we rotated the video screen coordinate system so that the inclination of the body was at 35° relative to horizontal:
![]() | (1a) |
![]() | (1b) |
With these transformations, x' and y' measured motion about an inclined body axis. This transformation resulted in a roughly horizontal average stroke plane for the sequences within our analysis.
The two-dimensional Cartesian coordinates of the wingtips were then converted to polar coordinates. The z coordinate was calculated assuming a constant wing length:
![]() | (2) |
where L is the length of the wing in the coordinate system of the digitized image, and z' is the coordinate in the plane perpendicular to the x',y' plane. In previous descriptions of wing motion during flight, wing flexion appears to be minimal, except for a slight bending at the end of the downstroke (Nachtigall, 1966; Wootton, 1981
). At present, the extent to which wing length stays constant has not been quantitatively measured. The polar coordinates, deviation (
) and elevation (
) angle, of each wingtip coordinate were calculated relative to this new coordinate system (Fig. 2):
|
![]() | (3) |
and
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Electrophysiological data analysis
We sorted spikes recorded from each EMG channel on the basis of threshold and shape using a custom-designed program written in MatLab (Mathworks). Although most muscle recordings were contaminated by cross-talk, its source was easily recognized by careful comparison with other channels. For muscles b2, b1 and I1, we quantified the firing phase () of each spike relative to the minima in piezoelectric oscillations:
| (5) |
where S is the time of occurrence of the largest maximum or minimum in the muscle spike waveform, m1 is the time of the piezoelectric minimum preceding the spike and m2 is the time of the minimum following the spike. Correlation with digitized kinematics from high-speed video recordings indicated that the minima in the piezoelectric record corresponded roughly to the minima of wing elevation (Fig. 1). For muscles III1 and III2III4, we quantified phase in the same manner relative to the maxima in piezoelectric oscillations. Assuming that our piezoelectric signal is a good approximation of oscillations in muscle length and that the delays between the spike in a muscle and its subsequent activation are constant, our method of phase calculation provides an estimate of the relative phase of muscle activation.
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Results |
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Summed over all recorded flight sequences, each muscle displayed a variety of firing phases, distributed around a characteristic preferred phase band within the wingbeat cycle (Fig. 4A). The preferred phase bands for each muscle were consistent with those observed by Heide (1983) from individually recorded muscles. Muscles b1 and b2 fired with highest probability near the time of pronation, I1 tended to fire during the downstroke and III1 and III2III4 tended to fire near the time of supination. Within flight sequences, the time course of firing phase variation also differed among muscles (Fig. 4B). The most tonically active muscles, b1 and III2III4, displayed gradual shifts in spike phase (
) within a firing burst. The occasional shifts in the firing phases of b2 and I1 were sporadic, and the firing phase of III1 varied widely from spike to spike.
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Plotting all measured values of d from several video sequences in the same manner revealed the consistency of these observed trends (Fig. 7A) (Table 1). The points representing the three patterns of basalare activity clustered within three distinct regressions differing most in their offset along the
d,n axis. This clustering indicates that patterns of basalare muscle activity in each cycle strongly influence the change in
d from one cycle to the next (Fig. 7B). Cycles in which both b1 and b2 fired (black circles) were correlated with the largest increments in
d, and the size of the change diminished as the level of the baseline increased (Fig. 7A,B). Cycles in which only b1 fired (gray circles) were correlated with somewhat smaller increases in
d and showed a similar dependence on absolute baseline (Fig. 7A,B). Cycles in which neither muscle fired (white circles) were correlated with a decrease in
d, with the size of the decrease increasing as the magnitude of
d,n1 rose (Fig. 7A,B). Within each video sequence, the y intercept of the b2+b1 spiking pattern regression (red line) was always the largest, that of the b1 only regression (green line) intermediate and that of the neither b1 nor b2 regression (blue line) the smallest (Fig. 7C) (Table 1). The difference among the three regressions probably reflects the synergistic interactions between b1 and b2 on the position of the basalare sclerite. During flight, the basalare apodeme oscillates back and forth in phase with the stroke cycle (Tu, 1995
). If b1 fires, the mean position of the basalare apodeme moves further anterior, causing a larger stroke deviation. If both b1 and b2 fire, the influence on the kinematics of the sclerite and the resultant increase in stroke deviation is greater. If neither motor neuron fires, the muscles relax, the mean position of the basalare apodeme moves posteriorly and stroke deviation diminishes.
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Downstroke deviation and spike phase
The specific timing of muscle spikes within the cycle is also known to be an important determinant of the mechanical output of the b1 (Tu and Dickinson, 1994, 1996) and possibly of other steering muscles. Consistent with these previous findings, much of the variation within the b1- and b2-related effects on
d was associated with the specific phase of the spike occurrence,
. Fig. 8A maps the firing phase of b1 and b2 onto the regressions of Fig. 7A using pseudocolor. As with Fig. 7A, the position of each point relative to the line
d,n=
d,n1 indicates whether downstroke deviation decreased, increased or stayed the same from one stroke to the next. For any given value of
d,n1, the firing phase of basalare spikes was well correlated with the direction and magnitude of change in
d (Fig. 8A,B). Regressions through points representing similar b1 spike phases produced roughly parallel lines with intercepts that rose with decreasing
(Fig. 8C). The points at which these lines intersect the line of unity (
d,n=
d,n1) represent the predicted maintained downstroke deviation were b1 to fire at wingbeat frequency with constant phase. Thus, by tonically adjusting firing phase, the fly could maintain different levels of downstroke deviation. The relationship between b1 spike phase and the point of intersection with the line of unity was consistent with our observation that, even when b1 fired at maximal frequency, the measured downstroke deviations could be low if b1 fired late in the cycle.
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Downstroke deviation and forward amplitude
Although the wing hinge is complex, the fly is nevertheless limited in the way it can adjust its kinematics throughout the stroke. For example, maximum forward amplitude (max) was strongly correlated with downstroke deviation (
d) in all animals (Table 2). This correlation suggests that, because of a structural or mechanical linkage, when the basalare muscles elicit a change in downstroke deviation, there is a concomitant increase in forward amplitude. However, there exists enough variation in the correlation between downstroke deviation and forward amplitude to suggest that play in the mechanical linkages of the wing hinge permits additional muscles to modify the effects of the basalare muscles.
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The deviation/amplitude relationship corresponding to low III2III4 activity (red curve) was also loosely associated with high I1 activity (Fig. 9C,D, right). Although I1 was not always active when forward amplitude varied with downstroke deviation as indicated by the red curve in Fig. 9C,D, high I1 activity was consistently correlated with the smallest downstroke deviations and forward amplitudes (black points in Fig. 9C,D). This lower plateau in amplitude and deviation was not the lowest achievable, as noted above.
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Discussion |
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Dynamic properties of the basalare muscles
Of the various activation parameters that can influence force development in a muscle, the rate and phase of activation are typically most potent (see Josephson, 1985). In the blowfly Calliphora vicina, the muscle properties of one steering muscle, b1, have been particularly well studied (Bergmann-Erb and Heide, 1990
; Tu and Dickinson, 1994
) and are linked to the control of wingbeat kinematics (Tu and Dickinson, 1996
). For muscle b1, phase shifts have emerged as the dominant control parameter used to adjust work output (Heide, 1983
; Tu and Dickinson, 1994
, 1996
). In contrast, the basalare muscle b2 appears to exert its influence on wing kinematics primarily through changes in rate, with firing phase being relatively constant within bursts of activity (Heide, 1983
; Tu and Dickinson, 1996
). However, given the variety of muscle activation patterns we identified in the present study, the distinctions between the control mechanisms of b1 and b2 become less clear. Activation of both these muscles can occur at a multitude of spike rates and phases (Figs 3, 4). Over the range of these firing patterns, the correlations between b1 versus b2 spikes and the associated kinematic parameters, such as downstroke deviation and forward amplitude, diminish (Tu and Dickinson, 1996
). We found that, by correlating b1 and b2 spike occurrences with cycle-to-cycle changes in downstroke deviation (Figs 7, 8), these two muscles could account for a large proportion of the observed variation in wing trajectory during visually induced steering reactions.
Our finding that the changes in downstroke deviation are dependent on the absolute level of stroke deviation suggests at least two similar hypotheses for the way muscle properties influence the modulation of kinematics. First, because of intrinsic physiological properties, the size of each twitch might be dependent on the rate of activation (Aidley, 1985). Such effects have been demonstrated under isometric conditions for muscle b1 (Tu and Dickinson, 1994
). Second, because the muscles operate within a complex system of skeletal attachments, the mechanical advantage, and thus the net effect on the wing, might change with the baseline level of activity. These hypotheses are not mutually exclusive. Either mechanism, a physiological rate-dependence or a changing mechanical advantage, could explain the diminished influence of muscle spikes at elevated baselines. Further, because the basalare muscles are attached to a common sclerite, the activity of any one muscle could alter either the length-dependent physiological properties or the mechanical advantage of the others. Our data from two of the muscles, b1 and b2, suggest that both muscles contribute to the summation process controlling downstroke deviation. Through these complex interactions, the sequence (Fig. 7) and the timing (Fig. 8) of spikes in just a few motor neurons exert a remarkably flexible control over motor output.
The cycle-by-cycle variation in downstroke deviation during cycles in which neither b1 nor b2 fired was relatively high (Fig. 7) (Table 1). This suggests that additional factors contribute to variation in this kinematic parameter, most notably the unrecorded activity of the remaining basalare muscle b3, which is positioned to act as an antagonist to b1 and b2, and the activity of muscles attached to the other wing sclerites.
Interaction between steering muscle groups
The steering muscles of flies have typically been grouped functionally according to the sclerites to which they are attached (see Wisser and Nachtigall, 1984). The functions assigned to each of these muscle groups have been that of either increasing or decreasing specific kinematic parameters, such as stroke amplitude averaged over many wingbeats. However, our findings suggest that this form of categorization needs to be modified for the real-time case. For example, as described in the previous section, the basalares can increase or decrease downstroke deviation and forward amplitude depending on the prior baseline. Further, because the basalares are probably not the only contributors to modulations in forward amplitude, the classification scheme must be modified to include the combined effects of concomitantly active steering muscles.
Consistent with the idea that combined activity of multiple muscles contributes to the conversions linking muscle spikes to kinematics, we found that the correlation between basalare activity and forward amplitude depended on the concomitant activity of muscles III2III4. As shown in Fig. 9C,D and summarized in Fig. 10, the forward amplitude accompanying a given downstroke deviation is larger while III2III4 is active (blue-green curve) than when it is not (red curve). The relatively small forward amplitudes accompanying each downstroke deviation are associated with the activity of I1 to some degree (Fig. 9C,D), but may also be due to the unrecorded activity of I2. Therefore, the manner in which the basalares control forward amplitude appears to depend on the activity of the muscles attached to both sclerites I and III.
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Nalbach (1989) attempted to correlate these kinematic changes with the activity of basalar muscles by observing the deflection of the basalar sclerite. On the basis of sclerite motion, contraction of b1 and b2 correlated with large stroke amplitudes and relaxation correlated with small stroke amplitudes, but motion of the basalare sclerite did not always coincide with mode switching. Motion of axillare 3 (pterale III), however, was closely correlated with mode switching. Although Nalbach (1989
) did not speculate about the mechanism by which the muscles of axillare 3 might participate in the control of mode selection, she hypothesized that the muscles of axillare 1 (pterale I) might pull the wing medially so that the RS contacts the PWP.
Our results from recordings of muscle activity are in accordance with Nalbachs (1989) inferences from sclerite motion. The spike activity of b1 and b2 was strongly correlated with forward amplitude (Table 2). In our analysis, we also found that low-frequency b1 and b2 activity combined with elevated activity in I1 was correlated with relatively large lower limits to downstroke deviation and forward amplitude compared with the limits achieved when III2III4 was active (Fig. 9C,D). This kinematic limit associated with I1 activity might be due to a mechanical obstruction such as that caused by contact of the RS with the PWP during the downstroke, whereas the activity of III2III4 might keep the two structures from engaging. In this case, the muscles of sclerites I and III appear to control mode-switching, as proposed by Nalbach (1989
), while the basalares effect changes in forward amplitude within modes.
Our results also confirm the proposal of Heide (1971b) that the muscles of pterale III support the basalare muscles in regulating the stroke amplitude. However, our analysis considered only the ON or OFF effects of III2III4 firing, and further contributions of the spike rate, firing phase and muscle recruitment remain to be quantified. The second role of the pterale III muscles postulated by Heide (1971b
), regulating the angle of attack, cannot be tested without reconstructing the three-dimensional kinematics of the wing. Because of its relatively phasic firing pattern under the current experimental conditions and its large size among steering muscles, we would expect each III1 spike to cause detectable changes in wing kinematics. The fact that III1 firing did not correlate with changes in wingtip trajectory suggests that its action may regulate some unmeasured kinematic parameters such as angle of attack.
Lessons from free flight
Although any extrapolation from the kinematics of one wing of a tethered fly must be made with caution, we can begin to address the implications for the neuromechanical control of free flight maneuvers. In his study on Musca domestica, Wagner (1986b) postulated that some of the delays in flight correction may be due to summation effects in the muscle system. The additive effects of the basalare muscles we observed indicate that cycle-by-cycle kinematic changes are indeed limited, and several cycles of repetitive activity are required to elicit substantial changes in kinematic parameters such as stroke deviation and amplitude. Further, both Wagner (1986a
) and Schilstra and van Hateren (1999
) observed that, while flies have the ability to alter yaw, pitch and roll independently, these directional parameters vary together in a characteristic manner during the most common turning behaviors. Blondeau (1981
) also described similar results for directional forces measured in tethered Calliphora erythrocephala. On the basis of these findings, wingbeat kinematics should similarly co-vary in a characteristic manner, while occasionally displaying a decoupling as observed in behavioral studies (Nachtigall and Roth, 1983
). In accordance with this expectation, we have observed one example in which downstroke deviation (
d) and forward amplitude (
max), while typically covariant, were decoupled depending on differential III2III4 activity. Further examination of wingbeat kinematics may reveal the partial decoupling of other kinematic parameters.
In summary, we found that the role of any single muscle cannot be considered in temporal or spatial isolation either from its prior activity or from the action of other steering muscles. Our correlational analysis identified some of the muscular and structural features that may influence the context-dependent effects of muscle activity on wingbeat kinematics. The causal relationships remain hypotheses that have yet to be tested and will require experiments involving the ablation and stimulation of individual muscles. Further, a larger data set is required to increase the range of observed wing kinematics and to identify the influence of other steering muscles. Most importantly, it will be necessary in future experiments to measure the instantaneous angle of attack of the wing during the types of wingbeat modulation observed in the present study. Recent studies of the kinematics and aerodynamics of Drosophila melanogaster have quantified the importance of subtle changes in angle of attack and rotation timing on force output (Dickinson et al., 1999; Sane and Dickinson, 2001
). Therefore, extending the analysis to three-dimensional wing kinematics will make it possible to explore the aerodynamic consequences of steering muscle activity and to identify other kinematic parameters that may be influenced by these muscles. With such continued studies, we may begin to decode motor patterns in terms of their interactions with the musculoskeletal system and the surrounding medium.
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Acknowledgments |
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