A comparison of visual and haltere-mediated equilibrium reflexes in the fruit fly Drosophila melanogaster
1 UCB/UCSF Joint Bioengineering Graduate Group, University of California at
Berkeley, Berkeley, CA 94720, USA
2 Department of Integrative Biology, University of California at Berkeley,
Berkeley, CA 94720, USA
* Author for correspondence (e-mail: alanas{at}socrates.berkeley.edu)
Accepted 14 October 2002
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Summary |
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Key words: haltere, mechanosensory, fruit fly, Drosophila melanogaster, flight, control system
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Introduction |
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Fruit flies are equipped with compound eyes that provide low spatial
resolution visual information (Buchner,
1976). Although there is no precise measure of the flicker fusion
rate for Drosophila, photoreceptor dynamics measured in other flies
indicate that dipteran visual systems display unusually high temporal
resolution (Autrum, 1958
;
Laughlin and Weckstrom, 1993
).
For instance, the flicker fusion rate of Calliphora was measured as
approximately 250 Hz (Autrum,
1958
). Downstream of the photoreceptors, motion-sensitive neurons
in the visual system allow flies to track both small objects and large field
rotations (Borst and Egelhaaf,
1989
; Egelhaaf and Borst,
1993
). In the blowfly Calliphora erythrocephla, Krapp and
coworkers (1998
,
1996
) have shown that certain
visual interneurons encode the optical flow fields that would be generated by
self-motion such as forward translation, roll or pitch. Blondeau and
Heisenberg (1982
) measured the
torque exhibited by Drosophila melanogaster in response to visual
rotation about the three body axes. In each case, the fly generated a torque
that would rotate it in the direction of the imposed stimulus. The magnitude
of a fly's response to large field image rotation is not a function of the
true angular velocity of the rotation, but instead a function of the contrast
frequency, defined as the angular velocity of the rotation divided by the
spatial wavelength of the image (for a review, see
Srinivasan et al., 1999
). This
feature is thought to result from the intrinsic properties of elementary
movement detectors, which measure temporal correlations of local luminance and
not absolute image velocity (Reichardt and
Poggio, 1976
).
In contrast to the visual system, the halteres can potentially provide an
accurate measure of angular velocity as the fly rotates in space. Halteres are
small evolutionarily modified hind wings
(Fig. 1A) that beat anti-phase
to the wings and serve a purely sensory function during flight. Derham
(1714) was the first to note
that flies cannot maintain stable flight once their halteres are removed. The
halteres beat through an amplitude of roughly 180°, in a plane reclined
approximately 30° to the transverse axis of the body in both
Calliphora (Nalbach,
1993
) and Drosophila
(Dickinson, 1999
). As the fly
rotates around the roll, pitch and yaw axes, angular velocity dependent
Coriolis forces act on the beating halteres
(Nalbach, 1993
;
Pringle, 1948
). Campaniform
sensilla and chordotonal organs at the base of the halteres are thought to
encode strains generated as the Coriolis forces cause the haltere to deviate
from the beating plane (Pflugstaedt,
1912
; Pringle,
1948
). Although Pringle proposed that halteres were sensitive
solely to yaw rotation, it was later shown by Faust
(1952
) that flies adjusted
wing kinematics in response to rotation around all three axes.
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Interconnections between the halteres and the flight control system have
been examined in the blowfly. Motor neurons controlling the neck muscles
receive input from both haltere afferents and motion sensitive neurons in the
visual system (Strausfeld and Seyan,
1985). Additionally, haltere mechanoreceptors provide synaptic
input to the motor neurons of the steering muscle B1
(Fayyazuddin and Dickinson,
1996
), an observation that has been repeated in
Drosophila (Trimarchi and
Murphey, 1997
). In Calliphora, motor neurons of the
haltere muscles also receive excitatory input from visual interneurons
(Chan et al., 1998
).
Haltere-mediated behavioral responses include both head movements and changes
in wing kinematics in Drosophila
(Dickinson, 1999
),
Calliphora (Nalbach,
1993
,
1994
;
Nalbach and Hengstenberg,
1994
) and Lucilia
(Sandeman, 1980
). Although
flight torques have never been measured during stimulation of the halteres,
the observed changes in wing kinematics are consistent with compensatory
reactions that would act to rotate the fly against the direction of imposed
motion.
Our focus in this study is the interaction between feedback from the halteres and the compound eyes. Using a flight simulator, we decouple these sensory inputs and characterize their temporal sensitivity to imposed rotational stimuli. Our results show that the two systems are complimentary. Whereas the gain of the visually mediated response decays with increasing frequency, the haltere-mediated response rises with stimulus velocity. The fusion of information from these two modalities would result in a broader bandwidth for detection of angular velocity during flight.
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Materials and methods |
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Flight simulator
The flight simulator consists of a visual display mounted within a
rotational gimbal (Fig. 1B,C).
The wrap-around display, composed of 11 340 light-emitting diodes (LEDs),
spans 316° horizontally and 88° vertically. Visual patterns, refreshed
at a minimum rate of 1 kHz to accommodate the high flicker fusion rate of
flies, were generated and controlled using a digital signal processor (Texas
Instruments TMS320C6701 EVM). Three brushless d.c. motors attached to pulleys
controlled the orientation of the visual display mounted within the gimbal
(Fig. 1C). The gimbal was
designed to achieve velocities up to 2000° s-1 and
accelerations up to 20 000° s-2 around each of the three
rotational axes. These specifications were based on velocity profiles that
were experimentally determined by tracking fruit flies during free flight
(Tammero and Dickinson,
2002).
Visual closed-loop flight
During experiments, the tethered fly was positioned in the center of the
visual display using a micromanipulator. An infrared LED, mounted directly
above the fly, illuminated the two photocells of a wingbeat analyzer beneath
the fly (Götz, 1987;
Lehmann and Dickinson, 1997
).
A shadow, created as the wings pass beneath the infrared (IR) light, falls
onto the photocells, generating output signals that are proportional to the
amplitude of each wing. The wingbeat analyzer also provides a precise measure
of the wingbeat frequency. Previous work has shown that flies adjust their
left and right wingbeat amplitudes to keep a dark vertical stripe centered
frontally in their field of view, a behavior known as fixations
(Götz, 1987
). A
closed-loop environment is created in which the output of the wingbeat
analyzer is used to control the angular position of the dark stripe,
essentially simulating the visual motion that would be generated by the flies'
wingbeat adjustments. Flies flying in the arena under closed-loop conditions
tend to display more robust behavioral responses than those operating in
open-loop mode, a condition where the stimulus is not dependent on the
behavior of the fly (Dickinson,
1999
). The basic experimental procedure was to superimpose visual
or mechanosensory rotation in open-loop while the fly performed closed-loop
fixation of the vertical stripe.
Rotation experiments
During mechanical rotation experiments, the gimbal was oscillated in
open-loop about either the roll, pitch or yaw axis. We allowed the fly to
fixate a stripe in visual closed-loop during presentation of mechanical
rotations. The angular position of the gimbal was modulated in a modified
sinusoidal sweep, stepping through frequencies from 0.8-3.0 Hz in discrete
increments of 0.2 Hz with an amplitude of ±32°, representing a peak
angular velocity range of 160-700° s-1. Each frequency was
presented for 5 cycles within the sweep. Each sweep was separated by a pause
of sufficient length to allow wingbeat amplitude and wingbeat frequency to
return to pre-trial values.
The visual open-loop stimuli consisted of striped spherical patterns presented on the cylindrical LED display. The motion of the pattern created the illusion of a sphere being rotated around the fly (Fig. 1D). To create behavioral conditions comparable to mechanosensory experiments, a dark stripe, which the fly fixated in closed-loop, moved independently of the open-loop spherical pattern. The pattern position was oscillated along a sinusoidal sweep that stepped in frequency from 0.1 to 3.9 Hz in 0.2 Hz increments. The amplitude of the image rotation was fixed at 45°, and thus the peak angular velocity changed according to the oscillation frequency of the visual stimulus. The oscillation frequencies within the sweep produced peak angular velocities ranging from 30-1100°s-1. One stimulus sweep was composed of six consecutive oscillation cycles at each frequency. Each fly was tested with at least five sweeps, alternated with recovery periods during which wingbeat parameters were able to return to pre-stimulus levels.
The data, sampled at 200 Hz, included right and left wingbeat amplitude,
wingbeat frequency, the position of the vertical stripe, the orientation of
the gimbal, and the position of the spherical pattern. The data were filtered
digitally (zero phase delay) with a low-pass cut-off of 40 Hz to remove any
high-frequency noise resulting from vibration of the motors. The relationship
of the wingbeat analyzer output to the stroke amplitude is known to be linear
over the operating region (Lehmann and
Dickinson, 1997). Although we could not calibrate the wingbeat
signal for each fly, in this study we used the output of the wingbeat analyzer
as a measure of the relative behavioral responses to sensory input, and not
for accurate measurement of stroke amplitude. For the group of flies
comprising each experimental treatment, the standard deviations (S.D.) of the
left and right wingbeat amplitude signals were calculated over a pre-stimulus
period of approximately 10 s. The wingbeat signals of each individual were
then scaled such that this pre-stimulus S.D. was normalized to that of the
group. To evaluate the flies' behavioral response representing the control of
roll and yaw, we focus on the difference between the amplitudes of the left
and right wings, since a disparity generates torque along these axes. The
behavioral response representing the control of pitch is the sum of the left
and right wingbeat amplitudes, since a bilateral increase or decrease in total
amplitude modulates flight forces around the pitch axis. The responses to each
stimulus frequency were averaged over multiple trials. We used an FFT
algorithm to determine the amplitude and phase of the sine curve that best fit
the averaged response at each stimulus frequency. In the subsequent sections
and figures, the amplitude of these calculated sine fits is referred to as the
change in wingbeat amplitude (
WBA), whereas raw wingbeat amplitude data
is labeled WBA. All analyses were performed using custom software written in
MATLAB (Mathworks).
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Results |
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Similarly, a visual rotation presented in the absence of mechanical stimuli elicited a compensatory response in wingbeat amplitude. In response to sinusoidal oscillations, flies modulated the difference between left and right wingbeat amplitude in a roughly harmonic pattern. As with mechanical rotation, the amplitude of the fly's response was a function of the angular velocity of the visual stimulus. However, when tested over roughly the same range of frequencies as that used for mechanical rotations, the magnitude of responses to visual roll decreased with increasing velocity (Fig. 2B), a trend that was consistent across flies (Fig. 3).
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We tested the responses in wingbeat amplitude (leftright for roll
and yaw, left+right for pitch) to mechanical and visual rotations across a
wide range of angular velocities. The mean amplitude of the sine wave fits to
the raw wingbeat responses is plotted against peak stimulus velocity in
Fig. 3 For all three rotational
axes, the visually elicited motor response behaved as a band-pass filter of
the sensory stimulus. The response is highly sensitive to intermediate
rotational speeds, but decays for both large and small angular velocities. In
contrast, the response to mechanical rotation rose with increasing angular
velocity for all three stimulus axes. Furthermore, whereas the visual
responses were similar for yaw, pitch and roll, the response to mechanical
oscillation varied significantly, depending on the axis of rotation. Of
particular note is the relatively weak effect of mechanical yaw. This finding
is consistent with the trend observed in previous studies measuring
haltere-mediated equilibrium reflexes at a single frequency
(Dickinson, 1999), although the
relative magnitude of the yaw response is even smaller in the present study.
It is unclear whether the weak yaw response is a due to the response
properties of yaw-sensitive mechanoreceptors in the haltere, or to downstream
sensory-motor circuitry.
The visually and mechanically elicited responses to comparable rotational stimuli are approximately 180° out of phase, as seen in the averaged response of a single fly to multiple presentations of rotation about the roll axis (Fig. 4). This phase disparity arises because flies rotate in the direction visual motion, attempting to stabilize the image, whereas they move against mechanical rotation, attempting to regain equilibrium. This phase difference is consistent with the reflexes being compensatory, because mechanical rotation of the fly's body will generate optic flow across the retina in the opposite direction.
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One important determinant of behavioral response to motion of a periodic
visual pattern in flies is contrast frequency
(Götz, 1972). In an
independent set of experiments at a constant oscillation frequency, we
measured the effect of spatial wavelength on the behavioral response to
sinusoidal pattern rotation about the yaw axis. For patterns with three
different stripe widths (8.8°, 17.5°, 35°) we found no
statistically significant difference in the magnitude of the response
(analysis of variance, ANOVA; P=0.5290)
(Fig. 5). Because our stimuli
consisted of bars, and not sinusoidal functions of intensity, each stimulus
comprised a series of contrast frequencies. However, most of the stimulus
energy resides in the fundamental. Our three different stripe widths
corresponded to contrast frequency fundamentals of 4.8 s-1, 2.4
s-1 and 1.2 s-1. Thus, our visually elicited equilibrium
responses did not vary significantly over a fourfold range in contrast
frequency.
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In addition to stroke amplitude adjustments, flies also modulated wingbeat frequency during compensatory reactions to visual and mechanical rotation. Fig. 6 shows the responses of both wingbeat amplitude and wingbeat frequency to pitch rotations. When subjected to mechanical pitch at two different frequencies, the fly's wingbeat amplitude response was larger for the faster oscillation (Fig. 6, top row). In contrast, the amplitude of wingbeat frequency modulation was smaller for the higher oscillation frequency. In response to visual pitch, modulation of both wingbeat amplitude and frequency decreased as the stimulus frequency increased. This result was consistent for all flies and indicates that the amplitude of wingbeat frequency modulations decreases with increasing stimulus velocity, even in cases when the wingbeat amplitude response rises (Fig. 7). This suggests that either wingbeat amplitude and frequency are controlled independently or that the wingbeat frequency response is dynamically limited.
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Discussion |
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The main limitation of these experiments is the necessity of analyses restricted to tethered flight conditions. Sensory feedback to the halteres and other organs is attenuated under tethered conditions. Consequently, the response of a tethered fly may be quite different than that of the animal in free flight, making extrapolations between the two conditions difficult. Further, although we can measure wingbeat amplitude and frequency, we have no information about many other significant stroke parameters such as angle of attack and deviation of the wing from the stroke plane. Sensory-motor control of these parameters may play a significant role in equilibrium reflexes. Despite these limitations, we have observed robust behavioral responses that constitute a good, if not complete, measures of flies' sensitivity to imposed visual and mechanical rotations.
Filter characteristics of the halteres and visual system
Both the visual system and halteres act as band-pass filters of sensory
stimuli. The visually elicited response decays both for fast and very slow
rotations (Fig. 3). Similar
results were found in Hengstenberg's study of visually elicited head roll
responses in Calliphora
(Hengstenberg, 1991). In a
study of the optomotor responses in Drosophila, a decrease of the
visual mediated torque was seen at slow speeds for both roll and pitch
(Blondeau and Heisenberg,
1982
). In the present study, we found that the wingbeat amplitude
response to mechanical rotation decayed linearly with decreasing stimulus
velocity. This decay was expected because the Coriolis force on the haltere is
linearly proportional to the angular velocity of the stimulus. Hengstenberg
found that the haltere-mediated head roll response was insensitive to roll
rotation below 50° s-1 in the absence of visual cues. Although
the haltere-mediated responses rise with stimulus velocity, this reflex also
possesses band-pass characteristics because mechanosensory neurons must
eventually fail as stimulus frequency increases. A measure of the upper limits
of halteres responses would provide further insight into the significance of
haltere feedback in flight maneuvers. Unfortunately, we could not operate our
apparatus fast enough to map this upper limit.
Function of multi-sensory feedback in flight performance
In all closed-loop control systems, the performance of the overall system
is dependent on the dynamics of the sensory feedback channels. Combining the
fast mechanosensory halteres with a slower visual system may allow the fly to
optimize bandwidth without sacrificing sensitivity. In addition to simply
extending the bandwidth of equilibrium reflexes, a visually independent source
of feedback would enable a fly to distinguish motion of its external
environment from that generated by self-motion. Along with their role in
equilibrium reflexes, the halteres probably provide critical feedback during
active flight maneuvers. The flight trajectories of many flies consist of
short straight flight segments punctuated by rapid turns called saccades
(Collett and Land, 1975;
Zeil, 1986
). The extended high
frequency response of the haltere system might enable flies to achieve these
straight segments by detecting quick perturbations beyond the range of the
visual system. Drosophila saccades vary little in amplitude, and are
typically 90° to the left or right
(Tammero and Dickinson, 2002
).
Although the stereotyped nature of saccades might result from a simple
feed-forward motor command, evidence suggests that haltere feedback plays a
role in terminating free flight saccades, which are significantly shorter than
their tethered flight analogs (Mayer et
al., 1988
). Angular velocity exceeds 1000° s-1
during free flight saccades (Fry and
Dickinson, 2001
; Tammero and
Dickinson, 2002
). As shown in
Fig. 3, the visual feedback is
considerably weaker than haltere-mediated responses at speeds greater than
500° s-1. Although we could not measure the haltere response at
speeds above 800° s-1, there is good evidence that the halteres
encode angular velocities well above 1000° s-1. For example,
Hengstenberg (1988
) has shown
in Calliphora that the maximal halteremediated head roll response
occurs at 1500° s-1. Thus it is likely that haltere feedback
plays an important role in regulating saccade amplitude.
In addition to the compound eye and haltere systems, flies receive visual
feedback from ocelli, as well as mechanosensory feedback from specialized
receptors on the neck, wings, legs and antennae. Although the role of these
sensory systems in flight is not as well characterized as that of the visual
system, they likely provide important feedback about the relative motion
between the fly's body, its head and its environment. For example, as in other
insects, the ocelli are thought to play a role in the orientation of the fly
with respect to the sky (for reviews, see
Mizunami, 1999;
Stange, 1981
;
Taylor, 1981
). Asymmetrical
stimulation of the ocelli in Calliphora will elicit a transient head
roll response as the fly tries to correctly position itself with respect to
light (Hengstenberg, 1993
).
Additionally, campaniform sensilla at the base of the wing sense asymmetrical
wing load and elicit compensatory head movements
(Hengstenberg, 1988
).
Convergence of visual and mechanosensory feedback on the flight
motor
The neuroanatomy of the halteres and visual system, as well as of the
flight motor, provides insight into the functional interaction between these
feedback channels. In Calliphora, lobula plate tangential neurons
synapse with a subset of motor neurons controlling neck muscles
(Strausfeld and Seyan, 1985).
Also in Calliphora, there is physiological evidence that visual
interneurons project to the motor neurons of haltere control muscles
(Chan et al., 1998
). Motor
neurons controlling two of the 17 wing steering muscles (B1 and B2) and
descending neurons from the visual system are dye-coupled in male flesh flies,
Neobellieria bullata (Gronenberg
and Strausfeld, 1991
). Thus, the combination of evidence from
anatomical and physiological studies indicates that descending visual
interneurons contact motor neurons in all three thoracic segments, controlling
the motion of the head, wings and halteres.
Studies suggest that feedback from haltere afferents influences motor
activity in flies. Neck motor neurons in Calliphora receive input
from haltere afferents (Strausfeld and
Seyan, 1985). This connection is quite fast, with latencies from
haltere stimulation to activity in the neck motor neurons of approximately 2-3
ms (Sandeman and Markl, 1980
).
The steering muscle B1 receives electrical synaptic input from haltere
afferents in both Calliphora
(Fayyazuddin and Dickinson,
1996
) and Drosophila
(Trimarchi and Murphey, 1997
).
In both species, B1 is known to control changes in wingbeat amplitude
(Heide and Götz, 1996
;
Tu and Dickinson, 1996
).
Whereas the pathways by which visual and haltere feedback influence
wingbeat amplitude have been at least partially identified, the circuits
controlling wingbeat frequency are not as well understood. Specialized
pleurosternal control muscles (ps1 and ps2) are thought to alter wingbeat
frequency via changes in the mechanical resonance of the thorax
(Kutsch and Hug, 1981;
Nachtigall and Wilson, 1967
).
The firing patterns of these muscles correlate with changes in the wingbeat
frequency of Calliphora and Muscina
(Kutsch and Hug, 1981
;
Nachtigall and Wilson, 1967
).
The maximum firing rate of pleurosternal muscles is 20 Hz, approximately one
tenth of the firing rate of B1 (Kutsch and
Hug, 1981
; Nachtigall and
Wilson, 1967
). The relatively slow firing rate of ps1 and ps2
might explain in part the slow adjustments of wingbeat frequency in the flight
responses. Although the factors that limit the bandwidth of the wingbeat
frequency response are not entirely understood, these results imply that this
response is qualitatively different from the wingbeat amplitude response.
In summary, we have characterized the dynamics of the visual and mechanosensory systems as a step towards understanding how flies integrate these two sensory modalities for flight control. Our results show that the halteres are more responsive to fast rotations, while the visual system is more sensitive to slow rotational stimuli. This study on isolated visual and mechanosensory responses will serve as a basis for future work on more natural, concurrent, sensory stimuli.
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Acknowledgments |
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