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First published online August 22, 2008
Journal of Experimental Biology 211, 2779-2785 (2008)
Published by The Company of Biologists 2008
doi: 10.1242/jeb.017756
Predicting acoustic orientation in complex real-world environments
Centre for Ecological Sciences, Indian Institute of Science, Bangalore, 560012, India
* Author for correspondence (e-mail: rohini{at}ces.iisc.ernet.in)
Accepted 24 June 2008
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Summary |
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 TOP Summary INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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Key words: phonotaxis, acoustic orientation, real-world environments, biomimetic simulation model
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INTRODUCTION |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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). Several of these
are now understood to the extent that quantitative modelling approaches have
been successfully used to mimic behaviour
(Webb, 2000). These models
attempt to mimic the sensory and neural systems that control behaviour and ask
whether they are sufficient to explain it
(Webb, 2001). The models are,
however, typically tested under conditions that are simpler than those faced
by animals in their natural environment. Neuroethological modelling studies,
which take a bottom-up approach to explaining behaviour, are based on the
premise that a complete understanding of the underlying mechanisms should
allow us to predict behaviour in any situation, including complex real-world
conditions (Dean, 1998). The
testing of models is, therefore, inadequate without quantitative comparisons
between the predictions of the models and the behaviour of animals in
real-world conditions.
Field cricket phonotaxis has been investigated in several laboratory
studies, which have shown that, when faced with multiple song sources of their
own species, female crickets preferentially approach louder songs
(Roemer, 1998;
Hedwig and Poulet, 2005).
Laboratory experiments are, however, carried out under ideal conditions and
the selectivity observed under these conditions cannot easily be extrapolated
to the field, where songs are attenuated and their temporal patterns degraded
by the environmental transmission channel
(Roemer, 1998). In addition,
several males often call simultaneously, interfering with each other's song
(Feng and Schul, 2006). This
creates a complex acoustic environment in which sound localization becomes a
challenging task, and little is known about orientation abilities under these
conditions. Field experiments using pitfall traps show that female crickets
prefer louder songs (Roemer,
1998; Gerhardt and Huber,
2002). However, since these experiments only recorded capture
data, one cannot infer much about orientation abilities from them.
Many aspects of the mechanisms underlying cricket phonotaxis are understood
across multiple levels: biophysical
(Michelsen, 1998),
neurobiological and behavioural (Pollack,
1998; Hedwig,
2006). This has allowed for the creation of robotic models
(Webb, 1995;
Reeve et al., 2005); however,
these models have not been validated in realistic, multi-source field
conditions (Webb, 2006).
We previously developed a simulation model of field cricket walking
phonotaxis based on auditory physiology and phonotactic walking behaviour
observed in the laboratory (Mhatre and
Balakrishnan, 2007). This simulation model attempts to capture the
perception of calling song by field crickets using information on the tuning
of the cricket ear, its directional properties and the ability to selectively
attend to louder songs; it also models the threshold and saturation of the
auditory receptors (Pollack,
1986; Pollack,
1988; Michelsen,
1998; Pollack,
1998). Virtual females in this model respond to perceived sounds
by moving towards the louder sound. Their motor behaviour is stochastic and is
modelled on the basis of data collected in our previous laboratory experiments
under closed-loop conditions in which females were exposed to two calling
songs at different absolute and relative sound pressure levels (SPLs)
(Mhatre and Balakrishnan,
2007). This model was able to successfully simulate the
phonotactic orientation behaviour of real females at the population level in
the laboratory experiment as well as in a two-source field experiment
(Mhatre and Balakrishnan,
2007). In the present study, we show that this simulation model
can successfully predict acoustic orientation behaviour in multi-source field
conditions.
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MATERIALS AND METHODS |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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) in the same habitat with intact vegetation.
Experiments were carried out between December and February (the breeding
season) 2005 and 2006 (the breeding season) at peak activity time
(18.30–20.00 h). Ambient temperatures ranged from 18°C to 22°C.
Stimuli were synthesized using a single chirp from a P. guttiventris
song recorded at 21°C (Mhatre and
Balakrishnan, 2007). The temporal pattern used was appropriate for
this temperature (carrier frequency=4.9 kHz, chirp duration=180 ms, chirp
period=339±32 ms) (Mhatre and
Balakrishnan, 2006). Stimuli were broadcast from either a pair of
Creative speakers (Creative Labs Inc., Singapore) (frequency range: 100
Hz–15 kHz) or these in combination with Philips BA109 loudspeakers
(Amsterdam, The Netherlands) (frequency range: 100 Hz–18 kHz). These two
pairs of speakers received input from two independent CD players (AIWA Co.
Ltd, Tokyo, Japan), which both played out two P. guttiventris songs,
which were aphasic with respect to each other, as is the case with
simultaneously singing males (Mhatre and
Balakrishnan, 2006). The songs were looped and started at random
points within the loop for each trial. The speakers were covered with black
cloth and placed on their sides, partially buried in the ground to reduce
visibility and mimic the calling behaviour of real male crickets that call
from ground level.
The broadcast SPLs of the speakers at source (10 cm from the speaker) and
at the positions of the females are indicated for each experiment in the
figures, as are the initial release positions and orientations. The positions
of the speakers were selected based on a map of a real chorus of males
observed in the field, and the distances between males reflect observed
intermale distances (Mhatre and
Balakrishnan, 2006). The particular chorus was selected as it
provided a situation in which a female might hear four simultaneously calling
males. The SPLs of the speakers were based on measurements of the calling song
SPLs of real males. Males produce calling song at an average of 75± 4.6
dB SPL (Mhatre and Balakrishnan,
2006). We chose broadcast SPLs from the centre, as well as
approximately one and two standard deviations of this distribution of song
SPLs. The SPLs from the speakers, as measured at the release positions, were
all above behavioural threshold and females could potentially hear all
speakers simultaneously and should experience song pattern masking similar to
field conditions (Mhatre and Balakrishnan,
2006). The broadcast SPLs (root mean square, RMS at the fast
setting) of the four speakers were measured one at a time using a Brüel
& Kjaer microphone (type 4189) and Integrating Sound Level Meter (Observer
2260) with a one-third octave band-pass filter (Brüel & Kjaer Sound
and Vibration Measurements A/S, Naerum, Denmark) centered at 5 kHz at ground
level, with the microphone facing the active speaker at a distance of 10 cm
and at the female release position in each experiment. Each experiment was
carried out in two physically separate outdoor locations with the setup
rotated by 180 deg. to control for directional bias due to non-acoustic
cues.
Animals
Virgin females from a laboratory culture were used during experiments. The
cultures were maintained, and females chosen and prepared for the experiment
as described previously (Mhatre and
Balakrishnan, 2007). Females were tested further only if they
responded to the softest broadcasting single speaker. The single speaker
control was presented from the left for approximately half of the females and
from the right for the remaining half. Females were given a rest of at least
10 min between trials. A set of 40 females was tested with both two and four
speakers active. The order of presentation was varied, and half the females
were presented with four speakers active before two speakers active and
vice versa for the remaining half.
An independent set of 38 females was used to test for the effects of initial orientation. Nineteen females were released with their initial position rotated by 180 deg. and 19 females with their initial position rotated by 30 deg. to the left. Thirty-nine females were used to test for the effect of different release positions and orientations, 20 females from release position 1 (RP1) and 19 females from release position 2 (RP2). Some of the females tested in the orientation experiment were re-tested in the release position experiment. Females were only tested once a day.
Data analysis
Female paths were recorded and digitized
(Mhatre and Balakrishnan,
2007), and a note was made of which speaker each female reached.
The paths were digitized until the background subtraction algorithm could not
discern the female. In some cases, the digitized path ended before the female
reached the speaker; however, this could be observed in the video and was
noted separately. The endings of such paths are indicated by dotted lines in
the figures. The number of females reaching the speakers was compared between
experiments using a chi-squared test using Statistica (1999; Statsoft, Inc.,
Tulsa, OK, USA).
A logistic multiple regression was carried out in R (version 2.5.1; R
Foundation for Statistical Computing, Vienna, Austria) with the following
independent variables; the SPL of each speaker at source, SPL at the release
position of the female, and distance to each speaker from release. Since
individual females were tested in more than one experiment, we used data only
from the experiments front, RP1 and RP2 in order to prevent pseudoreplication
due to repeated testing of individuals. Another reason for the exclusion of
data from the other experiments was because they showed results that were not
greatly different from the experiment with the frontal orientation. Female
arrival or non-arrival at each speaker was the categorical dependent variable.
Since each female contributed four data points to the analysis, a linear
mixed-effects model was used with female identity as a grouping variable in
order to control for pseudoreplication
(Crawley, 2002). The analysis
was first carried out with interaction effects, which were not statistically
significant. The analysis was then carried out without the interaction effects
and the results from this analysis are reported.
To compare path forms we calculated the path vectors
(Batschelet, 1981). We
delineated pauses within the paths of the females and calculated average
position within a pause. Pauses were defined as in an earlier study
(Mhatre and Balakrishnan,
2007) except that the cutoff was raised to 0.2 cm due to the lower
resolution of these videos. The angle of displacement between pauses was
determined, and path vectors were calculated for both the real and simulated
paths. Path vectors were compared between experiments and between a single
experiment and a simulation run using a Mardia two-sample test for bivariate
data followed by a Mardia–Watson–Wheeler test (
2
test statistic for N>17)
(Batschelet, 1981). This
non-parametric test was used as it does not assume a von Mises distribution of
vectors.
Simulations (for details, see Mhatre
and Balakrishnan, 2007) mimicking the real experiments, with the
same number of paths in each run were performed in Matlab (V. 6.5, The
Mathworks, Inc., Natick, MA, USA). Females who reached within 2 cm of a
speaker in the simulation were marked as having reached that speaker. For each
experimental scenario we ran 20 simulation runs and measured the mean number
of females reaching each speaker and not reaching speakers. These numbers were
then compared with the numbers in the experiments with real females using a
chi-squared test. Finally, the numbers of real females reaching and not
reaching speakers were also subjected to a bootstrap analysis (10,000
iterations) (carried out in Matlab 6.5) to estimate the confidence ranges on
the real data, which were then compared with the range of values predicted by
the simulation in 20 runs.
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RESULTS |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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)]. In the present study, when the number of active speakers
was increased to four, females showed reduced orientation towards that
speaker, which was still the loudest at the release position
(Fig. 1A, two vs four
speakers: 2=6.58, d.f.=2, P=0.03). The number of
females reaching the speaker that was loudest at their release position
(23/40) was reduced when compared with the two-speaker situation (31/40) and
females approached other speakers in significant numbers
(Fig. 1A). Therefore, the
presence of additional sources can alter the probability of a female reaching
a given sound source, even when it remains the loudest at her initial
position. The forms of the paths were also different, as judged by their path
vectors, which were more scattered (Fig.
1A,C, insets: 2=6.34, P=0.04).
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2=6.57, d.f.=4, P=0.16), and path forms were also not
significantly different (2=0.06, P=0.97). However,
when females were tilted by 30 deg. towards the softer speaker at release, we
found a small but significant change in comparison with the front orientation
(Fig. 1A vs
Fig. 2B,
2=10.36, d.f.=4, P=0.03) but not the back orientation
(Fig. 2A vs
Fig. 2B,
2=5.44, d.f.=4, P=0.24). When females were initially
oriented towards the left, we expected that a larger number of females would
reach the speaker to the left or in front of them. However, this did not
happen; instead, fewer females reached the speaker that was loudest at their
release position. Path vectors were not significantly different in either
comparison (front vs left, 2=4.15, P=0.12,
back vs left: 2=1.35, P=0.51), suggesting
only a weak overall effect of initial orientation.
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2=14.50, d.f.=4, P<0.01). Path vectors, were
however, not significantly different, possibly due to the large spread of
angles (RP1 vs RP2; 2=1.67, P=0.43). In RP1,
neither the two speakers that were loudest at the release position nor the two
that were equidistant received equal numbers of females
(Fig. 3A). In RP2, the speaker
that was loudest at release received as many females as the closest speaker
(Fig. 3B). The speaker that was
loudest at source did not receive the most females in either experiment. In order to decipher the influences of speaker SPL at source, at release position of the female and speaker distance, data from three experiments [front (Fig. 1A), RP1 and RP2 (Fig. 3A,B)] were combined and subjected to a logistic multiple regression analysis. The only significant predictor of the probability of reaching a speaker was the SPL of that speaker at the release position (SPL at release, t=2.24; P=0.02). The broadcast SPL and the distance of speakers from the release position were not significant predictors of the probability of a female reaching a speaker (SPL at source, t=–0.72; P=0.47; distance, t=–0.45, P=0.65). The first experiment had twice as many females as the experiments with RP1 and RP2, potentially biasing the outcome of the regression analysis. To test for this we removed 20 randomly selected females from the first experiment and re-ran the analysis on this truncated data set. This was repeated five times. In two out of the five analyses, SPL of a speaker at release was not a significant predictor of the probability of a female reaching a particular speaker (t1=1.56, P1=0.12; t2=2.14, P2=0.03; t3=1.58, P3=0.12; t4=2.43, P4=0.02; t5=2.39, P5=0.02).
Another approach to understanding and predicting phonotaxis behaviour that
can be generalized to any number and configuration of active sound sources is
a dynamic simulation model based on the known physiology of the cricket
auditory system. We tested the predictions of a simulation model that we
recently proposed against behaviour observed in the experiments from the
present study (Mhatre and Balakrishnan,
2007). As shown before (Mhatre
and Balakrishnan, 2007), the model was able to correctly predict
female preference in response to two active speakers (simulated vs
real outcomes; Fig. 1C;
2=1.01, d.f.=2, P=0.60). To estimate the confidence
intervals on the frequency of females reaching each speaker, we bootstrapped
the data 10,000 times and compared the range predicted by the simulation with
the bootstrapped range. The resulting frequency ranges overlapped considerably
(Fig. 1D, i). The results of
the simulation and those using real females were also similar in terms of path
forms; path vectors produced by a run of the simulation were similar to those
of real females (Fig. 1C;
2=0.21, P=0.90).
The simulation was then used to predict female behaviour using four active
speakers. It was able to predict female preference from the central release
position in all release orientations (Fig.
1B vs Fig.
1A, front, 2=2.98, d.f.=4, P=0.56;
Fig. 2C vs
Fig. 2A, back,
2=1.65, d.f.=4, P=0.80;
Fig. 2D vs
Fig. 2B, left,
2=3.49, d.f.=4, P=0.48). The frequency ranges
predicted by the simulation and the bootstrapped real data showed considerable
overlap (Fig. 1D and
Fig. 2E,F). The path vectors
produced by a run of the simulation model were also similar to the real path
vectors (Fig. 1B inset
vs Fig 1A inset,
front, 2=0.09, P=0.96;
Fig. 2C inset vs
Fig. 2A inset, back,
2=0.32, P=0.85;
Fig. 2D inset vs
Fig. 2B inset, left,
2=3.35, P=0.19).
The simulation was able to predict female orientation in the RP1 experiment
(Fig. 3C vs
Fig. 3A,
2=6.26, d.f.=4, P=0.18) with high overlap between the
frequency ranges predicted by the simulation and bootstrapped real data
(Fig. 3E). Path vectors were
also similar (Fig. 3C inset
vs Fig. 3A inset,
2=2.83, P=0.24). The simulation was, however, not
able to entirely capture female orientation behaviour in RP2
(Fig. 3D vs
Fig. 3B,
2=13.35, d.f.=4, P<0.01). In this case, real
females approached the nearest and loudest speakers (C and D) in equal numbers
whereas most females in the simulation approached the loudest speaker (D). The
frequency ranges produced by the simulation did show overlap with the
bootstrapped data, albeit to a lesser extent
(Fig. 3F). The path vectors,
however, were not significantly different between a run of the simulation and
the real paths (Fig. 3D inset
vs Fig. 3B inset,
2=0.14, P=0.93).
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DISCUSSION |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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). It was, nonetheless, able to recapture
acoustic orientation behaviour under multi-source conditions in the field when
the empirically measured characteristics of outdoor sound transmission were
incorporated in the model. The discrepancy between the simulated and real
female preferences in one of the experiments (RP2) might be explained by
visually mediated attraction towards the less loud but closer speaker, which
would be visible under ambient light conditions in the field. This speculation
is supported by the observation in the two-speaker experiment that a few
females were attracted to a silent speaker
(Mhatre and Balakrishnan,
2007). Female crickets modulate their preferences for song based
on visual input, sometimes becoming more selective under high light conditions
(Stout et al., 1987;
Weber et al., 1987). Female
cricket phonotaxis is also known to be modulated by their perception of
predation risk as judged by the lack of cover under which to hide
(Hedrick and Dill, 1993). In
the present study, females were tested in areas with almost no cover and might
have approached closer speakers in an attempt to reduce predation risk.
Our experiments with real females show that the ability to track and locate
the loudest speaker is reduced with an increasing number of sources, a result
similar to that obtained in a study with painted reed frogs
(Bishop et al., 1995). We found
that this ability also depends on the starting position although,
interestingly, only negligibly on initial orientation. There was also no
consistent female orientation towards the loudest source in a chorus. Both of
these observations were also supported by the results of the simulation.
Female orientation changed based on SPL at initial position and on distance of
the initial position relative to the sound sources, and was not easy to
dissect using conventional statistical methods. Our results suggest that
physiology-based simulation models may offer a more powerful alternative to
conventional statistical methods for predicting orientation and localization
behaviour in complex, real-world environments.
The experiments and the simulations both predict that female crickets in
dense, multi-male choruses are not always likely to locate the loudest male.
If they do choose the loudest males as mates, which has been implied from the
higher capture rate observed in pitfall trap experiments
(Forrest and Green, 1991;
Farris et al., 1997), results
from the present study indicate that this cannot result from the sound
localization mechanism alone but must involve strategies for sampling multiple
males. The simulation model is a useful tool for deciphering the components of
female choice that are a consequence of the sound localization mechanism
alone. Similarly, it can be used to isolate the acoustic component of
multimodal orientation behaviour.
Further elaboration of the model is required to capture the full complexity of cricket phonotaxis behaviour. Incorporation of multimodal information and female preferences for different song features could improve its predictive power. Nonetheless, we believe that this simulation model represents a significant step towards predicting orientation and localization in complex acoustic environments.
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Acknowledgments |
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References |
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