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First published online December 14, 2007
Journal of Experimental Biology 211, 9-14 (2008)
Published by The Company of Biologists 2008
doi: 10.1242/jeb.012823
Time-variant spectral peak and notch detection in echolocation-call sequences in bats
Department of Biologie II, Universität München, Großhadernerstr. 2 82152 Planegg-Martinsried, Germany
* Author for correspondence (e-mail: genzel{at}zi.biologie.uni-muenchen.de)
Accepted 17 October 2007
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Summary |
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 TOP Summary INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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Here, we measured the detection thresholds for temporal variations in the
spectral content of synthesized echolocation calls in the echolocating bat,
Megaderma lyra. In a two-alternative, forced-choice procedure, bats
were trained to discriminate synthesized echolocation-call sequences with
time-variant spectral peaks or notches from echolocation-call sequences with
invariant peaks or notches. Detection thresholds of the spectral modulations
were measured by varying the modulation depth of the time-variant
echolocation-call sequences for modulation rates ranging from 2 to 16 Hz. Both
for spectral peaks and notches, modulation-detection thresholds were at a
modulation depth of 
11% of the centre frequency. Interestingly,
thresholds were relatively independent of modulation rate. Acknowledging
reservations about direct comparisons of active-acoustic and passive-acoustic
auditory processing, the effectual sensitivity and modulation-rate
independency of the obtained results indicate that the bats are well capable
of tracking changes in the spectral composition of echoes reflected by complex
objects from different angles.
Key words: echolocation, object discrimination, frequency modulation, bat, Megaderma lyra
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INTRODUCTION |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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;
Schmidt, 1988).
In general, the intensity, temporal structure and spectral composition of
an echo provide information about the object's size, shape and structure
(Schmidt, 1988;
Grunwald et al., 2004;
Simon et al., 2006). When
moving around an object, the echolocating bat will perceive amplitude and
frequency modulations in the echoes' spectral envelopes that depend on the
angle from which the object is ensonified. Stich and Winter
(Stich and Winter, 2006)
described this echo-acoustic perceptual experience as resembling a visual
experience caused by so-called physical or metallic colours: due to spectral
interferences, these colours change their appearance with the angle of
illumination and observation.
von Helversen (von Helversen,
2004) showed that the bat Glossophaga soricina was able
to discriminate two hollow forms, a hemisphere and a paraboloid with the same
diameter and depth. Each object generated a spectral interference pattern with
frequency peaks and notches that varied systematically with ensonification
angle. This variation was highly specific to the object. It is conceivable
that the bats solved this task by evaluating the changes in the peak and notch
patterns in correlation with their movement around the objects
(Moss and Surlykke, 2001;
von Helversen and von Helversen,
2003).
Echo-acoustic analysis of complex surfaces is a challenging task for
gleaning bats. These bats pick up prey from the ground. A well-studied species
of gleaning bats is Megaderma lyra Geoffroy 1810, the great false
vampire bat. For prey detection, M. lyra relies on prey-generated
rustling noises (Neuweiler,
1990). To facilitate separation of prey objects from background,
M. lyra employs short, multi-harmonic, downward modulated frequency
sweeps as their echolocation calls
(Schmidt et al., 2000).
Complex objects of interest are typically ensonified from different aspects,
and the aspect-dependent interference patterns of the perceived echoes provide
important information about the three-dimensional shape of the ensonified
object. In terms of auditory processing, this behaviour requires tracking
changes of spectral interference patterns over time. This psychoacoustical
study was designed to investigate the auditory sensitivity of M. lyra
to changes in the position of spectral peaks and notches across a sequence of
synthesized echolocation calls. These call sequences were generated to mimic
the echoes as they would return from a three-dimensional object whose
reflection characteristics change with ensonification angle. Thereby, we want
to analyze the importance of time-variant spectral features for echo-acoustic
object discrimination. Unlike previous studies, the changes of the peak and
notch centre frequencies were time variant, varying sinusoidally with a
certain modulation frequency. The bats' detection threshold for variations in
the spectral envelope was measured by presenting a synthesized
echolocation-call sequence filtered with time-variant filters.
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MATERIALS AND METHODS |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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Experimental setup
All experiments were performed in an echo attenuated chamber (3.5
mx2.2 mx2.2 m) with a wall foam coating. The setup consisted of a
starting perch on one side of the room, ensuring a precise positioning of the
bat, and two ultrasonic speakers, one in the left and one in the right hemi
field. The two ultrasonic speakers were placed at the same distance and angle
in each hemi field to the bat's starting position: the distance from the
speakers to the bat's head was 1.2 m; the angle between the speakers and the
bat's head was 90°. A feeding dish was placed below each speaker.
Stimuli
The source signal was a sequence of 17 synthesized echolocation calls. Each
call was a multi-harmonic frequency sweep with a duration of 1.5 ms. The
fundamental frequency swept from 23 to 19 kHz. Five harmonics were generated
with attenuations of 30, 10, 5, 0 and 5 dB for harmonics one to five,
respectively. The call was windowed with a raised-cosine window with a 0.2 ms
rise time, 1.1 ms steady state and 0.2 ms decay time.
For the time-invariant echolocation-call sequence, a band-pass filter with a reference centre frequency (CF) of 60 kHz and a bandwidth of ±10% of the CF was applied to all 17 calls in the sequence. For the generation of the time-variant echolocation-call sequences, the CF of the band-pass (peak) filter was sinusoidally modulated around the reference CF along a log-frequency axis. The filter was designed as a finite-impulse-response, band-pass filter of order 62. The detection threshold for variations of spectral peaks was measured by varying the modulation depth (in % of the CF) of the time-variant filtered echolocation-call sequence. To measure the bats' sensitivity to the CF modulation, we presented modulation depths of 100, 52, 40, 30, 24, 18, 14, 11 and 9% of the CF. A modulation depth of 100% defined a frequency range of ± one octave around the CF and produced filter CFs between 30 and 120 kHz. The modulation rate of the CF modulation was 2, 4, 8 or 16 Hz. One echolocation-call sequence always contained two modulation periods. In consequence, the overall duration of the echolocation-call sequence and the temporal separation between the echolocation calls in the sequence decreased with increasing modulation rate. For a modulation rate of 2 Hz, the echolocation-call sequence was 1 s long and the temporal separation between the echolocation calls was about 61 ms; for a modulation rate of 16 Hz, the echolocation-call sequence was 125 ms long and the temporal separation between the echolocation calls was about 6 ms. Spectrograms of an unfiltered call and time-variant and time-invariant echolocation-call sequences are shown in Fig. 1A,B. These echolocation-call sequences simulate a bat moving twice around an abstract virtual acoustic object and ensonifying it from eight different angles. Different flight speeds are represented by modulation rates between 2 and 16 Hz. While this range of modulation rates is low compared with many auditory studies on the perception and encoding of time-variant signals, the rates are certainly high enough to include the speed of spectro-temporal modulations encountered by a bat when it moves around an object ensonifying it from different angles.
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To preclude the bats' use of overall presentation level or
absolute-frequency cues (Krumbholz and
Schmidt, 1999), the presentation level was roved by ±6 dB
and the reference CF was roved by ±10% over trials. Moreover, the phase
of the sinusoidal frequency modulation was roved over trials.
The echolocation-call sequences were computer generated (Matlab 5.3, Mathworks, Natick, MA, USA) and digital–analog converted (RX6, sampling rate 260 kHz; Tucker Davis Technologies, Gainesville, FL, USA). The echolocation-call sequences were amplified (Rotel RB 976 MK II; Worthing, UK) and presented over the ultrasonic loudspeakers (Matsushita EAS 10 TH 800D; Osaka, Japan) at a level of 65 dB SPL (preceding the roving level). The frequency response of all setup components, including speakers, was flat within ±5 dB between 5 and 100 kHz. The echolocation-call sequences were heterodyned by two DSPs (RP2, sampling rate 200 kHz; Tucker Davis Technologies), allowing the experimenter to follow the presentation acoustically via headphones.
Procedure
In a two-alternative, forced-choice experiment, psychometric functions were
obtained for variations in the spectral content of synthesized echolocation
calls. The time-variant filtered echolocation-call sequence was played back by
one speaker and the time-invariant filtered echolocation-call sequence by the
other. While hanging on the perch, the bat perceived the echolocation-call
sequences alternately from each speaker. There was a fixed inter-stimulus
interval of 500 ms between successive echolocation-call sequence
presentations. The echolocation-call sequence presentations stopped as soon as
the bat left the perch. The bat had to therefore make its decision at the
starting position. On the other side of the room, opposite to the perch, the
experimenter was seated, controlling the procedure and the data storage
via touch screen (WES TS, ELT121C-7SWA-1; Nidderau-Heldenbergen,
Germany). The experimental program was written in Matlab 5.3.
The bats were trained to fly to the speaker from where they perceived the time-variant filtered echolocation-call sequence. For the initial training, the modulation depth was set to 40% of the CF. As a control, one bat was trained to fly to the time-invariant filtered echolocation-call sequence. Whether the time-variant echolocation-call sequence was presented at the left or right position was determined by a pseudo-random sequence, with the same echolocation-call sequence never occurring more than three times in a row at the same position. As soon as the bats were able to solve this task with a stable performance of >85% correct choices over several days, the modulation depth of the time-variant filtered echolocation-call sequence was decreased and increased. 30 trials for each modulation depth were collected. The performance was calculated as decisions for the side of the time-variant echolocation-call sequence in percent correct as a function of the modulation depth. The significance level was set to 75% correct choices. After evaluating the threshold modulation depth for a specific modulation rate, the bats were trained for the next modulation rate and the corresponding threshold was measured.
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Stimuli
The source signals were the same synthetic call sequences as in Experiment
1. The filter was designed as a finite-impulse-response, band-stop (notch)
filter of order 64, a reference CF of 60 kHz and a bandwidth of ±10% of
the CF. For the time-invariant echolocation-call sequence, this filter was
applied to all 17 calls in the echolocation-call sequence.
For the generation of the time-variant echolocation-call sequences, the CF of the band-stop filter was sinusoidally modulated around the reference CF along a log-frequency axis. As in Experiment 1, the detection threshold for variations of spectral notches was measured by varying the modulation depth (in % of the CF) of the time-variant filtered echolocation-call sequence. The stimuli are illustrated in Fig. 1C,D.
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RESULTS |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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At a modulation rate of 2 Hz, the four bats were able to detect a frequency modulation depth of 10.9% of the CF, on average (Fig. 2A). At a modulation rate of 4 Hz, the four bats could detect a modulation depth of 10.9% of the CF, on average (Fig. 2B). At a modulation rate of 8 and 16 Hz, the three remaining bats could detect a modulation depth of 11.2 and 11% of the CF, respectively (Fig. 2C,D). For a CF of 60 kHz, 11% of the CF corresponds to a frequency bandwidth of 13 kHz.
Surprisingly, all animals readily transferred the discrimination task from one modulation rate to the next, although not only the modulation rate but also the overall echolocation-call sequence duration changed.
The slight decrease of the bats' performance when the modulation depth was increased from 40% of the CF to 100% can be attributed to the bats being trained on a modulation depth of 40%, and they seemed slightly irritated by the high modulation depths, allowing the assumption that these signals may have sounded different from the initially trained condition (40%).
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In general, we were able to observe that the spectral peaks have to vary by about 11% of the CF to be discriminated from the time-invariant peaks. Furthermore, this threshold seems to be independent of the modulation rate in the tested range.
Experiment 2: time-variant notch detection
Psychometric functions for the detection of a time-variant spectral notch
are shown in Fig. 4 in the same
format as for Experiment 1. Again, the threshold was calculated as a mean
value for three bats. For a modulation rate of 2 Hz, the threshold was 11.3%
of the CF. For modulation rates of 4, 8 and 16 Hz, the thresholds were 11.4,
10.9 and 11.8% of the CF, respectively. The general performance was slightly
worse, but all in all did not differ from that of the first experiment.
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DISCUSSION |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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Threshold value
The detection threshold for changes in the spectral domain lies at 11%
of the CF, independent of whether the CF of a peak or notch filter was varied.
This threshold is comparable to frequency modulations (7–21%) occurring
in the active-acoustic object-discrimination experiment of Simon et al.
(Simon et al., 2006) based on
the assumption that the bats exploited spectral-notch changes in that
experiment. In an earlier two-front, phantom-target study, Schmidt obtained
similar threshold values for M. lyra of 6–13% for
spectral-notch centre frequency changes
(Schmidt, 1992). Note,
however, that again, these thresholds were obtained in an active-acoustic
paradigm where the bats evaluated the spectral content of echoes of their own
calls. The frequency differences, on the other hand, were static within a
trial. The current data obtained in a passive-acoustic paradigm with
time-variant filtering corroborate these findings.
M. lyra is a gleaning bat; it rarely hunts actively for flying
insects and therefore does not have to detect wing flutter. Nevertheless, the
current thresholds, obtained in a passive-acoustic paradigm, are comparable to
values obtained for other bat species in active-acoustic paradigms
(Mogdans and Schnitzler, 1990;
Bartsch and Schmidt, 1993;
Esser and Kiefer, 1996).
Typically, M. lyra catches its prey from the ground and first detects
it by listening to prey-generated rustling noises. By first relying on passive
rustling noises and then moving in to evaluate and catch possible prey, it
might not need to analyse fine modulation differences.
Lyzenga and Carlyon measured in humans the detection of just noticeable
differences for a sinusoidal modulation of the CF of a synthetic formant with
a fixed fundamental (Lyzenga and Carlyon,
1999). The thresholds they obtained were larger, by a factor of
two, than thresholds for the discrimination of (static) formant frequencies
(Lyzenga and Horst, 1997). This
seems to hold for starlings as well, which also show 2–3 times larger
threshold depths for low modulation frequencies than for just noticeable
frequency differences between pure tones
(Langemann, 1991). This
difference might explain our slightly increased thresholds in comparison with
other studies, where frequency differences were static
(Schmidt, 1992;
Simon et al., 2006).
Modulation-rate independency
The current detection thresholds for spectral changes in the envelope were
apparently independent of modulation rate. Temporal processing therefore does
not seem to be a critical factor for the discrimination task. By contrast, the
current data are consistent with an analysis of place cues along a tonotopic
frequency axis. Moore and Sek (Moore and
Sek, 1995; Moore and Sek,
1996) and Sek and Moore (Sek
and Moore, 1995; Sek and
Moore, 2000) claim that the detection threshold for frequency
modulations of low-frequency pure tones for humans is modulation-rate
dependent, as the low-frequency tones are encoded by phase-locked, temporal
cues. In mammals, phase locking is limited to frequencies below 5 kHz
(Rose et al., 1968;
Palmer and Russell, 1986;
Oertel, 1999). Higher
frequencies are encoded exclusively by place cues. In humans, spectral place
cues provide worse frequency accuracy than phase-locked, temporal cues
(Moore and Sek, 1995).
In the bat, each of the presented ultrasonic calls can only be encoded by auditory place cues. Thus, no phase-locked, temporal information concerning the current frequency composition of the call is available. Consequently, the frequency acuity is limited. The phase-locking, low-pass filter does not impair the peripheral auditory representation of the modulation rate as all tested modulation rates were considerably lower than the phase-locking filter cut-off frequency, meaning that the fluctuations of the spectral envelope can easily be encoded through phase-locking. In summary, the current data are consistent with the hypothesis that the spectral peaks and notches are encoded via place cues in the peripheral auditory system and that the bats' central auditory system is fast enough to follow the changes of these place cues over time for the range of modulation frequencies tested.
Several electrophysiological studies on temporal encoding in the mammalian
auditory cortex have revealed low-pass characteristics of synchronous cortical
discharges with a cut-off frequency around 20 Hz
(Schulze and Langner, 1997;
Lu et al., 2001;
Liang et al., 2002). In an
electrophysiological study with rising and falling FM stimuli, responses of
neurons in the primary auditory cortex of the gerbil were recorded
(Ohl et al., 2000). Across the
range of tested modulation frequencies (1–24 Hz), the neurons' responses
did not vary with modulation rates. This again fits with the
modulation-rate-independent thresholds we obtained in this study for
modulation rates lying in a similar range.
In a psychophysical study in the bat Tadarida brasiliensis,
Bartsch and Schmidt tested perceptual sensitivity to sinusoidal frequency
modulation at much higher rates (10–2000 Hz, CF=40 kHz)
(Bartsch and Schmidt, 1993).
They found that threshold modulation depths deteriorated with increasing
modulation rate. As we only tested modulation rates between 2 and 16 Hz, we
are not able to comment on whether the bats may have showed increased
thresholds for even higher modulation rates. Note that our stimulus trains
were intended to simulate a stationary complex object ensonified by a bat
surrounding the object twice and ensonifying it from eight different angles.
In this context, modulation rates above 16 Hz would have represented a highly
unnatural situation, 16 Hz already representing an extreme.
Comparison of peak- and notch thresholds
In the current study, the bats were equally sensitive for time-variant
peaks and notches. In the following, we discuss this finding in regard to the
question of whether the bat M. lyra extracts pitch information from
its harmonically structured echolocation calls or whether echo analysis is
based on the auditory processing of spectral place profiles.
Sedlmeier was able to show that M. lyra categorizes ultrasonic
pure tones and complex harmonic structures with attenuated or missing
fundamentals almost identically
(Sedlmeier, 1992). This was
interpreted as that the bat perceives the `missing fundamental', enabling it
to integrate different acoustic qualities to a complex perception. Sedlmeier
suggested that the bats perceive a pitch corresponding to the fundamental
frequency of a sound and categorize sounds with different spectral features
according to their pitches (Sedlmeier,
1992). Preisler and Schmidt further investigated this topic, and
examined whether M. lyra evaluates complex harmonic structures
according to their pitch or on the basis of overall spectral similarity
(Preisler and Schmidt, 1998).
They observed that the tested bats differed in which of the strategies they
applied to solve the task. Krumbholz and Schmidt showed that M. lyra
spontaneously classified test signals according to their broadband spectral
similarity, using trained signals as spectral templates, not pitch cues
(Krumbholz and Schmidt,
1999).
As the slope of the filters used in the current study was rather steep
(filter-order 62), an echolocation call filtered with a band-pass (peak)
filter centred at 60 kHz will cause a pitch percept corresponding to 60 kHz.
Due to the time-variant filtering, the bats would hear a time-variant pitch.
When the notch filters are applied, on the other hand, the bats always hear
all harmonics except the one filtered out by the notch filter. Thus, the pitch
would always correspond to the calls' fundamental frequency of 21 kHz. As
pitch extraction is rather insensitive to amplitude modulations of higher
harmonics, this percept would not be strongly affected by the time-variant
filtering. In summary, if the bats had applied a pitch-based analysis, one
would expect a better performance with the band-pass (peak) filters than with
the band-stop (notch) filters. The finding that this is not the case
corroborates the conclusions of Krumbholz and Schmidt
(Krumbholz and Schmidt, 1999)
that in most cases the bats recruit a spectral profile rather than a pitch
analysis for echo imaging.
In summary, the current data show that the bat M. lyra can discriminate time-variant from time-invariant echolocation-call sequences with good accuracy. In the range of modulation rates tested (2–16 Hz), the discrimination performance was constant. The fact that sensitivity to time-variant spectral peaks and notches was similar argues in favour of a spectral profile analysis rather than a pitch-based analysis of the harmonic echolocation-call sequences. With the reservation of comparing passive-acoustical and active-acoustical auditory processing, the current data indicate that the bats' central auditory system is fast enough to track the changes in the spectral composition of returning echoes when the bat ensonifies an object while flying around it.
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Acknowledgments |
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