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First published online December 14, 2007
Journal of Experimental Biology 211, 106-113 (2008)
Published by The Company of Biologists 2008
doi: 10.1242/jeb.009688
Jamming avoidance response of big brown bats in target detection
1 Department of Psychology, Brown University, Providence, RI 02912, USA
2 Department of Neuroscience, Brown University, Providence, RI 02912, USA
* Author for correspondence (e-mail: Mary_Bates{at}brown.edu)
Accepted 30 October 2007
 |
Summary |
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 TOP Summary INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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Key words: echolocating bat, biosonar, jamming avoidance, echo processing
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INTRODUCTION |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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). In
the presence of so many echolocating conspecifics, they face the potential
problem of acoustical interference from neighbors utilizing the same range of
frequencies in their echolocation signals. Yet videos of swarming bats
indicate that they have little problem orienting and capturing prey in the
presence of many other echolocating bats
(Simmons et al., 2001).
Animals that emit their own orienting signals could adapt by changing the
frequencies of their signals in the presence of interference in order to avoid
masking or `jamming'. The best known example of this is the behavioral jamming
avoidance response (JAR) in weakly electric fish such as Eigenmannia
that use another active sensory system, electrolocation
(Bullock et al., 1972;
Heiligenberg, 1991;
Watanabe and Takeda, 1963).
These single-frequency wave-type electric fish alter the frequency of their
emitted electric organ discharge (EOD) when it overlaps with the EODs of
nearby conspecific fish.
The effects of acoustical interference from conspecifics on bats utilizing
broadband frequency-modulated (FM) biosonar are less well understood. In an
early test of jamming in echolocating bats, high intensity white noise only
moderately affected the performance of long-eared bats (Plecotus) in
obstacle-avoidance tests (Griffin et al.,
1963). The bats continued to avoid the wires but altered the
approach direction of their flights to create differences in reception of
echoes compared to the noise at the two ears. However, these experiments did
not address whether the bats shifted their own calls to different frequencies
in the presence of the noise in a manner analogous to the electric fish JAR.
More recent research on avoidance of mutual interference by echolocating bats
has consisted mainly of field observations, often of groups of bats flying
together. Some investigators have reported greater differences in emitted
frequency between two bats of the same species flying in close proximity than
between two randomly selected single bats of the same species
(Habersetzer, 1981;
Miller and Degn, 1981;
Surlykke and Moss, 2000;
Ratcliffe et al., 2004;
Ulanovsky et al., 2004). Bats
flying in groups have been observed to change the duration of their pulses or
their inter-pulse intervals (Obrist,
1995; Surlykke and Moss,
2000) as well as the frequencies of their broadcasts.
Interestingly, the observed shifts in emitted frequency sometimes only appear
to be upward (Gillam et al.,
2007; Ibáñez et
al., 2004). In a playback experiment in the field
(Gillam et al., 2007), bats
made only these upward frequency shifts even when their initial call frequency
was below that of the playback sounds. Other observations from the field
suggest that bats may actively avoid hunting in areas that contain high levels
of ultrasonic background noise (e.g. near turbulent water in streams) because
this noise interferes with their echolocation
(von Frenckell and Barclay,
1987). Moreover, there are other factors in the acoustic
environment that influence bats to change their calls, such as foraging
environment (Aldridge and Rautenbach,
1987; Simmons et al.,
1979; Simmons and Stein,
1980) and changes in the composition of the colony
(Hiryu et al., 2006). Taken
together, the existing observations of changes in broadcast frequency by bats
flying in groups or responding to playback in the field do not provide
conclusive evidence for a JAR in bats. In studies such as these, one cannot
identify individual bats among several bats flying together to observe how
they might alter their emissions in differing conditions. It is also difficult
to determine the extent to which changes in emitted frequency might be due to
the Doppler shift in frequencies when recordings of flying bats are made from
stationary microphones located on the ground. Finally, under these conditions,
unlike those of a detection task in a laboratory, one cannot be certain of
what the bats are attending to.
Our study was conducted to determine whether a frequency-specific JAR
occurs in the big brown bat Eptesicus fuscus. This species was chosen
because, although they emit harmonically structured FM sounds that cover a
wide band of ultrasonic frequencies from 20 to 100 kHz, there is a narrow
range of frequencies from about 22 to 28 kHz within this broader band that is
emphasized for long-range target detection. For insect-sized targets, the
operating range of echolocation in this species is at least 5 m
(Kick, 1982). When searching
for insects in open spaces at long range, big brown bats greatly lengthen the
shallow-sweeping part of the first-harmonic from 28 down to 22 kHz, which
boosts the energy in this band (Simmons et
al., 1979; Surlykke and Moss,
2000). Fig. 1
(Simmons et al., 1974) shows
the FM sweeps produced by a big brown bat in conditions of varying wideband
noise during a target detection task. In response to the noise, the bat
lengthens its FM sweeps. The arrow indicates the frequency of the
first-harmonic as it terminates at a nearly constant frequency, the component
of the sound used for long-range detection. By changing the duration to extend
the terminal portion of the sweep disproportionately, the bat emphasizes
energy in the 22–28 kHz band. Similar changes occur for the bat's sounds
in the field as operating range lengthens
(Surlykke and Moss, 2000). The
bat's emphasis on the low frequencies in the sound is important: atmospheric
absorption of sound is least at these low frequencies, so they can penetrate
farther through the air and still return as echoes that would be audible to
the bat (Lawrence and Simmons,
1982).
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).
In the present experiment, frequency analysis of the tail-end of the
first-harmonic FM sweeps in sounds emitted during jamming revealed that all
bats shifted the frequencies of their own signals up or down to move the
ending frequencies away from the CF jamming frequency, but only when the
jamming was within 2–3 kHz of their baseline frequency. Outside this
narrow window of frequencies, the bats did not alter the frequency of their
echolocation calls. |
MATERIALS AND METHODS |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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).] The bats were housed in individual cages in a temperature
and humidity controlled room on a 12:12 reverse light:dark cycle. They were
given vitamin-enriched (Poly-Vi-Sol) water ad libitum and fed
mealworms (Tenebrio molitor larvae) daily. All subjects weighed
between 14 and 15 g.
Procedure
Fig. 2 shows the behavioral
set-up for the experiment and the arrangement for the CF jamming sound
delivery system. Each bat was placed on an elevated Y-shaped platform and
trained on a two-alternative forced choice task to detect a target (plastic
cylinder, 3 cm high, 2.5 cm in diameter) located on the bat's right or left
side. The bat was trained to sit in the middle of the base of the platform,
direct its sonar signals to detect the target (located approximately 30 cm
away on either side), and then walk towards the target on the corresponding
arm of the Y-platform. Correct responses were rewarded with a piece of a
mealworm offered in plastic forceps, while incorrect responses were followed
by a broadband high frequency sound that signaled that the bat had made an
error. After each trial, the bat was picked up and returned to the base of the
platform, which it crawled up to from the trainer's hand. Trials were run in
the dark using a double-blind procedure. The trainer handling the bat was
unaware of the location of the target and a second experimenter moved the
target and recorded the responses of the bats. Target location on the left or
right was alternated according to a pseudorandom Gellerman sequence
(Gellerman, 1933). Bats were
trained to perform the detection task, in the absence of any interference, for
1 week with 50 trials per day. At the end of this period, all bats were above
90% correct. For testing, 20 trials were run for each jamming frequency (12
sessions) – 10 trials with no jamming sound, followed by 10 trials with
the jamming sound turned on. In addition, 20 trials were conducted as baseline
recordings for each bat in a separate session before testing trials were
initiated. The bats were well trained and motivated, and a typical trial
lasted less than 5 s.
The jamming stimulus was a continuous CF tone that was turned on and
remained on for all 10 jamming trials. Presenting tone-bursts instead of a
continuous tone introduces spectral `splatter' at the onset and offset of each
burst, and this widens the spectrum enough that it might disrupt the sharpness
of the jamming frequency to the bat. Without knowing how specific any
potential jamming effect might be to each frequency, it is better to keep the
interfering stimulus restricted to one frequency at a time. For each session a
different fixed frequency in the frequency range from 18 to 32 kHz was used as
the CF jamming stimulus. Each bat completed one session (day) of testing for
each jamming condition with the CF jamming stimulus at 18, 20, 22, 23, 24, 25,
26, 27, 28, 29, 30 and 32 kHz. These sessions were presented in a pseudorandom
order on separate days. The CF jamming sounds were generated by a Model 27A
Audio Generator (Leader, Inc., Yokohama, Japan), and delivered from an
electrostatic loudspeaker Model EST-2 (LTV, Corp., Los Angeles, CA, USA) after
being amplified by a Model 7500 power amplifier (Krohn-Hite, Inc., Avon, MA).
As shown in Fig. 2, the
loudspeaker was located 1.5 m from the bat and was oriented to produce a
uniform sound field around the bat's location on the Y-shaped platform. The
frequency of the jamming sound was adjusted by the recorder using a Model
LDC-831 Frequency Counter (Leader, Inc., Japan).
Fig. 3 shows the frequencies
and sound pressures of the CF jamming stimuli in relation to the hearing
sensitivity (audiogram) of the big brown bat
(Dalland, 1965;
Koay et al., 1997). Sound
pressures were measured at the center of the Y-platform, at the starting point
for the bats. The hearing sensitivity of the bats varies by only a few
decibels around 10 dB SPL at frequencies from 18 to 32 kHz, and the jamming
sounds were adjusted in amplitude to be at a fixed sensation level of 65 dB
for all these frequencies. This level is approximately that of the echoes that
the bat was receiving from the experimental target. The bats' own emissions
were much more intense (100–110 dB SPL) and were clearly discernable
from the jamming stimulus on waveforms and spectrograms of the trials.
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Data analysis
For each trial in the experiment, the recorded data were windowed to a 4
sec segment that contained all the echolocation emissions of the bat during
the detection task on a given trial. Each was then transferred from the Sony
recorder as a digital file in a PC-type Pentium-III computer (Gateway, Inc.)
using programs that are part of the Sony recorder system (Sony PC-Scan
Real-Time software package). The video of each trial was used to select the
period of time when the bat was scanning the two arms of the platform. All
sounds emitted during this time (1–3 s) were exported as stereo `.wav'
files (Sony PC-Scan Streamer software package) for analysis using Adobe
Audition v. 1.0 (Adobe Systems, Inc.). Only sounds emitted by the bat on
correct trials were analyzed to determine their tail-end frequency and
duration (
90% of trials; see Fig.
4). The files for each condition (CF frequency, jamming off or on)
were opened in Adobe Audition 1.0, and successive sounds were displayed as
spectrograms. The cursor was then expanded to encompass each sound in
succession to determine its low-end sweep frequency and duration. For
frequency, the Adobe Audition `Analyze Frequency' function was opened, and a
fast Fourier transform (FFT) was run with a 1024 sample size and Blackman
envelope windowing. To determine the low frequency in the sweep, the cursor
was moved to a point half-way from the peak of the first-harmonic energy
(typically 35 kHz) on the low-frequency skirt and the frequency value saved as
a text file. A separate text file was prepared for each CF jamming condition.
These frequency values serve as estimates for the nearly CF tail-end of the
first-harmonic FM sweep. The mean and 99% confidence intervals of the tail-end
frequency values for all sounds in a condition were determined for each bat
for each jamming frequency with the CF jamming tone on versus off.
The duration of each sound was measured from the spectrogram display using the
cursor because its color-coded levels made the starting and ending points
unambiguous.
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In Table 1, the number of echolocation emissions analyzed for all bats in each condition is listed. All sounds within the 1–3 s time window in which the bat was producing emissions and walking down the arm of the platform were analyzed. Because the bats differed in the length of time they spent on the platform (even between trials within a single session), we could not compare the number of sounds they emitted in different conditions. There appear to also be individual differences between the three bats in their number of emissions, but these differences were not associated with differences in target detection performance.
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RESULTS |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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For each bat, the JAR is restricted to a narrow frequency region that extends about 2–3 kHz above and below each bat's baseline frequency. Note that the JAR is bidirectional – with an increase in emitted frequency if the jamming sound is below the baseline frequency, and a decrease in emitted frequency if the jamming sound is above the baseline frequency. The bats shifted their own emitted frequencies upward until the stimulus tone corresponded to their own baseline frequency. When this frequency was reached, the bats shifted their echolocation frequencies downward, ensuring that the tail-end sweep frequency would diverge from the CF tone during target detection trials. Although the frequency at which this change occurred differed among the bats, they all demonstrated the same pattern of an upward frequency shift followed by a downward shift when the jamming sound passed each bat's baseline frequency.
Because the sonar sounds of big brown bats are frequency modulated, the terminal frequency in the first-harmonic sweeps can be adjusted either by raising the frequencies themselves, or they might be adjusted by altering the duration of the sounds. If the sounds are shortened in duration, the sweep as a whole could be truncated at a slightly higher frequency, whereas if the sounds are lengthened in duration, the sweep could finish at a lower frequency. To determine whether frequency shifts occurred directly or as a secondary effect of changes in duration, the durations of each bat's echolocation emissions were measured across the twelve jamming frequencies. Fig. 8 shows the mean durations for each bat. Although the three bats used sounds of different durations, just as they used sounds with different baseline frequencies, they used sounds with the same durations across the different jamming frequencies. Thus the shifts in frequency observed when the CF jamming frequency approached each bat's baseline frequency (the JAR; Fig. 7) were not caused by a shortening or lengthening of the echolocation emissions. They are a consequence of the bat changing the frequencies of the tail-end of its sweeps in response to the jamming.
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DISCUSSION |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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Our experiment demonstrates the occurrence of JAR in big brown bats by
embedding the jamming procedure within a psychophysical target detection task.
Other studies rely on field observations of freely moving bats; however, data
gathered in this manner may be difficult to analyze due to Doppler effects and
the difficulty of identifying individual subjects within a group. In field
observations in which two Tadarida teniotis were flying together, the
bat emitting the higher frequency call would shift its frequency upward by
more than 1 kHz, whereas the bat emitting at lower frequency shifted its call
downward by the same amount (Ulanovsky et
al., 2004). These symmetric shifts in frequency were apparent in
pairs of bats for several seconds of recording. In this same study, bats also
demonstrated a dynamic JAR in which high-frequency-call bats shifted upwards
when approached by a lower-frequency-call bat, whose frequency did not change.
Unlike the symmetric frequency shifts, these shifts were only brief frequency
fluctuations, much shorter in duration. In a field experiment that attempted
to jam the echolocation of the bat Tadarida brasilensis
(Gillam et al., 2007)
recordings of echolocation calls at six different frequencies were broadcast
to groups of foraging bats. The frequencies that the bats emitted, presumably,
but not definitely, in response to the playbacks, fell into a bimodal
distribution, with a notch in the distribution at the callback frequency. When
these emissions were compared to those produced in the absence of any
playback, it appeared that the bats shifted their frequencies upwards in the
presence of lower frequency playback calls. In a second experiment, the
frequency of the playback stimulus was abruptly switched as an echolocating
bat approached. All bats shifted their emitted frequencies up above the
playback, even when they were already above it. By contrast, we found that big
brown bats would either raise or lower their emitted frequency depending on
the frequency of the interfering signal.
Schmidt and Joermann suggest that bats that primarily depend upon CF
signals are more susceptible to jamming because a CF emission lacks the
bandwidth of an FM signal that might distinguish it from the calls of other
bats (Schmidt and Joermann,
1986). However, it has been more challenging to jam the
echolocation of CF bats than to jam that of bats using primarily FM sounds. No
frequency shift for the multiharmonic CF bat Rhinopoma microphyllum
in group flight was reported (Schmidt and
Joermann, 1986). When several Craseonycteris
thonglongyai, which employ a multiharmonic CF signal, were recorded
flying together, they all emitted signals centered closely around 73 kHz with
no evidence of frequency shifting
(Surlykke et al., 1993). In
two studies with bats in the family Hipposideridae, no evidence was
found for a shift in CF frequency during group flight
(Jones et al., 1993) or in
response to playback of calls from conspecifics
(Jones et al., 1994). A study
of the use of echolocation sounds by the mouse-tailed bat Rhinopoma
hardwickei (Habersetzer,
1981) raises questions about the context in which bats employ CF
and FM signals. They were observed to use FM emissions when leaving the roost
in clusters, but bats leaving singly emitted CF sounds. At the hunting
grounds, bats flying in groups produced CF sounds at three different frequency
bands, whereas bats flying alone used only the middle frequency band. This
suggests that the CF component of echolocation calls is treated differently by
the bat, and it either shifts the frequency of this component in the presence
of other bats, or switches to the use of broadband calls. In another study,
Miller and Degn (Miller and Degn,
1981) reported that when flying in groups, Pipistrellus
pipistrellus separated the CF portions of their calls by as much as 14
kHz. Again, this CF component appears to be the portion of the call that is
most actively protected from interference by the bat.
Although the three bats we tested demonstrated the same response pattern,
the point at which they shifted their frequencies, and the degree to which
they did so, differed among individuals. In other species of bat, researchers
have found variations in auditory cortex tonotopic representation that
correspond to individual differences in emitted frequency
(Suga et al., 1987). In the
mustached bat, Pteronotus parnellii, the resting frequency of the CF
component of the second harmonic (CF2) of the biosonar signal can vary several
kHz between individuals. The functional organization of the Doppler-shifted CF
processing (DSCF) area of the auditory cortex varies in a similar manner, with
the distribution of best frequencies of neurons matching the properties of the
bat's own CF2 resting frequency. In this way, both the orientation sound and
the auditory cortex of individual bats are `personalized' for echolocation. It
is possible that such personalized modifications of the auditory cortex exist
in species such as the big brown bat, as well. Their sonar signals are known
to differ enough between bats for individuals to recognize each other
(Masters et al., 1995). The
bats in the present experiment may have been shifting their tail-end CF
frequencies out of the range of interference in order to keep them within a
window of sensitive frequencies determined by their own baseline frequency and
corresponding sharply-tuned neurons.
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;
Simmons et al., 1995). The
bat's auditory system registers the timing of each frequency in echoes and
combines information across frequencies to achieve very high delay accuracy of
fractions of a microsecond (Simmons et
al., 1996). The frequency tuning of neurons used in echo delay
perception is only moderately sharp, which is necessary to maintain accuracy
of timing registration (Menne,
1988). The graphs in Fig.
9 plot the sharpness of frequency tuning (given as values of
Q10dB) as a function of frequency in the big brown bat's
cochlear nucleus and inferior colliculus (see
Haplea et al., 1994). Neurons
in the cochlear nucleus are tuned approximately optimally for registering the
timing of the frequencies, with Q10dB values mostly in the
range of about five to 15 from 20 to 75 kHz
(Menne, 1988). A different
subpopulation of neurons in the inferior colliculus is more sharply tuned,
with Q10dB values ranging from two to as high as 90 for
frequencies ranging from 22 to 28 kHz. These sharply-tuned neurons constitute
a separate neuronal pathway, parallel to the less sharply tuned pathway for
processing echo delay, which is used for target detection. Big brown bats lose
echo-delay accuracy in proportion to reduced relative echo bandwidth,
including for small frequency segments of 20–25 kHz
(Simmons et al., 2004). Thus,
the presence of a different population of neurons that have `normal', moderate
tuning indicates that these bats have two parallel sonar receivers at
frequencies of approximately 22–28 kHz – one for detection and the
other for delay estimation.
The jamming of echolocation by conspecifics may be a major problem for
free-flying bats, many of which live in large social groups and forage
together. It is likely that bats possess several mechanisms for dealing with
this type of potential interference. Suga et al.
(Suga et al., 1983) listed
several such possibilities, based on knowledge of bat neurophysiology,
including: (1) the directionality of the bat's emissions, (2) the directional
sensitivity of the bat's ear, (3) binaural processing, (4) sequential
processing of echoes and (5) an auditory time gate for echo processing.
Behavioral studies have also revealed strategies that echolocating bats may
use to reduce jamming in the presence of conspecifics. A commonly observed
mechanism is to alter the duration of pulses or the inter-pulse interval to
avoid overlapping the sounds produced by nearby bats
(Obrist, 1995;
Surlykke and Moss, 2000). This
change in the timing of emissions is also seen in `pulse'-type electric fish
(Heiligenberg, 1991). Finally,
bats that travel the same route from roost site to foraging grounds night
after night (Rydell, 1990) may
be relying on spatial memory and not on the echoes of their surroundings to
navigate in familiar areas (Griffin,
1958; Höller,
1995). Altering the frequency of their emissions may be only one
of several mechanisms that bats may use to solve the problem of interference
from other bats.
LIST OF SYMBOLS AND ABBREVIATIONS
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Acknowledgments |
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