PHYSIOLOGICAL REVIEWS Vol. ‘70, No. 3, July 1990 Printed in L?S.A.
Auditory
Adaptations
for Prey Capture in Echolocating
Bats
G. NEUWEILER Zoologisches
Institut,
Universittit
Miinchen,
Munich,
Federal
Republic
of Germany
I. Introduction ........................................................................................... II. Echolocation Signals and Foraging Habitats ......................................................... A. Foraging in open spaces ........................................................................... B. Foraging close to or within vegetation ............................................................ C. Gleaning from leaves and from ground ........................................................... D. Gleaning from water surfaces ..................................................................... III. Common Auditory Adaptations for Echolocation .................................................... A. Neuronal facilitation relevant to target detection ................................................ B. Time windows for target ranging ................................................................. C. Echo-delay sensitivity and target ranging ........................................................ D. Intensity leveling .................................................................................. E. Enhancement of echo analysis by a reafferent copy of vocalization command? ................. IV. Auditory Adaptations for Echolocation in Open Spaces ............................................. V. Auditory Adaptations for Echolocation in Echo-Cluttering Environments ......................... A. Fluttering-target detection ........................................................................ B. Echo colors ......................................................................................... C. Acoustical detection by listening to prey-generated noises ....................................... D. Acoustic prey detection on water surfaces ........................................................ VI. General Conclusions ..................................................................................
I.
INTRODUCTION
Next to rodents, bats are the most numerous order of mammals, and they are the most diversified of any order. They owe this phylogenetic success to two unusual capacities, flight and echolocation. Bats emit rapid sequences of brief high-frequency sound pulses that are broadcast either through the mouth or through the nostrils. The echoes reflected from objects in the environment carry information on the acoustical properties of the world surrounding the bat. This ability to create an internal representation of the external world independent of sunlight allowed bats to exploit the rich resources of nocturnal winged insects with hardly any competition from other vertebrates. There are two suborders of bats: the echolocating Microchiroptera and the fruit-eating and flower-visiting Megachiroptera or flying foxes of the Old World. With the exception of one genus, Rousettus, flying foxes are unable to echolocate, and a recent study on the binocular retinotectal pathways in bats (85) has initiated a debate on the possible diphyletic evolution of bats, with flying foxes having originated from primates and the microchiropterans from insectivores. Among the 680 echolocating species of Microchiroptera, most live on insects. However, many species have diverged to exploit entirely different food sources. For example, many phyllostomatid bats of the New World tropics feed on fruits or on nectar and pollen and 0031-9333/90
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are indispensable pollinators for many plants, such as wild bananas, agaves, and various forest trees. Three species of vampires are the only vertebrates that subsist exclusively on blood meals. Some larger species of the New World and the Old World have become carnivorous and catch frogs, lizards, fishes, birds, and small mammals; still others are omnivorous and eat everything from fruits to insects, frogs, and even other species of bats. This review is restricted to echolocation in insectivorous and carnivorous microchiropterans. Detection and pursuit of small winged prey is probably the most demanding task in echolocation, and much of this review is devoted to the mechanisms for accomplishing this task, including general adaptations of the auditory system to echolocation with emphasis on auditory specializations for foraging in acoustically highly divergent habitats. ‘Readers who want full information on all aspects of echolocation in bats and dolphins can refer to the most recent proceedings of the International Animal Sonar Symposium (68). Recent advances in bat research have also been reviewed (23a). II.
ECHOLOCATION
SIGNALS
AND
FORAGING
HABITATS
Echolocating bats not only “locate” a target, but they must also analyze the features of the target, for 615
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signal components
I-
open }-forager
gLeanerI--
space ,-I
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close/within +-~ogreJ$~n~-~ Hb s+c
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FIG. 1. Signal components and types of echolocation sounds emitted by bat species echolocating in different habitats. Left column: echolocation sounds only consist of three components, downward frequency modulated (FM \ ), upward frequency modulated (FM/), and constant-frequency tone (CF), and are composed of one to several harmonics. Bars on abscissa mark lo-ms intervals. c, Sound emitted while approaching and catching a target; s, sound emitted for searching a prey. Ap, Antrozous pallidus (7); Hb, Hipposideros bicolor (33); Ml, Megaderma Myra (75); My, Myotis lucifugus (92,93); Pm, Pipistrellus mimus (75); Rr, Rhinolophus rouxi (74); and Tk, Taphoxous kachhensis (75).
k
IOms
example, distinguish prey from nonprey and perform pattern recognition tasks, such as differentiating between a smooth surface and a rough surface suitable for landing. Therefore the term echolocation does not encompass the full capacity of this acoustical information system, and a term analogous to visualization, such as audification, would be more appropriate. The signals used for auditory representation of the external world are brief sounds of 0.3- to +!OO-ms duration that have rather high frequencies from 12 to 200 kHz. The echolocation signals are produced by the larynx and have simple frequency-to-time courses. They invariably consist of one of the following elements or of combinations of them and are emitted as single or multiple harmonics (Fig.1): 1) downward frequency-modulated sweep with linear or exponential time course (FMd,,,), 2) a tone of constant frequency or a shallowly modulated tonal element (CF), or 3) upward frequencymodulated sweep with linear or curved time course (FM,,), which only occurs in combination with other sound elements. Typical echolocation pulses of various bat species foraging in different habitats are shown in Figure 1. The sound pattern and frequency range emitted are species specific but also depend on the actual situation. For instance, when an echolocating bat approaches a target the echolocation sound invariably consists of or contains a FMdown component. As discussed in section III, B and C, this signal is useful for range finding and spectral inspection of the target. Several recent field studies have shown that different species of echolocating bats forage in (distinct habitats that impose very different acoustical constraints on the auditory detection of prey. The type of echolocation signals emitted by each species is linked to its foraging
habitat (for reviews see Refs. 20, 73, 92; Fig. 1). With respect to acoustical prey detection, classes of foraging habitats have been distinguished.
A. Foraging
in Open Spaces
I. Foraging
above vegetation
Fast-flying bat species with narrow and long wings preferably search for flying insects well above tree top level where they will not encounter any obstacles. Acoustically, this area is a “silent” and rather empty space populated by widely distributed insects in low densities except for occasional swarming ants, termites, and other similar insects. Many emballonurid, mollossid, and vespertilionid bats forage in this type of surroundings.
2. Foraging
between vegetation
Because insects are more abundant closer to vegetation, many bat species forage in open spaces between foliage of trees, around tree tops, along waterways, and along forest edges. The bats, however, keep away from the foliage, and therefore echoes returning from the background will arrive later and will be fainter with respect to echoes from flying prey. The bats might use the background echoes as guideline signals for their flight corridors. Bat species that forage for flying insects in open spaces commonly emit two types of echolocation signals
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FIG. 2. Correlation between preferred foraging habitat and best frequency (BF) of audition in echolocating bats. Bats gleaning prey from ground (Ml, Megaderma Myra) or foliage (Pa, Plecotus auritus) are most sensitive at frequencies between IO and 20 kHz below echo frequencies. Bats foraging for flying insects above vegetation (Ta, Tadarida aegyptiaca; Tk, Taphoxous kachhensis; Tm, Taphoxous melanopogon) employ low-frequency echolocation for detecting insects over long distances. Bat species catching flying insects between vegetation (Pd, Pipistrellus dormeri; Pm, Pipistrellus mimus; Rhh, Rhinopoma hardwickei) have sensitive audition in a medium ultrasonic frequency range. Bat species foraging in open spaces use long, CF-like signals for searching (s) and brief, broadband signals for catching (c) prey. Hipposiderid (Hb, Hipposideros bicolor; Hsp, Hipposideros speoris) and rhinolophid bat species often hunt close to or within vegetation and are specialized for fluttering-target detection. Bats foraging in this habitat may use echolocation with high frequencies. Inset: types of sounds used for echolocation in specific habitat. [BF of audiogram in PZecotus auritus from Coles et al. (11); all other audiograms from Neuweiler et al. (X5).]
(Figs. 1 and 2). One signal is a pure tone or shallow FM signal of 6- to 60-ms duration with one or several harmonics and is used when searching for prey (“s” in Fig. 1). This signal is gradually or abruptly transformed into a brief (up to 5 ms) FMdown pulse when the bats have detected the prey and are approaching their target (“c” in Fig. I).
B. Foraging Close to or Within Vegetation
Acoustically, this foraging zone is very different from open spaces, since unwanted echoes (so-called echo clutter) are inevitable. Bats foraging in this zone have to detect their flying prey within a multitude of timesmeared echoes returning from foliage and twigs, which requires sophisticated ways of detecting an auditory signal in noise. The large families of horseshoe bats and hipposiderids, which often forage in such habitats, consistently emit echolocation signals composed of a pure tone within a species-specific frequency range and one or two FM components (Figs. 1 and 2).
C. Gleaning From Leaves and From Ground
Bat species that preferably pick up prey from a surface are called gleaners. Acoustically their task is even more complicated than that of detecting flying prey in a cluttered environment. The auditory system of the gleaner has to differentiate a slowly moving or still target of small size against an extensive and acoustically highly reflective background. When gleaning bats echolocate, they emit brief low-intensity signals of durations often ~1 ms. Because of many harmonics the signals are broad band and extend over several octaves, e.g., 20-110 kHz in Megaderma Myra (Figs. 1 and 2). D. Gleaning From Water Surfaces
The well-known fishing bats Noctilio Zeporinus, Noctilio labialis, Pixonyx vivesi, Myotis adversus, M. daubentoni, and a few other species preferably trawl, with their large feet, arthropods and sometimes fish from lake and sea surfaces. The smooth water surface acts as an acoustic mirror, and therefore the situation
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for auditory prey detection is different from that of ground gleaners. Fishing species use various types of echolocation signals. Most bat species do not forage exclusively in one foraging area. When the preferred foraging habitat has become too poor, they may shift their activity into more promising areas. The fishing bat Noctilio Zeporinus, for example, also hunts flying insects on the wing (147). Megaderma lyra takes frogs from the ground as well as from water surfaces and effectively catches large flying insects. The insectivorous mouse-eared bat, Myotis myOtis, pursues insects on the wing but will also glean nonflying arthropods from the ground. In contrast to most species foraging in open spaces, some species that forage in diverse habitats do not change the structure of their echolocation signals. The mouse-eared bat, Myotis myotis, for instance, has never been observed to change the pattern of its FMdown echolocation signal despite the acoustically divergent foraging areas (for review see Ref. 70). Broadband FMdown signals probably are the signal for general purpose and hence useful in different acoustical situations. They are the most widely used echolocation signals and may have the largest information capacity (see sect. vB). III.
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COMMON
AUDITORY
ADAPTATIONS
70
loo80-
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Frequency
IkH2 I
FIG. 3. Comparison of audiograms of nonecholocating grounddwelling mammals and bats (continuous lines) and of echolocating bats (dashed lines). There is no difference in frequency range heard between 2 groups, and auditory sensitivity to ultrasound (x20 kHz) is not specific to echolocation. Behavioral audiograms: W-O, housemouse (15); x-x, cotton rat (35). Neuronal audiograms: O-O, nonecholocating, fruit-eating bat Cynopterus SJAGW; x--x, echolocating insectivorous bat Taphoxous kachhensis; and W-O, echolocating insectivorous bat Tadarida aeggptiaca (75).
FOR
ECHOLOCATION
What differentiates the auditory system of an echolocating bat from that of a nonecholocating mammal? This basic question has still no unequivocal answer. Sensitivity to ultrasonic frequencies (frequencies 90 kHz) would be the wrong answer. Audiograms obtained by neurophysiological or behavioral methods disclose that all small mammals, including the nonecholoeating fruit-eating bats (megachiropterans), hear well above 20 kHz. Figure 3 demonstrates that the range of frequencies heard by mice, cotton rats, nonecholocating fruit-eating bats, and bat species that exclusively detect and catch flying insects by echolocation are indistinguishable. In each species the audiograms extend far into the ultrasonic spectrum. There is no echolocation without a preceding vocalization. This fact uniquely differentiates audition in echolocation from that in communication or from listening to noises generated by alien sources. Information on the nature of the insonified target is carried by the spectral and temporal differences between the parameters of the emitted sound and those of the echoes. Therefore, in auditory imaging, information on the nature of the animal’s surroundings may be gained only by comparing the emitted signal with the returning echoes. In recent years the general hypothesis that the emission of echolocation sounds triggers specific auditory mechanisms that facilitate echo detection and analysis has been strongly backed by neural and behavioral experiments. The evidence is best for the specific task of echo ranging. As discussed in section IIIB, the data do not yet allow an extension of the concept of specific audi-
tory mechanism of echolocation.
s triggered
A. Neuronal Facilitation
by vocalization
to all tasks
Relevant to Target Detection
A study on neuronal responses of the inferior colliculus (auditory midbrain) to stimulus pairs mimicking an echolocation signal and its echo disclosed that specific neuronal mechanisms for echo detection may exist (65). In mammals, responses of auditory neurons to tone pulses are usually suppressed by a second, simultaneous stimulus tone. In horseshoe bats this is also true except for one group of neurons: those tuned to the range of CF (81-88 kHz). This CF frequency is the frequency of the most intense harmonic of the pure tone echo. Neurons with best frequencies (BF) in the CF range are not inhibited by a simultaneous or preceding tone just below the CF but rather the responses are enhanced. When the preceding tones are 500-4,000 Hz below CF, the response to a second, fainter, and echo-mimicking stimulus is enhanced, and its threshold is lowered by up to 20 dB (65). The lower frequency range of the first stimulus is the range actually emitted by a flying horseshoe bat, since it lowers the emitted frequency in order to compensate for Doppler shifts of the echo caused by its own flight speed (103). Doppler-shift compensation keeps the echo frequency within a narrow range of high auditory sensitivity. As indicated, enhancement by a preceding signal of a lower frequency is restricted to those units that are tuned to the narrow frequency band of the horseshoe bat’s CF echo component (81-88 kHz). The window of
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enhancement triggered by the first stimulus of appropriate frequency remained open for -250-500 ms. Thus sequences of echoes arriving from targets as far as 8-9 m would meet neurons sensitized by the emitted sound. Such sensitized neurons would process echoes in an enhanced fashion. This would be of great advantage for the foraging horseshoe bat, since the CF component of the echo is used for prey detection (145). It is not known if this facilitation mechanism in horseshoe bats is established at the level of the inferior colliculus or at more peripheral levels. Its most remarkable feature is its precise restriction to the narrow frequency band used for prey detection.
B. Time Windows
for Target Ranging
Most bats, if not all, use FM signals for measuring target range by computing the echo travel time. Roverud and Grinnell (96) trained Noctilio albiventris, a species that emits short CF-FM signals (CF: 71 kHz, -6 ms; FM: 71-57 kHz, 2 ms) to discriminate different distances of otherwise identical targets. The echolocating bats could no longer perform the task when additionally loud artificial pulses mimicking the CF-FM sound were played to the bats either in a free-running repetition mode or time locked to the emitted echolocation pulses. However, the artificial signals did not interfere with target ranging if they were presented as isolated CF or FM components or if the CF component was shifted outside of the frequency range of the natural echolocation signals (78-57 kHz). The critical parameters for signals effectively disrupting range discrimination were I) a 2ms CF onset had to be followed by a FM signal within 27 ms, 2) the starting frequency of the FM signal could not differ from the CF frequency by more than +2 and -5 kHz, 3) the intensity of the interfering signal had to be louder than 75-80 dB sound pressure level (SPL). In control experiments it was excluded that the observed effects were due to masking (96). These results are interpreted as evidence for a neuronal time window that is opened by the onset of the emitted CF-FM signal and is closed again after -27 ms. Only FM pulses heard while the time window is open are accepted as echo-ranging signals by the auditory system. Therefore artificial CF-FM echoes occurring while the time gate is open will confuse the echo-ranging mechanisms (95). If these conclusions are based on a general neural mechanism they should apply to target ranging in all bat species regardless of the emitted signal types. Roverud extended these experiments to horseshoe bats, which emit long FM-CF-FM signals (Rhinolophus rouxi), and to vespertilionid bats (Eptesicus fuscus), which emit brief FM pulses, and found similar effects. In all three bat species emitting different types of echolocation signals the effective gating time was --30 ms. This limits the effectiveness of the gate to target distances within 5 m. Because precise distance information may be needed only for the catching maneuvers, 5 m is a
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reasonable distance for bats catching flying insects on the wing. It was also tested whether such time windows are only active for echo ranging or whether they might also apply to other echolocation tasks, e.g., discrimination of wing beat rates of fluttering targets. Wing beat cycles cause “glints” in the echo (a sharp and brief amplitude modulation and broadening of the spectrum), and the periodicity of the glints corresponds to the wing beat frequency. Bat species that emit different types of echolocation signals were trained to discriminate rotation rates of small propellers, a method to mimic the wing beats of prey insects. When the bats correctly performed the discrimination task, it was tried to disrupt the performance by interfering signals as in the previously described echo-ranging experiments. These tests failed to give evidence for time windows (R. C. Roverud, personal communication). Thus the neuronal gating seems to be restricted to echo ranging. However, for this basic echolocation performance, neuronal gating most probably applies to all echolocating bat species (95). The most convincing cases for specific auditory processing time locked to sound emission are the cortical echo-ranging neurons discovered by O’Neill and Suga (81) in the FM-CF-FM bat, Pteronotus parnelli, and by O’Neill et al. (80) in the FM-CF-FM bat, Rhinolophus rouxi. There is an excellent review on this topic (79). C. Echo-Delay I. Behavioral
Sensitivity
and Target Ranging
evidence
The time delay between sonar pulse emission and the return of the echo provides a reliable measure of the distance between an echolocating bat and a target d = cM2
where d is the distance in mm, c is the sound velocity in air (= 344 mm/ms), and t is the delay, in ms, from onset of vocalization to return of echo. In behavioral experiments, Simmons (114) showed that echolocating bats detect target range differences of 1.2-1.5 cm at a distance of 30 cm. The two targets were 40” apart on the horizontal plane, and therefore the bats had to check the range of each target sequentially and compare the measures from memory. The bats also discriminated time delays of phantom targets (electronically delivered echoes from a loudspeaker) as small as 60 JUS, which corresponds to the range discrimination thresholds. From these results it was concluded that echolocating bats determine the range of a target by measuring the pulse-echo delay. For this task bats use brief FM pulses. Bats even discriminated a phantom target with a fixed delay (3.087 ms) from another target, the delay of which jittered with each emitted echolocation pulse
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(Z-20 pulses were emitted before a decision was made) by only 0.5 ps [delays of 3.087 + 0.0005 and 3.087 - 0.0005 ms (115)]. A bat would then be able to detect a change in target distance of only 0.1 mm. In another elegant experiment, Simmons et al. (116) tested the detection of a phantom target in the presence of “unwanted echoes” (echo clutter) from a nearby real or phantom echo source as a function of the distance between target and cluttering source. When the targets were presented at a distance of 40 cm and with an echo-to-clutter ratio of -10 dB, bats were unable to discriminate between targets with clutter and the clutter source alone if the clutter source was within -12 cm of the target. Thus the “clutter interference zone” extended for -25 cm around the target distance. In one of the two specimens tested, this clutter interference zone rose to 32 cm at 80-cm distance and to 60 cm at 160-cm distance. The authors concluded that within the interference zone, the bat does not perceive the target and the cluttering object as two echo sources separated in space. The increasing spatial extent, as a function of target distance, over which multiple targets are perceived as a single entity corresponds to similar neuronal results in auditory cortical neurons specialized on coding of echo delays (see below).
2. Neuronal adaptations for coding echo delays
The pulse-echo delay may be analyzed by neuronally encoding the interval between the auditory response to the emitted signal and to the echo. In the inferior colliculus and auditory cortex of echolocating bats, some neurons respond preferentially or selectively to a pair of stimuli separated by a specific interval. The units respond poorly or not at all to single stimuli, whereas the response to the second stimulus of a pair is facilitated (for review see Ref. 79). In these “delay-sensitive” units the time interval between the pair of stimuli (simulated emitted pulse and echo) is coded in one of two different modes. The first mode is temporal coding: the range information, i.e., the pulseecho delay, is represented by the latency of the neural response to the echo following the onset of the emitted pulse. This temporal type of interval coding requires that the latency of the facilitated echo response be precisely correlated to the echo delay (132). The second mode is range detectors: neurons are individually tuned to a distinct “best interval or delay” of the stimulus pair, and the neuronal tissue represents an array of such best delays. Pulse-echo intervals are thus encoded by the place of excitation within the neuronal structure (82, 126, 132; Fig. 4). In the auditory cortex of Myotis Zucifugus, 54% of the recorded cortical units were delay sensitive and responded preferentially to pairs of FM pulses, which are similar to the echolocation sounds of this species. A facilitated response to the pair of pulses required an intense first pulse (70-85 dB SPL) followed by a less in-
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tense second pulse [8-63 dB SPL (132)]. In these delaysensitive neurons both modes of delay coding are realized. I) About one-half of the delay-sensitive neurons were temporal coders. In these “E-units” the latency of the facilitated response is tightly correlated to the delay of the second pulse, encoding delays from 2.5 to 13.5 ms. In echolocation, this corresponds to target distances from 32 cm to 2.25 m. The range of delays within which the response is >50% of the maximal response is called the width of the delay-tuned facilitation of a single unit. For E-units the width is broad and ranges from 3 to 9 ms. Thus, because of the broad delay tuning, a large pool of E-units should fire synchronously to an echo that occurs within the broad facilitation window. The E-units may therefore be considered as event markers within a time window opened by the emitted pulse and closed by a preset interval (132, 133). 2) In the other type of units, so called P-units, the latency of the facilitated response is independent of the stimulus interval. However, they only respond to pairs of stimuli with distinct stimulus delays. The units are individually tuned to short delays between 0.5 and 4 ms (Fig. 4, B and 0. In echolocation, these delays correspond to target distances of 8-70 cm. Because the units respond to a distinct interval within the stimulus pair, range information is coded by which neurons are activated. The P-units act as target range detectors or target range filters. The delay width is narrower and ranges from 0.8 to 4.0 ms. In the auditory cortex of Myotis Zucifugus, units tuned to short delays tended to occur in more rostra1 locations and those tuned to longer delays occurred in more caudal locations, but a more detailed topography was not found (132). In Pteronotus parnelli (82, 126) and Rhinolophus rouxi (80), range information seems to be represented only by range detector units. These bats emit FMCF-FM signals consisting of two (R. rouxi) and up to four (P. parnelli) harmonics. In contrast to Myotis Zucifugus, auditory cortices of these bats are subdivided into areas that analyze the CF component and areas that process the final FM component for measuring echo delay (Fig. 4A). In the so-called FM-FM area, neurons preferentially respond to harmonically structured pairs of FM pulses with a particular interval or delay between emitted pulse and echo (Fig. 4). These range-tuned units are arranged in a map so that neurons sensitive to the shortest intervals (0.4 ms = 6-7 cm target distance) are found in the rostra1 pole and those sensitive to the longest delays (18-24 ms = 3-4 m target distance) in caudal locations of the FM-FM area. Neurons with “best delays” from 4 to 5 ms are overrepresented. The target ranges displayed in the entire map are apparently limited to closer distances that might be relevant in precise flight maneuvers for catching prey or for avoiding collisions with obstacles. Each unit is tuned to a particular range of delays, and the delay widths of neurons in the population increase as a function of their best delay [e.g., 2 ms
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lcwo
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Pulse
020'
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07 E-delay
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FIG. 4. Neurons coding pulse-echo delays in auditory cortex. A: auditory cortex of Pteronotus parnelli is subdivided into functionally different areas. Medial area is tonotopically organized with low frequencies (1) represented at caudal locations and higher frequencies (h) at frontal locations. CF marks area where narrow frequency range of constant-frequency echo component is represented. Neurons tuned to pulse-echo delays are found in FM-FM area (FM/FM), dorsal fringe area (DF), and ventral fringe area (VF). B: in FM/FM area, neurons tuned to pulse-echo delays are topologically organized so that neurons with brief “best delays” are found at rostra1 pole and those with long best delays are found at caudal locations. Numbers at “iso-delay contours” give best delays in milliseconds. Dashed lines demarkate areas of neurons responsive to specific combinations of harmonics: pulse has to contain first harmonic FM, of FM component, and echo contains second (FM,), fourth (FM,), or third (FM,) h armonic of FM component, respectively. C: responses of a pulse-echo tuned neuron of ventral fringe area to combinations of stimulus pairs mimicking first harmonic of emitted pulse (PH,) and second harmonic of returning echo (EH,). E-delay gives stimulus interval in milliseconds. Note that neuron does not respond to stimuli alone. D: Sullivan’s coincidence detector hypothesis for pulse-echo delay coding in Myotis Zuc$u~us. Top: working principle of hypothesis. Bottom: neuronal activity caused by an emitted pulse sweeps from rostra1 to caudal areas of auditory cortex (marked by blood vessels: thick lines) due to response latencies increasing from 7 to 15 ms in rostrocaudal axis. A coincidence response will occur at that location of auditory cortex (black spot) where total time of shorter latency to fainter echo plus echo delay equals longer latency to intense pulse. This location of coincident excitation will be situated more rostrally for short pulse-echo intervals and move caudally for longer intervals. [A and Cfrom Edamatsu et al. (14), B from O’Neill (W), and D from Sullivan (134).]
in a unit with a best delay of 1 ms and 7.4 ms in a unit with a best delay of 10 ms (122)]. Range-tuned units are sensitive to particular harmanic combinations in mustached bats and in horseshoe bats. The neurons will only respond when the first FM pulse (emitted echolocation signal) contains the first harmonic. For a facilitated response the second pulse
(echo) has to contain the second harmonic in FM,-FM, neurons and the third and fourth harmonic, respectively, in FM,-FM, and FM,-FM, units (Fig. 4, B and C). Apparently, the first harmonic of the emitted signal starts the time-measuring neuronal system, and the second, third, or fourth harmonic of the echo stops it. Neurons sensitive to the different harmonic combinations
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are arranged in a dorsoventral direction that is normal to the rostrocaudal time axis. Thus the time scale is represented three times in the FM-FM area (Fig. 4B). In Pteronotus pamelli, a dorsal fringe (DF) area, located dorsocaudally to the FM-FM area (Fig. 4A), also contains FM-FM range-tuned neurons that have a topographic arrangement identical to the FM-FM area; however, the time scale represented is limited to intervals not more than 8 ms (122). The DF area receives input from the FM-FM area. In the detailed study, no additional response features were found that were not present in the FM-FM area. The DF area in turn seems to project to still another smaller cortical area, the ventral fringe (VF) area (Fig. 4A), where the same range representation as in the DF area is again repeated (14). However, the range is even more limited to best delays up to 5.5 ms. The delaytuning curves were no sharper than those of units from DF or FM-FM areas. It is not clear why the echo range should be represented for each harmonic component of the echo separately and why this should be repeated three times. High harmonics might represent distances of small objects due to their small wavelength and the low harmonics that of larger targets. The fact that delay-tuned units are represented in harmonically ordered maps three times may point to another interpretation than the one suggested by the term range-finding areas. The best delays and the relatively wide delay widths might represent windows of echo ranges within which occurring echoes are analyzed for other purposes, e.g., for spectral fine structure. Each of the three cortical areas might subserve parallel analyses of different echo parameters. The neurons might function as a series of special auditory attention windows time locked to the emitted echolocation signal rather than as range-measuring or range-finding units. However, in Pteronotus parneZZi many range-tuned units are rather insensitive to echo amplitude and to small changes in echo frequency experienced by flying bats because of Doppler shifts. This suggests that their capacity to process echo parameters other than echo delay might be limited. A similarly complex FM-FM area has now been described in the auditory cortex of the horseshoe bat, Rhinolophus rouxi, which emits FM-CF-FM echolocation signals similar to Pteronotus pameZZi. Here, rangetuned units respond well when the first of a pair of stimuli contains the first harmonic (emitted pulse) and the second stimulus contains the second harmonic FM component at a particular delay (80). In all bats so far studied the target range information represented in the auditory cortex is confined to closer ranges up to 2.5-3 m, which are relevant for prey-catching maneuvers. Larger distances over which targets are detected and tracked are not represented in the cortical delay-tuned areas. 3. Neuronal
mechanisms
for echo-delay
coding
The neuronal circuitry that produces range tuning is not yet known. Range-tuned units with less rigorous
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specializations than in the cortex have also been reported from dorsal parts of the medial geniculate body. These areas are reciprocally connected with the FM-FM area in the auditory cortex (77). No such units have been found in the inferior colliculus (78), and therefore it is likely that the cortex receives its range tuning from the medial geniculate body. The delay lines for creating the set of systematically varying best delays come from still undefined subthalamic levels (54). The basic inputs to the yet unknown delay-tuning circuits might be the so-called constant latency responders (CLR) (88,119). These CLR units are not spontaneously active and respond phasically with one or two spikes to all intensities above threshold. They also respond to a second pulse at a very short interval after the first pulse, even when the second pulse is fainter than the first one. The latency variation is under t250 ps over a wide range of intensities when stimulated with FM pulses. However, this remarkable constancy of latencies disappeared when stimulated with pure tones. The precise timing of the response results from the selectivity of the CLR units to particular frequencies within the FM sweep, and it has been suggested that the remarkably small latency variations in CLR units result from the abrupt entrance of the stimulus sweep into the narrow frequency-response area of the unit (79,88). Such CLR units have been described in the nuclei of the lateral lemniscus and inferior colliculus but were rarely seen in the auditory cortex of FM bats [Myotis Zucifugus (119), Tadarida brasiliensis (88, 89), MoZossus ater and M molossus (144)]. They are, however, rarely found in the inferior colliculus of the FM-CF-FM bats Rhinolophus ferrumequinum (141) and Pteronotus parneLli (78). 4. Sullivan
k coincidence
detector model
For coincidence of two active inputs in a delaysensitive neuron to occur, the neuronal delay from the pulse must equal the sum of acoustic and neuronal delays from the echo. This requirement seems to be met by many delay-sensitive neurons that Sullivan (133) found in the auditory cortex of Myotis Zuci’fugus. When stimulated by single pulses, the units displayed long latencies if the stimulus intensity of the FM pulse was high; they abruptly shifted to short latencies when the stimulus intensity was low. Because this correlation between stimulus intensity and latency is reversed from normal, it is called a paradoxical latency shift. Latencies for echolike intensities were rather constant (7.5-9.5 ms), whereas those for pulselike intensities varied between 10 and 19 ms. In the auditory cortex, latencies for pulselike intensities increased for units from anterior locations to those at posterior locations concomitant with the best delays of the units. From these results it was concluded that coincidence detection may operate in the auditory cortex of Myotis Zucifugus (133). Thus an excitatory input from the emitted signal will sweep over the cortex in an anteroposterior direction due to the in-
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creasing latencies of the units (Fig. 40). A facilitated coincidence response will occur only at that cortical position at which the sum of echo delay and echo latency equals the latency to the intense emitted pulse. This mechanism would be also well suited to represent a sequence of echoes returning from targets at different distances on the anteroposterior cortical time axis. These results corroborate the hypothesis that in vertebrate auditory systems time is measured by coincidence detectors based on neuronal delay lines that compensate for the acoustical delays to be measured. Acoustic delays evaluated by vertebrates include interaural delays used for sound localization and sequential delays in echolocating animals for range finding. As shown in behavioral experiments, these neuronal time analyses may achieve a resolution in the microsecond range. Unlike in phase coding of electric fishes (36), the neuronal circuitries for this precise time analysis are not yet known in the auditory system of echolocating and nonecholocating mammals. There is a striking discrepancy between the precision of target range measurement or discrimination found in behavioral experiments and that suggested by the delay tuning of the cortical neurons. When the bats probed target distances or echo delays sequentially as single echo events, they discriminated delay differences in the microsecond range (114,115). However, when the bats had to discriminate delays of two echoes initiated by the same echolocation pulse [clutter experiment (116)], the widths of the discriminable range bands are far coarser than those found when one echo was presented at a time. These behavioral results not only ask for a precision of neuronal time analysis of less than a microsecond but also that these incredibly precise time measurements be stored in memory, read out from memory, and compared without loss of information and precision. One might also wonder to what behavioral end a bat might need a ranging acuity of less than a millimeter. However, the results of the jitter experiment suggest just that, unless the carefully controlled stimuli were confounded by some undetected cues locked to the delay differences. Therefore the debate will go on as to whether echolocation is primarily based on auditory analysis in the time or in the spectral domain until neuronal studies offer the wiring hardware for timing precision of even less than a microsecond in an auditory brain of a mammal. D. Intensity Leveling
Echolocating bats inevitably have to listen to pairs or sequences of auditory stimuli. The first one is always its own loudly vocalized echolocation sound (80-120 dB SPL) followed by one or several fainter echoes within a few milliseconds. In addition, for a flying bat approaching a prey, echo intensity rapidly rises as the distance to the echo target decreases. Therefore the auditory system has to process signals of widely differing amplitudes within a few milliseconds.
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Auditory neurons of the inferior colliculus do respond to faint signals delivered a few milliseconds after a first signal, which may be up to 80 dB louder. In more specialized units the response to the faint echo mimic may be even facilitated by the preceding loud pulse within a distinct time window locked to the onset of the initial stimulus (28, 29, 65; see also previous section). This striking capacity to process loud and faint signals in fast sequence has asked for central or peripheral mechanisms that might reduce the effective amplitude differences between vocalization and echoes and/or within an echo sequence heard by a bat approaching a target. Such intensity-leveling mechanisms have been described. I. Intensity
leveling within echo sequences
Kick and Simmons (46) described a simple mechanism that renders the heard echo intensity less variable. In Eptesicusfuscus the threshold for echo detection rose from 0 to >30 dB SPL as the delay between vocalization and an artificial echo was shortened from 6 to 1 ms. This reduction in delay corresponds to a target approach from 110 to 17 cm. In natural conditions the echo intensity will increase inversely by the square of target distance. Because of the rise in auditory threshold locked to decreasing echo delay, the perceived loudness of the echo is maintained within a narrow range above auditory threshold when the bat flies toward a target. The rise in thresholds observed for decreasing intervals between vocalization and echo arrival, however, might simply be the result of masking. Pteronotus parnelli achieves a similar effect by echo-intensity compensation (48). When the bats were moved toward a target from 4- to 0.2-m distance they systematically decreased the intensity of the emitted signal by 20-30 dB so that echo intensities were maintained in a range well suited for auditory analysis irrespective of target distance. Many field observations suggest that bats generally decrease sound intensity when they approach a target. 2. Intensity
leveling between vocalization and echoes
In the FM bat Myotis grisescens, responses to vocalized signals are neuronally attenuated by 25 dB compared with the responses to identical playback signals (128). Attenuation occurs at the lateral lemniscal or more peripheral level (129). Many units on various levels of the ascending auditory pathway have upper thresholds and respond no further to loud stimuli [e.g., auditory cortex (121)]. Specific capacities, such as encoding repetitive frequency and amplitude modulations, were often restricted to the linear part of the units’ dynamic range and therefore also limited to low and medium SPLs [e.g., cochlear nucleus (142), inferior colliculus (108, log)]. Mechanisms for intensity leveling peripheral to the
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cochlea have been inferred from examination of cochlea microphonic potentials in awake Pteronotus parneZZi (39, 41). The bats were fixed to a swinging pendulum or flying freely. Henson and co-workers found only weak or no microphonic potentials elicited by the emitted echolocation sound, whereas microphonics evoked by echoes were prominent even when the echoes were at least 43 dB fainter than the emitted pulses. The results were identical in moving and nonmoving bats. The authors explain the greatly reduced responsiveness to loud vocalizations by I) the narrow forward beaming of the emitted sound pattern, 2) the high directionality of the pinnae, and 3) by middle ear muscle contractions. However, there are contradictory results. As also demonstrated by microphonic potential recordings in fully awake but restrained and nonmoving bats, selfstimulation by sound emission ranged from 78 to 83 dB SPL in RhinoZophus rouxi (86) and up to 91 dB SPL in Pteronotus parnelli (44). Middle ear muscle contractions did not affect the main frequency range emitted. At present the conflicting results cannot be reconciled. Henson and co-workers (39,41) found minimal microphonic potentials to emitted loud sounds also in nonmoving bats, and therefore frequency differences between sound and Doppler-shifted echoes cannot account for the observed paradoxical effect. There are no apparent differences in the experimental set-ups used for recording self-stimulation by the emitted sounds, which may explain the opposing results. The test situations differed, however, in one aspect: in Henson’s experiments the bats had to listen to real echoes reflected from a complex environment, whereas in the other experiments the bats were kept in an echo-attenuated environment and were stimulated by synthetized echoes. It might be conceivable that real echolocation is correlated with a specific level of neural arousal that attenuates cochlear microphonics to vocalizations by the efferent cochlear innervation. However, this is a farfetched idea without any experimental evidence. In any case, cortical echo-ranging neurons are effectively triggered by the bat’s own vocalization (44), whether it elicits only a minor microphonic response (39,41) or is heard as a signal as loud as 91 dB SPL (44). Therefore it is not clear whether such intensityleveling mechanisms are essential for the analysis of echo range or for other tasks in echolocation. It is also not clear whether each bat species would use all mechanisms listed above or whether each mechanism is a different and speci .es-specific way to achieve the same end, i.e., to opti mize echo analysis. E. Enhancement of Echo Analysis by a Reaferent of Vocalization Command ?
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The experiments for echo ranging (44) unequivocally demonstrate that specific neurons are triggered by the heard vocalized echolocation sound. This finding does not rule out th e possible existence of corollary discharges from vocal command centers that temporarily
TO
condition pools of auditory neurons for echo analysis. There is only one test that supports this hypothesis (109). In the inferior colliculus of Rhinolophusferrumequinum the response of single cells to sinusoidal frequency modulations of pure tones was examined during vocalization. A few units faithfully coded the FM of an artificial echo only when the bat had vocalized simultaneously or no more than 40-60 ms earlier. When the vocalized signal was replaced by an identical signal from the loudspeaker the neurons did not code the FMs. However, the effectiveness of the weak first harmonic of the vocalized signal has not been tested, and it is now known that this part of the vocalization triggers echoranging neurons (80). It is conceivable that the heard first harmonic may have also initiated the specific capacity for FM coding. A recent search at the level of the lateral lemniscus for neurons enhanced for echo analysis by vocalizations was unsuccessful (W. Metzner, personal communication). Therefore this intriguing hypothesis is still open for debate. IV.
AUDITORY OPEN
ADAPTATIONS
FOR
ECHOLOCATION
IN
SPACES
The auditory requirements to be met by each bat species depend on the acoustical restraints of the habitat within which the species forages by echolocation. Therefore an acoustical characterization of the foraging zone precedes the description of auditory adaptations. The echolocation system of a bat foraging above vegetation will have to cover a long distance in order to give the bat a fair chance to hit a flying prey within a reasonable flight time. This ability is limited by the physics of sound propagation in air. Airborne sound decays for two reasons: I) spreading loss or geometrical attenuation due to sound expansion and 2) atmospheric attenuation due to energy absorption in air. Echolocation signals emitted by bats either through the mouth or through the nostrils may be considered as spherical wave fronts. As the travel distance of the wave front increases, its sound pressure will decrease by the same factor, e.g., a lo-fold increase of travel distance will also attenuate the sound pressure by a factor of 10 or by 20 dB. Bat species foraging in open spaces emit signals of -110 dB SPL and have best auditory sensitivities in the range of 0 dB SPL. Because echoes have to travel twice the distance from bat to target, echolocation will be principally confined to ranges well below 100 m. Spreading loss is independent of frequency, whereas sound attenuation due to energy absorption in air exponentially increases with frequency and additionally increases with humidity and air temperature. Atmospheric attenuation measured in still air at 25OC and 50% relative humidity amounts to 1 dB/m for 30 kHz, 3 dB/m for 100 kHz, and 8 dB/m for 200 kHz (55; Fig. 5). Because of these physical limitations of sound transmission in air, the auditory world of an echolocating bat will rarely exceed a radius of 50 m and will
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BATS
FIG. 5. Cumulative sound pressure loss in air for echoes returning from small targets that produce a spherical echo wave front. Target range shows distance between bat and target. Solid lines give total attenuation: outgoing and returning spreading loss plus outgoing and returning atmospheric attenuation for frequencies indicated by numbers. Note that dashed line shows spreading loss attenuation of sound incident on target, i.e., for outgoing sound only. [Modified from Lawrence and Simmons (55).] 015
1:o target
shrink even further with increasing echolocation frequencies (Fig. 5). Tadarida aegyptiaca emits search signals of 18 kHz and may therefore effectively scan air spaces as deep as 50 m, whereas in Hipposideros bicolor, which emits signals at 145 kHz, the auditory world will be “pitch dark” at distances >5-6 m. Thus longer wavelengths allow scanning of a greater distance, but shorter wavelengths result in better directionality and finer spatial grain of the acoustical reflections. For the bat, this creates a conflict of whether to optimize echolocation for long ranges or for high spatial resolution. As one might expect from the correlation of frequency with sound attenuation in air, bat species that forage in open spaces often emit searching calls of low ultrasonic frequencies (see Fig. 2). These signals are also of rather long duration (210 ms) and consist of a narrow frequency band or even a pure tone (CF). A relationship between the species-specific frequency of the searching calls and the altitude and range of the preferred foraging space has been demonstrated in a sympatrically living bat community of seven species (71). Species that forage for flying prey close to foliage emit frequencies of 130-150 kHz; those flying far above tree tops in long swings and at high speed search for prey with signals (30 kHz. As shown in neuronal audiograms (evoked potentials and multiunit recordings from inferior colliculus), the BF of audition follows the same trend (see Fig. 2). It matches the frequency of the narrow band searching call. It does not match the main frequencies of the FM signals emitted after prey detection (75). Apparently the sensitivity of audition is tuned to the detection range of the various foraging areas: the BF of the audiogram will faithfully predict whether a species is capable of foraging in open spaces or whether its activity radius is restricted to an area close to foliage (see Fig. 2). The tuning of the ears to low ultrasonic frequencies
2‘.0
i range
.
10
20
50
ImI
in species foraging on the wing and high above the ground should also give them access to an additional and very different food resource: arthropods moving on the ground. Rustling noises have considerable sound energy in the frequency band from 12 to 25 kHz and therefore should be detectable by these open-space foragers. Indeed, one species, Tadarida aegyptiaca, has been observed to come to the ground and feed on spiders, caterpillars, scarabids, and other ground-dwelling arthropods when flying insect density seasonally falls to low levels (1). As Table 1 shows, most of the echolocating bat species from which audiograms have been reported not only have sensitivity peaks for echo frequencies but also show good to excellent auditory sensitivity in the frequency range from 12 to 25 kHz. Listening to preygenerated noises may therefore serve as an additional means of prey detection. Sensitivity to the frequency range of rustling noises may have been retained from the bats’ phylogenetic ancestors, the insectivores, or perhaps tree shrews. It is evident why bats that echolocate over long distances emit low ultrasonic frequencies; however, it is not at all clear why so many of these species search for prey with narrow band signals of long duration. The most widely accepted argument purports that the bats put all vocal energy available into that frequency band to which their ears are most sensitive. This contention is corroborated by the fact that indeed searching call frequency coincides with best auditory sensitivity. However, in many species, e.g., Rhinopoma hardwickei, part of the precious sound energy is “wasted” on harmonics outside of the most sensitive auditory filter. Another argument may be more convincing: open air foragers search for wing-beating insects. A fluttering wing distinctly shows up in an echo as an acoustical glint (a brief spectral broadening and amplitude modulation) that occurs when the wing moves through the impinging sound beam (106). These glints are unmistakable indicators of flying insects and may
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1. Sensitivity to low ultrasonic in echolocating bats
TABLE
Megaderma lyra Macroderma gigas Rhinolophus ferrumequinum Rhinolophus rouxi Hipposideros spearis Hipposideros bicolor Hipposideros lankadiva Taphoxous kachhensis Taphoxous melanopogon Taphoxous georgianus Antroxous pallidus Eptesicus fuscus Myotis oxygnathus Plecotus townsendi Plecotus auritus Nyctophilus gouldi Noctilio leporinus Molossus ater Molossus molossus Tadarida brasiliensis Tadarida aegyptiaca Rhinopoma harwickei Pipistrellus dormeri Pipistrellus mimus Rhinolophus megaphyllus Rhinolophus ferrumequinum nippon Hipposideros diadema Hipposideros galeritus Hipposideros calcaratus Aselliscus tricuspidatus Emballonura nigrescens Saccopteryx bilineata Miniopterus schreibersi Myotis velifer Myotis lucifugus Pipistrellus papuanus Pteronotus suapurensis Pteronotus parnelli Phyllostomus hastatus Carollia perspicillata
* Audigrams
Threshold Frequency Echolocation
Best for
dB SPL
kHz
Reference
2
45-50 40-50
75 32
-15 -5 15 0 0 5 5 -13 8* -20 7 5 -5 5 0 5 30 45 20 60*
-1 -2 12 35 -5 15 0 0 30 10 0 30 10 12 0 20 -7 27 5 -8 17 0 35
83 85 137 150 71 25 26 24 40-50 60 35 55 40-50 35 57 40-50 35 42 17 35 55 50 70
59 110 75 110 84 75
55* 60* 60* 45* 65* 60* 35* 65* 45* 25* 65* 40” 45” 25* 35*
40 30 38 37 27 25 22 35 50 5 40 20 5 23 25
66 57 125 105 100 55 45 57 40-60 50 40 65 62 50 80
139 31
Threshold at 12-25 kHz, dB SPL
Species
-15
sounds
to -20 -15 -5 0 0
have been recorded from anesthetized
89 75
43
43 7 28 31 7 30
bats.
be more easily differentiated within a narrow band carrier than in a brief FM sweep. This argument may explain the tonal character of the search signals but does not account for their long duration. The probability that a wing beat will be encoded in an echo does not depend on signal duration but on the duty cycle, i.e., the percentage of a time span filled with sound energy. Duty cycles in bat species searching in open spaces with long-lasting signals are unfavorably low, ranging from 2% in Euderma maculaturn (56) to 23% in Taphoxous mauritianus (23). Total sound energy will be greater in long-duration echolocation signals, and this could increase signal detectabilitv over long distances if the auditorv signal de-
70
tector integrates over the full signal time. Evidence for such integration has not been found in bats, although there is behavioral evidence that echolocating dolphins use such an energy detection system (3). At present we cannot answer the question why bats foraging in open air frequently emit long-lasting and narrow band search signals. V.
43 7 12 49 29 11 32 146 144
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ECHO-CLUTTERING
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Bats foraging close to trees or bushes or close to the ground are confronted with a very different acoustical situation from those foraging in the open. They do not listen to single echoes returning from an acoustically “dusky or dark” space but have to differentiate relevant echoes from a multitude of time-smeared echoes, socalled echo clutter, returning from various backgrounds. Therefore the main auditory problem to be solved for such bats is clutter rejection. Because the sound-reflecting surfaces of the ground and foliage are large compared with echo point sources, such as small insects, the signal that indicates prey may be buried in an intense clutter of echoes, all at the identical frequency range. Interference among the multiple overlapping echoes will destroy the frequency-time structure of the emitted signal. Signal structure would be only preserved in the echo from a target situated in front of the background at a distance greater than onehalf of the range of the emitted signal. For instance, echolocation signals of 5-ms duration will extend over a range of 1.67 m, and echoes from insects flying 45 cm from the background will be masked by echoes from the background. Because moths and many other nocturnal insects favor spaces close to bushes and trees and within foliage, any bat that wants to exploit this rich resource niche will have to unmask the potential prey signal from heavy echo clutter. There are at least three different possible strategies for clutter rejection in the auditory system of echolocating bats: I) specialization on fluttering-target detection, Z) colored echoes or the detection of chromatic fluctuations in echoes, and 3) detection and location of noises generated by prey (in which case echolocation is not used for prey detection). A. Fluttering-Target
Detection
1. Echolocation
Bat species from various families consistently or seasonally forage close to vegetation or even within foliage. Among these bats there are two Old World families, the horseshoe bats (Rhinolophidae) and Hipposideridae, and one New World species, Pteronotus parneZZi (Mormoopidae, mustached bat). These species emit echolocation signals that alwavs contain a pure tone
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(CF) component (see Figs. 1 and 2). Horseshoe bats emit long pure tones lasting 8-200 ms, and hipposiderid bats emit brief tones of 4- to IlO-ms duration. Pteronotus parneLli emits a triple harmonic signal with a prominent pure tone element of ~20- to 30-ms duration. The frequencies of the CF parts are species specific and range from 32 kHz in Rhinolophus philippinensis (43) to 212 kHz in the hipposiderid bat Cloeotis percivali (22). In horseshoe bats and mustached bats, each individual bat faithfully maintains its own personal frequency, and females emit higher frequencies than males [RhinoZophus rouxi (74), Pteronotus parnelli (125)]. The CF components serve as search signals for prey (74,105,145). For instance, rufous horseshoe bats forage for flying insects close to foliage either on the wing or from stationary vantage points in a “sit-and-wait” strategy. The bats perch on isolated twigs under the canopy and continuously scan their surroundings with long pure tone signals of 45ms duration and with high duty cycles of 47%. When the bat acoustically encounters a flying insect, it flies off, returns with its prey to the perch, and immediately resumes acoustical scanning with CF signals (74). Behavioral experiments with insect and dummy baits disclosed that CF-emitting bats exclusively or preferably attack fluttering targets. Insects that did not move their wings were never touched [Pteronotus parnelli (27); Hipposideros ruber (5); Rhinolophus rouxi, Hipposideros speoris, and Hipposideros bicolor (58)]. Apparently, bat species that persistently emit a CF echolocation signal are specialized for fluttering-target detection. This notion is strongly supported by unique auditory specializations that so far seem to be unique to these groups of bats, i.e., Pteronotus parnelli, Hipposideridae, and Rhinolophidae. Z. Individually
tuned auditory
fovea
Audiograms of horseshoe bats (69) and mustached bats (30), derived from thresholds of evoked potentials or single-unit recordings in the inferior colliculus, disclosed that the auditory system of these bats features an extremely narrow filter tuned to the CF echo frequency. In horseshoe bats the slopes of the filter rise ~750 dB/ octave. Consequently a peak of insensitivity occurs only 2 kHz below the center frequency of the filter (-81 kHz in Rhinolophus ferrumequinum). Thresholds return to low levels only for frequencies >6 kHz below the peak of insensitivity. The center frequency of the filter is precisely tuned to the CF echo frequency used by the individual bat. For Pteronotus parnelli, all from the same cave in Jamaica, these individual frequencies range around 61.25 t 0.53 kHz for males and 62.29 t 0.54 kHz for females (125); in rufous horseshoe bats from Sri Lanka the individual frequencies range from 73.5 to 77 kHz for males and from 76.5 to 79 kHz in females (74). By these individually tuned filters, auditory processing of the CF echo signal is set apart from that of FM echo components or
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other auditory stimuli. This became evident with the discovery of two seperate areas in the auditory cortex of Pteronotus parnelli, one processing FM signals and the other processing CF signals within the narrow frequency range of the auditory filter (120,127). The same dichotomous organization of the auditory cortex was also found in horseshoe bats (80, 83). As described in the next section, the narrow CF frequency filter is localized in the cochlea (8, 87,123,130). In all stages of the ascending auditory pathway the narrow frequency range of the filter, Ns kHz around the CF echo frequency, is enormously overrepresented and sometimes occupies more than one-half of the volume of an auditory nucleus. Single units with such BFs are extremely narrowly tuned. A common measure of tuning width is QlodB, which is BF divided by width of tuning curve 10 dB above threshold. The higher the Q10dB value the sharper the tuning. Single units with BFs within the CF echo frequency have QlodB values of up to 600. Units with BFs outside the filter range have up to 20-30, which are values typical for Q10dB Values auditory neurons in other mammals, including other echolocating bat species (124). In some of the “filter neurons” the tuning curves were only 300 Hz wide [i.e., 0.36% of the BF at 83.8 kHz (66)]. Some of the narrowly tuned filter units respond rather poorly to pure tone stimuli but react briskly to minor frequency changes and modulations around the BF. In a detailed study on cochlear nucleus units in horseshoe bats, Vater (142) found sensitivity to sinusoidal frequency modulations as small as t20 Hz. The sensitivity was highest in units with BFs within the narrow filter range of 81-88 kHz, and for these units sensitivity was greatest when the carrier frequency of the frequency-modulated signal was positioned on the flanks of the excitatory area. Modulations were faithfully coded up to an intensity of 60 dB SPL, an intensity that will be not surpassed by echoes. The time course of repetitive sinusoidal frequency and amplitude modulations imposed on a carrier frequency was best encoded by units with tonic response patterns. The units faithfully encoded modulation rates up to 800 Hz. In the inferior colliculus, distinct evoked potentials locked to these modulations were elicited when a carrier frequency between 82 and 86 kHz was modulated by only 10 Hz, i.e. by 0.01% (107). Schuller (107) suggested that this extreme sensitivity to minute frequency changes may be used by the bat for detecting fluttering insects. When a pure tone echolocation signal is reflected from a flying insect, each wing beat will impose brisk amplitude modulations and spectral broadenings that are caused by the changing angle between the wing area and the impinging sound and by Doppler shifts of the frequency due to the speed of the beating wing. At each wing beat cycle, these simultaneously occurring effects will impose an acoustical glint on the carrier frequency of the echo. Kober (47) showed that these glints carry potential information on the relative angle in space between bat and prey irrespective of the type of insect pursued. The glints also
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carry information on species-specific traits of the insonified insect. Of course such glints also occur in FM echo signals; however, glints carried by pure tones have a better signal-to-noise ratio and may provide more information about the target (47). Neurons in the inferior colliculus (111) and auditory . cortex (83) with BFs Wi thin the narrow frequ ency range of the filter precise 1Y encode the glints in echo es reflected from flying insects. The neurons behave as perfect wing beat detectors, and because of their narrow tuning to the individual carrier frequency, they are noise resistant. This may explain why these bats are able to detect and pursue flying insects even in the echocluttering environment of foliage. However, for the narrowly tuned system, a problem arises when the bat flies off in pursuit of its prey. Because of its own flight speed the complete echo will be shifted to higher frequencies and therefore no longer matches the individual center frequency of the auditory filter. Horseshoe bats and mustached bats compensate for such Doppler shifts by lowering the frequency of their vocalizations (39, 103, 104, 140). In each echolocation signal, the bats lower th .e emitted freq uency by th .e same amou nt by which the previous echo surpassed a so-called reference frequency (112). This reference frequency corresponds to the center frequency of the auditory filter and may be maintained by an individual bat with an accuracy of t50 Hz. By Doppler-shift compensation (103) the bat locks the heard CF echo frequency to the center frequency of the auditory filter and effectively uncouples its movement-sensitive echolocation system from its own flight speed. The huge overrepresentation of the narrow range of individual CF frequencies in the ascending auditory pathway and Doppler-shift compensation suggest the following analogies to the visual fovea (113). 1) Just as the fovea1 area of the retina is overrepresented in the visual parts of the brain, in these bats a tiny fraction of the total frequency range heard is neuronally represented on a vastly expanded scale. 2) When the image of a target moves out of the retinal fovea it is brought back onto the fovea by tracking eye movements. The same occurs in Doppler-shift compensation: when the echo moves out of the narrow frequency filter because of Doppler shifts caused by the bat’s own flight speed, the echo is tracked back into the “foveal” frequency range by lowering the emitted frequency. Because of this analogy the auditory filter in the cochlea of horseshoe and mustached bats will be called an auditory fovea. Echolocation with a CF signal functions like a broadcasting system. Analogous to a broadcasting station, the bat emits a private carrier frequency, and the information transmitted is encoded in modulations of the carrier (music and speech in the case of the broad+ casting station, and acoustical glints from wing-beating insects in the case of the bats). In both systems the receivers have to be precisely tuned to the specific carrier frequency, and the narrow tuning of the receiving filters protects the transmitted information from interfering signals.
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The high degree of noise resistance in these bats is offset by the restriction of prey detection to wingbeating targets. Horseshoe bats and mustached bats will not detect any insect even at a distance of a few centimeters if it does not move its wings (27,58). Indeed, many moth species that hear echolocation signals of their predators stop flying or stay on leaves and twigs in a frozen manner and thereby escape bat predation (26, 63, 100). 3. Cochlear auditory fovea As mentioned in the previous section, the auditory fovea in horseshoe and mustached bats resides in the inner ear (8, 87,123,130). The auditory fovea in the cochlea has two specific features, the expanded frequency representation on the basilar membrane (BM) and the extremely sharp tuning of auditory units with BFs within the expanded frequency range. I)EXPANDEDFREQUENCYREPRESENTATION. The frequency representation on the BM was mapped in Rhinolophus rouxi by retrograde labeling of spiral ganglion cells and fibers innervating inner hair cells after horseradish peroxidase injections in physiologically defined sites of the cochlear nucleus (143). The resulting map disclosed that a narrow frequency range from 76 to 83 kHz (CF - 2 kHz to CF + 5 kHz) is expanded so that it occupies the complete second half-turn of the cochlea and covers a BM length that usually houses a complete octave, e.g., 40-80 kHz. The expanded frequency map is normalized to the individual CF echo frequency. For instance, in specimens from India that emit CF frequencies of 84 kHz and in specimens from Sri Lanka that emit 77 kHz, these distinctly different frequencies were represented at the same location on the BM (143). In Pteronotus pamelli, the frequency range from 70 to 54 kHz, i.e., from CF + 9 kHz to CF - 6 kHz, is expanded onto 50% of the total cochlear length, between 3 and 10 mm from the basal end (51). The range of CF echo frequencies, -61 kHz, are located in the center of the expanded frequency range. As in horseshoe bats, the place where the CF frequencies are represented receives maximal afferent innervation. Frequencies below and above the expanded frequency range are located on the BM on a logarithmic scale, as is usual in mammalian cochleas (Fig. 6). Apparently in horseshoe and mustached bats the frequency range of the CF echo component and upper part of the FM component, which comprise 9-13% of the auditory frequency range, are spread over one-third to one-half of the total length of the BM (Fig. 6). This expanded frequency-place transfer is the basis of the auditory fovea and together with the dense afferent innervation of the expanded frequency place results in a corresponding overrepresentation of the CF echo frequencies within the tonotopic organization of all nuclei of the ascending auditory pathway. The following is a summary of the overrepresented areas. In horseshoe bats they include I) anteroventral,
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FIG. 6. Cochlear frequency place map of 2 ground-dwelling mammals (solid lines) and 3 echolocating bat species that are specialized on flutteringtarget detection (dashed lines). In cats and rats, auditory frequencies are represented on BM on “typical mammalian” logarithmic scale. In 3 bat species, narrow frequency band of CF echo component is represented in a nonlogarithmic and highly expanded scale. This expanded cochlear frequency map is called an auditory fovea (hatched area; dotted horizontal lines give species-specific frequency of CF echo component, which is represented within auditory fovea). Cochlear frequency maps of 5 species shown here are only maps so far recorded with physiological methods [horseradish peroxidase marking: cat (57), rat (67), Rhinolophus rouxi (143), Pteronotus parnelli (52), Hipposideros lankadiva (84)].
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posteroventral, and dorsal subnuclei of the cochlear nucleus (18); 2) nuclei of the lateral lemniscus (62); 3) inferior colliculus, where Schuller and Pollak (113) report that 50% of the units have BFs between 78 and 88 kHz, i.e., from CF - 7 kHz to CF + 3 kHz; 4) medial geniculate body (17); and 5) primary auditory cortex, where the frequency range from 10 kHz below CF echo frequency to 3 kHz above is largely overrepresented (83). In Pteronotus parnelli they include 1) cochlear nucleus, where in each subnucleus the units with BFs between 54 and 66 kHz occupy -40% of the volumes (52); 2) superior olivary complex (94); 3) nuclei of the lateral lemniscus (94); 4) inferior colliculus, where Zook et al. (149) report that the dorsoposterior division, which covers 30-40% of the total collicular volume, only contains units with BFs around the CF echo frequency from 61 to 64 kHz; 5) medial geniculate body (76); and 6) auditory cortex, where in the so-called Doppler-shifted CF processing area of the auditory cortex 91% of the units have BFs between 1 kHz below and 2 kHz above the CF echo frequency (125). Remarkably, in mustached bats and in horseshoe bats the expanded frequency range is located on the basilar membrane just apically to conspicuous morphological specializations (51, 143). In horseshoe bats two specializations are particularly prominent (8). The basilar membrane of the first half-turn is specialized by a large thickening of the pars pectinata that supports the outer hair cells. This thickening abruptly disappears at a distance of 4.3 mm from base, precisely where the fovea1 frequency representation begins in the second halfturn. The outer anchoring system of the BM features a huge osseoussecondary spiral lamina that forms a mas-
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sive ledge extending from the base to the end of the second half-turn where the fovea1 frequency representation ends. In Pteronotus pamelli, the CF echo frequencies are located just apically to an abrupt decrease of the BM thickness (51), but other specializations of the cochlea are even more conspicuous. The first half-turn is enormous and extends over 10 mm, i.e., 70% of the total BM length. The Scala vestibuli is divided into a small basal chamber and a large chamber at the basal end. A sharp bony indentation of the inner wall -3 mm from the basal end marks the beginning of the fovea1 part of the cochlear frequency map and the narrowing point of the scala vestibuli. The vestibular wall of the first half-turn is covered by a dense substance called thick lining (91). It abruptly disappears forming a well-defined borderline 5.3 mm from the basal end, just basal to the place where the CF echo frequencies are represented. Such morphological cochlear specializations have been described only for bat species having an auditory fovea [Pteronotus pame& (37,38,91), horseshoe bats (8, 90,143), hipposiderid bats (9,84)]. How these specializations are functionally linked to the auditory fovea is, however, not at all understood. II) NARROW TUNING. The cochlear specializations might also contribute to another feature of the auditory fovea, narrow tuning. In all other mammals, including echolocating bats without an auditory fovea, the tuning is similar, and QlodBvalues rarely exceed 20. In bats with an auditory fovea, units in the peripheral or central nuclei of the auditory pathway are extremely narrowly tuned around the fovea1 frequency and may have QlodB values as high as 600 (52,124,130). This extremely sharp
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tuning is the result of cochlear frequency analysis, because such high QlodB values are found in auditory nerve fibers. At higher neuronal levels, lateral inhibition may eliminate the low-frequency tails of the tuning curves and narrow the tuning curve for stimulus intensities considerably above threshold (131) or create upper thresholds. However, at intensities close to threshold, frequency resolution is no better than at the cochlear level (72). The expanded frequency representation on the BM provides an extremely fine-grained frequency-place transformation; thus narrow tuning might simply be the result of the expanded mapping. The tuning curves of units with fovea1 BFs are extremely narrow when plotted on the common logarithmic frequency scale derived from the frequency-place map assumed to be valid for mammals (Fig. 7). However, the slopes of the tuning curves are not much different from those of units with BFs outside of the fovea when plotted as a function of the real frequency-place map of Rhinolophus ferrumequinum and R. rouxi and Pteronotus parnelli as described by Vater et al. (143) and K&s1 and Vater (51; Fig. 7), respectively. This indicates that the rate of threshold change in the tuning curve of an auditory nerve fiber may be a mirror image of the envelope of the traveling wave and therefore a function of the position on the BM (distance from base) from which the auditory nerve fiber arises. In other words, the distance along the BM over which auditory nerve fibers pick up BM vibrations for a given suprathreshold stimulus intensity may be the same for all BM locations. III) RESONATING SYSTEMS IN THE COCHLEA. A number of physiological features of the cochlea in horseshoe bats and in mustached bats suggest that the expanded frequency representation is only one part of the mechanism creating the sharp tuning. At least in Pteronotus pamelli, resonance phenomena may also be involved (87). K&s1 and Vater (52) have recently presented a working hypothesis that is based on a mechanical resonator in the cochlea tuned to the CF frequency range. Evidence for such a resonating system comes from experiments on otoacoustic emissions (OAE). The OAE is a sound that is emitted from the cochlea either spontaneously or elicited by an auditory stimulus. The following are the principal results. 1) The cochlea of Pteronotus parnelli has a loud (70 dB SPL) otoacoustic emission that is restricted to a single frequency close to the CF echo frequency [-61.8 kHz, i.e., 880 t 400 Hz above the vocalized CF frequency (50)]. 2) The amplitude and sensitivity of microphonic potentials reach an absolute maximum for a stimulus frequency that is precisely that of the OAE (42). 3) When elicited by stimulation with the OAE frequency, the microphonic potentials have a long rise time, and after the end of stimulation, they continue to oscillate for lo-15 ms irrespective of stimulus duration. Such prolonged rise and fall times of the cochlear microphonic envelopes are typical for resonating systems. When the ear is stimulated with broadband noise (IO-100 kHz), it resonates continuously at the OAE frequency (42). The OAE frequency is therefore called the
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FIG. 7. Tuning curves of cochlear nucleus units in horseshoe bats. when plotted on conventional logarithmic frequency scale, tuning curve with best frequencies in fovea1 frequency range (c-e) are extremely narrow. B: however, when plotted on real, experimentally documented scale of cochlear frequency representation with expanded representation of frequency band from 78 to 87 kHz, slopes of tuning curves become normally steep (c-e). This demonstrates that extremely sharp tuning within fovea1 frequency band is partly due to expanded frequency-place transformation on basilar membrane. Scale on B is based on frequency map from Vater et al. (143).
A:
resonance frequency and differs slightly from bat to bat. 4) In record .ings of sum mated aud itory nerve activities th e typical phasic-toni c prim arY response changes to a sharp on and off response for stimulus frequencies around the CF echo frequency or just below the OAE frequency. Units tuned to this frequency range are the most narrowly tuned of all VIIIth nerve fibers [BFs from 61.2 to 61.75 kHz (591. The occurrence of the on-off effects can be e xplained by an interaction of the stimulus-evoked BM vibration trave ling over th .e place of the resonator with the resonating oscillations elicited by the stimul us-evoked traveling wave. If the stimulus frequency is equal to or close to that of the resonator, then the reson ating system will oscillate and interfere with the stimulus-evoked oscillations. These vibrations will cancel out one another, and no tonic response will occur. However, a phasic respon se will persist: because the resonating response takes time to build up, the sti .mu-
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lus-evoked response will not be canceled out at the onset of the stimulation and an on response will occur. An off response will also occur, because the resonator has a slow decay time, and will continue to oscillate when the stimulus-evoked vibration has vanished. 5) The OAE is most effectively masked by stimuli of its own frequency or just above it, from 66 to 70 kHz. These frequencies have their maxima of BM vibration just basal to that of the OAE. From this result K&s1 and Vater (52) conclude that some portion of the BM basal to the place of OAE initiation participates in creating the resonance. They propose that a standing wave may reverberate between the oval window and the morphological discontinuities of the cochlea, for instance, the abrupt narrowing of the Scala vestibuli in the basal part of the large first cochlear half-turn. The idea of a reveberating wave is corroborated by the interesting finding that tuning curves of units with BFs just above the OAE frequency have a very steep slope toward the low-frequency side and a shallower slope at higher frequencies. This shape is the mirror image of the common shape of the tuning curve of auditory units in most mammals. (The shape of the tuning curve generally reflects the envelope of the ascending traveling wave.) Therefore the reversed shape of the tuning curve might indicate a descending traveling wave moving toward the base of the BM. Nevertheless, a mechanical resonator alone, such as that described above, will not fully explain the specific phenomena observed in the cochlea of Pteronotus parneLli. The OAEs, i.e., the resonance and the microphonic potentials, are susceptible to anesthesia and cooling (40, 50). Therefore unknown active metabolic processes must also participate in the tuning effects. The experimental data reported strongly support the notion that OAEs are produced by cochlear resonances. In other mammals and in humans, OAEs also occur at various frequencies and at lower intensity levels than in mustached bats (45, 150). Interestingly, in humans, OAEs always correlate with narrowly tuned individual sensitivity peaks in the audiogram (151). This suggests that resonances generally contribute to the fine tuning in the mammalian cochlea. The specific and prominent effects observed in Pteronotus might be an exaggerated version of a general mechanism for cochlear fine tuning. Therefore Pteronotus might be a suitable model for studying the unknown mechanisms of the fine frequency resolution achieved by the cochlear spectrum analyzer. Suprisingly, studies on physiological characteristics of the auditory fovea in horseshoe bats gave different results. The most striking differences of cochlear responses in mustached bats and horseshoe bats are listed in Table 2 (42). These opposing characteristics of microphonic potentials in Pteronotus parnelli and Rhinolophus rouxi suggest that the functional mechanisms of the auditory fovea are different in the two< bat species. Duifhuis and Vater (13) proposed an acoustic interference filter for the cochlea of the horseshoe bat. It produces a series of sharply tuned band-pass peaks. It is suggested that the
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2. Diferences in cochlear responses in horseshoe and mustached bats TABLE
Pteronotus
parnelli
1. Strong OAEs at a unique frequency just above CF echo frequency 2. CM envelopes for CF stimuli have long rise and fall times 3. CM has a marked amplitude peak at OAE frequency 4. There is no specific CM minimum 5. 180”phase shifts of CM occur when stimulus frequency sweeps through that of CM amplitude peak 6. CM amplitudes are generally large (maximum 40 pV) 7. Absolute CM threshold for OAE frequency is 20-25 dB lower than for other frequencies CM, cochlear microphonic; from Henson et al. (42).]
Rhinolophus
rouxi
1. No measurable OAE has been reported 2. CM envelopes for CF stimuli have fast rise and fall times 3. There is no CM amplitude peak at any stimulus frequency 4. A prominent CM minimum occurs for frequencies 3 kHz below CF echo frequency 5. 180”phase shifts occur when stimulus frequency sweeps through that of CM amplitude minimum 6. CM amplitudes are generally small (maximum 3 pV) 7. Absolute CM threshold at CF echo frequency is not lower than for other frequencies OAE, otoacoustic emission. [Adapted
center frequency of the fifth mode of the filter coincides with the frequency of the echolocation sound. The matching, however, critically depends on mechanical parameters that have not yet been determined. Pteronotus, from the New World, and horseshoe bats, from the Old World, are not related genera. It would be most surprising if the bat species would have independently evolved identical mechanisms to achieve the same highly specialized goal of wing beat detection in echo-cluttering environments. The functionally similar CF echolocation systems adapted for wing beat detection are a remarkable example of convergent evolution. 4. Gwnparative aspects
Fluttering-target detection in echo-cluttering environments by a long-lasting pure tone carrier and rendered noise resistant by an auditory fovea tuned to the individual carrier frequency seems to be a coherent and sophisticated auditory information system. However, there are inconsistencies. Small hipposiderid bat species also forage close to or within foliage and also always emit a CF component. In contrast to mustached bats and horseshoe bats, their CF signal only lasts 4-8 ms (31, 33). Hipposiderid bats also feature an auditory fovea [cochlear frequency map in Hipposideros lankadiva (84), tonotopy of the inferior colliculus in Hipposideros speoris (97)]. In the inferior colliculus of Hipposideros speoris the frequency range of the echo signals is overrepresented to a similar degree as in that of horseshoe bats and mustached bats, both of
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FIG. 8. Tonotopic frequency representation in inferior colliculus of some nonecholocating mammals (solid lines) and echolocating bats (dashed lines). Gleaning, echolocating bat Megaderma Zyra (x) shows same regular dorsoventral tonotopic arrangement as other, nonecholocating mammals. However, frequencies < 20 kHz (rustling noises of prey) and not echo frequencies are overrepresented (inset). In contrast, 2 bat species with an auditory fovea [Rhinolophus rouxi (0) and Hipposideros spew-is (o)] have dedicated nearly two-thirds of their collicular volume to a narrow frequency band of pure tone echo component: ‘i’-9% of auditory frequency range occupies 60% of neural tissue volume (steep slopes to the right). Data were normalized to minimal (at dorsal surface of inferior colliculus: 0% collicular distance) and maximal frequency (100% collicular distance) recorded in inferior colliculus. [Mouse (118); cat (61); marsupial, Dasyurus hallucatus (2); squirrel monkey (25); Megaderma Myra and Hipposideros speoris (97); Rhinolophus rouxi, unpublished data.]
which emit long pure tone signal components (Fig. 8). The range of overrepresented frequencies is broader than in horseshoe and mustached bats and is skewed to lower frequencies. In Hipposideros speoris the fovea1 range from 140 to -120 kHz includes the CF frequencies and also about two-thirds of the FM frequency range (Fig. 8). Despite a brief CF signal and a broader auditory fovea, hipposiderids are also specialized on echolocating fluttering prey and detect a wing-beating insect or dummy as successfully as horseshoe bats (5,58). Apparently, fluttering-target detection does not correlate with the duration of the CF signal and the sharpness of auditory filtering. The chance that a glint will be reflected from a beating wing depends on the wing beat frequency of the prey and the duty cycle (percentage of time filled with sound energy) of echolocation sound sequences (39). Even bat species that only emit brief FM signals are capable of coding and differentiating wing beat frequencies surprisingly well (135; R. C. Roverud, personal communication).
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Why then do horseshoe and mustached bats have such narrowly tuned foveae and long-lasting signals? The evolutionary driving force for perfecting pure tone echolocation may have been noise rejection and not fluttering-target detection. The narrower the auditory filter the more the auditory analyzer will be noise resistant, and the narrower the filter the longer the received signal has to be. Therefore improved noise rejection may be the reason that horseshoe bats have a sharply tuned fovea, long CF signals, and nearly 100% Dopplershift compensation of the echo carrier frequency. From behavioral observations, however, it is not clear why horseshoe bats should have a more noise-resistant system than hipposiderid bats, which can afford to use a brief CF signal of a more variable frequency and less complete Doppler-shift compensation because of their broader fovea (33, 84). Riibsamen et al. (97) suggested that in evolution the development of narrower auditory foveae is an adaptation for noise resistance and that the increasing restriction of the echolocation system to wing beat detection is a consequence of this. The auditory foveae may have evolved from the use of long narrow band sounds as search signals in many bat species that forage in open spaces above the canopy (71,92). Narrow cochlear tuning to the frequency of the search signal would allow the bat to forage closer to vegetation. Rhinopoma is a bat species that preferably forages in open spaces and already has a prominent sensitivity notch in its audiogram tuned to the pure tone frequency and therefore might be a species in the process of evolving an auditory fovea (71).
B. Echo Colors
If sound is reflected from a target with a rough surface texture, then interferences will occur between sound waves reflected from the peaks and the troughs of the texture. The resulting interference pattern will depend on the wavelengths of the impinging sound and on the differences of echo travel distances at the target surface. Interfering sound waves of the same frequency and amplitude will be canceled out when the two interacting oscillations are phase shifted by 18OO. Because an echo reflected from a textural indentation will have to travel twice the distance, an echo sound wave (X) will be canceled out when the depth of the texture is X/4 or uneven multiples of it and will be enhanced when the depth is X/2 or multiples of it. For instance, in Hipposideros bicoZor the pure tone echo component of 155 kHz will be canceled out if the effective target texture has a depth or roughness of 0.5 mm, whereas in Rhinopoma hardwickei, cancellation of the pure tone echo of 35 kHz will occur when it returns from a rough target with an effective depth of 2.4 mm. Therefore the spectrum of a broadband echo will contain notches and peaks at frequencies correlated with the roughness of the target surface. Bats should have no difficulties to discriminate textures of targets
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by analyzing the echo spectrum, because they discriminate frequency differences of ~1%. Only few experiments have been performed that tested the auditory capacity of echolocating bats to analyze complex spectra. In the pioneering experiment of Simmons et al. (II?), Eptesicus fuscus, a bat that emits a broadband FM signal sweeping from 100 to 30 kHz, had to discriminate Plexiglas plates with an identical pattern of drilled holes but of different depths. At a criterion of 75% correct responses the bats successfully discriminated depths of holes of 8 mm from those of 7.0-7.2 mm. Echoes reflected from these plates showed a series of spectral notches with deeper holes yielding lower frequency notches. The authors concluded that the bats made the decision on the basis of such spectral cues. However, later Simmons (115) interpreted the result as based on an auditory analysis in the time domain, requiring an auditory time resolution of ~0.6 ps. If this interpretation is correct, texture discrimination should improve with larger absolute depths of the holes, since the travel time of the echoes from the bottom of the holes will increase accordingly. The opposite effect was observed in an experiment that tested discrimination at hole depths of 4 and 8 mm (34). Discrimination thresholds were 0.8 mm for 4-mm holes and 1.0 mm for g-mm holes. This result is in agreement with a computer simulation of echo spectra reflected from two surfaces of various depths (6). In these spectra the spacing or the period (p) of the frequency notches was inversely correlated with the depth of the two front target p = l/At where At is the travel time difference between ethos from the closer and the farther front of the target. In a recent series of behavioral experiments, Schmidt (101) obtained evidence for a spectral basis of texture discrimination in echolocating bats. In twochoice experiments, false vampires (Megaderma &a), which emit brief broadband signals from 100 to 20 kHz, learned to discriminate randomly structured textures (real targets) that had an average grain size of 0.4 mm from those of ~2.5 mm. Spectra of the echoes showed notches and peaks characteristic for the different average grain sizes. Thereafter the bats were trained to discriminate simulated echoes with a single well-defined spectral notch. The emitted echolocation sound and a delayed copy of it were played back to the bat. The composite echo of playback and copy showed a sharp notch, the ) of which was inversely correlated with frw=ncY Cfnotch the delay At and uneven multiples of it f notch = ViAt
At=x,3x,5x..
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The bats learned to discriminate a simulated echo with a notch at 64.4 kHz (delay 7.77 ps, which corresponds to a target depth of 1.3 mm) from others with another fnotch. For a 75% correct response criterion the discrimination threshold was found at notch frequen-
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ties of 7-9 kHz higher or lower than the learned frequency, corresponding to a delay shift of only 1 ps or a change of target depth of only 0.2 mm. For three reasons Schmidt (101) concluded that this remarkable performance is based on a spectral analysis. 1) The response curves for larger and smaller delays than the learned one were symmetrical when plotted on a frequency scale and were asymmetrical when plotted on a delay-time scale. Z) As expected for a spectral but not for a time analysis, the performance was less good at the next uneven multiple of the learned delay, i.e., at At = 23.3 jet53 Or fnotc., = 21.5 kHz. 3) There is ample evidence that bats as well as other mammals may easily discriminate frequency shifts of 10%) whereas there are no neuronal data up to date that bats or any other mammal may detect a delay shift of 1 ps (but see sect. IIICI). These results indicate that an auditory analysis of the echo spectrum would be a powerful tool for getting texture information in acoustical imaging. When Megaderma Lyra had to choose between two simulated echoes that did not include the learned one, they chose the echo with a spectral pattern closest to the learned one. Apparently they had memorized the spectral pattern of the learned simulated target and based their decision on a similarity test between the heard and the stored pattern. They also responded correctly when the spectral patterns were presented as artificial stimuli without any correlation to the vocalized echolocation signals. This demonstrates that spectral pattern discrimination is not a unique capacity of echolocating animals but a general feature of audition. Just as white sunlight is reflected from objects with different spectral patterns creating colorful impressions, the white (broad band) echolocation signal of a bat will be reflected in a different spectral pattern according to the texture of the sound-reflecting surface. The nature of this surface is encoded in the spectral pattern or in the color of the echo. The auditory system of the bat could analyze this echo parameter for discriminating or even identifying prey or other targets, e.g., a rock face rough enough for landing from a smooth one. As indicated, the spectrum of the complex echo reflected from a rough target will have notches at fnotch values inversely correlated with the delay At and uneven multiples of it. Although the notch at the frequencies corresponding to At is sharp, the harmonically related notches are less distinct. Therefore the bats might restrict the analysis mainly to the first harmonic notch. In any case, bats with broadband signals would be more proficient in “echo color” analysis than those with narrow band signals. For instance, false vampires, which emit signals with frequencies from 100 to 20 kHz, could analyze spectral patterns within this frequency band corresponding to textural depths from 0.9 to 4.2 mm. However, horseshoe bats, which emit signals of 78-63 kHz, would be restricted to a textural range of 1.1-1.5 mm. The minimal texture resolution will be limited by the upper cutoff frequency of the emitted signal. The highest frequency emitted by any echolocating bat is ~200 kHz, which would allow detection of a minimal roughness in the range of 0.4 mm based on an echo-color
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analysis, with the assumption that only the first harmonic frequency notch and not its uneven multiples are used. If echolocating bats would want to use echo color for identifying prey items, then they would have to learn such patterns and store them in memory as the false vampires did in Schmidt’s experiments. Von der Emde (145a) showed that horseshoe bats could learn to differen tiate different insect species irrespective of the angle be tween incident sound and target. He assu mes that the bats achieve this remarkable spatially invariant discrimination by spectral cues. It is difficult to envisage that bats in this way identify different prey species in nature. They would have to undergo longer learning periods as in the experiments and would have to store invariant pictures of these patterns in their memory, preferably for a lifetime. Alternatively the bats should have a stock of genetically encoded patterns inherited from former generations. These inherited spectral patterns would act as release templates that select the prey items specific for this species when the heard echo fits into the spectral template. This is a wild and most unlikely hypothesis, since most observations on foraging bats show that they feed opportunistically on any edible insect of suitable size (21). More realistically, echo-color analysis might be very useful for detecting moving prey in echo clutter. When an insect sits motionless on leaves or twigs, a broadband echo reflected from this setup will have a differential spectral pattern or color due to the complex structure of the sound-reflecting surface and the angle of sound incidence. This pattern is undefined for the auditory receiver of the bat and therefore will not carry specific information on the potential prey. However, as soon as the insect slightly moves its body, the color of the echo will change. This change of echo color, then, will immediately indicate that on the insonified surface something is moving. The experiments of Schmidt (101) have demon strated that a ch ange i n texture depth of only 0.2 mm will cau se a shift in th e spectral pattern of several kilohertz that is easily detected by any auditory system. If we assume that echolocating bats detect a frequency shift of I%, then a bat emitting 155 kHz (e.g., Hipposideros bicolor) could detect changes in target texture of only 5 pm or changes of 220 pm with an echolocation signal of ~20 kHz (e.g., Tadarida aegyptiaca). Therefore listening for shifting echo colors might be a highly sensitive way to detect prey in an echocluttering environment, such as foliage. Echo colors will also shift when the echolocating bat is moving, and it would have to differentiate changing echo colors caused by its own flight from those caused by the target. Interestingly, some gleaning bats (Megaderma lyra, Plecotus auritus), which pick up insects or spiders from leaves, hover motionlessly for some time before they dart down and seize their prey. In this way they might avoid color shifts of echoes caused by their own movements. All gleaning bats so far studied only emit brief and broadband signals that are best
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suited for auditory spectral pattern analysis. These sounds are also faint and therefore will be only useful for close range inspection. There are no behavioral or neurophysiological experiments on the auditory analysis of changing spectral patterns either in echolocating bats or in other mammals. This is rather surprising, because listening to a flow of changing spectral patterns or acoustic colors is nothing specific for echolocation. For instance, our auditory system analyzes such patterns whenever we listen to music, and our delight or frustration indicates the importance of these patterns for the acoustic information transfer. In echolocation the auditory analysis of colors and tints of echoes, or “Klangbilder” as it is appropriately called in German, and their continuous changes in time will extract detailed and refined information on the nature of the acoustically probed target. In my opinion, auditory and behavioral research on echo colors or Klangbilder will be most rewarding and will hit the bull’s eye of echolocation. C. Acoustical Detection by Listening Prey-Generated Noises
to
For carnivorous and insectivorous bat species that pick up prey from the ground (ground gleaner) or from foliage (foliage gleaners), listening to prey-generated noises and sounds might be a more economical way to detect targets acoustically than echolocation in echo clutter. It is well known, for instance, that Eptesicus fuscus may detect the low-frequency sounds of katydids over hundreds of meters (10). The frog-eating bat Trachops cirrhosus is attracted to its prey by frog creakings and will even tell apart poisonous from edible frogs by the type of their calls (98). The insectivorous bat Antroxous paLlidus locates its prey by the noises produced on ground or under cover, e.g., the noises of fluttering insects within a bag, and does not react to nonmoving insects (4). Interestingly, the bats do not respond to callings of orthopterans. The carnivorous Megaderma Zyra located and caught moving mice in complete darkness without uttering a single echolocation call and ignored dead or nonmoving mice (24). For this species (60) and another megadermatid, Cardioderma car (99), it was experimentally shown that they detect and locate their staple food, frogs, only by prey-generated noises. Surprisingly, neither species ever reacted to frog creakings. It appears that faint noises and not loud sounds are powerful releasers for the catching behavior. Similar experiments in the Australian megadermatid bat, Macroderma gigas, also disclosed that faint noise sources on the ground were located and vigorously attacked (53). These experiments and numerous field observations suggest that bat species that search for prey on the ground or on foliage may preferably detect and locate their prey by noises generated by moving targets. Frogs moving over an earth floor will generate noises with energy peaks at 8-12 and at 18-25 kHz (60). This would
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AUDITION
IN ECHOLOCATING
100 I90 l80
60
4 6 8 10 Frequency
20 40 60 [kHz]
100
150
FIG. 9. Audiograms of 3 ground- and foliage-gleaning bat species that not only hunt flying insects but also detect arthropods on leaves [P, Plecotus au&us (ll)] or small vertebrates, such as frogs, lizards, mice, and birds [Ma, Macroderma gigas (32); Me, Megaderma lyra (97)], by listening to rustling noises produced by a moving prey. Note that frequencies of maximal auditory sensitivity are below frequency range for echolocation (thick horizontal bars) and coincide with frequency spectrum of rustling noises (IO-30 kHz) and that thresholds for frequencies between 10 and 30 kHz are w-20 dB SPL, which results in highest auditory sensitivity so far measured in mammals.
imply that audition of such bat species should be very sensitive in the low-frequency range. This is indeed the case. Audiograms are available for three gleaning species, the carnivorous Macroderrna gigas (32) and Megaderma Zyra [behavioral audiogram (102), neural audiogram (97)] and the insectivorous PZecotus auritus (11). The audiograms (derived from multiunit recordings in the inferior colliculus) disclose an extreme sensitivity in the range of lo-20 kHz with thresholds below -20 dB SPL (Fig. 9). These are the most sensitive ears so far documented. This sensitivity peak occurs at frequencies well below those of the echolocation signals. In the audiograms of all three species there is a second, less-sensitive peak in the frequency range containing most of the sound energy of the echolocation sound. However, thresholds are ~15-25 dB higher than for the low-frequency sensitivity maximum. In all three species, part of this exceptional sensitivity comes from the huge pinnae that are fused in the midline in the two megadermatid species and that form
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a large ear trumpet directed to the ground in the flying or perched bat. The pinnae act as conical horns (11,32) and not only create directionality but also produce a sound pressure gain at the tympanum. The gain reaches a maximum of 25-30 dB at 8 kHz in Macroderma gigas, 17-23 dB between 9 and 20 kHz in Plecotus auritus, and 15-20 dB at 15 kHz in Megaderma Zyra (unpublished data). In most gleaning bat species, large pinnae are common and due to their dimensions and conical shapes probably produce considerable sensitivity gains in the same low-frequency band as in the three species experimentally tested. In Megaderma Zyra, many sensitive units of the inferior colliculus with BFs in the low-frequency range had upper thresholds and fell silent for tone stimuli louder than 40-50 dB SPL (97). In rostra1 parts of the inferior colliculus many units reacted poorly or not at all to pure tones but vigorously responded to faint noises. Upper thresholds and specific responsiveness to faint noise signals may be interpreted as neuronal auditory adaptations to detecting prey by listening to faint rustling noises. Specific neuronal noise sensitivity might also explain why Cardioderma COT (99) and Megaderma Zyra (60) vigorously attacked moving frogs but never responded to frog creakings. The tonotopy of the inferior colliculus in Megaderma Zyra underlines the importance of low-frequency audition for this ground-gleaning species (Fig. 8). From dorsal to more ventral layers the complete range of audible frequencies from a few kilohertz to 110 kHz are represented. On the average a 1-kHz isofrequency sheet is -30 pm thick. Units with BFs < 20 kHz were found throughout the dorsal and lateral one-third of the inferior colliculus and extended over a dorsoventral depth of 850 pm, reaching a depth of 1,250 pm at the rostra1 pole, where noise-sensitive units were encountered. Thus frequencies < 20 kHz and not those of the echolocation signal are overrepresented in the ascending auditory pathway of this ground-gleaning bat species. A comparison of the tonotopy in Hipposideros speoris and Megaderma Zyra illustrates how differently the same problem of acoustical prey detection in an echo-cluttering habitat has been solved (97). Hipposideros speoris has retained echolocation and has specialized on fluttering insect detection. To this end the bat has made its auditory receiver noise resistant by utilizing a narrow filter tuned to the individual carrier frequency of the echo (in the range of 120-130 kHz), i.e., that of the pure tone component of the heard echolocation sound. In the neuronal auditory pathway nearly two-thirds of the volumes are dedicated to this narrow range of echo frequencies. In contrast, Megaderma Zyra has aborted echolocation for detecting ground-dwelling prey and locates faint noises generated by the targets. In the auditory system low frequencies are overrepresented, and specific neuronal sensitivity to faint signals and noises is created. A behavioral study also disclosed that auditory lateralization in the horizontal plane occurs at 2” from the midline for 20-kHz signals, and
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therefore sound localization should be excellent in Megaderma Myra (148). A comparison of sensitivity peaks in many species indicates that bats might have excellent auditory sensitivity to frequencies below those of their echolocation calls. Table 1 shows sensitivity peaks in audition of all bat species from which audiograms have been recorded. The 40 species come from all common families of bats and include species that catch insects on the wing, are specialized for fluttering-target detection, or are specialized for gleaning prey from the ground and from leaves. As expected, all species have a peak of auditory sensitivity in the frequency range of their echolocation signals (Table 1). However, many species have another peak of auditory sensitivity at the same or a much lower threshold level in the lower frequency range of 12-25 kHz (Table I). Interestingly, in only those species from which audiograms were recorded under anesthesia were thresholds for lower frequencies appreciably higher than for echolocation frequencies, except for Rhinopoma and two pipistrelles. It is therefore reasonable to assume that most if not all insectivorous and carnivorous bat species enjoy highest auditory sensitivity in the lower frequency range, which is the main energy band in rustling noises. By this general low-frequency sensitivity, echolocating bats may be attracted to the flight noises of swarming insects; may detect moving insects, spiders, or caterpillars on close inspection of vegetation; or may find larger ground-dwelling prey, such as frogs, lizards, birds, and mice moving even under cover. This common sensitivity to frequencies below those for echolocation may be a heritage from their insectivorous ancestry that also may have searched prey acoustically by listening to rustling noises, or it might be a general adaptations to prey detection at night in addition to echolocation. D. Acoustic
Prey Detection
on Water %rfaces
There are some species that preferably hunt over rivers, lakes, and marine coastlines and take prey from the water surface (136). Such species are No&&o Zeporinus, NoctiZio Zabialis (138), Pixonyx vivesi, Megaderma Zyra (137), Myotis adversus (19), and Myotis daubentoni (64). Some species have enlarged feet by which they gaff small fishes and arthropods from the water surface. Most of the fishing bats also feed on flying insects. Echolocation and audition of the fishing behavior is best examined in NoctiZio Zeporinus (136, 146,147). This bat detects its prey by echolocating water surface disturbances and commonly emits a brief CF-FM signal (CF, 56-59 kHz; FM, from CF frequency to maximally 28 kHz). In the experimental situation the bats emitted broadband signals by increasing the band width of the FM component and by adding a second harmonic FM component of low intensity whenever they started to fly over the pond. Because of the mediocre auditory sensitivity for frequencies from 60 to 90 kHz, echoes of the second harmonic will be only heard by the bat at close
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ranges of t2 m (146), which corresponds to the minimal distance of detection described by Suthers (137). An ideally smooth water surface will act as an acoustical mirror, and it should be difficult for echoloeating bats to receive an echo. Water ripples and objects protruding from the surface will create a kind of a texture on the water surface. Because all known fishing bat species use brief broadband signals during all fishing maneuvers, it is suggested that they detect and discriminate such fine or coarse surface textures as colored echoes (spectral interference patterns) in the same way as the ground-gleaning Megaderma Zyra (101). As suggested for Megaderrna, changing echo colors that indicate movements may be the most relevant cue for prey detection in fishing bats. A detected fish may submerge and become acoustically invisible. It would be advantageous for a fishing bat to predict the position of the submerged prey from an extrapolation of the fish’s relative swimming velocity. Therefore the ability to measure closing velocities relative to moving targets, i.e., the change of range between bat and target over time or the range rate per second, has been behaviorally tested (147). Noctilio Zeporinus is able to discriminate range rate differences of 35-45 cm/s and, indeed, lowers its feet for a catch at that position of the water surface where a tracked, linearly moving target is expected after it had suddenly submerged. This is the first and only experimental proof that bats use target range information to measure the velocities of moving targets. The results imply that the auditory system is capable of differentiating changes in echo arrival time of ilO0 ps. The authors exclude the possibility that target velocity was measured by Doppler shifts of the CF frequency. It is not clear for what purpose NoctiZio Zeporinus uses the CF component that is most prominent in perched and cruising bats. The bats are maximally sensitive to the CF frequency. Auditory thresholds steeply rise by 260-550 dB/octave for frequencies above CF frequency, whereas for frequencies below CF, thresholds only slightly increase over 2 kHz and then again fall to a minimum, creating a broad sensitivity peak from 50 to 20 kHz. Despite the shallow low-frequency slope, the auditory filter for the CF frequency is sharp enough to evoke Doppler-effect compensation, although incomplete, for increases of the CF echo frequency caused by the bat’s own flight speed. Recordings of auditory brain stem responses suggest that a large volume of neural tissue is dedicated to processing the frequency range from 16 to 32 kHz (146). This is the frequency band relevant for listening to prey-generated noises. It has to be emphasized that NoctiZio Zeporinus also feeds on flying insects, and some populations of fish-catching bats may do so exclusively (147). It is therefore suggested that the CF component may be used for detecting wing-beating insects by acoustical glints and the low-frequency sensitivity in audition may be used for detecting prey-generated noises.
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z.uo
VI.
GENERAL
AUDITION
IN
ECHOLOCATING
CONCLUSIONS
Apart from dolphins, bats are the only mammals that base the neural representation of the external world on audition. They are therefore good models for studying not only acoustical imaging but also specific and general auditory mechanisms. The results of auditory research in echolocation suggest that bats have not implemented new ways of auditory analysis not available to nonecholocating mammals but rather have refined and specialized the ones already existing. However, it is not yet clear what specifically differentiates an echolocating from a nonecholocating auditory system. It is a unique feature of echolocation that auditory stimuli, i.e., fast sequences of echoes, have to be detected and perceived strictly time locked to sound emissions. Studies on echo-range coding and on neuronal responses to stimuli mimicking sound echo pairs disclosed specific facilitations and fine time analysis, which is time locked to sound emissions or to the initial soundmimicking stimulus. Such time windows may be the key for understanding echolocation, and their specific neuronal basis may be subcortical delay lines with highly convergent auditory inputs. However, in the auditory brain of bats, so far no neuronal circuits have been physiologically or histologically identified that might generate such specific time windows for echolocation. Despite the incomplete evidence, it is safe to say that echolocation is achieved by specializations of neuronal auditory analysis in the time domain. This review focused on specific auditory adaptations to ecological constraints in echolocation: I) lowfrequency sensitivity for echolocation over long distances, Z) expanded frequency representations (auditory foveae) in the inner ear for clutter rejection (noise resistance) and for specific fluttering-target detection, 3) specific sensitivity to faint noises, and 4) the concept of echo-color perception as a possible means for detecting moving prey on echo-cluttering substrates. This review shows that these auditory specializations are closely linked to acoustical restraints of the habitats the bats use for searching and catching prey. It is apparent that these ecological limitations were and still are the driving forces for the evolution of such auditory specializations. Therefore detailed comparative studies that combine field observations of echolocation behavior with neuronal studies of audition will uncover to which utmost efficiencies mammalian auditory mechanisms may be driven by environmental selection. One of the best examples for this contention are the auditory foveae in hipposiderid bats, horseshoe bats, and the mustached bat. These foveae are narrowly tuned to an individual echo-carrier frequency and are the basis of the most sophisticated auditory system so far reported. For preventing echo clutter while searching for insects in dense jungles, these bats have driven cochlear frequency filtering to an unprecedented precision. In some of these bat species, effective clutter rejec-
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tion is paid by a restriction of prey detection to fluttering targets. Insects that do not beat their wings are not detected. The cochlear mechanisms that generate the extremely narrowly tuned frequency filters are not yet understood. Morphological specializations of the BM that are linked to the place where the fovea resides and the close correlation of the otoacoustic emission frequency with the center frequency of the fovea indicate that the narrow filtering may be achieved by the same mechanisms commonly ascribed to fine frequency analysis in mammals, for instance, resonant gain circuits working close to or in a ringing state (electromechanical interactions between inner and outer hair cells or mechanical reverberant, specialized portions of the basilar membrane). Therefore a study of the fovea1 mechanisms in these highly specialized auditory systems might also help to disclose the hitherto unknown details of fine frequency analysis in mammals and in humans. Many if not all ground-gleaning bat species circumvent echoclutter problems by dropping echolocation for prey detection. They listen and locate faint noises generated by their prey. The finding of auditory neurons with upper thresholds at such low intensities as 40 dB SPL combined with a specific sensitivity to noise signals reopens the debate on feature detectors in the auditory system. Only a systematic analysis of the responsiveness of such noise-sensitive neurons and their circuitry will show whether the brisk alertness of these bats to extremely faint noises is based on such neuronal “feature detectors.” Again, a highly specialized animal model, such as ground-gleaning bats, may help to elucidate how the auditory system categorizes spectral characteristics of auditory stimuli. A new aspect of auditory research may be highlighted by the behavioral studies on what was called echo colors. The behavioral experiments demonstrate that bats are able to differentiate complex spectral cues generated as interference patterns when broadband signals are reflected from a coarse surface. Auditory spectral analysis is potentially a powerful tool for differentiating surface structures that are smaller than the wavelengths of the echolocation signals. It could be used for identifying various prey species. This would require that bats learn, categorize, and memorize over long time spans different complex spectral patterns. It is difficult to conceive that bats use such learned spectral templates for recognizing prey species in a natural environment where the insect population consists of many different species and where its composition largely varies with seasons and climatical changes. In contrast, changing spectral patterns might be brisk and clear-cut indicators of a moving target, i.e., a potential prey, on an echo-cluttering complex background, such as foliage or grassland. For instance, if a beetle changes its posture or slowly moves on grass and hence changes the spatial structure of the sound-reflecting surface, the spectral pattern of the echo will change accordingly, and the peaks and troughs of the echo spectrum will shift to other frequencies (the echoes change their colors). . The concept of echo color or spectral pattern per-
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ception has interesting general perspectives. Bats might perceive such complex echoes as an acoustical “Gestalt,” as suggested by the finding that bats learn a spectral pattern and compare heard signals for similarity or nonsimilarity with the learned one. Auditory Gestalt perception would be an analogue in the frequency domain to Gestalt perception of visual contours in the spatial domain. In human audition there is ample evidence that complex spectra perceived as acoustical Gestalt play a dominant role in speech recognition and in listening to music. The auditory and neuronal basis for this fascinating perceptual performance has never been analyzed, most probably because there was no animal model for an experimental approach. Again, echolocating bats will be ideal subjects to study neurophysiologitally and behaviorally auditory perception in mammals on a level of complexity aequivalent to that of the real acoustical world. I am very J. H. Casseday, manuscript and This work Munich.
grateful to M. Ksssl, R. Riibsamen, E. Covey, and J. Wenstrup for critically reading the correcting the English. was supported by Grant SFB 204 “Gehiir,”
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14. EDAMATSU,
H., M. KAWASAKI, AND N. SUGA. Distribution of combination-sensitive neurons in the ventral fringe area the auditory cortex of the mustached bat. J Neurophysiol.
of
61:
202-207,1989. 15. EHRET, G. Masked 17.
18.
19. 20.
auditory thresholds, critical ratios, and scales of the basilar membrane of the housemouse (Mus muscu1~s). J Camp. Physiol. 103: 329-341, 1975. ENGELSTATTER, R. Hiirphysiologische Untersuchungen an Neuronen der aufsteigenden H&bahn der echoortenden Fledermaus Rhinolophus rouxi (PhD thesis). Frankfurt, FRG: Goethe Univ., 1981. FENG, A. S., AND M. VATER. Functional organization of the cochear nucleus of rufous horseshoe bats (Rhinolophus rouxi): frequency and internal connections are arranged in slabs. J. Camp. Neurol. 235: 529-553,1985. FENTON, M. B. Echolocation calls and patterns of hunting and habitat use of bats from Chillagoe, North Queensland. Aust. J 2001 30: 417-425,1982. FENTON, M. B. Design of bat echolocation calls: implications for foraging ecology and communication. Mammalia 50: 193-203,
1986. 21. FENTON, 22.
M. B., AND G. P. BELL. Echolocation and feeding behaviour in four species of Myotis. Can. J. 2001. 57: 1271-1277,1979. FENTON, M. B., AND G. P. BELL. Recognition of species of insectivorous bats by their echolocation calls. J Mammal. 62: 233-243,
1981. 23. FENTON, and
feeding
M. B., G. P. BELL, of Taphoxous
D. W. THOMAS. Echolocation mauritianus. Can. J. 2001. 58:
AND
1174-1777,198O. REFERENCES 1. ADVANI, R. Feeding ecology of Tadarida aegyptiaca in the Indian desert. 2. Saeugetierkd. 47: 18-22, 1982. 2. AITKIN, L. M., D. R. F. IRVINE, J. E. NELSON, M. M. MERZENICH, AND J. C. CLAREY. Frequency representation in the auditory midbrain and forebrain of a marsupial, the Northern native cat (Dasyurus hallucatus). Brain Behav. Evol. 29: 1728,1986. 3. AU, W. W. L., P. W. B. MOORE, AND D. A. PAWLOSKI. Detection of complex echoes in noise by an echolocating dolphin. J. Acoust. Sot. Am. 83: 662-668,1988. 4. BELL, G. P. Behavioral and ecological aspects of gleaning by a desert insectivorous bat, Antroxous pallidus. Behav. Ecol. Socio-
biol. 10: 217-223, 1982. 5. BELL, G. P., AND M. B. FENTON. The use of Doppler-shifted echoes as a flutter detection and clutter rejection system: the echolocation and feeding behavior of Hipposideros ruber. Behav. Ecol. Sociobiol. 15: 109-114, 1984. 6. BEUTER, K. A new concept of echo evaluation in the auditory system of bats. In: Animal Sonar Systems, edited by R. G. Busnel and J. F. Fish. New York: Plenum, 1980, p. 747-761. 7. BROWN, P. E., AND A. D. GRINNELL. Echolocation ontogeny in bats. In: Animal Sonar Systems, edited by R. G. Busnel and J. F. Fish. New York: Plenum, 1980, p. 355-377. 8. BRUNS, V. Peripheral auditory tuning for fine frequency analysis by the CF-FM bat, Rhinolophus ferrumequinum. II. Frequency mapping in the cochlea. J. Comp. Physiol. 106: 87-97,1976. 9. BRUNS, V., M. M. HENSON, H. J. KRAUS, AND J. FIEDLER. Vergleichende und funktionelle Morphologie der Fledermaus Cochlea. Myotis 19: 90-106, 1983. 10. BUCHLER, E. R., AND S. B. CHILDS. Orientation to distant sounds by foraging big brown bats (Eptesicus fuscus). Anim. Behav. 29: 428-432,198l. 11. COLES, R., A. GUPPY, M. E. ANDERSON, AND P. SCHLEGEL. Frequency sensitivity and directional hearing in the gleaning bat, Plecotus auritus. J. Camp. Physiol. 165: 269-280, 1989. 12. DALLAND, J. I. Hearing sensitivity in bats. Science Wash. DC
150:1185-1186,1965. 13. DUIFHUIS, H., AND M. VATER.
On the mechanics of the horseshoe bat cochlea. In: Peripheral Auditory Mechanisms, edited by J. B. Allen, J. L. Hall, A. Hubbard, S. T. Neely, and A. Tubis. Heidelberg, FRG: Springer-Verlag, 1985, p. 89-96.
23a.FENTON, M. B., P. RACEY, AND J. M. V. RAYNER (Editors). International Animal Sonar Symposium. London: Cambridge Univ. Press, 1987. 24. FIEDLER, J. Prey catching with and without echolocation in the Indian false vampire (Megaderma lyra). Behav. Ecol. Sociobiol. 6:
155-160,1979. 25. FITZPATRICK, K. A. Cellular architecture and topographic organization of the inferior colliculus of the squirrel monkey. J. Comp. Neurol. 164:185-208,1975. 26. FULLARD, J. H., M. B. FENTON, AND J. A. SIMMONS. Jamming bat echolocation: the clicks of arctiid moths. Can. J. 2001. 57: 647-649,1979. 27. GOLDMAN, L. J., AND 0. W. HENSON. Prey recognition and selection by the constant frequency bat, Pteronotus parnellii. Behav. Ecol. Sociobiol. 2: 411-419, 1977. 28. GRINNELL, A. D. The neurophysiology of audition in bats: intensity and frequency parameters. J. Physiol. Land. 167: 38-66,
1963. 29. GRINNELL, A. D. The neurophysiology of audition in bats: temporal parameters. J Physiol. Lond. 167: 67-96, 1963. 30. GRINNELL, A. D. Comparative auditory neurophysiology of neotropical bats employing different echolocation signals. 2. Vgl. Physiol. 68: 117-153, 1970. 31. GRINNELL, A. D., AND S. HAGIWARA. Adaptations of the auditory nervous system for echolocation. Studies of New Guinea bats. 2. Vgl. Physiol. 76: 41-81, 1972. 32. GUPPY, A., AND R. B. COLES. Acoustical and neural aspects of hearing in the Australian gleaning bats, Macroderma gigas and Nyctophilus gouldi. J Camp. Physiol. 162: 653-668, 1988. 33. HABERSETZER, J., G. SCHULLER, AND G. NEUWEILER. Foraging behavior and Doppler shift compensation in echolocating hipposiderid bats, Hipposideros bicolor and Hipposideros speoris. J Comp. Physiol. 155: 559-567, 1984. 34. HABERSETZER, J., AND B. VOGLER. Discrimination of surface-structured targets by the echolocating bat Myotis myotis during flight. J. Comp. Physiol. 152: 275-282, 1983. 35. HEFFNER, H., AND B. MASTERTON. Hearing in glirea: domestic rabbit, cotton rat, feral mouse, and kangaroo rat. J. Acoust. Sot. Am 68: 1584-1599,198O. 36. HEILIGENBERG, W. Central processing of sensory information in electric fish. J. Comp. Physiol. 161: 621-631, 1987. 37. HENSON, M. M. The basilar membrane of the bat Pteronotus parnellii. Am. J. Anat. 153: 143-159, 1978. 38. HENSON, M. M., 0. W. HENSON, AND L. J. GOLDMAN. The
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1990
AUDITION
IN ECHOLOCATING
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