A modeling approach to explain pulse design in bats

Amplitude discrimination is predictably affected by echo frequency filtering in wideband echolocating bats

Big brown bats echolocate using wideband frequency-modulated (FM) ultrasonic pulses, perceiving target range from echo delay and target size from echo amplitude. Echolocation pulses contain two prominent down-sweeping harmonics (FM1, ∼55-22 kHz; FM2, ∼100-55 kHz), which are affected differently by propagation to the target and back to the bat. Previous work demonstrates that big brown bats utilize the low frequencies in FM1 for target ranging, while FM2 only contributes if FM1 is also present. The present experiments test the hypothesis that the bat's ability to discriminate echo amplitude is also affected by selectively attenuating FM1 or FM2 in target or nontarget echoes. Bats were trained to perform an amplitude discrimination task with virtual echo targets located 83 cm away. Echo delay was fixed and echo amplitude was varied, while either FM1 or FM2 was attenuated by highpass or lowpass filtering. Bats' performance decreased when lower frequencies were attenuated in target echoes and when higher frequencies were attenuated in nontarget echoes. Performance was reversed in the opposite filtering conditions. The bat's ability to distinguish between virtual targets varying in amplitude at the same simulated range indicates a high level of focused attention for perceptual isolation of target from non-target echoes.

Functional differences in echolocation call design in an adaptive radiation of bats

All organisms have specialized systems to sense their environment. Most bat species use echolocation for navigation and foraging, but which and how ecological factors shaped echolocation call diversity remains unclear for the most diverse clades, including the adaptive radiation of neotropical leaf-nosed bats (Phyllostomidae). This is because phyllostomids emit low-intensity echolocation calls and many inhabit dense forests, leading to low representation in acoustic surveys. We present a field-collected, echolocation call dataset spanning 35 species and all phyllostomid dietary guilds. We analyze these data under a phylogenetic framework to test the hypothesis that echolocation call design and parameters are specialized for the acoustic demands of different diets, and investigate the contributions of phylogeny and body size to echolocation call diversity. We further link call parameters to dietary ecology by contrasting minimum detectable prey size estimates (MDPSE) across species. We find phylogeny and body size explain a substantial proportion of echolocation call parameter diversity, but most species can be correctly assigned to taxonomic (61%) or functional (77%) dietary guilds based on call parameters. This suggests a degree of acoustic ecological specialization, albeit with interspecific similarities in call structure. Theoretical MDPSE are greatest for omnivores and smallest for insectivores. Omnivores significantly differ from other dietary guilds in MDPSE when phylogeny is not considered, but there are no differences among taxonomic dietary guilds within a phylogenetic context. Similarly, predators of non-mobile/non-evasive prey and predators of mobile/evasive prey differ in estimated MDPSE when phylogeny is not considered. Phyllostomid echolocation call structure may be primarily specialized for overcoming acoustic challenges of foraging in dense habitats, and then secondarily specialized for the detection of food items according to functional dietary guilds. Our results give insight into the possible ecological mechanisms shaping the diversity of sensory systems, and their reciprocal influence on resource use.

A sensorimotor model shows why a spectral jamming avoidance response does not help bats deal with jamming

For decades, researchers have speculated how echolocating bats deal with masking by conspecific calls when flying in aggregations. To date, only a few attempts have been made to mathematically quantify the probability of jamming, or its effects. We developed a comprehensive sensorimotor predator-prey simulation, modeling numerous bats foraging in proximity. We used this model to examine the effectiveness of a spectral Jamming Avoidance Response (JAR) as a solution for the masking problem. We found that foraging performance deteriorates when bats forage near conspecifics, however, applying a JAR does not improve insect sensing or capture. Because bats constantly adjust their echolocation to the performed task (even when flying alone), further shifting the signals' frequencies does not mitigate jamming. Our simulations explain how bats can hunt successfully in a group despite competition and despite potential masking. This research demonstrates the advantages of a modeling approach when examining a complex biological system.

Active acoustic interference elicits echolocation changes in heterospecific bats

Echolocating bats often forage in the presence of both conspecific and heterospecific individuals, which have the potential to produce acoustic interference. Recent studies have shown that at least one bat species, the Brazilian free-tailed bat (Tadarida brasiliensis), produces specialized social signals that disrupt the sonar of conspecific competitors. We herein discuss the differences between passive and active jamming signals and test whether heterospecific jamming occurs in species overlapping spatiotemporally, as well as whether such interference elicits a jamming avoidance response. We compare the capture rates of tethered moths and the echolocation parameters of big brown bats (Eptesicus fuscus) challenged with the playback of the jamming signal normally produced by Brazilian free-tailed bats and playback of deconstructed versions of this signal. There were no differences in the capture rates of targets with and without the jamming signal, although significant changes in both spectral and temporal features of the bats' echolocation were observed. These changes are consistent with improvements of the signal-to-noise ratio in the presence of acoustic interference. Accordingly, we propose to expand the traditional definition of the jamming avoidance response, stating that echolocation changes in response to interference should decrease similarity between the two signals, to include any change that increases the ability to separate returning echoes from active jamming stimuli originating from conspecific and heterospecific organisms. Flexibility in echolocation is an important characteristic for overcoming various forms of acoustic interference and may serve a purpose in interspecific interactions as well as intraspecific ones.

Big brown bats (Eptesicus fuscus) reveal diverse strategies for sonar target tracking in clutter

Bats actively adjust the acoustic features of their sonar calls to control echo information specific to a given task and environment. A previous study investigated how bats adapted their echolocation behavior when tracking a moving target in the presence of a stationary distracter at different distances and angular offsets. The use of only one distracter, however, left open the possibility that a bat could reduce the interference of the distracter by turning its head. Here, bats tracked a moving target in the presence of one or two symmetrically placed distracters to investigate adaptive echolocation behavior in a situation where vocalizing off-axis would result in increased interference from distracter echoes. Both bats reduced bandwidth and duration but increased sweep rate in more challenging distracter conditions, and surprisingly, made more head turns in the two-distracter condition compared to one, but only when distracters were placed at large angular offsets. However, for most variables examined, subjects showed distinct strategies to reduce clutter interference, either by (1) changing spectral or temporal features of their calls, or (2) producing large numbers of sonar sound groups and consistent head-turning behavior. The results suggest that individual bats can use different strategies for target tracking in cluttered environments.

Object localization using a biosonar beam: how opening your mouth improves localization

Determining the location of a sound source is crucial for survival. Both predators and prey usually produce sound while moving, revealing valuable information about their presence and location. Animals have thus evolved morphological and neural adaptations allowing precise sound localization. Mammals rely on the temporal and amplitude differences between the sound signals arriving at their two ears, as well as on the spectral cues available in the signal arriving at a single ear to localize a sound source. Most mammals rely on passive hearing and are thus limited by the acoustic characteristics of the emitted sound. Echolocating bats emit sound to perceive their environment. They can, therefore, affect the frequency spectrum of the echoes they must localize. The biosonar sound beam of a bat is directional, spreading different frequencies into different directions. Here, we analyse mathematically the spatial information that is provided by the beam and could be used to improve sound localization. We hypothesize how bats could improve sound localization by altering their echolocation signal design or by increasing their mouth gape (the size of the sound emitter) as they, indeed, do in nature. Finally, we also reveal a trade-off according to which increasing the echolocation signal's frequency improves the accuracy of sound localization but might result in undesired large localization errors under low signal-to-noise ratio conditions.

Localization and tracking of moving objects in two-dimensional space by echolocation

Bats use frequency-modulated echolocation to identify and capture moving objects in real three-dimensional space. Experimental evidence indicates that bats are capable of locating static objects with a range accuracy of less than 1 μs. A previously introduced model estimates ranges of multiple, static objects using linear frequency modulation (LFM) sound and Gaussian chirplets with a carrier frequency compatible with bat emission sweep rates. The delay time for a single object was estimated with an accuracy of about 1.3 μs by measuring the echo at a low signal-to-noise ratio (SNR). The range accuracy was dependent not only on the SNR but also the Doppler shift, which was dependent on the movements. However, it was unclear whether this model could estimate the moving object range at each timepoint. In this study, echoes were measured from the rotating pole at two receiving points by intermittently emitting LFM sounds. The model was shown to localize moving objects in two-dimensional space by accurately estimating the object's range at each timepoint.

Evaluation of the echolocation model for range estimation of multiple closely spaced objects

Experimental evidence indicates that bats can use frequency-modulated echolocation to identify objects with an accuracy of less than 1 μs. However, when modeling this process, it is difficult to estimate the delay times of multiple closely spaced objects by analyzing the echo spectrum, because the sequence of delay separations cannot be determined without information on the temporal changes in the interference patterns of the echoes. To extract the temporal changes, Gaussian chirplets with a carrier frequency compatible with bat emission sweep rates are introduced. The delay time for object 1 (T(1)) is estimated from the echo spectrum around the onset time. The T(2) is obtained by adding the T(1) to the delay separation between objects 1 and 2. Further objects are located in sequence by this procedure. Here echoes were measured from single and multiple objects at a low signal-to-noise ratio. It was confirmed that the delay time for a single object could be estimated with an accuracy of about 1.3 μs. The range accuracy was less than 6 μs when the frequency bandwidth was less than 10 kHz. The delay time for multiple closely spaced objects could be estimated with a high range resolution by extracting the interference pattern.

High duty cycle echolocation and prey detection by bats

There are two very different approaches to laryngeal echolocation in bats. Although most bats separate pulse and echo in time by signalling at low duty cycles (LDCs), almost 20% of species produce calls at high duty cycles (HDCs) and separate pulse and echo in frequency. HDC echolocators are sensitive to Doppler shifts. HDC echolocation is well suited to detecting fluttering targets such as flying insects against a cluttered background. We used two complementary experiments to evaluate the relative effectiveness of LDC and HDC echolocation for detecting fluttering prey. We measured echoes from fluttering targets by broadcasting artificial bat calls, and found that echo amplitude was greatest for sounds similar to those used in HDC echolocation. We also collected field recordings of syntopic LDC and HDC bats approaching an insect-like fluttering target and found that HDC bats approached the target more often (18.6% of passes) than LDC bats (1.2% of passes). Our results suggest that some echolocation call characteristics, particularly duty cycle and pulse duration, translate into improved ability to detect fluttering targets in clutter, and that HDC echolocation confers a superior ability to detect fluttering prey in the forest understory compared with LDC echolocation. The prevalence of moths in the diets of HDC bats, which is often used as support for the allotonic frequency hypothesis, can therefore be partly explained by the better flutter detection ability of HDC bats.

Complex echo classification by echo-locating bats: a review

Echo-locating bats constantly emit ultrasonic pulses and analyze the returning echoes to detect, localize, and classify objects in their surroundings. Echo classification is essential for bats' everyday life; for instance, it enables bats to use acoustical landmarks for navigation and to recognize food sources from other objects. Most of the research of echo based object classification in echo-locating bats was done in the context of simple artificial objects. These objects might represent prey, flower, or fruit and are characterized by simple echoes with a single up to several reflectors. Bats, however, must also be able to use echoes that return from complex structures such as plants or other types of background. Such echoes are characterized by superpositions of many reflections that can only be described using a stochastic statistical approach. Scientists have only lately started to address the issue of complex echo classification by echo-locating bats. Some behavioral evidence showing that bats can classify complex echoes has been accumulated and several hypotheses have been suggested as to how they do so. Here, we present a first review of this data. We raise some hypotheses regarding possible interpretations of the data and point out necessary future directions that should be pursued.

What a plant sounds like: the statistics of vegetation echoes as received by echolocating bats

A critical step on the way to understanding a sensory system is the analysis of the input it receives. In this work we examine the statistics of natural complex echoes, focusing on vegetation echoes. Vegetation echoes constitute a major part of the sensory world of more than 800 species of echolocating bats and play an important role in several of their daily tasks. Our statistical analysis is based on a large collection of plant echoes acquired by a biomimetic sonar system. We explore the relation between the physical world (the structure of the plant) and the characteristics of its echo. Finally, we complete the story by analyzing the effect of the sensory processing of both the echolocation and the auditory systems on the echoes and interpret them in the light of information maximization. The echoes of all different plant species we examined share a surprisingly robust pattern that was also reproduced by a simple Poisson model of the spatial reflector arrangement. The fine differences observed between the echoes of different plant species can be explained by the spatial characteristics of the plants. The bat's emitted signal enhances the most informative spatial frequency range where the species-specific information is large. The auditory system filtering affects the echoes in a similar way, thus enhancing the most informative spatial frequency range even more. These findings suggest how the bat's sensory system could have evolved to deal with complex natural echoes.

Determining biosonar images using sparse representations

Echolocating bats are thought to be able to create an image of their environment by emitting pulses and analyzing the reflected echoes. In this paper, the theory of sparse representations and its more recent further development into compressed sensing are applied to this biosonar image formation task. Considering the target image representation as sparse allows formulation of this inverse problem as a convex optimization problem for which well defined and efficient solution methods have been established. The resulting technique, referred to as L1-minimization, is applied to simulated data to analyze its performance relative to delay accuracy and delay resolution experiments. This method performs comparably to the coherent receiver for the delay accuracy experiments, is quite robust to noise, and can reconstruct complex target impulse responses as generated by many closely spaced reflectors with different reflection strengths. This same technique, in addition to reconstructing biosonar target images, can be used to simultaneously localize these complex targets by interpreting location cues induced by the bat's head related transfer function. Finally, a tentative explanation is proposed for specific bat behavioral experiments in terms of the properties of target images as reconstructed by the L1-minimization method.

Role of broadcast harmonics in echo delay perception by big brown bats

Big brown bats (Eptesicus fuscus) emit frequency-modulated (FM) echolocation sounds containing two principal down-sweeping harmonics (FM(1) approximately 55-25 kHz, FM(2) approximately 105-50 kHz). To determine whether each harmonic contributes to perception of echo delay, bats were trained to discriminate between "split-harmonic" echoes that differed in delay. The bat's broadcasts were picked up with microphones, and FM(1) and FM(2) were separated with highpass and lowpass filters at about 55 kHz, where they overlap in frequency. Both harmonics then were delivered from loudspeakers as positive stimuli in a 2-choice delay discrimination procedure with FM(1) delayed 3.16 ms and FM(2) delayed 3.46 ms (300 mus delay split). Negative stimuli contained FM(1) and FM(2) with the same filtering but no delay separation. These were presented at different overall delays from 11 down to 3 ms to measure the bat's delay discrimination acuity for each harmonic in the split harmonic echoes. The bats determined the delays of both FM(1) and FM(2), but performance was overlaid by a broad pedestal of poor performance that extended for 800 micros. Splitting the harmonics by 300 micros appears to defocus the bat's representation of delay, revealing the existence of a process for recognizing the normally simultaneous occurrence of the harmonics.

Comparing passive and active hearing: spectral analysis of transient sounds in bats

In vision, colour constancy allows the evaluation of the colour of objects independent of the spectral composition of a light source. In the auditory system, comparable mechanisms have been described that allows the evaluation of the spectral shape of sounds independent of the spectral composition of ambient background sounds. For echolocating bats, the evaluation of spectral shape is vitally important both for the analysis of external sounds and the analysis of the echoes of self-generated sonar emissions. Here, we investigated how the echolocating bat Phyllostomus discolor evaluates the spectral shape of transient sounds both in passive hearing and in echolocation as a specialized mode of active hearing. Bats were trained to classify transients of different spectral shape as low- or highpass. We then assessed how the spectral shape of an ambient background noise influenced the spontaneous classification of the transients. In the passive-hearing condition, the bats spontaneously changed their classification boundary depending on the spectral shape of the background. In the echo-acoustic condition, the classification boundary did not change although the background-and spectral-shape manipulations were identical in the two conditions. These data show that auditory processing differs between passive and active hearing:echolocation represents an independent mode of active hearing with its own rules of auditory spectral analysis.

An autocorrelation model of bat sonar

Their sonar system allows echolocating bats to navigate with high skill through a complex, three- dimensional environment at high speed and low light. The auditory analysis of the echoes of their ultrasonic sounds requires a detailed comparison of the emission and echoes. Here an auditory model of bat sonar is introduced and evaluated against a set of psychophysical phantom-target, echo-acoustic experiments. The model consists of a relatively detailed simulation of auditory peripheral processing in the bat, Phyllostomus discolor, followed by a functional module consisting of a strobed, normalised, autocorrelation in each frequency channel. The model output is accumulated in a sonar image buffer. The model evaluation is based on the comparison of the image-buffer contents generated in individually simulated psychophysical trials. The model provides reasonably good predictions for both temporal and spectral behavioural sonar processing in terms of sonar delay-, roughness, and phase sensitivity and in terms of sensitivity to the temporal separations in two-front targets and the classification of spectrally divergent phantom targets.

Understanding signal design during the pursuit of aerial insects by echolocating bats: tools and applications

Bats are among the few predators that can exploit the large quantities of aerial insects active at night. They do this by using echolocation to detect, localize, and classify targets in the dark. Echolocation calls are shaped by natural selection to match ecological challenges. For example, bats flying in open habitats typically emit calls of long duration, with long pulse intervals, shallow frequency modulation, and containing low frequencies-all these are adaptations for long-range detection. As obstacles or prey are approached, call structure changes in predictable ways for several reasons: calls become shorter, thereby reducing overlap between pulse and echo, and calls change in shape in ways that minimize localization errors. At the same time, such changes are believed to support recognition of objects. Echolocation and flight are closely synchronized: we have monitored both features simultaneously by using stereo photogrammetry and videogrammetry, and by acoustic tracking of flight paths. These methods have allowed us to quantify the intensity of signals used by free-living bats, and illustrate systematic changes in signal design in relation to obstacle proximity. We show how signals emitted by aerial feeding bats can be among the most intense airborne sounds in nature. Wideband ambiguity functions developed in the processing of signals produce two-dimensional functions showing trade-offs between resolution of time and velocity, and illustrate costs and benefits associated with Doppler sensitivity and range resolution in echolocation. Remarkably, bats that emit broadband calls can adjust signal design so that Doppler-related overestimation of range compensates for underestimation of range caused by the bat's movement in flight. We show the potential of our methods for understanding interactions between echolocating bats and those prey that have evolved ears that detect bat calls.