Bats enhance their call identities to solve the cocktail party problem

Theoretical investigation of active listening behavior based on the echolocation of CF-FM bats

Bats perceive the three-dimensional environment by emitting ultrasound pulses from their nose or mouth and receiving echoes through both ears. To determine the position of a target object, it is necessary to know the distance and direction of the target. Certain bat species that use a combined signal of long constant frequency and short frequency modulated ultrasounds synchronize their pinnae movement with pulse emission, and this behavior has been regarded as helpful for localizing the elevation angle of a reflective sound source. However, the significance of bats' ear motions remains unclear. In this study, we construct a model of an active listening system including the motion of the ears, and conduct mathematical investigations to clarify the importance of ear motion in direction detection of the reflective sound source. In the simulations, direction detection under rigid ear movements with interaural level differences was mathematically investigated by assuming that bats accomplish direction detection using the amplitude modulation in the echoes caused by ear movements. In particular, the ear motion conditions required for direction detection are theoretically investigated through exhaustive simulations of the pseudo-motion of the ears, rather than simulations of the actual ear motions of bats. The theory suggests that only certain ear motions, namely three-axis rotation, allow for accurate and robust direction detection. Our theoretical analysis also strongly supports the behavior whereby bats move their pinnae in the antiphase mode. In addition, we suggest that simple shaped hearing directionality and well-selected uncomplicated ear motions are sufficient to achieve precise and robust direction detection. Our findings and mathematical approach have the potential to be used in the design of active sensing systems in various engineering fields.

Effect of bat pinna on sensing using acoustic finite difference time domain simulation

The practicality of the finite-difference time-domain (FDTD) method was confirmed by comparing head-related transfer functions obtained from a three-dimensional (3D) digital model of a bat (Rhinolophus ferrumequinum nippon) head with acoustic experiments using a 3D printed physical model. Furthermore, we simulated the auditory directionality using a 3D digital model that was modified based on the pinna movement of a bat during echolocation and found that the alternating movements of the left and right pinna result in a binaural sound pressure difference for vertical sources. Using the FDTD method, suitable for simulating acoustics in large spaces, we could analyze in detail the binaural echoes that bats receive and the acoustic cues they use for echolocation.

Echo reception in group flight by Japanese horseshoe bats, Rhinolophus ferrumequinum nippon

The ability to detect behaviourally relevant sensory information is crucial for survival. Especially when active-sensing animals behave in proximity, mutual interferences may occur. The aim of this study was to examine how active-sensing animals deal with mutual interferences. Echolocation pulses and returning echoes were compared in spaces of various sizes (wide and narrow) in Rhinolophus ferrumequinum nippon flying alone or in a group of three bats. We found that in the narrow space, the group-flying bats increased the duration and bandwidth of the terminal frequency-modulated component of their vocalizations. By contrast, the frequency of the returning echoes did not differ in the presence of conspecifics. We found that their own echo frequencies were compensated within the narrow frequency ranges by Doppler shift compensation. By contrast, the estimated frequencies of the received pulses emitted by the other bats were much more broadly distributed than their echoes. Our results suggest that the bat auditory systems are sharply tuned to a narrow frequency to filter spectral interference from other bats.

Three-Dimensional Trajectory Construction and Observation of Group Behavior of Wild Bats During Cave Emergence

Echolocating bats perceive the surrounding environment by processing echoes of their ultrasound emissions. Echolocation enables bats to avoid colliding with external objects in complete darkness. In this study, we sought to develop a method for measuring the collective behavior of echolocating bats (Miniopterus fuliginosus) emerging from their roost cave using high-sensitivity stereo-camera recording. First, we developed an experimental system to reconstruct the three-dimensional (3D) flight trajectories of bats emerging from the roost for nightly foraging. Next, we developed a method to automatically track the 3D flight paths of individual bats so that quantitative estimation of the population in proportion to the behavioral classification could be conducted. Because the classification of behavior and the estimation of population size are ecologically important indices, the method established in this study will enable quantitative investigation of how individual bats efficiently leave the roost while avoiding colliding with each other during group movement and how the group behavior of bats changes according to weather and environmental conditions. Such high-precision detection and tracking will contribute to the elucidation of the algorithm of group behavior control in creatures that move in groups together in three dimensions, such as birds.

Absence of Jamming Avoidance and Flight Path Similarity in Paired Bent-Winged Bats,

Echolocating bats perceive their surroundings by listening to the echoes of self-generated ultrasound pulses. When multiple conspecifics fly in close proximity to each other, sounds emitted from nearby individuals could mutually interfere with echo reception. Many studies suggest that bats employ frequency shifts to avoid spectral overlap of pulses with other bats. Technical constraints in recording technology have made it challenging to capture subtle changes in the pulse characteristics of bat calls. Therefore, how bats change their behavior to extract their own echoes in the context of acoustic interference remains unclear. Also, to our best knowledge, no studies have investigated whether individual flight paths change when other bats are present, although movements likely reduce acoustic masking. Here, we recorded the echolocation pulses of bats flying alone or in pairs using telemetry microphones. Flight trajectories were also reconstructed using stereo camera recordings. We found no clear tendency to broaden individual differences in the acoustic characteristics of pulses emitted by pairs of bats compared to bats flying alone. However, some bats showed changes in pulse characteristics when in pairs, which suggests that bats can recognize their own calls based on the initial differences in call characteristics between individuals. In addition, we found that the paired bats spend more time flying in the same directions than in the opposite directions. Besides, we found that the flight paths of bats were more similar in “paired flight trials” than in virtual pairs of paired flight trials. Our results suggest that the bats tend to follow the other bat in paired flight. For the following bat, acoustic interference may be reduced, while the opportunity to eavesdrop on other bats’ calls may be increased.

The second harmonic neurons in auditory midbrain of Hipposideros pratti are more tolerant to background white noise

Although acoustic communication is inevitably influenced by noise, behaviorally relevant sounds are perceived reliably. The noise-tolerant and -invariant responses of auditory neurons are thought to be the underlying mechanism. So, it is reasonable to speculate that neurons with best frequency tuned to behaviorally relevant sounds will play important role in noise-tolerant perception. Echolocating bats live in groups and emit multiple harmonic signals and analyze the returning echoes to extract information about the target features, making them prone to deal with noise in their natural habitat. The echolocation signal of Hipposideros pratti usually contains 3-4 harmonics (H₁H₄), the second harmonic has the highest amplitude and is thought to play an essential role during echolocation behavior. Therefore, it is reasonable to propose that neurons tuned to the H₂, named the H₂ neurons, can be more noise-tolerant to background noise. Taking advantage of bat's stereotypical echolocation signal and single-cell recording, our present study showed that the minimal threshold increases (12.2 dB) of H₂ neurons in the auditory midbrain were comparable to increase in bat's call intensity (14.2 dB) observed in 70 dB SPL white noise condition, indicating that the H₂ neurons could work as background noise monitor. The H₂ neurons had higher minimal thresholds and sharper frequency tuning, which enabled them to be more tolerant to background noise. Furthermore, the H₂ neurons had consistent best amplitude spikes and sharper intensity tuning in background white noise condition than in silence. Taken together, these results suggest that the H₂ neurons might account for noise-tolerant perception of behaviorally relevant sounds.

Modulation of acoustic navigation behaviour by spatial learning in the echolocating bat Rhinolophus ferrumequinum nippon

Using echolocation, bats receive acoustic information on their surroundings, which is assumed to help them sophisticatedly navigate complex environments. In this study, to understand spatial learning and acoustic sensing in bats, we investigated how flight and echolocation control changed in Rhinolophus ferrumequinum nippon as they learnt about their surroundings in an obstacle course that they flew through repeatedly. In these experiments, two testing environments (acoustically permeable and acoustically reflective) were prepared using chains and acrylic boards as obstacles to evaluate the interactive effects of spatial learning and flight environments. We found that bats reduced the meandering width of their flights and pulse emissions, and also seemed to reduce their shifts in pulse direction as they learnt more about their environments in both conditions. Throughout all our experiments, the bats with slower flight speeds tended to emit more pulses, which suggests that the number of pulse emissions reflects the echolocation tactics of each bat. The maximum flight speed was especially increased in the acoustically permeable condition, with frequent emissions of multiple pulses (≧triplets) in the early stages of flight, suggesting that bats adjust their flight plan based on how much of their surroundings they are able to sense in advance.

Defining "active sensing" through an analysis of sensing energetics: homeoactive and alloactive sensing

The term "active sensing" has been defined in multiple ways. Most strictly, the term refers to sensing that uses self-generated energy to sample the environment (e.g., echolocation). More broadly, the definition includes all sensing that occurs when the sensor is moving (e.g., tactile stimuli obtained by an immobile versus moving fingertip) and, broader still, includes all sensing guided by attention or intent (e.g., purposeful eye movements). The present work offers a framework to help disambiguate aspects of the "active sensing" terminology and reveals properties of tactile sensing unique among all modalities. The framework begins with the well-described "sensorimotor loop," which expresses the perceptual process as a cycle involving four subsystems: environment, sensor, nervous system, and actuator. Using system dynamics, we examine how information flows through the loop. This "sensory-energetic loop" reveals two distinct sensing mechanisms that subdivide active sensing into homeoactive and alloactive sensing. In homeoactive sensing, the animal can change the state of the environment, while in alloactive sensing the animal can alter only the sensor's configurational parameters and thus the mapping between input and output. Given these new definitions, examination of the sensory-energetic loop helps identify two unique characteristics of tactile sensing: 1) in tactile systems, alloactive and homeoactive sensing merge to a mutually controlled sensing mechanism, and 2) tactile sensing may require fundamentally different predictions to anticipate reafferent input. We expect this framework may help resolve ambiguities in the active sensing community and form a basis for future theoretical and experimental work regarding alloactive and homeoactive sensing.

Separation of overlapping sources in bioacoustic mixtures

Source separation is an important step to study signals that are not easy or possible to record individually. Common methods such as deep clustering, however, cannot be applied to signals of an unknown number of sources and/or signals that overlap in time and/or frequency-a common problem in bioacoustic recordings. This work presents an approach, using a supervised learning framework, to parse individual sources from a spectrogram of a mixture that contains a variable number of overlapping sources. This method isolates individual sources in the time-frequency domain using only one function but in two separate steps, one for the detection of the number of sources and corresponding bounding boxes, and a second step for the segmentation in which masks of individual sounds are extracted. This approach handles the full separation of overlapping sources in both time and frequency using deep neural networks in an applicable manner to other tasks such as bird audio detection. This paper presents method and reports on its performance to parse individual bat signals from recordings containing hundreds of overlapping bat echolocation signals. This method can be extended to other bioacoustic recordings with a variable number of sources and signals that overlap in time and/or frequency.

Modeling active sensing reveals echo detection even in large groups of bats

Active sensing animals perceive their surroundings by emitting probes of energy and analyzing how the environment modulates these probes. However, the probes of conspecifics can jam active sensing, which should cause problems for groups of active sensing animals. This problem was termed the cocktail party nightmare for echolocating bats: as bats listen for the faint returning echoes of their loud calls, these echoes will be masked by the loud calls of other close-by bats. Despite this problem, many bats echolocate in groups and roost socially. Here, we present a biologically parametrized framework to quantify echo detection in groups. Incorporating properties of echolocation, psychoacoustics, acoustics, and group flight, we quantify how well bats flying in groups can detect each other despite jamming. A focal bat in the center of a group can detect neighbors in group sizes of up to 100 bats. With increasing group size, fewer and only the closest and frontal neighbors are detected. Neighbor detection is improved by longer call intervals, shorter call durations, denser groups, and more variable flight and sonar beam directions. Our results provide a quantification of the sensory input of echolocating bats in collective group flight, such as mating swarms or emergences. Our results further generate predictions on the sensory strategies bats may use to reduce jamming in the cocktail party nightmare. Lastly, we suggest that the spatially limited sensory field of echolocators leads to limited interactions within a group, so that collective behavior is achieved by following only nearest neighbors.

Behaviour, biology and evolution of vocal learning in bats

The comparative approach can provide insight into the evolution of human speech, language and social communication by studying relevant traits in animal systems. Bats are emerging as a model system with great potential to shed light on these processes given their learned vocalizations, close social interactions, and mammalian brains and physiology. A recent framework outlined the multiple levels of investigation needed to understand vocal learning across a broad range of non-human species, including cetaceans, pinnipeds, elephants, birds and bats. Here, we apply this framework to the current state-of-the-art in bat research. This encompasses our understanding of the abilities bats have displayed for vocal learning, what is known about the timing and social structure needed for such learning, and current knowledge about the prevalence of the trait across the order. It also addresses the biology (vocal tract morphology, neurobiology and genetics) and evolution of this trait. We conclude by highlighting some key questions that should be answered to advance our understanding of the biological encoding and evolution of speech and spoken communication. This article is part of the theme issue 'What can animal communication teach us about human language?'

Biosonar interpulse intervals and pulse-echo ambiguity in four species of echolocating bats

In complex biosonar scenes, the delay of echoes represents the spatial distribution of objects in depth. To avoid overlap of echo streams from successive broadcasts, individual echolocation sounds should only be emitted after all echoes of previous sounds have returned. However, close proximity of obstacles demands rapid pulse updates for steering to avoid collisions, which often means emitting a new sound before all of the previous echoes have returned. When two echo streams overlap, there is ambiguity about assigning echoes to the corresponding broadcasts. In laboratory tests of flight in dense, cluttered scenes, four species of echolocating bats exhibited different patterns of pulse emissions to accommodate potential pulse-echo ambiguity. Miniopterus fuliginosus emitted individual FM pulses only after all echoes of previous pulses had returned, with no alternating between long and short intervals. Pipistrellus abramus and Eptesicus fuscus alternated between emitting long FM pulse intervals to receive all echoes before the next pulse, and short intervals to update the rapidly changing scene while accepting partial overlap of successive echo streams. Rhinolophus ferrumequinum nippon transmitted CF/FM pulses in alternating short and long intervals, usually two to four closely spaced sounds that produced overlapping echo streams, followed by a longer interval that separated echo streams. Rhinolophus f. nippon is a statistical outlier from the three FM species, which are more similar to each other. The repeated overlap of CF/FM echo streams suggests that CF components have a distinct role in rejection of clutter and mitigation of ambiguity.

Adaptive frequency shifts of echolocation sounds in Miniopterus fuliginosus according to the frequency-modulated pattern of jamming sounds

When flying in a group, echolocating bats have to separate their own echoes from pulses and echoes belonging to other individuals to extract only the information necessary for their own navigation. Previous studies have demonstrated that frequency-modulated (FM) bats change the terminal frequencies (TFs) of downward FM pulses under acoustic interference. However, it is not yet clear which acoustic characteristics of the jamming signals induce the TF shift according to the degree of acoustic interference. In this study, we examined changes in the acoustic characteristics of pulses emitted by Miniopterus fuliginosus while presenting jamming stimuli with different FM patterns to the bat flying alone. Bats significantly altered their TFs when responding to downward (dExp) and upward (uExp) exponential FM sounds as well as to a constant-frequency (CF) stimulus, by approximately 1-2 kHz (dExp: 2.1±0.9 kHz; uExp: 1.7±0.3 kHz; CF: 1.3±0.4 kHz) but not for linear FM sounds. The feature common to the spectra of these three jamming stimuli is a spectrum peak near the TF frequency, demonstrating that the bats shift the TF to avoid masking of jamming sounds on the TF frequency range. These results suggest that direct frequency masking near the TF frequency range induces the TF shift, which simultaneously decreases the similarity between their own echolocation sounds and jamming signals.

The Sonar Model for Humpback Whale Song Revised

Why do humpback whales sing? This paper considers the hypothesis that humpback whales may use song for long range sonar. Given the vocal and social behavior of humpback whales, in several cases it is not apparent how they monitor the movements of distant whales or prey concentrations. Unless distant animals produce sounds, humpback whales are unlikely to be aware of their presence or actions. Some field observations are strongly suggestive of the use of song as sonar. Humpback whales sometimes stop singing and then rapidly approach distant whales in cases where sound production by those whales is not apparent, and singers sometimes alternately sing and swim while attempting to intercept another whale that is swimming evasively. In the evolutionary development of modern cetaceans, perceptual mechanisms have shifted from reliance on visual scanning to the active generation and monitoring of echoes. It is hypothesized that as the size and distance of relevant events increased, humpback whales developed adaptive specializations for long-distance echolocation. Differences between use of songs by humpback whales and use of sonar by other echolocating species are discussed, as are similarities between bat echolocation and singing by humpback whales. Singing humpback whales are known to emit sounds intense enough to generate echoes at long ranges, and to flexibly control the timing and qualities of produced sounds. The major problem for the hypothesis is the lack of recordings of echoes from other whales arriving at singers immediately before they initiate actions related to those whales. An earlier model of echoic processing by singing humpback whales is here revised to incorporate recent discoveries. According to the revised model, both direct echoes from targets and modulations in song-generated reverberation can provide singers with information that can help them make decisions about future actions related to mating, traveling, and foraging. The model identifies acoustic and structural features produced by singing humpback whales that may facilitate a singer's ability to interpret changes in echoic scenes and suggests that interactive signal coordination by singing whales may help them to avoid mutual interference. Specific, testable predictions of the model are presented.