Sensing in a Noisy World: Lessons from Auditory Specialists, Echolocating Bats Aaron J

REVIEW Sensing in a noisy world: lessons from auditory specialists, echolocating bats Aaron J. Corcoran1,* and Cynthia F. Moss2

ABSTRACT behavioral adjustments to compensate for noise, such as shifting All animals face the essential task of extracting biologically their calling frequencies to avoid spectral overlap with competing meaningful sensory information from the ‘noisy’ backdrop of their background signals (Shannon et al., 2016). However, receivers also environments. Here, we examine mechanisms used by echolocating make behavioral adjustments in noise; for example, moving to a bats to localize objects, track small prey and communicate in complex more favorable location or increasing active scanning of the and noisy acoustic environments. Bats actively control and coordinate environment (Brumm and Slabbekoorn, 2005). Animals also tend both the emission and reception of sound stimuli through integrated to rely more on multi-modal sensing (see Glossary) in noisy sensory and motor mechanisms that have evolved together over tens environments, processing congruent stimuli acquired through of millions of years. We discuss how bats behave in different complementary senses and/or placing greater weight on ecological scenarios, including detecting and discriminating target modalities that are less subject to interference (Munoz and echoes from background objects, minimizing acoustic interference Blumstein, 2012). For instance, animals may rely on visual and from competing conspecifics and overcoming insect noise. Bats acoustic stimuli from a common source (Taylor and Ryan, 2013) or tackle these problems by deploying a remarkable array of auditory depend more on hearing in darkness (Danilovich et al., 2015). ‘ ’ behaviors, sometimes in combination with the use of other senses. Echolocation and electrolocation are considered active sensory ’ Behavioral strategies such as ceasing sonar call production and modalities, because they operate through the animal s production active jamming of the signals of competitors provide further insight of signals (sound and electricity, respectively) into the environment into the capabilities and limitations of echolocation. We relate these to generate sensory information, which then guides behaviors findings to the broader topic of how animals extract relevant sensory (Nelson and MacIver, 2006). Active sensing (see Glossary) also ’ information in noisy environments. While bats have highly refined refers to an organism s movements that influence sensory signal abilities for operating under noisy conditions, they face the same reception (Schroeder et al., 2010), and the contribution of challenges encountered by many other species. We propose that the movement to perception is widespread throughout the animal specialized sensory mechanisms identified in bats are likely to occur kingdom. Primates, for example, are well known for using rapid in analogous systems across the animal kingdom. eye movements, or saccades, to sequentially direct their foveae at objects in a scene (Land, 2006). Active gaze control (i.e. head or KEY WORDS: Active sensing, Acoustic interference, Animal eye movements that control sampling of visual information) is communication, Jamming, Noise important to animals as diverse as jumping spiders, stalk-eyed flies and zebra finches (Tarsitano and Andrew, 1999; Ribak et al., 2009; Introduction Eckmeier et al., 2008). Many animals actively control sniffing to To find mates and food sources or evade predators, animals must use improve olfactory sampling (e.g. Catania, 2006), explore objects one or more of their senses to detect, localize and discriminate through touch by whisking (Ganguly and Kleinfeld, 2004; Towal signals from the noisy backdrop of their natural habitats (Stevens, and Hartmann, 2006) and localize sound sources by moving 2013; Bradbury and Vehrencamp, 2011). Sensory systems have the head and ears (pinnae) (Populin and Yin, 1998). Active evolved to detect and discriminate stimuli that are important to the control of sensing results in influxes of sensory information, organism’s survival and reproduction (Capranica and Moffat, 1983; which are used to inform further actions (Schroeder and Lakatos, Wehner, 1987). However, animals routinely encounter situations 2009). This leads to action–perception feedback loops, where where there is an abundance of stimuli (abiotic or biotic) that have available sensory information drives the acquisition of future the capacity to interfere with biologically relevant signals. These information. Under noisy conditions, active sensing improves stimuli are commonly referred to as noise (see Glossary). Natural stimulus detection and discrimination in support of diverse environments are composed of numerous competing stimuli, which survival tasks. have the potential to serve as signal or noise, depending on an In this review, we consider echolocating bats as model organisms animal’s current behavioral goal (Fig. 1). to gain a broader view of the mechanisms by which animals cope Animals have evolved a variety of mechanisms for sensing in with noisy sensory environments. To use echolocation or biological noisy environments. Signalers are well known for making sonar, an animal produces acoustic signals and then compares their temporal and spectral features with those of returning echoes (Griffin, 1958; Surlykke et al., 2014). This process allows 1Department of Biology, Wake Forest University, Box 7325 Reynolda Station, echolocating animals to reconstruct acoustic scenes. Biological Winston-Salem, NC 27109, USA. 2Department of Psychological and Brain ‘ ’– Sciences, Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD 21218, sonar can also be considered a form of auto-communication that USA. is, a system in which signaler and receiver are the same individual. Many of the factors that improve communication under conditions *Author for correspondence ([email protected]) of noise (Brumm and Slabbekoorn, 2005) are well developed in bats

A.J.C., 0000-0003-1457-3689 for auto-communication under low light levels. Journal of Experimental Biology

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Glossary Active sensing Use of active processes to influence the influx of sensory information. Attention Selectively processing stimuli that are relevant to the current behavioral task. Call direction The bat call’s aim, as indicated by the axis of greatest acoustic energy. Call directionality A measure of the width of the sonar beam. Clutter Echoes returning from objects that are not the focus of an echolocating animal’s attention. Frequency modulated A call that changes in frequency over time. Masking A situation where one sensory stimulus influences the perception of a second stimulus. Low-pass filter Fig. 1. Cartoon illustration of a noisy acoustic environment of a bat. A focal Changing a sound so that lower frequencies are enhanced relative to bat (left) emits an echolocation signal (black). Echoes (gray) return higher frequencies. simultaneously from a potential prey item and a tree obstacle. A second insect Multi-modal sensing emits an acoustic signal (red), and a conspecific echolocates nearby (green). The use of multiple sensory modalities for sensory perception. Note that each of these acoustic stimuli could serve as signal or as noise, Noise depending on the focal animal’s current behavioral goals. Environmental stimuli that have the potential to interfere with the sensation of biologically meaningful stimuli. Narrowband control of both signal emission and echo reception are central to the A call whose acoustic energy is concentrated within a relatively short range of frequencies. success of bats. By studying these sensory specialists, we hope to Ranging gain broader and deeper insight into how animals in general cope Determining the distance to a target object. with noisy sensory environments. Receptive field We begin this review by briefly summarizing the mechanisms The specific range of stimuli that elicit a response from a sensory neuron. bats use to localize target echoes and separate them from sinFM background clutter echoes (see also Moss and Surlykke, 2010). Sinusoidally frequency-modulated calls: specialized signals used by Mexican free-tailed bats to jam the echolocation of conspecifics. Next, we consider how bats adapt to ecological scenarios involving SNR noise, including interactions with conspecifics and prey. We also Signal to noise ratio: a measure of the ratio between the strength of the highlight the importance of multi-modal sensing to the success of signal that is being attended to and the competing background noise. bats. We finish by relating these findings to common sensory Spatial release problems faced by a variety of animals. The process of using binaural hearing cues to reduce acoustic masking of sounds that are coming from different directions. Fundamentals of echolocation: common problems and SPL Sound pressure level: a measure of the amplitude of an acoustic signal. solutions Tymbal organ More than 1100 bat species use echolocation for a wide variety of A sound-producing structure found in some insects, including tiger moths tasks, and in diverse habitats (Denzinger and Schnitzler, 2013; (Family Noctuidae, subfamily Arctiinae). Fenton and Simmons, 2015). Bat auditory systems are composed of Waggle the same basic neural architecture and pathways as those of other Rapid head movements that change the orientation of the ears and are mammals (Popper and Fay, 1995). Like other animals, bats compare proposed to amplify auditory cues used for target localization. the amplitude and arrival time of sounds at their two ears to determine the azimuth of sound sources (Wohlgemuth et al., 2016a). Bat ears typically feature a large tragus – a spear-like Echolocation itself is inherently subject to noise interference: projection that modifies the spectral profile of echoes arriving with target echoes are often several orders of magnitude weaker than respect to sound source elevation (Müller, 2004; Wotton et al., echolocation signals, and sonar calls and echoes are separated by 1995). Bats can use elevation-dependent spectral cues to determine tens of milliseconds or less (Moss and Surlykke, 2010). Target the vertical direction of a sound source (Wotton and Simmons, echoes can easily be masked by the bat’s own emission, or by 2000). A distinguishing feature of spatial localization by ‘clutter’ echoes (see Glossary) returning from other objects in the echolocation is the ability to determine target distance (ranging; environment (Fig. 1). Bats also must contend with the rustling of see Glossary) with high precision. Bats accomplish this by wind and noise from flowing water, conspecific calls and chorusing estimating the time delay between outgoing pulses and returning insects that produce sounds in the ultrasound range. Despite these echoes (Simmons, 1973). Sound travels at approximately challenges, bats perform natural echolocation behaviors with 343 m s−1. Big brown bats can discriminate echo arrival time apparent ease. For example, bats exit cave roosts, sometimes differences of about 58 µs, supporting range discrimination amongst thousands of echolocating conspecifics (Gillam et al., performance of approximately 1 cm (summarized in Moss and 2010), capture evasive insects in a fraction of a second (Kalko, Schnitzler, 1995; Wohlgemuth et al., 2016a). Some studies have 1995), and navigate in darkness through dense foliage, while flying even found evidence that bats can detect echo arrival timing changes at high speed (Kong et al., 2016). Tight coordination and adaptive ( jitter) of less than 1 μs (Simmons, 1979; Simmons et al., 1990; Journal of Experimental Biology

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Moss and Schnitzler, 1989), corresponding to jitter along the range emissions are shown in black. Simulated target echoes have been axis of less than 1 mm. added to the figure (in red), based on the physics of sound Most bats produce short (<20 ms) frequency-modulated (FM; see propagation in air and measured 3D positions of the bat and prey. Glossary) calls that are followed by long silent intervals, during Assumptions about echo arrival times have been verified in several which time bats listen for echo returns from objects (Griffin, 1958; studies, where echoes were recorded from microphones placed Schnitzler and Henson, 1980; Moss and Schnitzler, 1995). FM calls directly behind the bat (e.g. Hiryu et al., 2007). Fig. 2B shows that have a low duty cycle, i.e. a low proportion of time filled with bats progressively shorten both pulse duration and pulse interval sound. Approximately 200 bat species produce calls that start or end (time between successive pulses) such that the echo returns after the with FM components, but also include a constant frequency (CF) end of the outgoing pulse but before the beginning of the next pulse. component (approximately 8–100 ms). Long CF calls (>50 ms) By shortening pulse duration, bats avoid temporal overlap between have a high duty cycle, i.e. a large percentage of the time is filled pulses and echoes that could lead to masking (see Glossary) or with sound. High duty cycle bats can hear echoes at the same time interference of echo detection from the sonar call emission (Kalko that they are producing much more intense calls. This is possible and Schnitzler, 1993). Pulse structure also changes over the because the relative motion of the flying bat with respect to its target sequence. The bat uses relatively long and narrowband calls (see introduces Doppler shifts in sonar returns, which separates the Glossary) in the search phase (pulse 4 in bottom row of Fig. 2A). sound frequencies of calls and echoes into different listening These calls concentrate acoustic energy within limited frequency channels. High duty cycle bats have highly specialized auditory bands, which facilitates echo detection (Griffin et al., 1960; systems (Neuweiler et al., 1980) that enable fine frequency Surlykke and Moss, 2000). Short, broadband calls used late in the discrimination (e.g. Long and Schnitzler, 1975). Greater attack (e.g. pulse 28 in Fig. 2A) allow the bat to integrate ranging horseshoe bats, species that use long CF signals for echolocation, information across many auditory neurons tuned to different can discriminate and recognize fluttering insect prey by listening to frequencies (Simmons and Kick, 1984), and therefore they are spectral and amplitude modulations in echoes (von der Emde and well suited for distance measurement (Simmons and Stein, 1980; Menne, 1989; von der Emde and Schnitzler, 1990). This specialized Surlykke, 1992). This allows precise distance measurement for the form of echolocation also serves to reject noise outside a narrow final prey interception maneuver. frequency band used for target echo detection and discrimination, The echo stream in Fig. 2B also illustrates that, despite the which for the greater horseshoe bat is about 83 kHz. Unless dramatic reduction in pulse intervals late in the sequence, bats otherwise noted, the discussion that follows applies to FM, or low typically allow sufficient time for target echoes to return prior to the duty cycle, bats, which rely heavily on the timing of calls and echoes next emission. This allows bats to avoid ambiguity in assigning to extract spatial information from the environment (Moss and echoes to the correct pulse, a requirement for accurate range Schnitzler, 1995). For further discussion of bats that use high duty estimation. Another strategy for ensuring correct assignment of cycle calls, we refer the reader to recent reviews (Fenton et al., 2012; pulses and echoes is to produce two or more calls in groups (i.e. Schnitzler and Denzinger, 2011). ‘sound groups’), flanked by sonar signals at longer intervals (Kothari et al., 2014), which serves to link calls and echoes through Assignment of calls and echoes through dynamic control of signal distinct temporal patterning. Bats may integrate echo information duration, timing and frequency within sound groups to increase sonar resolution (Moss et al., 2006). To accurately localize and sort object echoes in the environment, a Pulses within a group may also have distinct time–frequency bat must solve several problems: target echo detection, localization, profiles (Jung et al., 2007; Ratcliffe et al., 2011; Hiryu et al., 2010), recognition and tracking, in the midst of acoustic noise. This is which could aid further in call–echo assignment. Fig. 2D shows the achieved in large part by the echolocating bat’s dynamic and bat Cormura brevirostris producing triplets of calls that increase in adaptive control of biosonar emissions: bats modulate the duration, sound frequency. This may allow the bat to match calls and echoes intensity, frequency, directionality (see Glossary), direction of the not only by their temporal patterning but also by their frequency. A sonar beam (see Glossary) and timing of emissions to optimize echo similar strategy has been reported in the big brown bat operating in a reception from targets, while minimizing acoustic interference highly cluttered environment (Hiryu et al., 2010). This suggests that (Moss and Surlykke, 2010). Bats actively adapt the features of bats can simultaneously store multiple time–frequency call profiles, echolocation calls they use to localize and track insect prey (Fig. 2), against which echo returns are compared. which can be categorized into three phases (Griffin et al., 1960). During the ‘search phase’, insectivorous FM bats produce sonar Echo feature recognition calls at a rate of 3–20 Hz, depending on the species (Holderied and Echolocating bats face the fundamental task of recognizing echoes von Helversen, 2003). After detecting a target echo, the bat enters from their own sonar emissions and distinguishing them from other the ‘approach phase’, in which call rate steadily increases and call sounds in the environment. Psychophysical experiments have been duration decreases. The sweep of the FM sonar signals also conducted that measure the echolocating bat’s ranging performance becomes progressively steeper (Fig. 2A). In the ‘terminal buzz in playback experiments that electronically delay the arrival of phase’, the pulse rate approaches its maximum of 150–200 Hz and simulated sonar echoes. These experiments support the idea that intensity decreases (Jakobsen et al., 2013). Bats have specialized bats compare the time–frequency structure of the outgoing call with ‘superfast’ muscles in the larynx that allow such extraordinary call the echo return. Bats that use FM signals suffer reduced ranging rates (Elemans et al., 2011). ability when listening to echoes that are manipulated in time– By re-aligning the echolocation sequence so that the time from frequency structure, i.e. sweeping from low to high frequencies the beginning of each echolocation call until the end of the next call (Masters and Jacobs, 1989), when natural FM signals are replaced is stacked in a sequence (to illustrate a ‘sonar stream’; Fig. 1B), by noise bursts (Surlykke, 1992), have altered sweep shape (Masters certain features of the echolocation sequence stand out. Fig. 2A and Raver, 2000) or have the time–frequency structure from another shows an acoustic recording of a Mexican free-tailed bat (Tadarida individual bat (Masters and Raver, 1996). Bats can also learn to brasiliensis) hunting prey under natural field conditions. Call differentiate calls from different individuals based on subtle Journal of Experimental Biology

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ABTarget distance (m) Terminal 0 5 10 15 20 Search Approach buzz 1 Pulse Echo Pulse Search 6 p1 p36 Echo p16 p6 p11 11 Approach 100

0 lse no. –1.4 0

Time (s) Pu 21 100 p4 p12 p28 Terminal 26

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0 00013 10 6 36 Time (s) 0 30 60 90 120 Time after pulse (ms)

CD6 Capture p36 t ( =0) 60 Bat 4 p16 p1 Moth Hz)

(m) y p11 2 3 3 2 2 1 1

Frequency (k 0 p6 20 0 2 4 6 8 500 x (m) 0 Time (ms)

Fig. 2. Adaptive features of the bat echolocation attack sequence. (A) Echolocation sequence of the Mexican free-tailed bat, Tadarida brasiliensis, attacking a moth in the field. Shown are an oscillogram (top) and spectrogram (middle) of the entire sequence, and (bottom) spectrograms of select calls. Echoes (red) were added based on known target distances at the time of each pulse. (B) The spectrogram from A is re-organized relative to the beginning of each pulse. Pulses are aligned on the y-axis. The time period is shown from each pulse to the following pulse. Note that the bat progressively shortens the pulse duration and pulse interval to ensure that each echo occurs between the end of the first pulse and the beginning of the following pulse. (C) Overhead viewof T. brasiliensis attacking a moth in the field. Circles indicate echolocation pulses. Numbers indicate selected pulses for reference across panels. (D) The bat Cormura brevirostris is one of several species that produces search calls that alternate in frequency. This bat produces calls in triplets (labeled 1–3) that increase in frequency from 26 to 33 kHz. Note that calls from other bats are also present. It has been hypothesized that frequency alternation aids in correct assignment of calls and echoes in cluttered environments. D is reproduced, with permission, from Moss and Surlykke (2001). differences in the distribution of energy across frequencies (Yovel directional, and increasingly so at higher frequencies (Fig. 2B; et al., 2009). If given sufficient training, a bat can learn to Aytekin et al., 2004; Jakobsen et al., 2013). Echoes returning from discriminate with high accuracy the delay between its own call and objects off-axis from the bat’s beam aim are both weaker and low- echoes having a different time–frequency structure (Masters and pass filtered (see Glossary; right inset in Fig. 3C). The bat’s auditory Raver, 1996). In one study, bat sonar ranging performance was system can separate off-axis low-pass-filtered clutter echoes from disrupted by broadband insect clicks that arrived within a short time on-axis target echoes, which prevents clutter echoes from masking window of echoes (Miller, 1991). Collectively, these studies show target echoes (Bates et al., 2011). This observation is based on the that bats utilize the distinct time–frequency structure of their own following. Echoes are detected by populations of neurons that echoes to detect and discriminate their signals from other noises, respond to different frequency components of the bat’s FM sonar and that bats can learn to recognize novel call and echo patterns signals (Simmons et al., 1990). The latency of neural firing, which when given sufficient time. registers echo arrival time, depends on echo intensity, with neurons firing at shorter latencies for higher amplitude echoes (Simmons and Adaptive control of sonar beam aim, directionality and intensity Kick, 1984; Simmons, 1989). Because of the directionality of sonar In noisy environments, echoes can return simultaneously from signal production and reception, echoes returning from targets along many objects. How do bats perceptually segregate object echoes in the bat’s midline are more intense than echoes returning from the cluttered environments? One solution is to sequentially aim the bat’s periphery, and this intensity difference is registered by the sonar beam axis (i.e. to control call direction; see Glossary) to bat’s auditory system as differences in arrival time of echoes from inspect targets of interest (Fig. 3A; Surlykke et al., 2009; Falk et al., objects along the midline and off to the bat’s side. Importantly,

2011; Seibert et al., 2013). Bat sonar emissions and hearing are both directional differences in echo intensity are greater for high- Journal of Experimental Biology

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AB10 10 0 25 kHz 50 kHz −10 Insect −20 Net −30 m) 5 −40

5 ation (dB)

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Attenu Right edge −70 0 0 −80 −5 5 −5 5 x (m) x (m) C Beam Focal aim object Masker

Fig. 3. Acoustic scanning behavior and spatial release from masking. (A) Reconstruction of the sonar beam aim of a big brown bat as it flies through a hole in a net and then captures an insect (after Surlykke et al., 2009). The bat sequentially fixates on the right and then left edges of the net opening before directing its beam at the insect target. (B) Directionality of big brown bat sonar at frequencies that correspond to the first (25 kHz) and second (50 kHz) harmonics of its call, respectively. Attenuation is a result of the directionality of the sonar beam (after Hartley and Suthers, 1989), bat hearing (after Aytekin et al., 2004) and frequency-specific attenuation of sound (Bazley, 1976). (C) Spatial release from masking. Echoes returning from objects near the center of the sonar beam (left inset) return a full complement of frequencies, whereas off-axis objects reflect weaker echoes that are low-pass filtered (right inset). The bat has neural mechanisms that de-focus off-axis echoes, preventing them from masking echoes from focal objects (Bates et al., 2011). frequency components of sonar signals than for low-frequency Active control of sound reception components. In other words, at the bat’s periphery, high-frequency Complementing active control of sonar emissions, bats also control components of echo returns are weaker and therefore registered at the shape, separation and orientation of their pinnae. Pinna longer neural response latencies than low frequencies, and this movements were first studied in high duty cycle CF bats (Griffin creates a temporal misalignment of the low- and high-frequency et al., 1962) and more recently in a low duty cycle FM bat, Eptesicus components of echo returns from objects off to the bat’s side. This fuscus (Wohlgemuth et al., 2016b). Wohlgemuth et al. (2016b) misalignment has the effect of ‘defocusing’ objects in the bat’s trained E. fuscus to rest on a platform and track prey items that were periphery (Bates et al., 2011). Thus, a combination of the physics of moved along different trajectories using a motorized pulley system. sound transmission in the environment and the effect of sound This allowed the investigators to monitor sonar vocalizations and intensity on neural response latency differentially affects sonar ear movements with high precision as bats tracked moving prey. processing of low- and high-frequency target echoes arriving from Eptesicus fuscus employ two types of pinna movement; the first off-axis objects. Bates et al. (2011) hypothesize that the sonar type is associated with rapid head rotations or ‘waggles’ (see defocusing of off-axis clutter echoes prevents these signals from Glossary) that alternate the vertical orientation of the two pinnae masking target echoes in the bat’s central ‘field of view’, relative to echo returns, and the second, which has been observed in determined by its beam aim. In this context, it is noteworthy that both E. fuscus and high duty cycle bats, involves changes in the bats show spatial release (see Glossary) from masking at small erectness and separation between the pinnae. angular separations of target and clutter. For example, one study Regarding the first type, bats produced waggles more often when reports that bats achieve complete spatial release from masking targets moved along complex trajectories. Wohlgemuth et al. when sound sources are separated by only 23 deg (Sümer et al., (2016b) hypothesized that these ear movements amplify interaural- 2009), far better performance than is achieved by animals that do not level cues and spectral cues in a manner that is analogous to visual echolocate. motion parallax, where head movements are used to aid depth By adjusting call frequency or mouth aperture, bats can perception. dynamically control the directionality of their sonar emissions For the second type of pinna movement, erect pinnae focus the (Jakobsen et al., 2013). One recent study found that bats alter the ears towards echoes in front of the bat; lateral ear deformations size of their mouth gape to adjust the width of their sonar beam as increase the distance between the tips of the pinnae and change their they move through habitats that differ in spatial structure (Kounitsky shape, which amplifies sounds coming from more-peripheral et al., 2015). This appears to be another strategy that allows bats to regions (Gao et al., 2011). In a target-tracking study, E. fuscus adaptively avoid acoustic interference from off-axis objects in increased inter-pinna separation as targets approached it on a different environments. platform, broadening the bat’s acoustic field of view when it faced Bats also alter their beam directionality during the last moments the challenge of intercepting a fast-moving target (Wohlgemuth of an attack on an insect. Specifically, late in attacks on prey, bats et al., 2016b). Bats also made rapid changes to inter-pinna typically decrease their calling frequency, which broadens the sonar separation as they tracked moving prey, a behavior that might beam (Jakobsen and Surlykke, 2010). This may be an adaptive enhance cues for sonar localization accuracy. response to ensure that the prey stays in the ensonified volume These studies show that bats exhibit fine control over their through to the end of the attack, when prey might otherwise acoustic field of view, which they change through head and ear maneuver outside the sonar beam (Corcoran and Conner, 2016). movements, under different contexts (such as distance to a target), Journal of Experimental Biology

4558 REVIEW Journal of Experimental Biology (2017) 220, 4554-4566 doi:10.1242/jeb.163063 and over millisecond time scales in coordination with sonar emissions and echo returns, rather than echo returns from the bat’s vocalizations. These mechanisms should enhance the bat’s ability own sonar vocalizations. Moreover, studies of the bat nervous to extract acoustic information under noisy sensory conditions. system have been largely conducted in passively listening, and often anesthetized, bats in the laboratory. We are therefore left with the Neural basis of echolocation question of how neural responses to artificial stimuli in passively To understand mechanisms that allow bats to operate in acoustically listening bats informs us of activity patterns that are evoked by noisy and dynamic environments, it is important to consider how the echoes of the bat’s sonar vocalizations. No doubt, the representation bat’s brain processes echoes and compares them with outgoing of noisy sonar scenes arises from the activity of populations of emissions. Here, we consider aspects of the bat’s neural machinery neurons (Simmons, 2012). Recent studies of the dynamics of echo- that are relevant to echo processing under dynamic and noisy evoked activity in the bat sonar receiver of the free-flying actively conditions. We also direct the reader to reviews of other aspects of echolocating animal indeed demonstrate remapping and shifts in 3D neural signal processing in the bat’s sonar receiver (Suga, 1990; spatial tuning of midbrain auditory neurons with the bat’s sonar Simmons, 2012; Wohlgemuth et al., 2016a). inspection of objects (Kothari et al., 2016). These findings can serve The bat’s brain is specialized for extracting sonar signal features to motivate a broad and intense investigation of neural activity that are important for echolocation. Specific neurons have been patterns in animals that freely explore noisy sensory environments. characterized that respond selectively to a restricted range of pulse– echo delays (Suga and O’neill, 1979), signal durations (Casseday Acoustically noisy ecological scenarios et al., 1994), frequency modulation rates (Razak and Fuzessery, Here, we examine in detail three ecological scenarios where bats are 2008) and sound source directions (Valentine and Moss, 1997). The faced with noisy environmental conditions. These scenarios features encoded by these neurons (i.e. their receptive fields, see highlight the flexibility that is afforded to bats by using multiple Glossary) tend to cover those that the bat processes as it echolocates mechanisms for overcoming challenging sensory conditions. in the natural environment. For example, individual delay-tuned neurons show strongest responses to delays from 1 to 36 ms (up to Scenario 1: echolocating conspecifics roughly 6 m of target distance), which corresponds to the bat’s Bat echolocation calls are among the most intense acoustic signals operating range for small objects, such as insect prey (Dear et al., in nature, sometimes exceeding 140 dB sound pressure level SPL 1993). (see Glossary) at 0.1 m (Holderied et al., 2003; Surlykke and Kalko, Neurophysiological studies have revealed specializations in the 2008). Bats routinely encounter conspecifics when departing from a processing of biologically natural sound sequences in passively shared roost, commuting or foraging. A potential challenge arises listening bats. For instance, research has shown that midbrain when a bat must filter high-intensity conspecific calls to detect and neurons are more selective to broadcasts of natural sonar emissions discriminate echo streams that are at a much lower sound level. This than simple, computer-generated FM sweeps or noise (Wohlgemuth problem has received considerable attention in the literature over the and Moss, 2016) and are selective to the temporal dynamics of past 15 years (e.g. Ulanovsky et al., 2004; Gillam et al., 2007; sound stimulation (Sanderson and Simmons, 2005), providing Cvikel et al., 2015a). Much of the discussion in the literature has evidence that bat neural pathways are selective to acoustic features focused on the hypothesis that, like electric fish (Heiligenberg, of their own calls. More research is needed to determine the neural 1991), bats alter the frequency of their emissions to avoid spectral basis of this selectivity, and how it changes over time. overlap with conspecific calls, a behavior known as the jamming Studies have also begun to change our understanding of how the avoidance response (JAR). bat’s brain processes streams of echoes (Bartenstein et al., 2014; Early evidence for JAR in bats came from studies of bats calling Beetz et al., 2016). It is increasingly clear that bat neural pathways alone or in pairs in the wild (Habersetzer, 1981; Ulanovsky et al., process not only individual pulse–echo pairs but also streams of 2004; Ratcliffe et al., 2004). Pairs of bats flying together frequently pulses and echoes across a sequence. For example, the auditory adjusted their peak calling frequency to maintain a 3–4 kHz cortex of many bat species shows topographic organization, with separation. Field (Gillam et al., 2007) and laboratory (Bates et al., systematic shifts in echo delay tuning of neurons located along the 2008; Takahashi et al., 2014) playback experiments later confirmed rostrocaudal axis (e.g. Suga, 1990; Kössl et al., 2014). It was long this finding: bats rapidly (in one study <200 ms) adjust their calling assumed that this map was static, but a recent study demonstrated frequency to avoid spectral overlap between playbacks and the most that the map changes rapidly and dynamically when a sequence of shallowly FM components of their calls. Another study examined pulses and echoes is presented to a passively listening, anesthetized the call structure of bats flying alone or in pairs in a laboratory (Chiu bat (Bartenstein et al., 2014). When pulses and echoes were et al., 2009). Bats adjusted their call structure when flying near presented at progressively shorter delays, such as occurs when conspecifics to a degree that was dependent on the baseline approaching a target (see Fig. 2B), the map shifted towards a higher similarity between the two bats’ calls when flying alone. That is, representation of short delays. The degree and direction of the shift pairs of bats that had similar calls when flying alone made larger depended on the sequence of pulses and echoes that were presented. changes to their calls when flying together. These studies This, and other recent neurophysiological (Beetz et al., 2016) and conclusively demonstrate that at least some bats use the JAR to behavioral studies (Kugler et al., 2016; Warnecke et al., 2016), avoid acoustic interference from conspecifics. shows that bats are specialized for integrating the flow of echoes as Recent studies have led to an alternative hypothesis for observed they return from multiple sonar pulses. frequency changes in groups of echolocating bats (Cvikel et al., Mechanisms have been proposed to explain how the bat nervous 2015a; Götze et al., 2016). Namely, the authors hypothesize, and system might compute the spatial location of objects in an echo have found strong evidence, that some bats alter call frequency as a scene (Simmons, 1973, 2012; Simmons et al., 1990; Valentine and reaction to the physical presence of other bats, not their acoustic Moss, 1997). These discussions remain speculative, because almost presence. These studies show that not all bats use JAR, and that all neurophysiological studies of the bat auditory system have been frequency shifts alone are not sufficient for demonstrating JAR in conducted with artificial sonar stimuli that simulate the bat’s sonar bats. This alternative hypothesis does not explain the data from Journal of Experimental Biology

4559 REVIEW Journal of Experimental Biology (2017) 220, 4554-4566 doi:10.1242/jeb.163063 some previous studies that controlled for the physical presence of Another strategy observed in pairs of big brown bats competing bats either by using playback experiments (Gillam et al., 2007; for food is ‘silent behavior’ (Chiu et al., 2008). Specifically, when Takahashi et al., 2014) or by carefully measuring the positions and flying within 1 m of conspecifics, paired bats routinely orientations of the bats that were present (Chiu et al., 2010). Thus, it (approximately 40% of the time) ceased echolocating for periods appears that some, but not all, bats use JAR. of 0.2–2.55 s (Fig. 4B). These behaviors were almost never Regardless of whether they employ JAR, bats are likely to use observed in bats flying alone. Silence was more common when multiple mechanisms to correctly sort conspecific calls from their pairs of bats had echolocation calls with similar design. This could own echoes (see discussions in Ulanovsky and Moss, 2008; Bates be interpreted in one of two ways: (1) bats could use silence as a et al., 2008). A bat’s own echoes are likely to form predictable mechanism for avoiding jamming from conspecifics that produce streams (Fig. 2B) and have a time–frequency structure and directional similar calls to their own, or (2) the similarity in call design between cues that will differ from calls of conspecifics (Yovel et al., 2009). the two bats could make it easier for the bat engaging in silent One recent study found that Pipistrellus kuhlii solved the problem of behavior to use the conspecific’s calls and echoes for its own sonar extreme acoustic interference from conspecifics not by adjusting call system. This could, in turn, enable a bat’s stealth attack on the prey frequency but by increasing call duration, intensity and pulse rate item. At present, these hypotheses remain untested. (Amichai et al., 2015). These adjustments all improve the signal-to- Finally, Mexican free-tailed bats use sinusoidally frequency- noise ratio (SNR; see Glossary) of calls over background noise, a modulated (sinFM; see Glossary) calls to jam the echolocation of finding that indicates the problem posed by conspecific calls (at least competing bats attempting to capture prey (Corcoran and Conner, when numerous conspecifics are present) is acoustic masking, not 2014). Bats produce sinFM calls only when a competing bat is in the differentiating one’s own calls from those of conspecifics. approach and terminal buzz phase of prey capture (Fig. 4C, Fig. 5B). There are conflicting data on how bats adjust their calling rate in When conspecifics produced sinFM calls that overlapped their response to conspecifics. Some studies indicate that bats decrease feeding buzz, bats captured prey during only 6% of attacks, their calling rate when calls of one conspecific are present (Jarvis compared with 35% when no sinFM calls were present. Playback et al., 2010, 2013; Adams et al., 2017), but others have found that experiments showed that the timing and time–frequency structure of bats increase their calling rate, particularly when faced with calls of sinFM calls are important for interfering with the competitor’s numerous bats (Amichai et al., 2015; Lin et al., 2016). Suppressed attack. 3D reconstructions of bat flight trajectories showed bats calling rates have been interpreted as evidence for group engaged in extended bouts of food competition where they took cooperation (Adams et al., 2017), but alternatively this could turns jamming one another while the other bat attempted to capture indicate that bats are devoting more of their attention (see Glossary) prey (Fig. 4C). to passively listening to conspecific calls (Barber et al., 2003). Studies of food competition strategies give insight into how bats Collectively, these studies demonstrate that bats use numerous cope with acoustic interference. First, these data provide further mechanisms for separating signals and noise, and their reliance on evidence that bats are a potential source of acoustic interference, these mechanisms can shift depending on the prevailing conditions. either because of the calls that they make or because of their physical presence as a sound-reflecting object. Second, silent behavior Scenario 2: competing with conspecifics for food indicates that bats are capable of orienting by eavesdropping on the Group foraging involves a fundamental tradeoff: bats can improve calls (and perhaps echoes) of conspecifics. Third, specialized sonar- searcher efficiency by eavesdropping on the feeding calls of jamming calls demonstrate that, despite the extraordinary conspecifics (Gillam et al., 2007; Dechmann et al., 2009), but this adaptations observed in echolocating bats, they are not can increase competition for food. A high density of foraging bats impervious to acoustic interference, particularly when trying to also increases the complexity of the acoustic and physical capture prey. Jamming signals provide insight into fundamental environment, taking the bat’s attention away from foraging constraints on echolocation, a topic we discuss further below. (Cvikel et al., 2015b). Bats may be under selective pressure to fend off competitors, even though they themselves benefit from Scenario 3: insect noise eavesdropping on others. Recent research has revealed multiple Aside from bats, chorusing insects such as katydids are one of the acoustic strategies that bats use during competition for food. most common sources of ultrasound in the environment (Robinson One such strategy is the use of food-claiming calls. A recent and Hall, 2002). Playback experiments provide evidence that insect laboratory study showed that big brown bats make specific noise is a potential source of acoustic interference for bat communication calls called FM bouts (FMBs) when competing echolocation. Gillam and McCracken (2007) recorded T. with other bats fora prey item (Wright et al., 2014). FMB calls contain brasiliensis echolocation calls in the field in the presence of silence individual-specific signatures, and, when produced, they caused an or playbacks of insect noise that varied in peak frequency from 16.5 to increase in the spatial separation between the bats. Bats that produced 29 kHz. Bats shifted their calling frequency upward depending on the more FMBs were more likely to capture food items (Fig. 4A). Field frequency of the playback, always maintaining a 2–4 kHz separation studies have shown that pipistrelle bats (Pipistrellus spp.) produce between their calling frequency and that of the insect noise. This social calls that might have a similar function (Barlow and Jones, finding indicates that bats exhibit a JAR not only in response to 1997). Pipistrelles produce these calls more often when food density conspecifics but also to a variety of interfering signals. is low, and playbacks of the social calls had a deterrent effect on Several insects, including several families of moths (Blest et al., conspecifics. Bats at foraging sites are frequently observed chasing 1963; Barber and Kawahara, 2013; Corcoran and Hristov, 2014) and conspecifics while emitting social calls (e.g. Miller and Degn, 1981). tiger beetles (Yager and Spangler, 1997), produce bursts of Dominant bats could be aggressively chasing away competitors and ultrasonic clicks in response to the attack cries of bats. Clicks advertising their presence with specialized, individual-specific calls. produced at relatively low rates have the primary function of This would not only reduce competition for food but also simplify the warning bats that the insect is toxic (Hristov and Conner, 2005; acoustic and physical environment so that the bat can focus attention Ratcliffe and Fullard, 2005); some palatable moths also mimic these on finding prey (Cvikel et al., 2015b). sounds to deceive bats (Barber and Conner, 2007). Journal of Experimental Biology

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A 3 Bat 1 FMB Capture FMB Bat 2 Bat 1

Bat 2 (m) y Insect

0 0 x (m) 3.5

B 3 Bat 1 Bat 1 Bat 2

Capture (m) Bat 2 y Insect Silence

0 0 3.5 x (m)

C 15 Bat 1 sinFM Miss Miss sinFM (m) y Bat 1 Bat 2 Miss Miss Capture

Bat 2 0 0 20 1 s x (m)

Fig. 4. Acoustic competition strategies in bats. Three distinct food competition strategies have been discovered in bats: (A) food claiming calls (frequency- modulated bouts, FMBs), (B) silent behavior and (C) jamming calls (sinusiodally frequency modulated, sinFM). Food claiming and silence have been documented in the big brown bat, Eptesicus fuscus (Chiu et al., 2008; Wright et al., 2014), while jamming calls have been documented in the Mexican free-tailed bat, Tadarida brasiliensis (Corcoran and Conner, 2014). For each strategy, plots of the echolocation and social/jamming calls of each bat (left) and an overhead view of bat flight trajectories (right) are shown. FMBs and sinFM calls are highlighted in green. Blue and red lines/dots indicate echolocation calls. Feeding buzzes are labeled as either ‘capture’ or ‘miss’. In A, the two bats follow one another closely while echolocating and producing FMBs. Bat 1 produces more FMBs and captures the insect. In B, bat 2 exhibits silent behavior while following bat 1, then makes a feeding buzz to capture the insect. In C, the two bats alternate in producing feeding buzzes while the other bat makes sinFM calls that jam the sonar emissions of the buzzing bat. Bat 2 eventually captures the insect, after bat 1 has left the area. Video animations of each sequence are available as supplemental videos in the original publications. Adapted figures are reprinted with permission.

Of particular interest here are some species of tiger moths and from noise. Because these signals appear to have evolved hawkmoths that produce clicks at high rates to jam bat echolocation specifically to jam bat sonar, they might contain elements that (Corcoran et al., 2009; Kawahara and Barber, 2015). Like the either infiltrate or disrupt the bat’s neural pathways. Currently, this jamming sinFM calls of bats, these clicks are produced during the discussion is speculative because no studies have examined how the bat’s approach and buzz phases of echolocation. Psychophysical structure of jamming signals affects their disruptive capacity. (Miller, 1991) and neurophysiological (Tougaard et al., 1998) Moth clicks and bat sinFM calls have dramatically different experiments show that clicks disrupt the target ranging ability of acoustic structures, but they also have some common features bats by multiple orders of magnitude, but, to do so, clicks must (Fig. 5). Both signals occupy a high proportion of time during the occur within 1–2 ms of echo returns. Moths cannot anticipate when bat’s terminal buzz, overlap spectrally with the bat’s calls, and have this window will occur, so their solution is to click at extremely high frequency components that change rapidly over time. Tiger moths rates (as high as 4000 clicks s−1) that ensure some clicks will co- produce bursts of 20–30 clicks at a time through the sequential occur with each set of echo returns. Experiments pitting bats against buckling and elastic recoil of their tymbal organ (see Glossary) jamming moths found that bats often continued prey pursuit through (Blest et al., 1963). Clicks are very short (0.24 ms) and broadband. the barrage of noise, but missed the prey by a distance similar to the The peak frequency of clicks in a series decreases and then increases errors observed in psychophysical and neurophysiological with the sequential buckling and elastic recoil of striations on the experiments (Corcoran et al., 2011). surface of the tymbal. In comparison, sinFM calls consist of one to How do the jamming signals described above interfere with bat five relatively long (mean 65 ms) syllables that are produced as long echolocation? The specialized jamming signals of bats and moths as a competing bat continues its buzz. These calls oscillate up and might provide insight into how bats process and segregate echoes down over the frequency band of conspecific buzz calls (Fig. 5B). Journal of Experimental Biology

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100 100 80 80 60 60 40 40 20 20 0 0 0 25 50 75 0 25 50 75 100 80 60 Moth clicks

Frequency (kHz) sinFM 60 40 40

20 20 Buzz Buzz 0 100 200 300 400 0 100 200 300 400 500 Time (ms)

Fig. 5. Sonar jamming signals of moths and bats. (A) Clicks produced by the tiger moth Bertholdia trigona to jam the sonar of the big brown bat, Eptesicus fuscus (Corcoran et al., 2009). (B) Intraspecific sonar jamming signals (sinFM) of the Mexican free-tailed bat, Tadarida brasiliensis (Corcoran and Conner, 2014). Oscillograms and spectrograms are shown of the jamming signals alone (top), and spectrograms are shown of jamming signals made during a bat attack sequence (bottom). Note the distinctive time–frequency structures of the jamming signals, and that they are both produced to overlap in time and frequency with the attacking bat’s feeding buzz.

SinFM calls oscillate at a rate of 166 Hz, which is similar to the bat’s (Horowitz et al., 2004; Orbach and Fenton, 2010; Boonman et al., calling rate of 154 Hz during the feeding buzz (Corcoran and 2013). A recent study showed that Egyptian fruit bats (Rousettus Conner, 2014). This suggests that the rhythmic sinFM oscillations aegyptiacus) alter their echolocation signaling rate depending on might have evolved specifically to elicit responses from neurons that light levels (Danilovich et al., 2015). Despite having excellent fire in response to feeding buzz calls. vision, these bats never ceased echolocating entirely. This could be The acoustic structure of bat and moth jamming signals hints at because echolocation and vision provide complementary sensory the possibility that they have specific features that infiltrate the bat information. Echolocation allows detection of small targets under sonar receiver. It is unlikely that bats perceive jamming signals as low light levels, and provides better ranging ability, whereas vision actual echoes, because bats have highly refined echo discrimination is effective over longer distances and provides better spatial abilities (Masters and Raver, 1996; Corcoran et al., 2010). A more resolution along the dimensions of azimuth and elevation likely possibility is that the acoustic structure of jamming signals (Boonman et al., 2013). We propose that multimodal sensing may actively disrupts echo processing in the bat’s neural pathways. be widespread in naturally behaving animals, and is not only a Further behavioral and neurophysiological experiments are required means for coping with uncertainty in preferred sensory modalities to test these hypotheses. (Munoz and Blumstein, 2012). An open question is to what extent bats rely on vision for obstacle Multi-modal sensing as a mechanism for coping with noise detection and avoidance. If a bat is subject to severe acoustic A common solution to sensing in noisy environments is to use interference, such as when flying amongst hundreds of calling multiple sensory modalities (Munoz and Blumstein, 2012). Bats conspecifics, could it utilize vision to avoid flying into vegetation or provide numerous examples of this phenomenon, both as short-term other bats (Kong et al., 2016)? Some studies have modified either behavioral responses and as evolutionary adaptations to specific light levels (Horowitz et al., 2004) or the visual conspicuousness of foraging niches (Schnitzler and Kalko, 1998). Echolocation is poorly obstacles (Orbach and Fenton, 2010) to show that bats can use suited for detecting objects resting on vegetation or the ground vision for obstacle avoidance. However, further experiments are because target and background echoes return nearly simultaneously. needed that independently control for both the visual and echo- Bats that acquire stationary food items from surfaces (including acoustic cues of obstacles. insects, fruit and nectar) show increased reliance on passive listening (reviewed by Jones et al., 2016), olfaction (Korine and Kalko, 2005) Discussion and vision (Bell, 1985; Eklöf and Jones, 2003). Bats that forage close Bats exhibit numerous adaptations to successfully operate in noisy to vegetation tend to have larger eyes and better visual acuity than bats sensory environments. Central to the bat’s success is the ability to that forage in open spaces (table 2 in Eklöf, 2003). These examples dynamically coordinate signal emission and reception over fine time show an increased reliance on multi-modal sensing for bats that scales (Moss and Surlykke, 2010; Wohlgemuth et al., 2016b). These forage in cluttered habitats. adjustments optimize information acquisition and minimize the There is increasing evidence that bats routinely integrate echo– effects of interference arising from background objects, such as acoustic and visual information to perceive their surroundings the signals produced by conspecifics and insects. The bat sonar Journal of Experimental Biology

4562 REVIEW Journal of Experimental Biology (2017) 220, 4554-4566 doi:10.1242/jeb.163063 system can be considered a highly refined form of animal changes dynamically on a very rapid time scale. What remains to be communication, where the signaler and receiver are one and investigated are the ways in which acoustic clutter or noise operate through shared neural processes that have evolved over tens contribute to dynamic neural representations. We hypothesize that of millions of years. Here, we relate studies of bat echolocation in neurons tracking targets in the presence of acoustic clutter sharpen noisy environments to sensory challenges encountered by a wide their response areas, and this can be tested through systematic range of animals. empirical studies. Dynamic sensory processing is important to the lives of many, if Dynamic representations of echo scenes not all, animals. For example, in the presence of masking noise, The bat’s auditory system is specialized to process features of sonar birds and other animals adjust the frequency of their courtship pulses and echoes. The neural basis of acoustic imaging by sonar is signals to improve the SNR (Shannon et al., 2016). It has been still an area of active investigation, but both behavioral (Chiu et al., proposed that a tradeoff exists between optimizing signal 2009; Yovel et al., 2009) and neurophysiological studies transmission and saliency of the signal to the receiver (Patricelli (Wohlgemuth and Moss, 2016; Kothari et al., 2016) indicate that and Blickley, 2006). A bird that shifts its calling frequency in noise bat auditory systems have evolved to detect and discriminate could improve the SNR at the receiver, but the female receiver might features of their own calls from other sounds. An exciting recent be less responsive to this altered signal. It therefore benefits discovery is that the receptive fields of bat auditory neurons change receivers to have flexible feature detection and recognition systems, rapidly in ways that appear to facilitate the transformation of echo especially under noisy conditions. Future research on sensory streams into perceptual representations of auditory objects representation in dynamic environments may reveal the extent to (Bartenstein et al., 2014; Beetz et al., 2016). It has also been which animals other than bats encode dynamic natural stimuli. reported that 3D spatial response profiles of midbrain neurons remap to represent shorter distances with higher resolution when Signal interference freely echolocating big brown bats adjust their echolocation A downside of selective feature recognition may be that it puts behavior to inspect sonar objects (Kothari et al., 2016). These animals at increased risk to specific types of interference, which can findings, illustrated in Fig. 6, indicate that the bat’s auditory receiver be exploited by other animals. This appears to occur in the jamming signals of bats and moths (Fig. 5). Active sensory interference also appears to occur in other communication systems. For example, Relative neural response male oyster toadfish (Opsanus tau) produce precisely timed ‘grunts’ that interfere with communication between competing males and Neuron 1 females (Mensinger, 2014). These grunts might reduce the Neuron 2 perceived frequency of advertisement calls made by competitors, Neuron 3 and thereby reduce their attractiveness to females. Thus, interference signals provide distinct opportunities for probing the inner workings of animal communication receivers.

Coordination between sender and receiver Sensing requires animals to first detect and discriminate signals from noise and then extract meaningful information from those Relative echo delay signals. Animals must have in place mechanisms for achieving each of these sensory tasks. Bats have solved this problem elegantly, again because they actively control signal emission and reception with respect to behavioral state and informational need. As

Frequency (kHz) Search Approach Buzz Time discussed above, bats shift rapidly from producing signals that are optimized for detection to signals that are optimized for localization Fig. 6. Cartoon representation of dynamic echo delay response profiles and feature extraction. This is possible because bat echolocation of three idealized neurons, shown separately in red, blue and green, in the operates through an action–perception loop to adjust signal bat auditory system. Along the lower x-axis are spectrograms of echolocation parameters dynamically with informational needs. Because sender calls produced by an FM bat through the search, approach and capture phases of insect pursuit. Solid horizontal lines below calls at each insect pursuit phase and receiver are the same individual in bat echolocation systems, represent signal duration, and dotted lines represent the interval between there is rapid and tight coordination between call production and successive calls. Note that call duration and interval decrease progressively echo processing. It follows that the level of coordination between from search to approach to capture phases. The y-axis shows relative echo sender and receiver in other animal communication systems should delays (target distances) over which the neurons respond. The upper x-axis impact both the timing and reliability of signal transmission and plots the relative response of the neurons to echo delays at each of these insect reception. This proposal can be tested directly through comparative capture phases. Neurons 1, 2 and 3 respond to echoes at the search and approach phases of insect pursuit, but at different echo delays: neuron 1 analyses of communication behaviors throughout the animal responds to the longest echo delays, neuron 2 to intermediate echo delays, kingdom. and neuron 3 to short echo delays. At the capture phase, only neuron 3 responds to a subset of echoes from the calls produced at a high repetition rate Comparative studies of active sensing in noisy environments (short intervals). Note that neurons 1 and 2 show shifts in responses to shorter While bats and other echolocating animals actively control the timing echo delay as the bat adapts its echolocation behavior and approaches the and features of biosonar signals used to probe the environment, active prey. At the end of the approach phase, the echo delay response areas of the sensing operates in species throughout the animal kingdom three neurons are close to overlapping. All three neurons show a sharpening of echo delay tuning with increasing call repetition rate. This cartoon is based on a (Schroeder et al., 2010). Active sensing refers to the movements synthesis of data reported in Suga and O’Neill (1979); Sullivan (1982); Wong animals make to modify sensory input, which in turn guides future et al. (1992); Bartenstein et al. (2014); Beetz et al. (2016); Kothari et al. (2016). behaviors. Eye movements, for example, allow an animal to scan the Journal of Experimental Biology

4563 REVIEW Journal of Experimental Biology (2017) 220, 4554-4566 doi:10.1242/jeb.163063 environment and represent objects across a broad panorama. The Brumm, H. and Slabbekoorn, H. (2005). Acoustic communication in noise. Adv. visual stimuli acquired through eye movements are also used to Study Behav. 35, 151-209. Capranica, R. R. and Moffat, J. M. (1983). Neurobehavioral correlates of sound inform decisions for subsequent behaviors (Land, 2006). Similarly, communication in anurans. In Advances in Vertebrate Neuroethology (ed. J.-E. head and ear movements introduce changes in acoustic signals Ewert, R. R. Capranica and D. J. Ingle), pp. 701-730. Boston, MA: Springer US. received at the two ears to enhance cues for auditory localization and Casseday, J. H., Ehrlich, D. and Covey, E. (1994). Neural tuning for sound duration: role of inhibitory mechanisms in the inferior colliculus. Science 264, influence perception of an auditory scene (Populin and Yin, 1998; 847-850. Wohlgemuth et al., 2016b). Along related lines, sniffing and Catania, K. C. (2006). Olfaction: underwater “sniffing” by semi-aquatic mammals. whisking serve to modulate sensory signals that can be used to Nature 444, 1024-1025. build up information over time (Ganguly and Kleinfeld, 2004; Chiu, C., Xian, W. and Moss, C. F. (2008). Flying in silence: Echolocating bats cease vocalizing to avoid sonar jamming. Proc. Natl. Acad. Sci. USA 105, Catania, 2006; Towal and Hartmann, 2006). We propose that 13116-13121. quantitative analyses of the echolocating bat’s adaptive behaviors in Chiu, C., Xian, W. and Moss, C. F. (2009). Adaptive echolocation behavior in bats noisy environments will provide the motivation for new lines of for the analysis of auditory scenes. J. Exp. Biol. 212, 1392-1404. investigation on active sensing in a wide range of species across the Corcoran, A. J. and Conner, W. E. (2014). Bats jamming bats: food competition through sonar interference. Science 346, 745-747. animal kingdom. Ultimately, such comparative studies of active Corcoran, A. J. and Conner, W. E. (2016). How moths escape bats: predicting sensing will serve to differentiate between species-specific outcomes of predator-prey interactions. J. Exp. Biol. 219, 2704-2715. specializations and general solutions animals employ to perform Corcoran, A. J. and Hristov, N. I. (2014). Convergent evolution of anti-bat sounds. J. Comp. Physiol. A 200, 811-821. natural behavioral tasks in noisy sensory environments. Corcoran, A. J., Barber, J. R. and Conner, W. E. (2009). Tiger moth jams bat sonar. Science 325, 325-327. Acknowledgements Corcoran, A. J., Conner, W. E. and Barber, J. R. (2010). Anti-bat tiger moth We thank William Conner and two reviewers for critical feedback on earlier drafts of sounds: Form and function. Curr. Zool. 56, 358-369. this manuscript. Corcoran, A. J., Barber, J. R., Hristov, N. I. and Conner, W. E. (2011). How do tiger moths jam bat sonar? J. Exp. Biol. 214, 2416-2425. Competing interests Cvikel, N., Levin, E., Hurme, E., Borissov, I., Boonman, A., Amichai, E. and The authors declare no competing or financial interests. Yovel, Y. (2015a). On-board recordings reveal no jamming avoidance in wild bats. Proc. R. Soc. B 282, 20142274. Cvikel, N., Egert Berg, K., Levin, E., Hurme, E., Borissov, I., Boonman, A., Funding Amichai, E. and Yovel, Y. (2015b). Bats aggregate to improve prey search but The following grants supported research conducted by the authors and the might be impaired when their density becomes too high. Curr. Biol. 25, 206-211. preparation of this article: Human Frontiers Science Program (RGP0040); Office of Danilovich, S., Krishnan, A., Lee, W.-J., Borrisov, I., Eitan, O., Kosa, G., Moss, Naval Research (N00014-12-1-0339); Air Force Office of Scientific Research C. F. and Yovel, Y. (2015). 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