The precedence effect describes the phenomenon whereby echoes are spatially fused to the location of an initial sound by selectively suppressing the directional information of lagging sounds (echo suppression). Echo suppression is a prerequisite for faithful sound localization in natural environments but can break down depending on the behavioral context. To date, the neural mechanisms that suppress echo directional information without suppressing the perception of echoes themselves are not understood. We performed in vivo recordings in Mongolian gerbils of neurons of the dorsal nucleus of the lateral lemniscus (DNLL), a GABAergic brainstem nucleus that targets the auditory midbrain, and show that these DNLL neurons exhibit inhibition that persists tens of milliseconds beyond the stimulus offset, so-called persistent inhibition (PI). Using in vitro recordings, we demonstrate that PI stems from GABAergic projections from the opposite DNLL. Furthermore, these recordings show that PI is attributable to intrinsic features of this GABAergic innervation. Implementation of these physiological findings into a neuronal model of the auditory brainstem demonstrates that, on a circuit level, PI creates an enhancement of responsiveness to lagging sounds in auditory midbrain cells. Moreover, the model revealed that such response enhancement is a sufficient cue for an ideal observer to identify echoes and to exhibit echo suppression, which agrees closely with the percepts of human subjects.

Short-term adjustments of signal characteristics allow animals to maintain reliable communication in noise. Noise-dependent vocal plasticity often involves simultaneous changes in multiple parameters. Here, we quantified for the first time the relative contributions of signal amplitude, duration, and redundancy for improving signal detectability in noise. To this end, we used a combination of behavioural experiments on pale spear-nosed bats (Phyllostomus discolor) and signal detection models. In response to increasing noise levels, all bats raised the amplitude of their echolocation calls by 1.8–7.9 dB (the Lombard effect). Bats also increased signal duration by 13%–85%, corresponding to an increase in detectability of 1.0–5.3 dB. Finally, in some noise conditions, bats increased signal redundancy by producing more call groups. Assuming optimal cognitive integration, this could result in a further detectability improvement by up to 4 dB. Our data show that while the main improvement in signal detectability was due to the Lombard effect, increasing signal duration and redundancy can also contribute markedly to improving signal detectability. Overall, our findings demonstrate that the observed adjustments of signal parameters in noise are matched to how these parameters are processed in the receiver’s sensory system, thereby facilitating signal transmission in fluctuating environments.

Through echolocation, a bat can perceive not only the position of an object in the dark; it can also recognize its 3D structure. A tree, however, is a very complex object; it has thousands of reflective surfaces that result in a chaotic acoustic image of the tree. Technically, the acoustic image of an object is its impulse response (IR), i.e., the sum of the reflections recorded when the object is ensonified with an acoustic impulse. The extraction of the acoustic IR from the ultrasonic echo and the detailed IR analysis underlies the bats' extraordinary object-recognition capabilities. Here, a phantomobject playback experiment is developed to demonstrate that the bat Phyllostomus discolor can evaluate a statistical property of chaotic IRs, the IR roughness. The IRs of the phantom objects consisted of up to 4,000 stochastically distributed reflections. It is shown that P. discolor spontaneously classifies echoes generated with these IRs according to IR roughness. This capability enables the bats to evaluate complex natural textures, such as foliage types, in a meaningful manner. The present behavioral results and their simulations in a computer model of the bats' ascending auditory system indicate the involvement of modulation-sensitive neurons in echo analysis.T he neural interpretation of sensory input into an objectbased sensory scenery is a major focus in neuroscience. The echolocation of bats and dolphins is an ideal model system, because echolocating mammals have perfect control over their sensory data acquisition due to the active nature of echolocation. A useful analysis of the acoustic scenes, as they are represented in sequences of echoes, requires the identification of the acoustically complex objects surrounding the animals in their natural habitat. Many studies have provided insights into the extraordinary capabilities of echolocating animals in object recognition and classification (1-12).In their natural nocturnal habitat, bats are forced to orient in and navigate through a highly structured environment. How can echolocation serve these tasks? The echoes produced by potential landmarks for orientation, such as trees or bushes, are highly chaotic: the ultrasonic emission of a bat is reflected from a multitude of surfaces, the leaves, which are chaotically distributed in space and angle to the sound source and receiver. Thus, the echoes reflected from such an object will have a chaotic waveform and no systematic spectral interference pattern (Fig. 1). Moreover, the echoes are highly unstable over time, because they are susceptible to both changes of the bat's observation angle and, e.g., wind-induced movement of the object. Thus, a bat will rarely receive the same echo of an individual object twice.Until now, object recognition in echolocation has been studied only with deterministic echoes from small objects with very few reflections. The echoes from such objects can be evaluated according to their characteristic waveforms and͞or frequency patterns (2, 9, 13). However, these concepts appear insuffi...

Echolocation is typically associated with bats and toothed whales. To date, only few studies have investigated echolocation in humans. Moreover, these experiments were conducted with real objects in real rooms; a configuration in which features of both vocal emissions and perceptual cues are difficult to analyse and control. We investigated human sonar target-ranging in virtual echo-acoustic space, using a short-latency, real-time convolution engine. Subjects produced tongue clicks, which were picked up by a headset microphone, digitally delayed, convolved with individual head-related transfer functions and played back through earphones, thus simulating a reflecting surface at a specific range in front of the subject. In an adaptive 2-AFC paradigm, we measured the perceptual sensitivity to changes of the range for reference ranges of 1.7, 3.4 or 6.8 m. In a follow-up experiment, a second simulated surface at a lateral position and a fixed range was added, expected to act either as an interfering masker or a useful reference. The psychophysical data show that the subjects were well capable to discriminate differences in the range of a frontal reflector. The range-discrimination thresholds were typically below 1 m and, for a reference range of 1.7 m, they were typically below 0.5 m. Performance improved when a second reflector was introduced at a lateral angle of 45°. A detailed analysis of the tongue clicks showed that the subjects typically produced short, broadband palatal clicks with durations between 3 and 15 ms, and sound levels between 60 and 108 dB. Typically, the tongue clicks had relatively high peak frequencies around 6 to 8 kHz. Through the combination of highly controlled psychophysical experiments in virtual space and a detailed analysis of both the subjects' performance and their emitted tongue clicks, the current experiments provide insights into both vocal motor and sensory processes recruited by humans that aim to explore their environment by echolocation.

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.

The mammalian auditory system is the temporally most precise sensory modality: To localize low-frequency sounds in space, the binaural system can resolve time differences between the ears with microsecond precision. In contrast, the binaural system appears sluggish in tracking changing interaural time differences as they arise from a low-frequency sound source moving along the horizontal plane. For a combined psychophysical and electrophysiological approach, we created a binaural stimulus, called "Phasewarp," that can transmit rapid changes in interaural timing. Using this stimulus, the binaural performance in humans is significantly better than reported previously and comparable with the monaural performance revealed with amplitude-modulated stimuli. Parallel, electrophysiological recordings of binaural brainstem neurons in the gerbil show fast temporal processing of monaural and different types of binaural modulations. In a refined electrophysiological approach that was matched to the psychophysics, the seemingly faster binaural processing of the Phasewarp was confirmed. The current data provide both psychophysical and physiological evidence against a general, hard-wired binaural sluggishness and reconcile previous contradictions of electrophysiological and psychophysical estimates of temporal binaural performance.

Echolocation is an active sense enabling bats and toothed whales to orient in darkness through echo returns from their ultrasonic signals. Immediately before prey capture, both bats and whales emit a buzz with such high emission rates (≥180 Hz) and overall duration so short that its functional significance remains an enigma. To investigate sensory-motor control during the buzz of the insectivorous bat Myotis daubentonii, we removed prey, suspended in air or on water, before expected capture. The bats responded by shortening their echolocation buzz gradually; the earlier prey was removed down to approximately 100 ms (30 cm) before expected capture, after which the full buzz sequence was emitted both in air and over water. Bats trawling over water also performed the full capture behavior, but in-air capture motions were aborted, even at very late prey removals (<20 ms = 6 cm before expected contact). Thus, neither the buzz nor capture movements are stereotypical, but dynamically adapted based on sensory feedback. The results indicate that echolocation is controlled mainly by acoustic feedback, whereas capture movements are adjusted according to both acoustic and somatosensory feedback, suggesting separate (but coordinated) central motor control of the two behaviors based on multimodal input. Bat echolocation, especially the terminal buzz, provides a unique window to extremely fast decision processes in response to sensory feedback and modulation through attention in a naturally behaving animal.ost sensory systems passively sample the environment by relying on extrinsic energy sources like light or sound to stimulate sensory receptors. Truly active senses, e.g., the electric sense of weakly electric fishes (1) and echolocation (2), where the animal itself produces the energy used to probe the surroundings, are rare (3). The advanced echolocation systems of bats and toothed whales involve dynamic adaptation of the outgoing sound and behavior based on perception of the surroundings through information processing of returning echoes.The temporal pattern of echolocation signals during prey pursuit changes through three phases: search, approach, and terminal buzz. The buzz, immediately preceding prey capture, is characterized by a dramatic increase in signal repetition rate and is universally present in both bats and whales capturing moving prey (4-8). Repetition rates up to 640 Hz have been reported for porpoises and, contrary to bats, odontocete buzzes usually continue beyond prey contact (6). The buzz of many vespertilionid and molossid bats has two distinct subphases: buzz I with decreasing call durations and intervals, followed by buzz II, with a constant maximum call repetition rate and a characteristic frequency drop of up to an octave (4,(9)(10)(11)(12)(13)(14).The function of the terminal buzz is still not understood (15). It has been hypothesized that odontocete buzzes not only track prey before capture (7), but may also serve to follow escaping prey (6). Bat buzzes have also been hypothesized to help track ev...

Echolocating bats can identify three-dimensional objects exclusively through the analysis of acoustic echoes of their ultrasonic emissions. However, objects of the same structure can differ in size, and the auditory system must achieve a size-invariant, normalized object representation for reliable object recognition. This study describes both the behavioral classification and the cortical neural representation of echoes of complex virtual objects that vary in object size. In a phantom-target playback experiment, it is shown that the bat Phyllostomus discolor spontaneously classifies most scaled versions of objects according to trained standards. This psychophysical performance is reflected in the electrophysiological responses of a population of cortical units that showed an object-size invariant response (14/109 units, 13%). These units respond preferentially to echoes from objects in which echo duration (encoding object depth) and echo amplitude (encoding object surface area) co-varies in a meaningful manner. These results indicate that at the level of the bat's auditory cortex, an object-oriented rather than a stimulus-parameter–oriented representation of echoes is achieved.