A computational model of echo processing and acoustic imaging in frequency- modulated echolocating bats: The spectrogram correlation and transformation receiver

Saillant, Prestor A.; Simmons, James A.; Dear, Steven P.; McMullen, Teresa A.

doi:10.1121/1.407353

Cited by 150 publications

(129 citation statements)

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“…It was therefore suggested that bats perceive two front echoes in the spectral domain and then translate the spectral notch pattern into a full time domain representation of the actual range profile (Simmons et al, 1990). The spectrogram correlation and transformation (SCAT) model (Saillant et al, 1993) explains the transformation of spectral information into time information. Assuming this mechanism, gap 1-2 duration may well have played a decisive role for the discrimination of different sized hollow hemispheres.…”

Section: Temporal Pattern and Spectral Domainmentioning

confidence: 99%

Size discrimination of hollow hemispheres by echolocation in a nectar feeding bat

Simon

Holderied

Helversen

2006

Journal of Experimental Biology

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the echo's temporal and spectral pattern as well as in amplitude.Bats were simultaneously confronted with seven different sizes of hollow hemispheres presented from their concave sides. Visits to one particular size were rewarded with sugar water, while we recorded the frequency of visits to the unrewarded hemispheres. We found that: (1) bats learned to discriminate between hemispheres of different size with ease; (2) the minimum size difference for discrimination was a constant percentage of the hemisphere's size (Weber fraction: approximately 16% of the radius); (3) the comparison of behavioural data and impulse response measurements of the objects' echoes yielded discrimination thresholds for mean intensity differences (1.3·dB), the temporal pattern (3-22· s) and the change of spectral notch frequency (approximately 16%). We discuss the advantages of discrimination in the frequency and/or time domain.

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Section: Temporal Pattern and Spectral Domainmentioning

confidence: 99%

Size discrimination of hollow hemispheres by echolocation in a nectar feeding bat

Simon

Holderied

Helversen

2006

Journal of Experimental Biology

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“…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)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12).…”

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confidence: 99%

Classification of natural textures in echolocation

Grunwald

Schörnich

Wiegrebe

2004

Proc. Natl. Acad. Sci. U.S.A.

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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...

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“…We found that a receiver model incorporating the two most salient physiological features of the auditory time͞frequency representation (V-shaped tuning curves with different high-and low-frequency slopes, and an active process for compressive gain nonlinearity) replicates the relations between the bat's delay thresholds, echo bandwidth, and Q. Bats perform exceptionally well in tasks requiring classification of targets by shape by using a small number of echoes (34), and it is possible to transform time͞frequency information to depict target shape from delays (35)(36)(37)(38). Knowing that the underlying reciprocal relation is to relative bandwidth, Q, not absolute bandwidth, B, gives new insights into the nature of this transformation.…”

Section: Discussionmentioning

confidence: 99%

Delay accuracy in bat sonar is related to the reciprocal of normalized echo bandwidth, or Q

Simmons

Neretti

Intrator

et al. 2004

Proc. Natl. Acad. Sci. U.S.A.

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Big brown bats (Eptesicus fuscus) emit wideband, frequencymodulated biosonar sounds and perceive the distance to objects from the delay of echoes. Bats remember delays and patterns of delay from one broadcast to the next, and they may rely on delays to perceive target scenes. While emitting a series of broadcasts, they can detect very small changes in delay based on their estimates of delay for successive echoes, which are derived from an auditory time͞frequency representation of frequency-modulated sounds. To understand how bats perceive objects, we need to know how information distributed across the time͞frequency surface is brought together to estimate delay. To assess this transformation, we measured how alteration of the frequency content of echoes affects the sharpness of the bat's delay estimates from the distribution of errors in a psychophysical task for detecting changes in delay. For unrestricted echo frequency content and high echo signal-to-noise ratio, bats can detect extremely small changes in delay of about 10 ns. When echo bandwidth is restricted by filtering out low or high frequencies, the bat's delay acuity declines in relation to the reciprocal of relative echo bandwidth, expressed as Q, which also is the relative width of the target impulse response in cycles rather than time. This normalized-time dimension may be efficient for target classification if it leads to target shape being displayed independent of size. This relation may originate from cochlear transduction by parallel frequency channels with active amplification, which creates the auditory time͞frequency representation itself.

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A computational model of echo processing and acoustic imaging in frequency- modulated echolocating bats: The spectrogram correlation and transformation receiver

Cited by 150 publications

References 0 publications

Size discrimination of hollow hemispheres by echolocation in a nectar feeding bat

Size discrimination of hollow hemispheres by echolocation in a nectar feeding bat

Classification of natural textures in echolocation

Delay accuracy in bat sonar is related to the reciprocal of normalized echo bandwidth, or Q

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