Literature DB >> 33596199

A comprehensive computational model of animal biosonar signal processing.

Chen Ming1, Stephanie Haro2, Andrea Megela Simmons3, James A Simmons1.   

Abstract

Computational models of animal biosonar seek to identify critical aspects of echo processing responsible for the superior, real-time performance of echolocating bats and dolphins in target tracking and clutter rejection. The Spectrogram Correlation and Transformation (SCAT) model replicates aspects of biosonar imaging in both species by processing wideband biosonar sounds and echoes with auditory mechanisms identified from experiments with bats. The model acquires broadband biosonar broadcasts and echoes, represents them as time-frequency spectrograms using parallel bandpass filters, translates the filtered signals into ten parallel amplitude threshold levels, and then operates on the resulting time-of-occurrence values at each frequency to estimate overall echo range delay. It uses the structure of the echo spectrum by depicting it as a series of local frequency nulls arranged regularly along the frequency axis of the spectrograms after dechirping them relative to the broadcast. Computations take place entirely on the timing of threshold-crossing events for each echo relative to threshold-events for the broadcast. Threshold-crossing times take into account amplitude-latency trading, a physiological feature absent from conventional digital signal processing. Amplitude-latency trading transposes the profile of amplitudes across frequencies into a profile of time-registrations across frequencies. Target shape is extracted from the spacing of the object's individual acoustic reflecting points, or glints, using the mutual interference pattern of peaks and nulls in the echo spectrum. These are merged with the overall range-delay estimate to produce a delay-based reconstruction of the object's distance as well as its glints. Clutter echoes indiscriminately activate multiple parts in the null-detecting system, which then produces the equivalent glint-delay spacings in images, thus blurring the overall echo-delay estimates by adding spurious glint delays to the image. Blurring acts as an anticorrelation process that rejects clutter intrusion into perceptions.

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Mesh:

Year:  2021        PMID: 33596199      PMCID: PMC7888678          DOI: 10.1371/journal.pcbi.1008677

Source DB:  PubMed          Journal:  PLoS Comput Biol        ISSN: 1553-734X            Impact factor:   4.475


  77 in total

Review 1.  Timing in the auditory system of the bat.

Authors:  E Covey; J H Casseday
Journal:  Annu Rev Physiol       Date:  1999       Impact factor: 19.318

2.  An echolocation model for range discrimination of multiple closely spaced objects: transformation of spectrogram into the reflected intensity distribution.

Authors:  Ikuo Matsuo; Kenji Kunugiyama; Masafumi Yano
Journal:  J Acoust Soc Am       Date:  2004-02       Impact factor: 1.840

3.  Corticofugal modulation of the paradoxical latency shifts of inferior collicular neurons.

Authors:  Xiaofeng Ma; Nobuo Suga
Journal:  J Neurophysiol       Date:  2008-07-02       Impact factor: 2.714

Review 4.  The volley theory and the spherical cell puzzle.

Authors:  P X Joris; P H Smith
Journal:  Neuroscience       Date:  2008-03-08       Impact factor: 3.590

5.  Target structure and echo spectral discrimination by echolocating bats.

Authors:  J A Simmons; W A Lavender; B A Lavender; C A Doroshow; S W Kiefer; R Livingston; A C Scallet; D E Crowley
Journal:  Science       Date:  1974-12-20       Impact factor: 47.728

6.  Selectivity for echo spectral interference and delay in the auditory cortex of the big brown bat Eptesicus fuscus.

Authors:  Mark I Sanderson; James A Simmons
Journal:  J Neurophysiol       Date:  2002-06       Impact factor: 2.714

7.  Phase Locking of Auditory Nerve Fibers: The Role of Lowpass Filtering by Hair Cells.

Authors:  Adam J Peterson; Peter Heil
Journal:  J Neurosci       Date:  2020-05-06       Impact factor: 6.167

8.  Automatic gain control in the bat's sonar receiver and the neuroethology of echolocation.

Authors:  S A Kick; J A Simmons
Journal:  J Neurosci       Date:  1984-11       Impact factor: 6.167

9.  Time and Frequency domain processing in the inferior colliculus of echolocating bats.

Authors:  R D Bodenhamer; G D Pollak
Journal:  Hear Res       Date:  1981-11       Impact factor: 3.208

10.  Neural responses to overlapping FM sounds in the inferior colliculus of echolocating bats.

Authors:  M I Sanderson; J A Simmons
Journal:  J Neurophysiol       Date:  2000-04       Impact factor: 2.714

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  3 in total

1.  Non-invasive auditory brainstem responses to FM sweeps in awake big brown bats.

Authors:  Andrea Megela Simmons; Amaro Tuninetti; Brandon M Yeoh; James A Simmons
Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2022-06-28       Impact factor: 2.389

2.  Faster Repetition Rate Sharpens the Cortical Representation of Echo Streams in Echolocating Bats.

Authors:  Silvio Macias; Kushal Bakshi; Michael Smotherman
Journal:  eNeuro       Date:  2022-02-09

3.  Analysis of echolocation behavior of bats in "echo space" using acoustic simulation.

Authors:  Yu Teshima; Yasufumi Yamada; Takao Tsuchiya; Olga Heim; Shizuko Hiryu
Journal:  BMC Biol       Date:  2022-03-14       Impact factor: 7.431

  3 in total

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