Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Stereausis: binaural processing without neural delays.

S A Shamma1, N M Shen, P Gopalaswamy

  • 1Electrical Engineering Department, University of Maryland, College Park 20742.

The Journal of the Acoustical Society of America
|September 1, 1989
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

MANTA--an open-source, high density electrophysiology recording suite for MATLAB.

Frontiers in neural circuits·2013
Same author

Spectro-temporal response field characterization with dynamic ripples in ferret primary auditory cortex.

Journal of neurophysiology·2001
Same author

Robust spectrotemporal reverse correlation for the auditory system: optimizing stimulus design.

Journal of computational neuroscience·2000
Same author

Spectral-ripple representation of steady-state vowels in primary auditory cortex.

The Journal of the Acoustical Society of America·1998
Same author

Analysis of dynamic spectra in ferret primary auditory cortex. I. Characteristics of single-unit responses to moving ripple spectra.

Journal of neurophysiology·1996
Same author

Analysis of dynamic spectra in ferret primary auditory cortex. II. Prediction of unit responses to arbitrary dynamic spectra.

Journal of neurophysiology·1996

This study introduces a novel neural network for binaural hearing, processing sound localization cues without delay lines. The model enhances noisy signals and lateralizes sounds across all frequencies.

Area of Science:

  • Neuroscience
  • Computational Auditory Neuroscience
  • Signal Processing

Background:

  • Binaural hearing relies on interaural time differences (ITDs) and interaural level differences (ILDs) for sound localization.
  • Existing models often require complex neural delay lines to process these cues.
  • Understanding the neural mechanisms underlying binaural processing is crucial for auditory perception research.

Purpose of the Study:

  • To propose a novel neural network model for binaural processing of ITDs and ILDs.
  • To demonstrate that the model can achieve binaural hearing attributes without neural delay lines.
  • To explore the model's capabilities in sound lateralization and noisy signal enhancement.

Main Methods:

  • A two-dimensional neural network architecture was developed.

Related Experiment Videos

  • The network detects interaural differences by comparing spatial disparities in auditory nerve fiber outputs.
  • It systematically compares spatiotemporal responses at various horizontal shifts, mimicking cross-correlation.
  • The model utilizes inherent delays in basilar membrane traveling waves.

    • Main Results:

    • The proposed network successfully processes interaural time and level cues.
    • It achieves sound lateralization across all frequencies without requiring explicit neural delay lines.
    • The model demonstrates potential for detecting and enhancing signals in noisy environments.
    • Simulations show comparable performance to computational schemes used in visual stereopsis.

    Conclusions:

    • A novel neural network model offers an efficient mechanism for binaural processing.
    • This model provides a biologically plausible explanation for binaural hearing phenomena.
    • The findings suggest a new computational approach for auditory signal processing and prosthetics.