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Related Experiment Video

Updated: Jun 15, 2026

Semi-Automated Analysis of Peak Amplitude and Latency for Auditory Brainstem Response Waveforms Using R
06:01

Semi-Automated Analysis of Peak Amplitude and Latency for Auditory Brainstem Response Waveforms Using R

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ABRpresto: An algorithm for automatic thresholding of the Auditory Brainstem Response using resampled

Luke A Shaheen1, Brad N Buran2, Kirupa Suthakar3,4

  • 1Regeneron Pharmaceuticals, Tarrytown NY.

Biorxiv : the Preprint Server for Biology
|November 22, 2024
PubMed
Summary

A new algorithm accurately estimates auditory brainstem response (ABR) thresholds by cross-correlating response averages. This method improves objectivity and efficiency in preclinical hearing research.

Keywords:
ABRAlgorithmCorrelationHearingResamplingThreshold

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Area of Science:

  • Neuroscience
  • Audiology
  • Biomedical Engineering

Background:

  • Auditory Brainstem Response (ABR) is crucial for assessing cochlear health in research and clinics.
  • Estimating ABR threshold, the minimum sound level evoking a response, is challenging due to waveform shifts and low signal-to-noise ratio.
  • Current standard practice relies on subjective visual evaluation of ABR waveforms.

Purpose of the Study:

  • To develop and validate an objective algorithm for precise ABR threshold estimation.
  • To improve upon existing methods for ABR threshold determination in preclinical studies.

Main Methods:

  • Developed a novel algorithm using cross-correlation of two independent response averages for each stimulus level.
  • Responses were split into two groups, median waveforms calculated, and normalized cross-correlation computed.
  • Repeated cross-correlation 500 times, analyzed distributions, and fitted data with sigmoid or power law functions to estimate thresholds.

Main Results:

  • The algorithm achieved 92% accuracy within ±10 dB of human-rated thresholds on extensive mouse data.
  • Demonstrated superior performance compared to several previously published algorithms on the same dataset.
  • Successfully replaced manual ABR threshold estimation in preclinical studies, enhancing speed and objectivity.

Conclusions:

  • The developed cross-correlation algorithm provides a robust, accurate, and objective method for ABR threshold estimation.
  • This algorithmic approach significantly improves efficiency and reliability in auditory research.
  • The findings support the adoption of this algorithm for standardized preclinical auditory assessments.