Background: Auditory brainstem responses (ABRs) are used to study auditory acuity in animal-based medical research. ABRs are evoked by acoustic stimuli, and consist of an electrical signal resulting from summated activity in the auditory nerve and brainstem nuclei. ABR analysis determines the sound intensity at which a neural response first appears (hearing threshold). Traditionally, threshold has been assessed by visual estimation of a series of ABRs evoked by different sound intensities. Here we develop an automated threshold detection method that eliminates the variability and subjectivity associated with visual estimation. Results: The automated method is a robust computational procedure that detects the sound level at which the peak amplitude of the evoked ABR signal first exceeds four times the standard deviation of the baseline noise. Implementation of the procedure was achieved by evoking ABRs in response to click and tone stimuli, under normal and experimental conditions (adult stem cell transplantation into cochlea). Automated detection revealed that the threshold shift from pre- to post-surgery hearing levels was similar in mice receiving stem cell transplantation or sham injection for click and tone stimuli. Visual estimation by independent observers corroborated these results but revealed variability in ABR threshold shifts and significance levels for stem cell-transplanted and sham-injected animals. Conclusion: In summary, the automated detection method avoids the subjectivity of visual analysis and offers a rapid, easily accessible http://axograph.com/source/abr.html approach to measure hearing threshold levels in auditory brainstem response.
ASJC Scopus subject areas
- Cellular and Molecular Neuroscience