Abstract
Auditory brainstem responses (ABRs) require averaging responses to hundreds or thousands of repetitions of a stimulus (e.g., tone pip) to obtain a measurable evoked response at the scalp. Fast repetition rates lead to changes in ABR amplitude and latency due to adaptation. To minimize the effect of adaptation, stimulus rates are sometimes as low as 10 to 13.3 stimuli per second, requiring long acquisition times. The trade-off between reducing acquisition time and minimizing the effect of adaptation on ABRs is an especially important consideration for studies of cochlear synaptopathy, which use the amplitude of short latency responses (wave 1) to assess auditory nerve survival. It has been proposed that adaptation during ABR acquisition can be reduced by interleaving tones at different frequencies, rather than testing each frequency serially. With careful ordering of frequencies and levels in the stimulus train, adaptation in the auditory nerve can be minimized, thereby permitting an increase in the rate at which tone bursts are presented. However, widespread adoption of this stimulus design has been hindered by lack of available software. Here, we develop and validate an interleaved stimulus design to optimize the rate of ABR measurement while minimizing adaptation. We implement this method in an open-source data acquisition software tool that permits either serial or interleaved ABR measurements. The open-source software library, psiexperiment, is compatible with widely used ABR hardware. Consistent with previous studies, careful design of an interleaved stimulus train can reduce ABR acquisition time by more than half, with minimal effect on ABR thresholds and wave 1 latency, while improving measures of wave 1 amplitude.
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Acknowledgements
The authors would like to acknowledge Jesyin Lai’s assistance in acquiring data from ferret and Garnett McMillian for tutorials on implementing Bayesian models. Adaptation of the software to Tucker-Davis hardware was provided by Decibel Therapeutics, Inc. We are grateful to Ann Hickox for providing extensive testing and feedback on the software.
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Buran, B.N., Elkins, S., Kempton, J.B. et al. Optimizing Auditory Brainstem Response Acquisition Using Interleaved Frequencies. JARO 21, 225–242 (2020). https://doi.org/10.1007/s10162-020-00754-3
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DOI: https://doi.org/10.1007/s10162-020-00754-3