bioRxivNeurosciencePreprint
Auditory Brainstem Response as an Objective Measure of Temporal Resolution
Abstract
Background and AimsTemporal resolution is assessed using behavioral tests, which are highly affected by extraneous variables. We explored the relationship between behavioral Across-Channel Gap Detection Threshold (AC GDT) and different temporal parameters of an objective measure, Auditory Brainstem Response (ABR), to account for the extraneous variables. Settings and DesignWe conducted an experimental study on thirty native Kannada-speaking adults with normal hearing sensitivity in the age range of 18-25 years. Materials and MethodsWe estimated the Gap detection threshold (GDT) using an across-channel (AC) paradigm, and Auditory Brainstem Response (ABR) was recorded at 80 dBnHL for three repetition rates of 11.1, 30.1, and 90.1/sec. Statistical Analyses usedNormality testing, the Friedman test, post-hoc analysis by Wilcoxon Signed-Rank test, along with descriptive statistics was performed using SPSS v20 (IBM Statistical Package for Social Sciences, New York, USA). ResultsThe results showed a significant positive correlation between AC GDT scores and latency of wave I for the repetition rates of 11.1 and 30.1/sec and latency of wave V at 30.1 and 90.1/sec. There was a negative correlation (but not significant) between AC GDT scores and the slope of wave V across the repetition rates. ConclusionsThe results suggest a relationship between the behavioral and electrophysiological measures of temporal processing. Measuring the latency of wave I and wave V of ABR would give an estimate of their AC GDT scores, especially in difficult-to-test populations. Key messagesTo test temporal resolution abilities in individuals with normal hearing sensitivity, we can use an objective measure of latency of wave I and wave V of ABR. ABR can be highly useful in reducing testing time and obtaining reliable estimates in children and individuals with associated disorders like autism, below-average intelligence, and so on.
- organism: human
- assay: electronic health records
- research focus: benchmarking
- approach: statistical model
- Citations
- 0
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