Auditory steady-state responses (ASSRs) are sustained potentials used to assess the physiological integrity of the auditory pathway and objectively estimate hearing thresholds. ASSRs are typically analyzed using statistical procedures in order to remove the subjective bias of human operators. Knowing when to terminate signal averaging in ASSR testing is also critical for making efficient clinical decisions and obtaining high-quality data in empirical research. Here, we investigated a new detection metric for ASSRs based on mutual information (MI) [Bidelman, G. M. (2014). Objective information-theoretic algorithm for detecting brainstem evoked responses to complex stimuli. J. Am. Acad. Audiol., 25(8), 711-722], previously bench tested using only a single suprathreshold stimulus. ASSRs were measured in n=10 normal hearing listeners to various stimuli varying in modulation rate (40, 80 Hz) and level (80 – 20 dB SPL). MI-based classifiers applied to ASSRs recordings showed that accuracy of ASSR detection ranged from ~75 - 99% and was better for 40 compared to 80 Hz responses and for higher compared to lower stimulus levels. Detailed receiver operating characteristics (ROC) were used to establish normative ranges for MI for reliable ASSR detection across levels and rates (MI=0.9-1.6). Relative to current statistics for ASSR identification (F-test), MI was found to be a more efficient metric for determining the stopping criterion for signal averaging. Our new results confirm that MI can be applied across a broad range of ASSR stimuli and might offer improvements to conventional objective techniques for ASSR detection.
37Auditory steady-state responses (ASSRs) are sustained potentials used to assess the physiological 38 integrity of the auditory pathway and objectively estimate hearing thresholds. ASSRs are typically 39 analyzed using statistical procedures in order to remove the subjective bias of human operators. Knowing 40 when to terminate signal averaging in ASSR testing is also critical for making efficient clinical decisions 41 and obtaining high-quality data in empirical research. Here, we investigated a new detection metric for 42ASSRs based on mutual information (MI) [Bidelman, G. M. (2014). Objective information-theoretic 43 algorithm for detecting brainstem evoked responses to complex stimuli. J. Am. Acad. Audiol., 25(8), 722], previously bench tested using only a single suprathreshold stimulus. ASSRs were measured in n=10 45 normal hearing listeners to various stimuli varying in modulation rate (40, 80 Hz) and level (80 -20 dB 46 SPL). MI-based classifiers applied to ASSRs recordings showed that accuracy of ASSR detection ranged 47 from ~75 -99% and was better for 40 compared to 80 Hz responses and for higher compared to lower 48 stimulus levels. Detailed receiver operating characteristics (ROC) were used to establish normative ranges 49 for MI for reliable ASSR detection across levels and rates (MI=0.9-1.6). Relative to current statistics for 50 ASSR identification (F-test), MI was found to be a more efficient metric for determining the stopping 51 criterion for signal averaging. Our new results confirm that MI can be applied across a broad range of 52 ASSR stimuli and might offer improvements to conventional objective techniques for ASSR detection.
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