The auditory brainstem response (ABR) is a measure of subcortical activity in response to auditory stimuli. The wave V peak of the ABR depends on the stimulus intensity level, and has been widely used for clinical hearing assessment. Conventional methods estimate the ABR average electroencephalography (EEG) responses to short unnatural stimuli such as clicks. Recent work has moved toward more ecologically relevant continuous speech stimuli using linear deconvolution models called temporal response functions (TRFs). Investigating whether the TRF waveform changes with stimulus intensity is a crucial step toward the use of natural speech stimuli for hearing assessments involving subcortical responses. Here, we develop methods to estimate level-dependent subcortical TRFs using EEG data collected from 21 participants listening to continuous speech presented at 4 different intensity levels. We find that level-dependent changes can be detected in the wave V peak of the subcortical TRF for almost all participants, and are consistent with level-dependent changes in click-ABR wave V. We also investigate the most suitable peripheral auditory model to generate predictors for level-dependent subcortical TRFs and find that simple gammatone filterbanks perform the best. Additionally, around 6 min of data may be sufficient for detecting level-dependent effects and wave V peaks above the noise floor for speech segments with higher intensity. Finally, we show a proof-of-concept that level-dependent subcortical TRFs can be detected even for the inherent intensity fluctuations in natural continuous speech.
Keywords: audiology; deconvolution; neural speech tracking; neuroimaging; piecewise linear model.
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