Comparing Methods for Deriving the Auditory Brainstem Response to Continuous Speech in Human Listeners

Abstract

AbstractSeveral tools have recently been developed to derive the Auditory Brainstem Response (ABR) from continuous natural speech, facilitating investigation into subcortical encoding of speech. These tools rely on deconvolution, which models the subcortical auditory pathway as a linear system, where a nonlinearly processed stimulus is taken as the input (i.e., regressor), the electroencephalogram (EEG) data as the output, and the ABR as the impulse response deconvolved from the recorded EEG and the regressor. In this study, we analyzed EEG recordings from subjects listening to both unaltered natural speech and synthesized “peaky speech.” We compared the derived ABRs using three regressors: the half-wave rectified stimulus (HWR) from Maddox and Lee (2018), the glottal pulse train (GP) from Polonenko and Maddox (2021), and the auditory nerve modeled response (ANM) from Shan et al. (2024). Our evaluation focused on the fidelity, efficiency, and practicality of each method in different scenarios. The results indicate that the ANM regressor for both peaky and unaltered speech and the GP regressor for peaky speech provided the best performance, whereas the HWR regressor demonstrated relatively poorer performance. The findings in this study will guide future research in selecting the most appropriate paradigm for ABR derivation from continuous, naturalistic speech.