Subcortical responses to music and speech are alike while cortical responses diverge

Abstract

Music and speech are encountered daily and are unique to human beings. Both are transformed by the auditory pathway from an initial acoustical encoding to higher level cognition. Studies of cortex have revealed distinct brain responses to music and speech, but differences may emerge in the cortex or may be inherited from different subcortical encoding. In the first part of this study, we derived the human auditory brainstem response (ABR), a measure of subcortical encoding, to recorded music and speech using two analysis methods. The first method, described previously and acoustically based, yielded very different ABRs between the two sound classes. The second method, however, developed here and based on a physiological model of the auditory periphery, gave highly correlated responses to music and speech. We determined the superiority of the second method through several metrics, suggesting there is no appreciable impact of stimulus class (i.e., music vs speech) on the way stimulus acoustics are encoded subcortically. In this study’s second part, we considered the cortex. Our new analysis method resulted in cortical music and speech responses becoming more similar but with remaining differences. The subcortical and cortical results taken together suggest that there is evidence for stimulus-class dependent processing of music and speech at the cortical but not subcortical level.

Level Dependent Subcortical EEG Responses to Continuous Speech

“…As expected, the wave V peak amplitude increases and the latency decreases with increasing intensity. Earlier peaks of the canonical ABR are not visible, similar to some prior studies (Maddox & Lee, 2018; Shan et al, 2024; Bachmann et al, 2023).…”

“…negative latency slopes and positive amplitude slopes) after only 5 minutes of data within each level (or 20 minutes of total data). Additionally, we investigated the amount of data required to fit TRFs with reliable wave V peaks within each level using the wave V SNR as a performance metric, similar to prior work (Shan et al, 2024; Kulasingham et al, 2024; Bachmann et al, 2023; Maddox & Lee, 2018; Polonenko & Maddox, 2021). Given that wave V peak amplitudes are larger for high compared to low intensities, it is reasonable to expect that wave V SNR will also be larger at higher intensities (see Fig.…”

“…This model consists of several stages approximating non-linear cochlear filters, inner and outer hair cell properties, auditory nerve synapses, and adaptation. The implementation in the Python cochlea package (Rudnicki et al, 2015) was used with 43 auditory nerve fibers with high spontaneous firing rates and center frequencies logarithmically spaced between 125 Hz and 16 kHz, in line with previous work (Shan et al, 2024). The outputs of this model are the mean firing rates of the auditory nerves, which were averaged to form the final predictors.…”

“…The TRF is a linear model that maps stimulus features (predictors) to the EEG in a continuous manner (Lalor et al, 2009). Although TRFs have been widely used to investigate cortical responses (Brodbeck & Simon, 2020;Kulasingham & Simon, 2023), there have been far fewer studies on subcortical TRFs (Polonenko & Maddox, 2021;Shan et al, 2024;Bachmann et al, 2021;Kulasingham et al, 2024).These subcortical TRFs have similar morphologies to conventional ABR ERPs, especially regarding the wave V peak (Bachmann et al, 2023). Moving towards ecologically relevant, natural speech stimuli could provide several benefits when investigating the auditory system (Hamilton & Huth, 2020), and may also increase patient comfort during clinical hearing assessments.…”

“…Since the TRF is a linear model, it cannot model the highly non-linear processing stages in the auditory periphery. Recent studies have used auditory peripheral models to generate predictors that incorporate these non-linearities (Shan et al, 2024; Kulasingham et al, 2024). These predictors are then used to fit TRFs, resulting in a more linearized estimation problem, and improved subcortical TRFs.…”