Biology subjects

Enqvist, M.

Publications and source records attributed to Enqvist, M..

3 recordsLinked to original sources

bioRxiv2024

Level Dependent Subcortical EEG Responses to Continuous Speech

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 stimulus intensity level, and has been widely used for clinical hearing assessment. Conventional methods to estimate the ABR average electroencephalography (EEG) responses to short unnatural stimuli such as clicks. Recent work has moved towards 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 towards 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 minutes 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. Visual abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/587607v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@1a0f46corg.highwire.dtl.DTLVardef@eeb99org.highwire.dtl.DTLVardef@18d951forg.highwire.dtl.DTLVardef@393d96_HPS_FORMAT_FIGEXP M_FIG C_FIG Significance statementSubcortical EEG responses to sound depend on the stimulus intensity level and provide a window into the early human auditory pathway. However, current methods detect responses using unnatural transient stimuli such as clicks or chirps. We develop methods for detecting level-dependent responses to continuous speech stimuli, which is more ecologically relevant and may provide several advantages over transient stimuli. Critically, we find consistent patterns of level dependent subcortical responses to continuous speech at an individual level, that are directly comparable to those seen for conventional responses to click stimuli. Our work lays the foundation for the use of subcortical responses to natural speech stimuli in future applications such as clinical hearing assessment and hearing assistive technology.

neuroscience↗

bioRxiv2023

Extending Subcortical EEG Responses to Continuous Speech to the Sound-Field

The auditory brainstem response (ABR) is a valuable clinical tool for objective hearing assessment, which is conventionally detected by averaging neural responses to thousands of short stimuli. Progressing beyond these unnatural stimuli, brainstem responses to continuous speech presented via earphones have been recently detected using linear temporal response functions (TRFs). Here, we extend earlier studies by measuring subcortical responses to continuous speech presented in the sound-field, and assess the amount of data needed to estimate brainstem TRFs. Electroencephalography (EEG) was recorded from 24 normal hearing participants while they listened to clicks and stories presented via earphones and loudspeakers. Subcortical TRFs were computed after accounting for non-linear processing in the auditory periphery by either stimulus rectification or an auditory nerve model. Our results demonstrated that subcortical responses to continuous speech could be reliably measured in the sound-field. TRFs estimated using auditory nerve models outperformed simple rectification, and 16 minutes of data was sufficient for the TRFs of all participants to show clear wave V peaks for both earphones and sound-field stimuli. Subcortical TRFs to continuous speech were highly consistent in both earphone and sound-field conditions, and with click ABRs. However, sound-field TRFs required slightly more data (16 minutes) to achieve clear wave V peaks compared to earphone TRFs (12 minutes), possibly due to effects of room acoustics. By investigating subcortical responses to sound-field speech stimuli, this study lays the groundwork for bringing objective hearing assessment closer to real-life conditions, which may lead to improved hearing evaluations and smart hearing technologies.

neuroscience↗

bioRxiv2023

Predictors for Estimating Subcortical EEG Responses to Continuous Speech

Perception of sounds and speech involves structures in the auditory brainstem that rapidly process ongoing auditory stimuli. The role of these structures in speech processing can be investigated by measuring their electrical activity using scalp-mounted electrodes. However, typical analysis methods involve averaging neural responses to many short repetitive stimuli that bear little relevance to daily listening environments. Recently, subcortical responses to more ecologically relevant continuous speech were detected using linear encoding models. These methods estimate the temporal response function (TRF), which is a regression model that minimises the error between the measured neural signal and a predictor derived from the stimulus. Using predictors that model the highly non-linear peripheral auditory system may improve linear TRF estimation accuracy and peak detection. Here, we compare predictors from both simple and complex peripheral auditory models for estimating brainstem TRFs on electroencephalography (EEG) data from 24 participants listening to continuous speech. We also discuss the data length required for estimating subcortical TRFs with clear peaks. Interestingly, predictors from simple models resulted in TRFs that were similar to those estimated using complex models, and were much faster to compute. This work paves the way for efficient modelling and detection of subcortical processing of continuous speech, which may lead to improved diagnosis metrics for hearing impairment and assistive hearing technology.

neuroscience↗