Bojana Mirkovic1, Stefan Debener2, Julia Schmidt3, Manuela Jaeger4, Tobias Neher5. 1. Department of Psychology, University of Oldenburg, Ammerländer Heerstraße 114, 26129, Oldenburg, Germany; Cluster of Excellence "Hearing4all", Oldenburg, Germany. Electronic address: bojana.mirkovic@uni-oldenburg.de. 2. Department of Psychology, University of Oldenburg, Ammerländer Heerstraße 114, 26129, Oldenburg, Germany; Cluster of Excellence "Hearing4all", Oldenburg, Germany. Electronic address: stefan.debener@uni-oldenburg.de. 3. Department of Psychology, University of Oldenburg, Ammerländer Heerstraße 114, 26129, Oldenburg, Germany. Electronic address: julia.schmidt@uni-oldenburg.de. 4. Department of Psychology, University of Oldenburg, Ammerländer Heerstraße 114, 26129, Oldenburg, Germany. Electronic address: manuela.jaeger@uni-oldenburg.de. 5. Institute of Clinical Research, University of Southern Denmark, Campusvej 55, 5230, Odense M, Denmark. Electronic address: tneher@health.sdu.dk.
Abstract
OBJECTIVE: It has been suggested that the next major advancement in hearing aid (HA) technology needs to include cognitive feedback from the user to control HA functionality. In order to enable automatic brainwave-steered HA adjustments, attentional processes underlying speech-in-noise perception in aided hearing-impaired individuals need to be better understood. Here, we addressed the influence of two important factors for the listening performance of HA users - hearing aid processing and motivation - by analysing ongoing neural responses during long-term listening to continuous noisy speech. METHODS: Sixteen normal-hearing (NH) and 15 linearly aided hearing-impaired (aHI) participants listened to an audiobook recording embedded in realistic speech babble noise at individually adjusted signal-to-noise ratios (SNRs). A HA simulator was used for simulating a directional microphone setting as well as for providing individual amplification. To assess listening performance behaviourally, participants answered questions about the contents of the audiobook. We manipulated (1) the participants' motivation by offering a monetary reward for good listening performance in one half of the measurements and (2) the SNR by engaging/disengaging the directional microphone setting. During the speech-in-noise task, electroencephalography (EEG) signals were recorded using wireless, mobile hardware. EEG correlates of listening performance were investigated using EEG impulse responses, as estimated using the cross-correlation between the recorded EEG signal and the temporal envelope of the audiobook at the output of the HA simulator. RESULTS: At the behavioural level, we observed better performance for the NH listeners than for the aHI listeners. Furthermore, the directional microphone setting led to better performance for both participant groups, and when the directional microphone setting was disengaged motivation also improved the performance of the aHI participants. Analysis of the EEG impulse responses showed faster N1P2 responses for both groups and larger N2 peak amplitudes for the aHI group when the directional microphone setting was activated, but no physiological correlates of motivation. SIGNIFICANCE: The results of this study indicate that motivation plays an important role for speech understanding in noise. In terms of neuro-steered HAs, our results suggest that the latency of attentional processes is influenced by HA-induced stimulus changes, which can potentially be used for inferring benefit from noise suppression processing automatically. Further research is necessary to identify the neural correlates of motivation as an exclusive top-down process and to combine such features with HA-driven ones for online HA adjustments.
OBJECTIVE: It has been suggested that the next major advancement in hearing aid (HA) technology needs to include cognitive feedback from the user to control HA functionality. In order to enable automatic brainwave-steered HA adjustments, attentional processes underlying speech-in-noise perception in aided hearing-impaired individuals need to be better understood. Here, we addressed the influence of two important factors for the listening performance of HA users - hearing aid processing and motivation - by analysing ongoing neural responses during long-term listening to continuous noisy speech. METHODS: Sixteen normal-hearing (NH) and 15 linearly aided hearing-impaired (aHI) participants listened to an audiobook recording embedded in realistic speech babble noise at individually adjusted signal-to-noise ratios (SNRs). A HA simulator was used for simulating a directional microphone setting as well as for providing individual amplification. To assess listening performance behaviourally, participants answered questions about the contents of the audiobook. We manipulated (1) the participants' motivation by offering a monetary reward for good listening performance in one half of the measurements and (2) the SNR by engaging/disengaging the directional microphone setting. During the speech-in-noise task, electroencephalography (EEG) signals were recorded using wireless, mobile hardware. EEG correlates of listening performance were investigated using EEG impulse responses, as estimated using the cross-correlation between the recorded EEG signal and the temporal envelope of the audiobook at the output of the HA simulator. RESULTS: At the behavioural level, we observed better performance for the NH listeners than for the aHI listeners. Furthermore, the directional microphone setting led to better performance for both participant groups, and when the directional microphone setting was disengaged motivation also improved the performance of the aHI participants. Analysis of the EEG impulse responses showed faster N1P2 responses for both groups and larger N2 peak amplitudes for the aHI group when the directional microphone setting was activated, but no physiological correlates of motivation. SIGNIFICANCE: The results of this study indicate that motivation plays an important role for speech understanding in noise. In terms of neuro-steered HAs, our results suggest that the latency of attentional processes is influenced by HA-induced stimulus changes, which can potentially be used for inferring benefit from noise suppression processing automatically. Further research is necessary to identify the neural correlates of motivation as an exclusive top-down process and to combine such features with HA-driven ones for online HA adjustments.
Authors: G Nike Gnanateja; Dhatri S Devaraju; Matthias Heyne; Yina M Quique; Kevin R Sitek; Monique C Tardif; Rachel Tessmer; Heather R Dial Journal: Front Comput Neurosci Date: 2022-06-23 Impact factor: 3.387