Selective attention in the brainstem and speech-in-noise comprehension

Marina Saiz-Alia, Antonio Elia Forte, Tobias Reichenbach

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


Understanding speech in noise is a challenging task. Moreover, the ability to understand speech in background noise varies considerably from person to person, even for people that have normal audiograms and hence no measurable hearing loss. Recently we proposed a method for measuring the brainstem's response to natural non-repetitive speech and showed that this response is modulated by selective attention to one of two competing speakers. Here we investigate to what extent this brainstem response varies from subject to subject. We find significant between-subject variation in the amplitude of the brainstem response to continuous speech, in its latency, signal-to-noise-ratio, as well as in its modulation by selective attention. This variability may result from impairments in the auditory periphery, such a cochlear synaptopathy, as well as from damages of the neural pathways in the brainstem and in the central nervous system that are responsible for sound processing, and may potentially lead to deficits with speech-in-noise comprehension.

Original languageEnglish
Title of host publicationProceedings of the 23rd International Congress on Acoustics
Subtitle of host publicationIntegrating 4th EAA Euroregio 2019
EditorsMartin Ochmann, Vorlander Michael, Janina Fels
PublisherInternational Commission for Acoustics (ICA)
Number of pages6
ISBN (Electronic)9783939296157
Publication statusPublished - 2019
Event23rd International Congress on Acoustics: Integrating 4th EAA Euroregio, ICA 2019 - Aachen, Germany
Duration: 9 Sept 201923 Sept 2019

Publication series

NameProceedings of the International Congress on Acoustics
ISSN (Print)2226-7808
ISSN (Electronic)2415-1599


Conference23rd International Congress on Acoustics: Integrating 4th EAA Euroregio, ICA 2019


  • Auditory brainstem response
  • Selective attention
  • Speech processing


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