Abstract

When multiple sound sources are present at the same time, auditory perception is often challenged with disentangling the resulting mixture and focusing attention on the target source. It has been repeatedly demonstrated that background (distractor) sound sources are easier to ignore when their spectrotemporal signature is predictable. Prior evidence suggests that this ability to exploit predictability for foreground-background segregation degrades with age. On a theoretical level, this has been related with an impairment in elderly adults’ capabilities to detect certain types of sensory deviance in unattended sound sequences. Yet the link between those two capacities, deviance detection and predictability-based sound source segregation, has not been empirically demonstrated. Here we report on a combined behavioral-EEG study investigating the ability of elderly listeners (60–75 years of age) to use predictability as a cue for sound source segregation, as well as their sensory deviance detection capacities. Listeners performed a detection task on a target stream that can only be solved when a concurrent distractor stream is successfully ignored. We contrast two conditions whose distractor streams differ in their predictability. The ability to benefit from predictability was operationalized as performance difference between the two conditions. Results show that elderly listeners can use predictability for sound source segregation at group level, yet with a high degree of inter-individual variation in this ability. In a further, passive-listening control condition, we measured correlates of deviance detection in the event-related brain potential (ERP) elicited by occasional deviations from the same spectrotemporal pattern as used for the predictable distractor sequence during the behavioral task. ERP results confirmed neural signatures of deviance detection in terms of mismatch negativity (MMN) at group level. Correlation analyses at single-subject level provide no evidence for the hypothesis that deviance detection ability (measured by MMN amplitude) is related to the ability to benefit from predictability for sound source segregation. These results are discussed in the frameworks of sensory deviance detection and predictive coding.

Highlights

  • Hearing is a daily life challenge as the auditory system needs to disentangle the incoming sound mixture into meaningful streams by linking sounds belonging to one source together, and separating sounds belonging to different sources (Bregman, 1990)

  • A significant correlation between Average hearing loss (AHL) and age was observed (r = 0.43, p = 0.02, N = 30; see Figure 2A), indicating that peripheral hearing ability decreased with increasing age within our sample spanning 15 years of age

  • The current study was designed to measure elderly listeners’ abilities to extract an auditory spectrotemporal regularity and to use the same regularity for stream segregation

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Summary

Introduction

Hearing is a daily life challenge as the auditory system needs to disentangle the incoming sound mixture into meaningful streams by linking sounds belonging to one source together, and separating sounds belonging to different sources (Bregman, 1990). Sound segregation ability and the ability to track a particular sound source (e.g., a speaker) across time in a concurrent acoustic mixture is crucial to follow the target stream while ignoring background noise (e.g., other speakers, cafeteria noise) In most listeners, these auditory processes work surprisingly smoothly. As simple and elegant as this explanation seems, recent work has pointed toward some unresolved issues related to the predictivecoding account of auditory perception (Denham and Winkler, 2017; Heilbron and Chait, 2018) Both reviews reiterate the concern that detecting the predictability of a sound source does not imply forming actual predictions about this sound source, and that the underlying neural mechanisms are not entirely clear. Whether detecting a predictability violation (i.e., sensory deviance detection) and sensory prediction are related, is notoriously difficult to demonstrate (Denham and Winkler, 2017; Heilbron and Chait, 2018)

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