Decoding of Envelope vs. Fundamental Frequency During Complex Auditory Stream Segregation.

Keelin M. Greenlaw,Sebastian Puschmann,Emily B. J. Coffey

doi:10.1162/nol_a_00013

Abstract

Hearing-in-noise perception is a challenging task that is critical to human function, but how the brain accomplishes it is not well understood. A candidate mechanism proposes that the neural representation of an attended auditory stream is enhanced relative to background sound via a combination of bottom-up and top-down mechanisms. To date, few studies have compared neural representation and its task-related enhancement across frequency bands that carry different auditory information, such as a sound's amplitude envelope (i.e., syllabic rate or rhythm; 1-9 Hz), and the fundamental frequency of periodic stimuli (i.e., pitch; >40 Hz). Furthermore, hearing-in-noise in the real world is frequently both messier and richer than the majority of tasks used in its study. In the present study, we use continuous sound excerpts that simultaneously offer predictive, visual, and spatial cues to help listeners separate the target from four acoustically similar simultaneously presented sound streams. We show that while both lower and higher frequency information about the entire sound stream is represented in the brain's response, the to-be-attended sound stream is strongly enhanced only in the slower, lower frequency sound representations. These results are consistent with the hypothesis that attended sound representations are strengthened progressively at higher level, later processing stages, and that the interaction of multiple brain systems can aid in this process. Our findings contribute to our understanding of auditory stream separation in difficult, naturalistic listening conditions and demonstrate that pitch and envelope information can be decoded from single-channel EEG data.

Highlights

Hearing-in-noise (HIN) is a complex and computationally challenging task that is critical to human function in social, educational, and vocational contexts
Three background streams were included to provide a consistent level of “multi-music” background noise, and to reduce the perception of salient or disturbing coincidences created by the offset between to-be-attended and to-be-ignored streams
This manipulation ensured that the attended and unattended streams were well buried in the noise and could not be separated solely by paying attention to high or low pitch ranges; these background streams were played at a reduced volume (*0.6 amplitude with respect to the attended and ignored streams) and in both ears, such that it would theoretically be possible to separate the to-be-ignored stream from the rest of the background noise based on sound level, timbre, and spatial separation

Summary

Introduction

Hearing-in-noise (HIN) is a complex and computationally challenging task that is critical to human function in social, educational, and vocational contexts. Three background streams were included to provide a consistent level of “multi-music” background noise, and to reduce the perception of salient or disturbing coincidences created by the offset between to-be-attended and to-be-ignored streams (e.g., if the unattended stream was jittered by half a beat on a given trial, it might have been perceived as a new “fused” melody at double the original tempo). EEG data were recorded in a magnetically shielded audiometric booth from monopolar active Ag/AcCl electrodes placed at Cz (10–20 International System), and both mastoids, using an averaged reference (BioSemi; www.biosemi.com). EEG data were band-pass filtered both from 1–9 Hz for sound envelope reconstruction and from 80–300 Hz for fundamental response (default order); both outputs were down-sampled to 1,000 Hz, and re-referenced to the average of the right and left mastoid channels. Filtering was performed using a third order Butterworth filter and the filtfilt function in MATLAB for zero-phase digital filtering of the data, as in Puschmann et al (2018)

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