Binaural detection with narrowband and wideband reproducible noise maskers. IV. Models using interaural time, level, and envelope differences

Mao, Junwen; Carney, Laurel H.

doi:10.1121/1.4861848

Cited by 11 publications

(16 citation statements)

References 40 publications

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“…Predictions computed using synchrony cues are not shown here because synchrony to the 500-Hz tone was not significantly correlated to listeners' detection patterns. Detection patterns were highly correlated across different pairs of listeners in the diotic narrowband and wideband and dichotic wideband conditions (Mao et al 2013;Mao and Carney 2014), indicating that listeners used a similar strategy to detect tones in noise in each of these conditions. In this study, model predictions are only shown for the average listeners in these three conditions.…”

Section: Resultsmentioning

confidence: 92%

“…A recent study shows that predictions based on an optimal combination of energy and temporal cues approach the predictable variance in detection patterns (the common variance among different listeners' performance) for the diotic condition (Mao et al 2013 (Davidson et al 2009;Isabelle 1995); however, these predictions were substantially lower than the predictable variance. A binaural envelope slope cue, the slope of the interaural envelope difference (SIED), yields significantly better predictions than ILD and/or ITD cues (Mao and Carney 2014). Thus, among stimulus-based models, those using envelope cues are most successful in predicting listeners' performance for both diotic and dichotic conditions.…”

Section: Introductionmentioning

confidence: 99%

“…Listeners' detection performance for diotic and dichotic tone-in-noise detection was obtained from previous experiments (Davidson et al 2006;Evilsizer et al 2002;Mao and Carney 2014). Detection in the presence of reproducible noise maskers was tested on each listener in these studies.…”

Section: Datasetsmentioning

confidence: 99%

“…For the dichotic condition, binaural differences occur because of the addition of out-of-phase tones to in-phase noises at the two ears. The SIED model (Mao and Carney 2014) focuses on the binaural envelope difference cues. Figure 4A shows a schematic diagram of the SIED model, in which envelopes from the contralateral and ipsilateral sides are extracted from the analytic signal computed from a fourth-order gammatone-filtered stimulus.…”

Section: Dichotic Models For Tone-in-noise Detectionmentioning

confidence: 99%

“…The combined excitatory and inhibitory inputs are sent to the IC modulation filter. For the IC model, a band-pass modulation filter centered at 50 Hz was used; this modulation frequency contains the largest envelope differences related to tone presence in the dichotic condition (Mao and Carney 2014). The dichotic physiological model envelope cues based on either rate or response fluctuations were obtained from the model IC synapse output.…”

Section: Dichotic Models For Tone-in-noise Detectionmentioning

confidence: 99%

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Tone-in-Noise Detection Using Envelope Cues: Comparison of Signal-Processing-Based and Physiological Models

Mao

Carney

2014

JARO

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Tone-in-noise detection tasks with reproducible noise maskers have been used to identify cues that listeners use to detect signals in noisy environments. Previous studies have shown that energy, envelope, and finestructure cues are significantly correlated to listeners' performance for detection of a 500-Hz tone in noise. In this study, envelope cues were examined for both diotic and dichotic tone-in-noise detection using both stimulus-based signal processing and physiological models. For stimulus-based envelope cues, a modified envelope slope model was used for the diotic condition and the binaural slope of the interaural envelope difference model for the dichotic condition. Stimulusbased models do not include key nonlinear transformations in the auditory periphery such as compression, rate and dynamic range adaptation, and rate saturation, all of which affect the encoding of the stimulus envelope. For physiological envelope cues, stimuli were passed through models for the auditory nerve (AN), cochlear nucleus, and inferior colliculus (IC). The AN and cochlear nucleus models included appropriate modulation gain, another transformation of the stimulus envelope that is not typically included in stimulus-based models. A model IC cell was simulated with a linear band-pass modulation filter. The average discharge rate and response fluctuations of the model IC cell were compared to human performance. Previous studies have predicted a significant amount of the variance across reproducible noise maskers in listeners' detection using stimulusbased envelope cues. In this study, a physiological model that includes neural mechanisms that affect encoding of the stimulus envelope predicts a similar amount of the variance in listeners' performance across noise maskers.

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Section: Resultsmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Section: Datasetsmentioning

confidence: 99%

Section: Dichotic Models For Tone-in-noise Detectionmentioning

confidence: 99%

Section: Dichotic Models For Tone-in-noise Detectionmentioning

confidence: 99%

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Tone-in-Noise Detection Using Envelope Cues: Comparison of Signal-Processing-Based and Physiological Models

Mao

Carney

2014

JARO

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Neural Mechanisms of Binaural Processing in the Auditory Brainstem

Yin

Smith

Joris

2019

Comprehensive Physiology

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Spatial hearing, and more specifically the ability to localize sounds in space, is one of the most studied and best understood aspects of hearing. Because there is no coding of acoustic space at the receptor organ, physiological sensitivity to spatial aspects of sounds first emerges in the central nervous system. Much progress has been made in the identification and characterization of the circuits in the auditory brainstem that create sensitivity to binaural and monaural cues toward acoustic space. We review the progress over the past third of a century, with a focus on the mammalian brainstem and on the anatomy and cellular physiology underlying the physiological tuning of monaural and binaural circuits to acoustic cues toward spatial hearing. In addition to examining the detailed mechanisms involved in the processing of the three main spatial cues, we also review the integration of these cues and their use toward behavior.

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Cues for Diotic and Dichotic Detection of a 500-Hz Tone in Noise Vary with Hearing Loss

Mao

Koch

Doherty

et al. 2015

JARO

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Hearing in noise is a challenge for all listeners, especially for those with hearing loss. This study compares cues used for detection of a low-frequency tone in noise by older listeners with and without hearing loss to those of younger listeners with normal hearing. Performance varies significantly across different reproducible, or "frozen," masker waveforms. Analysis of these waveforms allows identification of the cues that are used for detection. This study included diotic (N0S0) and dichotic (N0Sπ) detection of a 500-Hz tone, with either narrowband or wideband masker waveforms. Both diotic and dichotic detection patterns (hit and false alarm rates) across the ensembles of noise maskers were predicted by envelope-slope cues, and diotic results were also predicted by energy cues. The relative importance of energy and envelope cues for diotic detection was explored with a roving-level paradigm that made energy cues unreliable. Most older listeners with normal hearing or mild hearing loss depended on envelope-related temporal cues, even for this low-frequency target. As hearing threshold at 500 Hz increased, the cues for diotic detection transitioned from envelope to energy cues. Diotic detection patterns for young listeners with normal hearing are best predicted by a model that combines temporal- and energy-related cues; in contrast, combining cues did not improve predictions for older listeners with or without hearing loss. Dichotic detection results for all groups of listeners were best predicted by interaural envelope cues, which significantly outperformed the classic cues based on interaural time and level differences or their optimal combination.

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Binaural detection with narrowband and wideband reproducible noise maskers. IV. Models using interaural time, level, and envelope differences

Cited by 11 publications

References 40 publications

Tone-in-Noise Detection Using Envelope Cues: Comparison of Signal-Processing-Based and Physiological Models

Tone-in-Noise Detection Using Envelope Cues: Comparison of Signal-Processing-Based and Physiological Models

Neural Mechanisms of Binaural Processing in the Auditory Brainstem

Cues for Diotic and Dichotic Detection of a 500-Hz Tone in Noise Vary with Hearing Loss

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