Selective attention reduces physiological noise in the external ear canals of humans. I: Auditory attention

Walsh, Kyle P.; Pasanen, Edward G.; McFadden, Dennis

doi:10.1016/j.heares.2014.03.012

Cited by 31 publications

(70 citation statements)

References 70 publications

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“…The physiological measure used here was a nonlinear version of the stimulus-frequency otoacoustic emission (SFOAE), called the nSFOAE (Walsh et al, 2010a(Walsh et al, , 2014a. The SFOAE is a continuous tonal reflection that is evoked from the cochlea by a long-duration tone (Kemp, 1980); after a time delay, the reflection adds with the input sound in the ear canal.…”

Section: The Nsfoae Proceduresmentioning

confidence: 99%

“…For each block of trials, the physiological responses from the trials having a correct behavioral response were based on about 20 to 30 trials. [Reprinted with permission from Walsh et al (2014a).] stimulus used to elicit the nSFOAE so that the presentation levels for the two earphones were as similar as possible.…”

Section: The Nsfoae Proceduresmentioning

confidence: 99%

“…The reason is that tone-plusnoise is well known for its ability to trigger the MOC reflex Walsh et al, 2010aWalsh et al, , 2014a; a rising, dynamic response having a time constant of about 100 to 200 ms is a common result (e.g., Backus and Guinan, 2006). Tone-alone is not as effective at triggering the MOC reflex, especially a tone as weak as 60 dB SPL .…”

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confidence: 99%

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Changes in otoacoustic emissions during selective auditory and visual attention

Walsh

Pasanen

McFadden

2015

The Journal of the Acoustical Society of America

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Previous studies have demonstrated that the otoacoustic emissions (OAEs) measured during behavioral tasks can have different magnitudes when subjects are attending selectively or not attending. The implication is that the cognitive and perceptual demands of a task can affect the first neural stage of auditory processing-the sensory receptors themselves. However, the directions of the reported attentional effects have been inconsistent, the magnitudes of the observed differences typically have been small, and comparisons across studies have been made difficult by significant procedural differences. In this study, a nonlinear version of the stimulus-frequency OAE (SFOAE), called the nSFOAE, was used to measure cochlear responses from human subjects while they simultaneously performed behavioral tasks requiring selective auditory attention (dichotic or diotic listening), selective visual attention, or relative inattention. Within subjects, the differences in nSFOAE magnitude between inattention and attention conditions were about 2-3 dB for both auditory and visual modalities, and the effect sizes for the differences typically were large for both nSFOAE magnitude and phase. These results reveal that the cochlear efferent reflex is differentially active during selective attention and inattention, for both auditory and visual tasks, although they do not reveal how attention is improved when efferent activity is greater.

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Section: The Nsfoae Proceduresmentioning

confidence: 99%

Section: The Nsfoae Proceduresmentioning

confidence: 99%

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Changes in otoacoustic emissions during selective auditory and visual attention

Walsh

Pasanen

McFadden

2015

The Journal of the Acoustical Society of America

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“…To efficiently extract the feature of the spectrogram, the selective attention mechanism is used. The selective attention mechanism is the high-level cognitive ability, which is helpful to pay attention to the target information and eliminate the interference [10]. The study on the auditory selective attention mechanism is very few and mainly focused on the research field of physiology and cognition [11].…”

Section: Spectrogram Feature Extractionmentioning

confidence: 99%

A Salient Feature Extraction Algorithm for Speech Emotion Recognition

Liang

Tao

Tang

et al. 2015

IEICE Trans. Inf. & Syst.

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SUMMARYA salient feature extraction algorithm is proposed to improve the recognition rate of the speech emotion. Firstly, the spectrogram of the emotional speech is calculated. Secondly, imitating the selective attention mechanism, the color, direction and brightness map of the spectrogram is computed. Each map is normalized and down-sampled to form the low resolution feature matrix. Then, each feature matrix is converted to the row vector and the principal component analysis (PCA) is used to reduce features redundancy to make the subsequent classification algorithm more practical. Finally, the speech emotion is classified with the support vector machine. Compared with the tradition features, the improved recognition rate reaches 15%.

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“…Activity in these muscles could affect thresholds by introducing acoustic noise or by impairing middle ear transmission. It has also been suggested that selective attention may reduce broadband noise associated with cochlear function via activation of the efferent system (Walsh et al 2014); in contrast to other sources of self-generated noise, cochlear noise is not predominantly low frequency.…”

Section: Introductionmentioning

confidence: 99%

Effects of self-generated noise on estimates of detection threshold in quiet in school-age children and adults

Buss

Porter

Leibold

et al. 2014

The Journal of the Acoustical Society of America

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Objectives-Detection thresholds in quiet become adult-like earlier in childhood for high than low frequencies. When adults listen for sounds near threshold, they tend to engage in behaviors that reduce physiologic noise (e.g., quiet breathing), which is predominantly low frequency. Children may not suppress self-generated noise to the same extent as adults, such that lowfrequency self-generated noise elevates thresholds in the associated frequency regions. This possibility was evaluated by measuring noise levels in the ear canal simultaneous with adaptive threshold estimation.Design-Listeners were normal-hearing children (4.3-16.0 yrs) and adults. Detection thresholds were measured adaptively for 250-, 1000-and 4000-Hz pure tones using a three-alternative forcedchoice procedure. Recordings of noise in the ear canal were made while the listeners performed this task, with the earphone and microphone routed through a single foam insert. Levels of selfgenerated noise were computed in octave-wide bands. Age effects were evaluated for four groups: 4-to 6-year-olds, 7-to 10-year-olds, 11-to 16-year-olds, and adults.Results-Consistent with previous data, the effect of child age on thresholds was robust at 250 Hz and fell off at higher frequencies; thresholds of even the youngest listeners were similar to adults' at 4000 Hz. Self-generated noise had a similar low-pass spectral shape for all age groups, although the magnitude of self-generated noise was higher in younger listeners. If self-generated noise impairs detection, then noise levels should be higher for trials associated with the wrong answer than the right answer. This association was observed for all listener groups at the 250-Hz signal frequency. For adults and older children, this association was limited to the noise band centered on the 250-Hz signal. For the two younger groups of children, this association was strongest at the signal frequency, but extended to bands spectrally remote from the 250-Hz signal. For the 1000-Hz signal frequency, there was a broadly tuned association between noise and response only for the two younger groups of children. For the 4000-Hz signal frequency, only the HHS Public AccessAuthor manuscript Ear Hear. Author manuscript; available in PMC 2017 November 01. Author Manuscript Author ManuscriptAuthor ManuscriptAuthor Manuscript youngest group of children demonstrated an association between responses and noise levels, and this association was particularly pronounced for bands below the signal frequency.Conclusions-These results provide evidence that self-generated noise plays a role in the prolonged development of low-frequency detection thresholds in quiet. Some aspects of the results are consistent with the possibility that self-generated noise elevates thresholds via energetic masking, particularly at 250 Hz. The association between behavioral responses and noise spectrally remote from the signal frequency is also consistent with the idea that self-generated noise may also reflect contributions of more central factor...

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Selective attention reduces physiological noise in the external ear canals of humans. I: Auditory attention

Cited by 31 publications

References 70 publications

Changes in otoacoustic emissions during selective auditory and visual attention

Changes in otoacoustic emissions during selective auditory and visual attention

A Salient Feature Extraction Algorithm for Speech Emotion Recognition

Effects of self-generated noise on estimates of detection threshold in quiet in school-age children and adults

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