Effects of Self-Generated Noise on Estimates of Detection Threshold in Quiet for School-Age Children and Adults

Abstract

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 low-frequency 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 forced-choice 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 self-generated 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 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 factors (e.g., inattention to the task). Evaluation of self-generated noise could improve diagnosis of minimal or mild hearing loss.

Improving Auditory Filter Estimation by Incorporating Absolute Threshold and a Level-dependent Internal Noise

“…We would like to know whether AT is completely determined in quiet by the noise floor, N c false( Q false) false( f false), or whether some other factor is also involved. Buss et al (2016) reported that the distribution of internal “self-generated noise” of NH listeners is similar to the 0-dB HL function (ANSI_S3.6-2010, 2010) on a dB scale as shown in Figure 2(a). If we assume that the distribution of the noise floor, N c false( Q false) false( f false), is indeed the 0-dB HL function, L H L 0 ′ false( f false), it can be formulated as in Equation 15 in Appendix A.…”

“…(a) Relationship between self-generated noise (Buss et al, 2016) and the HL-0dB function (ANSI_S3.6-2010, 2010) at the ear drum (dashed lines), and at the input to the cochlea (solid lines). (b) The middle ear transfer function, T m i d false( f false) (Glasberg & Moore, 2006) for compensating between them.…”

Muscles in and around the ear as the source of “physiological noise” during auditory selective attention: A review and novel synthesis

“…These nonacoustic responses are likely to involve the tensor tympani (Klockhoff, 1981;Klockhoff & Anderson, 1960). Given diffuse co-activation of the muscles around the ear, this implicates the tensor tympani in both gain control and selective attention-and supports the observed correlation between hearing thresholds and ear canal noise (Buss et al, 2016).…”

“…Stekelenburg and Van Boxtel actually suggest that pericranial relaxation is accompanied by relaxation of the middle ear muscles and, given that the basic role of these muscles is to regulate hearing sensitivity (e.g., Borg, 1972), this regulation will in itself lead to lower auditory thresholds. A recent paper (Buss et al., 2016) supports this conclusion by finding that, in a group of tested individuals, lower hearing thresholds were correlated with reduced ear canal noise.…”

The impact of spectral and temporal processing on speech recognition in children with cochlear implants

“…That is, research has shown that peripheral, within-channel spectral resolution-such as auditory filter width and critical ratio-matures in infancy 16,17 . However, behavioral measures of within-channel spectral resolution (auditory filter width 18 ; on-frequency masking [19][20][21][22][23][24][25] ) and across-channel spectral resolution (spectral ripple discrimination or spectral modulation detection 26,27 ; off-frequency masking 20,22,28 ) in infants and children with normal hearing (NH) are typically poorer than that observed for adult listeners, and do not reach maturation until teenage years [29][30][31][32][33] . This maturational trajectory, however, has not been observed for pediatric CI users 26,29,31,34,35 .…”