Measurement of swept level distortion product otoacoustic emission growth functions at multiple frequencies simultaneously.

Otoacoustic emissions (OAEs) are low-level sounds generated by the inner ear that provide a non-invasive assessment of cochlear health. Advanced applications require recording OAEs across a wide range of frequencies and stimulus levels. Detailed here is a method for efficiently measuring distortion product otoacoustic emissions (DPOAEs) across an expansive stimulus space. Specifically, DPOAEs are recorded by sweeping the evoking stimuli in level across multiple frequencies simultaneously. This method generates DPOAE growth functions at multiple f2 frequencies in several minutes. Results indicate the swept level method yields DPOAEs equivalent to those measured in a traditional (discrete stimulus) paradigm, but with several advantages.

Distortion Product Otoacoustic Emission (DPOAE) Growth in Aging Ears with Clinically Normal Behavioral Thresholds.

Age-related hearing loss (ARHL) is a devastating public health issue. To successfully address ARHL using existing and future treatments, it is imperative to detect the earliest signs of age-related auditory decline and understand the mechanisms driving it. Here, we explore early signs of age-related auditory decline by characterizing cochlear function in 199 ears aged 10-65 years, all of which had clinically defined normal hearing (i.e., behavioral thresholds ≤ 25 dB HL from .25 to 8 kHz bilaterally) and no history of noise exposure. We characterized cochlear function by measuring behavioral thresholds in two paradigms (traditional audiometric thresholds from .25 to 8 kHz and Békésy tracking thresholds from .125 to 20 kHz) and distortion product otoacoustic emission (DPOAE) growth functions at f2 = 2, 4, and 8 kHz. Behavioral thresholds through a standard clinical frequency range (up to 8 kHz) showed statistically, but not clinically, significant declines across increasing decades of life. In contrast, DPOAE growth measured in the same frequency range showed clear declines as early 30 years of age, particularly across moderate stimulus levels (L2 = 25-45 dB SPL). These substantial declines in DPOAE growth were not fully explained by differences in behavioral thresholds measured in the same frequency region. Additionally, high-frequency Békésy tracking thresholds above ~11.2 kHz showed frank declines with increasing age. Collectively, these results suggest that early age-related cochlear decline (1) begins as early as the third or fourth decade of life, (2) is greatest in the cochlear base but apparent through the length of the cochlear partition, (3) cannot be detected fully by traditional clinical measures, and (4) is likely due to a complex mix of etiologies.

Semi-supervised learning of a nonnative phonetic contrast: How much feedback is enough?

Semi-supervised learning refers to learning that occurs when feedback about performance is provided on only a subset of training trials. Algorithms for semi-supervised learning are popular in machine learning because of their minimal reliance on labeled data. There have been, however, only a few reports of semi-supervised learning in humans. Here we document human semi-supervised learning on a nonnative phonetic classification task. Classification performance remained unchanged when 60 feedback trials were provided on each of the two days of training. In contrast, performance improved when 60 feedback trials were combined with 240 no-feedback trials each day. In variants of this successful semi-supervised regimen, increasing the daily number of feedback trials from 60 to 240 did not increase the amount of learning, while decreasing that number to 30 abolished learning. Finally, replacing the no-feedback trials with stimulus exposure alone had little effect on the outcome. These results were an unexpected consequence of combining training periods with feedback and testing periods without feedback, illustrating that no-feedback testing can influence learning outcomes. More broadly, these data suggest that task performance with feedback can function as an all-or-none trigger for recruiting the contribution of trials without feedback, or mere stimulus exposures, to human learning.