Exploring the relationship between physiological measures of cochlear and brainstem function

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Abstract

Objective

Otoacoustic emissions and the speech-evoked auditory brainstem response are objective indices of peripheral auditory physiology that are used clinically for assessing hearing function. While each measure has been extensively explored, their interdependence and the relationships between them remain relatively unexplored.

Methods

Distortion product otoacoustic emissions (DPOAEs) and speech-evoked auditory brainstem responses (sABRs) were recorded from 28 normal-hearing adults. Through correlational analyses, DPOAE characteristics were compared to measures of sABR timing and frequency encoding. Data were organized into two DPOAE (Strength and Structure) and five brainstem (Onset, Spectrotemporal, Harmonics, Envelope Boundary, and Pitch) composite measures.

Results

DPOAE Strength shows significant relationships with sABR Spectrotemporal and Harmonics measures. DPOAE Structure shows significant relationships with sABR Envelope Boundary. Neither DPOAE Strength nor Structure is related to sABR Pitch.

Conclusions

The results of the present study show that certain aspects of the speech-evoked auditory brainstem responses are related to, or covary with, cochlear function as measured by distortion product otoacoustic emissions.

Significance

These results form a foundation for future work in clinical populations. Analyzing cochlear and brainstem function in parallel in different clinical populations will provide a more sensitive clinical battery for identifying the locus of different disorders (e.g., language based learning impairments, hearing impairment).

Introduction

Distortion product otoacoustic emissions (DPOAEs) and speech-evoked auditory brainstem responses (sABRs) are objective measures of peripheral auditory physiology. These tools are used in both clinical and research applications, often in tandem for differential diagnosis. It is important, therefore, to understand issues related to their overlap and independence. The current study is our maiden attempt to explore these relationships in normal hearing young adults. The underlying objective is to examine and document the links between cochlear and brainstem function and ultimately improve the clinical power of these instruments by using them together for specific clinical purposes.

Otoacoustic emissions (OAEs) are signals generated in the cochlea that are detectable in the ear canal (Kemp, 1978, Kemp, 1979). These acoustic signals are considered a byproduct of physiological processes necessary for normal hearing, specifically outer hair cell function (Brownell, 1982). Otoacoustic emissions can be generated spontaneously (SOAEs) and can also be evoked by clicks (transient-evoked otoacoustic emissions, TEOAEs), single tones (stimulus-frequency otoacoustic emissions, SFOAEs), or tone pairs (distortion product otoacoustic emissions, DPOAEs).

Emissions evoked by tone pairs, or DPOAEs, are equally popular in the clinic and the laboratory. They are measured by stimulating the cochlea simultaneously with two pure tones (f1 and f2, f1 < f2). Distortion products at various frequencies arithmetically related to the stimulus frequencies are generated in the cochlea. The DPOAE at 2f1  f2 is the most robust in human ears under certain stimulus conditions and is used routinely in clinical practice. DPOAEs such as the one at 2f1  f2 are lower in frequency than the stimulus tones making their characteristic frequency (CF) place apical to F1 and F2 on the basilar membrane. There is now irrefutable evidence that for apical DPOAE that, the signal measured in the ear canal is a mixture of two components, one from the overlap region between the traveling wave patterns of the stimulus tones and the other from the CF region of the DPOAE itself (Mauermann et al., 1999a, Talmadge et al., 1999). In many current theories of OAE generation, these two DPOAE components are modeled to arise from fundamentally different mechanisms resulting in significantly different phase-frequency functions of each component (Shera and Guinan, 1999). The phase of the overlap component (also called wave-fixed or distortion component in the literature) is relatively invariant with frequency. On the other hand, the phase of the DP CF component (also called the place-fixed or the reflection component in the literature) varies rapidly with frequency.

As these two components with different phase gradients are mixed in the ear canal, the interaction between them causes a pattern of alternating maxima and minima in the level-frequency function known as fine structure (Dhar et al., 2002). The presence of fine structure in a given ear reflects the presence of the two components and their relative magnitudes determine the depth of fine structure. Two equal components would lead to the deepest fine structure while complete domination by either component would result in little or no fine structure. There is initial evidence that fine structure characteristics could be a more sensitive indicator of alterations in cochlear status than the currently-used metric of overall level of DPOAEs (Wagner et al., 2008). Thus, the origin of fine structure in basic mechanical properties of the cochlea makes it interesting to examine its relationship with other physiological phenomena in the auditory system. Here we report such an exploration of the relationship between distortion product fine structure and speech-evoked brainstem responses.

The auditory brainstem, a conglomerate of nuclei belonging to the efferent and afferent auditory systems, receives and processes the output of the cochlea en route to the higher centers of auditory processing. The function of the brainstem nuclei can be assessed using stimulus-evoked electrophysiology. Evoked brainstem responses, often using click stimuli, can be diagnostic of clinical populations because of their temporal precision. When evoked by a periodic stimulus, such as speech or music, a frequency-following response (FFR) results. The FFR is driven by neural phase locking and reflects the fundamental periodicity of the stimulus and its harmonics. It is likely generated in the inferior colliculus and lateral lemniscus (Hoormann et al., 1992, Marsh et al., 1970, Moushegian et al., 1973, Smith et al., 1975, Worden and Marsh, 1968). There is also a growing body of literature showing that the human brainstem response is malleable with lifelong linguistic (Krishnan et al., 2005, Swaminathan et al., 2008) and musical experience (Kraus et al., in press, Musacchia et al., 2007, Strait et al., 2009, Wong et al., 2007), as well as short-term auditory training (Russo et al., 2005, Song et al., 2008).

The speech-evoked brainstem response to a consonant–vowel syllable, such as the voiced syllable [da] used in this study, contains both an onset, similar to the click-evoked response, due to the initial noise burst marking the onset of the consonant, and an FFR corresponding to the periodic, voiced formant transition. In the response, the acoustic properties of the stimulus are represented by discrete response peaks representing both transient events in the stimulus, such as voicing onset, and a sustained FFR to the fundamental periodicity (i.e., glottal pulsing) of the vowel.

Latency delays in transient sABR peaks have been found in children with language impairments relative to normal learning children (Banai et al., 2005, Banai et al., 2009, Banai and Kraus, 2008, Cunningham et al., 2001, Johnson et al., 2005, King et al., 2002, Wible et al., 2004) and in this population, peak latencies are particularly affected by the stimulus presentation rate and background noise (Basu et al., in press, Wible et al., 2004). The FFR peaks track the fundamental frequency (F0) of the stimulus; yet, the raw peak latencies are also likely modulated by the high frequency content of the stimulus (Johnson et al., 2008, Hornickel et al., 2009b) which is important for determining phonemic identity. The latencies of FFR peaks have been shown to differ depending on ear of stimulation (Hornickel et al., 2009a) and their timing is related to reading ability (Banai et al., 2005, Banai et al., 2009).

Frequency-domain analyses of the sABR reveal energy at the fundamental frequency and harmonics of the voiced syllable. Measures of harmonics have been found to differ for right and left ear presentation (Hornickel et al., 2009a), between reading impaired and normal learning children (Cunningham et al., 2001, Johnson et al., 2005, Wible et al., 2004, Banai et al., 2009), and to be significantly correlated with measures of reading ability (Banai et al., 2009). These effects are likely due to the importance of harmonics in determining and distinguishing speech sounds. In contrast, measures of F0 representation have not been found to be significantly related to reading (Banai et al., 2009), nor does its encoding differ between reading impaired and normal learning children (Johnson et al., 2005, Kraus and Nicol, 2005, Wible et al., 2004, Banai et al., 2009) or ear of stimulation (Hornickel et al., 2009a).

While there is a vast literature on DPOAEs and brainstem responses, little is known about the relationship between these measures despite their widespread use in the assessment of hearing. Only a few studies have examined both measures in the same subjects (Cone-Wesson et al., 2000, Elsisy and Krishnan, 2008, Oswald et al., 2006, Purcell et al., 2006) and even fewer have related the function of both despite their common relationship to clinical populations and efferent control (de Boer and Thornton, 2008, Hall, 1992, Russo et al., 2005, Song et al., 2008). The current study proposes to identify relationships between DPOAEs and speech-evoked brainstem responses recorded in normal hearing young adults. Deeper understanding of the aspects that do and do not overlap between the two responses will allow for a more detailed knowledge of hearing function and better inform clinical practice.

Section snippets

Participants

Participants were 28 adults (ages 19–30, mean = 25; 17 women) who were right handed. All participants had normal (less than 20 dB HL) audiometric thresholds for octaves from 250 to 8000 Hz, no conductive loss as evidenced by a lack of an air-bone threshold gap, and normal click-evoked brainstem response, as measured by wave V latency. All OAE and sABR results reported are from the right ear.

Procedure

In order to encourage participants to remain as still as possible, they were allowed to watch a movie of

Relationships between DPOAE Strength and sABR measures

The strongest model predicting variance in DPOAE Strength comprised the Spectrotemporal and Harmonics composite measures only (R = 0.611, adjusted R2 = 0.323, F(2, 27) = 7.432, p < 0.01). No other brainstem measures significantly contributed unique variance to the predictive model (see Fig. 3, which schematically shows overlap among all the measures and indicates R2 values for each pairing). The Spectrotemporal and Harmonics composite sABR measures were weighted similarly in the model with standardized β

Discussion

The results of the current study show clear and significant relationships between speech-evoked auditory brainstem responses and cochlear function assessed via distortion product otoacoustic emissions. In exploring these relationships we have organized the data to represent specific aspects of brainstem and cochlear function. Two DPOAE (Strength and Structure) and five sABR (Onset, Spectrotemporal, Harmonics, Envelope Boundary, Pitch) composite measures were created. Relationships with the

Conclusion

The results of the present study show that certain aspects of the speech-evoked auditory brainstem responses to speech (Harmonics, Spectrotemporal, and Envelope Boundary) are related to, or covary with, cochlear function as measured by Strength and Structure of DPOAEs. As such, these results form a foundation for future work in clinical populations, such as patients with hearing loss, individuals with language-based learning impairments, and patients with speech in noise perception deficits.

Acknowledgments

Work reported here was supported by Grants DC008420 and DC01510 from the NIH/NIDCD. We wish to thank the members of the Auditory Research Lab and the Auditory Neuroscience Lab, specifically Judy H. Song for her help with data collection and other aspects of this work. We also thank Professor Steven Zecker for his advice on appropriate statistical treatment of these data.

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