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Obtaining reliable phase-gradient delays from otoacoustic emission data.

ABSTRACT: Reflection-source otoacoustic emission phase-gradient delays are widely used to obtain noninvasive estimates of cochlear function and properties, such as the sharpness of mechanical tuning and its variation along the length of the cochlear partition. Although different data-processing strategies are known to yield different delay estimates and trends, their relative reliability has not been established. This paper uses in silico experiments to evaluate six methods for extracting delay trends from reflection-source otoacoustic emissions (OAEs). The six methods include both previously published procedures (e.g., phase smoothing, energy-weighting, data exclusion based on signal-to-noise ratio) and novel strategies (e.g., peak-picking, all-pass factorization). Although some of the methods perform well (e.g., peak-picking), others introduce substantial bias (e.g., phase smoothing) and are not recommended. In addition, since standing waves caused by multiple internal reflection can complicate the interpretation and compromise the application of OAE delays, this paper develops and evaluates two promising signal-processing strategies, the first based on time-frequency filtering using the continuous wavelet transform and the second on cepstral analysis, for separating the direct emission from its subsequent reflections. Altogether, the results help to resolve previous disagreements about the frequency dependence of human OAE delays and the sharpness of cochlear tuning while providing useful analysis methods for future studies.

SUBMITTER: Shera CA

PROVIDER: S-EPMC3427360 | biostudies-other | 2012 Aug

REPOSITORIES: biostudies-other

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Project description:BackgroundAlthough several candidate-gene association studies have been conducted to investigate noise-induced hearing loss (NIHL) in humans, most are underpowered, unreplicated, and account for only a fraction of the genetic risk. Mouse genome-wide association studies (GWASs) have revolutionized the field of genetics and have led to the discovery of hundreds of genes involved in complex traits. The hybrid mouse diversity panel (HMDP) is a collection of classic inbred and recombinant inbred strains whose genomes have been either genotyped at high resolution or sequenced. To further investigate the genetics of NIHL, we report the first GWAS based on distortion product otoacoustic emission (DPOAE) measurements and the HMDP.MethodsA total of 102 strains (n = 635) from the HMDP were evaluated based on DPOAE suprathreshold amplitudes before and after noise exposure. DPOAE amplitude variation was set at 60 and 70 dB SPL of the primary tones for each frequency separately (8, 11.3, 16, 22.6, and 32 kHz). These values provided an indirect assessment of outer hair cell integrity. Six-week-old mice were exposed for 2 h to 10 kHz octave-band noise at 108 dB SPL. To perform local expression quantitative trait locus (eQTL) analysis, gene expression microarray profiles were generated using cochlear RNA from 64 hybrid mouse strains (n = 3 arrays per strain).ResultsSeveral new loci were identified and positional candidate-genes associated with NIHL were prioritized, especially after noise exposure (1 locus at baseline and 5 loci after exposure). A total of 35 candidate genes in these 6 loci were identified with at least 1 probe whose expression was regulated by a significant cis-eQTL in the cochlea. After careful analysis of the candidate genes based on cochlear gene expression, 2 candidate genes were prioritized: Eya1 (baseline) and Efr3a (post-exposure).Discussion and conclusionFor the first time, an association analysis with correction for population structure was used to map several loci for hearing traits in inbred strains of mice based on DPOAE suprathreshold amplitudes before and after noise exposure. Our results identified a number of novel loci and candidate genes for susceptibility to NIHL, especially the Eya1 and Efr3a genes. Our findings validate the power of the HMDP for detecting NIHL susceptibility genes.

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Obtaining reliable phase-gradient delays from otoacoustic emission data.

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