The chinchilla animal model for hearing science and noise-induced hearing loss

Trevino, Monica; Lobariñas, Edward; Maulden, Amanda C.; Heinz, Michael G.

doi:10.1121/1.5132950

Cited by 40 publications

(25 citation statements)

References 214 publications

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“…The results from chinchilla studies ( Harding & Bohne 2009 ) showed that 4-kHz octave band of noise could produce greater NIPTS especially for outer hair cell damage than 0.5 kHz octave band of noise, suggesting the chinchilla cochlea is more sensitive to high-frequency noise, especially at 4 kHz. The chinchilla animal model supports the results shown in Figure 3 because the chinchilla’s auditory system is very similar to that of humans ( Trevino et al 2019 ). Moreover, it can be seen from Figures 3 B and C that the hearing loss notch degree at the high frequencies (3 to 6 kHz) deepens with the increase of L Aeq and kurtosis, and reaches the maximum at 4 kHz.…”

Section: Discussionsupporting

confidence: 78%

Applying Kurtosis as an Indirect Metric of Noise Temporal Structure in the Assessment of Hearing Loss Associated With Occupational Complex Noise Exposure

et al. 2021

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Objective: The association of occupational noise-induced hearing loss (NIHL) with noise energy was well documented, but the relationship between occupational noise and noise temporal structure is rarely reported. The objective of this study was to investigate the principal characteristics of the relationship between occupational NIHL and the temporal structure of noise. Methods: Audiometric and shift-long noise exposure data were collected from 3102 Chinese manufacturing workers from six typical industries through a cross-sectional survey. In data analysis, A-weighted 8-h equivalent SPL ( L Aeq.8h ), peak SPL, and cumulative noise exposure (CNE) were used as noise energy indicators, while kurtosis (β) was used as the indicator of noise temporal structure. Two NIHL were defined: (1) high-frequency noise-induced hearing loss (HFNIHL) and (2) noise-induced permanent threshold shift at test frequencies of 3, 4, and 6 kHz (noise-induced permanent threshold shift [NIPTS 346 ]). The noise characteristics of different types of work and the relationship between these characteristics and the prevalence of NIHL were analyzed. Results: The noise waveform shape, with a specific noise kurtosis, was unique to each type of work. Approximately 27.92% of manufacturing workers suffered from HFNIHL, with a mean NIPTS 346 of 24.16 ± 14.13 dB HL. The Spearman correlation analysis showed that the kurtosis value was significantly correlated with the difference of peak SPL minus its L Aeq.8h across different types of work ( p < 0.01). For a kurtosis-adjusted CNE, the linear regression equation between HFNIHL% and CNE for complex noise almost overlapped with Gaussian noise. Binary logistic regression analysis showed that L Aeq.8h , kurtosis, and exposure duration were the key factors influencing HFNIHL% ( p < 0.01). The notching extent in NIPTS at 4 kHz became deeper with the increase in L Aeq.8h and kurtosis. HFNIHL% increased most rapidly during the first 10 years of exposure. HFNIHL% with β ≥ 10 was significantly higher than that with β < 10 ( p < 0.05), and it increased with increasing kurtosis across different CNE or L Aeq.8h levels. When L Aeq.8h was 80 to 85 dB(A), the HFNIHL% at β ≥ 100 was significantly higher than that at 10 ≤ β < 100 or β < 10 ( p < 0.05 and p < 0.01, respectively). Conclusions: In the evaluation of hearing loss caused by complex noise, not only noise energy but also the temporal structure of noise must be considered. Kurtosis of noise is an indirect metric that is sensitive ...

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Section: Discussionsupporting

confidence: 78%

Applying Kurtosis as an Indirect Metric of Noise Temporal Structure in the Assessment of Hearing Loss Associated With Occupational Complex Noise Exposure

et al. 2021

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“…This gap can be addressed by extending acoustic SI models to the neural spike-train domain. In particular, spike-train data obtained from preclinical animal models of sensorineural hearing loss can be used to explore the neural correlates of perceptual deficits faced by hearing-impaired listeners [ 78 ]. These insights will be crucial for developing accurate SI models for hearing-impaired listeners.…”

Section: Discussionmentioning

confidence: 99%

Spectrally specific temporal analyses of spike-train responses to complex sounds: A unifying framework

2021

Self Cite

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Significant scientific and translational questions remain in auditory neuroscience surrounding the neural correlates of perception. Relating perceptual and neural data collected from humans can be useful; however, human-based neural data are typically limited to evoked far-field responses, which lack anatomical and physiological specificity. Laboratory-controlled preclinical animal models offer the advantage of comparing single-unit and evoked responses from the same animals. This ability provides opportunities to develop invaluable insight into proper interpretations of evoked responses, which benefits both basic-science studies of neural mechanisms and translational applications, e.g., diagnostic development. However, these comparisons have been limited by a disconnect between the types of spectrotemporal analyses used with single-unit spike trains and evoked responses, which results because these response types are fundamentally different (point-process versus continuous-valued signals) even though the responses themselves are related. Here, we describe a unifying framework to study temporal coding of complex sounds that allows spike-train and evoked-response data to be analyzed and compared using the same advanced signal-processing techniques. The framework uses a set of peristimulus-time histograms computed from single-unit spike trains in response to polarity-alternating stimuli to allow advanced spectral analyses of both slow (envelope) and rapid (temporal fine structure) response components. Demonstrated benefits include: (1) novel spectrally specific temporal-coding measures that are less confounded by distortions due to hair-cell transduction, synaptic rectification, and neural stochasticity compared to previous metrics, e.g., the correlogram peak-height, (2) spectrally specific analyses of spike-train modulation coding (magnitude and phase), which can be directly compared to modern perceptually based models of speech intelligibility (e.g., that depend on modulation filter banks), and (3) superior spectral resolution in analyzing the neural representation of nonstationary sounds, such as speech and music. This unifying framework significantly expands the potential of preclinical animal models to advance our understanding of the physiological correlates of perceptual deficits in real-world listening following sensorineural hearing loss.

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“…On the other hand, exotic species can serve as important models for human diseases. Examples are the armadillo Dasypus novemcinctus for research on leprosy [97], the turtle Trachemys scripta to study brain hypoxia and anoxia [98], and the pet Chinchilla lanigera to investigate hearing loss [99]. Diurnal rodents represent unique models of cone-related retinal diseases [100].…”

Section: The Use Of Experimental Models In Biomedicinementioning

confidence: 99%

Understanding and Treating Niemann–Pick Type C Disease: Models Matter

Pallottini

Pfrieger

2020

IJMS

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Biomedical research aims to understand the molecular mechanisms causing human diseases and to develop curative therapies. So far, these goals have been achieved for a small fraction of diseases, limiting factors being the availability, validity, and use of experimental models. Niemann–Pick type C (NPC) is a prime example for a disease that lacks a curative therapy despite substantial breakthroughs. This rare, fatal, and autosomal-recessive disorder is caused by defects in NPC1 or NPC2. These ubiquitously expressed proteins help cholesterol exit from the endosomal–lysosomal system. The dysfunction of either causes an aberrant accumulation of lipids with patients presenting a large range of disease onset, neurovisceral symptoms, and life span. Here, we note general aspects of experimental models, we describe the line-up used for NPC-related research and therapy development, and we provide an outlook on future topics.

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The chinchilla animal model for hearing science and noise-induced hearing loss

Cited by 40 publications

References 214 publications

Applying Kurtosis as an Indirect Metric of Noise Temporal Structure in the Assessment of Hearing Loss Associated With Occupational Complex Noise Exposure

Applying Kurtosis as an Indirect Metric of Noise Temporal Structure in the Assessment of Hearing Loss Associated With Occupational Complex Noise Exposure

Spectrally specific temporal analyses of spike-train responses to complex sounds: A unifying framework

Understanding and Treating Niemann–Pick Type C Disease: Models Matter

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