Introduction: The stria vascularis (SV) may have a significant role in various otologic pathologies. Currently, researchers manually segment and analyze the stria vascularis to measure structural atrophy. Our group developed a tool, SVPath, that uses deep learning to extract and analyze the stria vascularis and its associated capillary bed from whole temporal bone histopathology slides (TBS).
Methods: This study used an internal dataset of 203 digitized hematoxylin and eosin-stained sections from a normal macaque ear and a separate external validation set of 10 sections from another normal macaque ear. SVPath employed deep learning methods YOLOv8 and nnUnet to detect and segment the SV features from TBS, respectively. The results from this process were analyzed with the SV Analysis Tool (SVAT) to measure SV capillaries and features related to SV morphology, including width, area, and cell count. Once the model was developed, both YOLOv8 and nnUnet were validated on external and internal datasets.
Results: YOLOv8 implementation achieved over 90% accuracy for cochlea and SV detection. nnUnet SV segmentation achieved a DICE score of 0.84-0.95; the capillary bed DICE score was 0.75-0.88. SVAT was applied to compare both the ears used in the study. There was no statistical difference in SV width, SV area, and average area of capillary between the two ears. There was a statistical difference between the two ears for the cell count per SV.
Conclusion: The proposed method accurately and efficiently analyzes the SV from temporal histopathology bone slides, creating a platform for researchers to understand the function of the SV further.
Otoacoustic emissions (OAEs) are generated in the cochlea and recorded in the ear canal either as a time domain waveform or as a collection of complex responses to tones in the frequency domain (Probst et al. J Account Soc Am 89:2027-2067, 1991). They are typically represented either in their original acquisition domain or in its Fourier-conjugated domain. Round-trip excursions to the conjugated domain are often used to perform filtering operations in the computationally simplest way, exploiting the convolution theorem. OAE signals consist of the superposition of backward waves generated in different cochlear regions by different generation mechanisms, over a wide frequency range. The cochlear scaling symmetry (cochlear physics is the same at all frequency scales), which approximately holds in the human cochlea, leaves its fingerprints in the mathematical properties of OAE signals. According to a generally accepted taxonomy (Sher and Guinan Jr, J Acoust Soc Am 105:782-798, 1999), OAEs are generated either by wave-fixed sources, moving with frequency according with the cochlear scaling (as in nonlinear distortion) or by place-fixed sources (as in coherent reflection by roughness). If scaling symmetry holds, the two generation mechanisms yield OAEs with different phase gradient delay: almost null for wave-fixed sources, and long (and scaling as 1/f) for place-fixed sources. Thus, the most effective representation of OAE signals is often that respecting the cochlear scale-invariance, such as the time-frequency domain representation provided by the wavelet transform. In the time-frequency domain, the elaborate spectra or waveforms yielded by the superposition of OAE components from different generation mechanisms assume a much clearer 2-D pattern, with each component localized in a specific and predictable region. The wavelet representation of OAE signals is optimal both for visualization purposes and for designing filters that effectively separate different OAE components, improving both the specificity and the sensitivity of OAE-based applications. Indeed, different OAE components have different physiological meanings, and filtering dramatically improves the signal-to-noise ratio.
To enable nervous system function, neurons are powered in a use-dependent manner by mitochondria undergoing morphological-functional adaptation. In a well-studied model system-the mammalian cochlea, auditory nerve fibers (ANFs) display distinct electrophysiological properties, which is essential for collectively sampling acoustic information of a large dynamic range. How exactly the associated mitochondrial networks are deployed in functionally differentiated ANFs remains scarcely interrogated. Here, we leverage volume electron microscopy and machine-learning-assisted image analysis to phenotype mitochondrial morphology and distribution along ANFs of full-length in the mouse cochlea inner spiral bundle. This reveals greater variance in mitochondrial size with increased ANF habenula to terminal path length. Particularly, we analyzed the ANF terminal-residing mitochondria, which are critical for local calcium uptake during sustained afferent activities. Our results suggest that terminal-specific enrichment of mitochondria, in addition to terminal size and overall mitochondrial abundance of the ANF, correlates with heterogenous mitochondrial contents of the terminal.
Purpose: Tone-pip-evoked otoacoustic emissions (PEOAEs) are transient-evoked otoacoustic emissions (OAEs) that are hypothesized to originate from reflection of energy near the best-frequency (BF) cochlear place of the stimulus frequency. However, individual PEOAEs have energy with a wide range of delays. We sought to determine whether some PEOAE energy is consistent with having been generated far from BF.
Methods: PEOAEs from 35 and 47 dB SPL tone pips were obtained by removing pip-stimulus energy by subtracting the ear-canal sound pressure from scaled-down 59 dB SPL tone pips (which evoke relatively small OAEs). PEOAE delays were measured at each peak in the PEOAE absolute-value waveforms. While measuring PEOAEs and auditory-nerve compound action potentials (CAPs), amplification was blocked sequentially from apex to base by cochlear salicylate perfusion. The perfusion time when a CAP was reduced identified when the perfusion reached the tone-pip BF place. The perfusion times when each PEOAE peak was reduced identified where along the cochlea it received cochlear amplification. PEOAEs and CAPs were measured simultaneously using one pip frequency in each ear (1.4 to 4 kHz across 16 ears).
Results: Most PEOAE peaks received amplification primarily between the BF place and 1-2 octaves basal of the BF place. PEOAE peaks with short delays received amplification basal of BF place. PEOAE peaks with longer delays sometimes received amplification apical of BF place, consistent with previous stimulus-frequency-OAE results.
Conclusion: PEOAEs provide information about cochlear amplification primarily within ~ 1.5 octave of the tone-pip BF place, not about regions > 3 octaves basal of BF.
Purpose: The interaural time difference (ITD) is a primary horizontal-plane sound localization cue computed in the auditory brainstem. ITDs are accessible in the temporal fine structure of pure tones with a frequency of no higher than about 1400 Hz. How listeners' ITD sensitivity transitions from very best sensitivity near 700 Hz to impossible to detect within 1 octave currently lacks a fully compelling physiological explanation. Here, it was hypothesized that the rapid decline in ITD sensitivity is dictated not by a central neural limitation but by initial peripheral sound encoding, specifically, the low-frequency (apical) portion of the cochlear excitation pattern produced by a pure tone.
Methods: ITD sensitivity was measured in 16 normal-hearing listeners as a joint function of frequency (900-1500 Hz) and level (10-50 dB sensation level).
Results: Performance decreased with increasing frequency and decreasing sound level. The slope of performance decline was 90 dB/octave, consistent with the low-frequency slope of the cochlear excitation pattern.
Conclusion: Fine-structure ITD sensitivity near 1400 Hz may be conveyed primarily by "off-frequency" activation of neurons tuned to lower frequencies near 700 Hz. Physiologically, this could be realized by having neurons sensitive to fine-structure ITD up to only about 700 Hz. A more extreme model would have only a single narrow channel near 700 Hz that conveys fine-structure ITDs. Such a model is a major simplification and departure from the classic formulation of the binaural display, which consists of a matrix of neurons tuned to a wide range of relevant frequencies and ITDs.
This perspective reviews the current state of the art and literature on tinnitus in children, prevalence and risk factors, clinical management, and future priorities for healthcare provision and research. Most research in the field to date appears to be prevalence studies, which have reached dramatically different estimates; this reflects the lack of a standard language when asking about the presence of tinnitus, or how bothersome, distressing, or negatively impacting it is for the child. Estimates are also likely affected by a lack of awareness of tinnitus amongst children and parents. Children are less likely to spontaneously report tinnitus than adults, and parents are often unaware their child could even develop tinnitus, considering it a disease of older age for example. It is critical that children are asked and learn about tinnitus. In hearing clinics, clinicians should routinely ask about all children about tinnitus and offer tinnitus care and settings that are child- and family-friendly. As well as asking directly, clinicians should be alert to soft signs of tinnitus such as unexplained listening, speech perception, concentration difficulties, worry or anxiety, or difficulties completing hearing tests or using hearing aids. The recently developed impact of Tinnitus in Children Questionnaire (iTICQ) can then be used to assess problems that are most commonly core to children's experience of tinnitus. Clinical guidelines for tinnitus in children are few but provide recommendations for additional paediatric questionnaires and alternative assessments and for a range of treatment options. Of note, however, is the lack of clinical trials and, therefore, evidence of the effectiveness of any treatment for tinnitus in children. Significant and concerted work is therefore needed to raise awareness of tinnitus in children, understand the scale of clinical need, and standardise and evaluate clinical management options.
Tinnitus, the perception of sound without a corresponding external sound source, and tinnitus disorder, which is tinnitus with associated suffering, present a multifaceted clinical challenge due to its heterogeneity and its incompletely understood pathophysiology and especially due to the limited therapeutic options. In this narrative review, we give an overview on various clinical aspects of tinnitus including its heterogeneity, contributing factors, comorbidities and therapeutic pathways with a specific emphasis on the implications for its pathophysiology and future research directions. Tinnitus exhibits high perceptual variability between affected individuals (heterogeneity) and within affected individuals (temporal variability). Hearing loss emerges as predominant risk factor and the perceived pitch corresponds to areas of hearing loss, supporting the compensatory response theory. Whereas most people who have tinnitus can live a normal life, in 10-20% tinnitus interferes severely with quality of life. These patients suffer frequently from comorbidities such as anxiety, depression or insomnia, acting as both risk factors and consequences. Accordingly, neuroimaging studies demonstrate shared brain networks between tinnitus and stress-related disorders shedding light on the intricate interplay of mental health and tinnitus. The challenge lies in deciphering causative relationships and shared pathophysiological mechanisms. Stress, external sounds, time of day, head movements, distraction, and sleep quality can impact tinnitus perception. Understanding these factors provides insights into the interplay with autonomic, sensory, motor, and cognitive processes. Counselling and cognitive-behavioural therapy demonstrate efficacy in reducing suffering, supporting the involvement of stress and anxiety-related networks. Hearing improvement, especially through cochlear implants, reduces tinnitus and thus indirectly validates the compensatory nature of tinnitus. Brain stimulation techniques can modulate the suffering of tinnitus, presumably by alteration of stress-related brain networks. Continued research is crucial for unravelling the complexities of tinnitus. Progress in management hinges on decoding diverse manifestations, identifying treatment-responsive subtypes, and advancing targeted therapeutic approaches.
Purpose: Several treatment methods for hearing disorders rely on attaching medical devices to the tympanic membrane. This study aims to systematically analyze the effects of the material and geometrical properties and location of the medical devices attached to the tympanic membrane on middle-ear vibrations.
Methods: A finite-element model of the human middle ear was employed to simulate the effects of attachment of medical devices. Various types of material and geometrical properties, locations, and modeling scenarios were investigated for the medical device.
Results: The attachment of the device magnifies the effects of anti-resonances of the middle ear. Additionally, the variations of the material properties of the device significantly alter the middle-ear resonance frequency while changes in the umbo and stapes footplate motions are negligible at frequencies above 5 kHz. Furthermore, modeling the device as a point mass cannot accurately represent the implanted middle-ear behavior. The variations of the diameter and height of the medical device have negligible effects on the middle-ear vibrations at frequencies below 200 Hz but can have considerable impacts at higher frequencies. The effects of changing the device height were negligible at frequencies above 2 kHz. We also discuss the effects of medical device attachment on the vibration patterns of the tympanic membrane as well as the impacts of the variations of the location of the device on the stapes footplate responses.
Conclusion: The findings of our study aid the development and optimization of new therapeutic devices, attached to the tympanic membrane, to have the least adverse effects on middle-ear vibrations.
Objectives: Tinnitus subtypes are proposed to lie on a continuum of different symptom dimensions rather than be categorical. However, there is no comprehensive empirical data showing this complex relationship between different tinnitus symptoms. The objective of this study is to provide empirical evidence for the dimensional nature of tinnitus and how different auditory and non-auditory symptoms interact with each other through complex interactions. We do this using graph theory, a mathematical tool that empirically maps this complex interaction. This way, graph theory can be utilised to highlight a new and possibly important outlook on how we can understand the heterogeneous nature of tinnitus.
Design: In the current study, we use the screening databases of the Treatment Evaluation of Neuromodulation for Tinnitus-Stage A1 (TENT-A1) and A2 (TENT-A2) randomised trials to delineate the dimensional relationship between different clinical measures of tinnitus as a secondary data analysis. We first calculate the empirical relationship by computing the partial correlation. Following this, we use different measures of centrality to describe the contribution of different clinical measures to the overall network. We also calculate the stability of the network and compare the similarity and differences between TENT-A1 and TENT-A2.
Results: Components of the auditory subnetwork (loudness discomfort level, sound sensitivity, average hearing loss and high frequency hearing loss) are highly inter-connected in both networks with sound sensitivity and loudness discomfort level being highly influential with high measures of centrality. Furthermore, the relationship between the densely connected auditory subnetwork with tinnitus-related distress seems to vary at different levels of distress, hearing loss, duration and age of the participants.
Conclusion: Our findings provide first-time evidence for tinnitus varying in a dimensional fashion illustrating the heterogeneity of this phantom percept and its ability to be perceptually integrated, yet behaviourally segregated on different symptomatic dimensions.
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