Auditory changes in awake guinea pigs exposed to overcompressed music.

Exposure to loud sound during leisure time is identified as a significant risk factor for hearing by health authorities worldwide. The current standard that defines unsafe exposure rests on the equal-energy hypothesis, according to which the maximum recommended exposure is a tradeoff between level and daily exposure duration, a satisfactory recipe except for strongly non-Gaussian intense sounds such as gunshots. Nowadays, sound broadcast by music and videoconference streaming services makes extensive use of numerical dynamic range compression. By filling in millisecond-long valleys in the signal to prevent competing noise from masking, it pulls sound-level statistics away from a Gaussian distribution, the framework where the equal-energy hypothesis emerged. Auditory effects of a single 4 hour exposure to the same music were compared in two samples of guinea pigs exposed either to its original or overcompressed version played at the same average level of 102 dBA allowed by French regulations. Apart from a temporary shift of otoacoustic emissions at the lowest two frequencies 2 and 3 kHz, music exposure had no detectable cochlear effect, as monitored at 1, 2 and 7 days post-exposure. Conversely, middle-ear muscle strength behaved differentially as the group exposed to original music had fully recovered one day after exposure whereas the group exposed to overcompressed music remained stuck to about 50% of baseline even after 7 days. Subsamples were then re-exposed to the same music as the first time and sacrificed for density measurements of inner-hair-cell synapses. No difference in synaptic density was found compared to unexposed controls with either type of music. The present results show that the same music piece, harmless when played in its original version, induces a protracted deficit of one auditory neural pathway when overcompressed at the same level. The induced disorder does not seem to involve inner-hair cell synapses.

Large-scale annotated dataset for cochlear hair cell detection and classification.

Our sense of hearing is mediated by cochlear hair cells, of which there are two types organized in one row of inner hair cells and three rows of outer hair cells. Each cochlea contains 5-15 thousand terminally differentiated hair cells, and their survival is essential for hearing as they do not regenerate after insult. It is often desirable in hearing research to quantify the number of hair cells within cochlear samples, in both pathological conditions, and in response to treatment. Machine learning can be used to automate the quantification process but requires a vast and diverse dataset for effective training. In this study, we present a large collection of annotated cochlear hair-cell datasets, labeled with commonly used hair-cell markers and imaged using various fluorescence microscopy techniques. The collection includes samples from mouse, rat, guinea pig, pig, primate, and human cochlear tissue, from normal conditions and following in-vivo and in-vitro ototoxic drug application. The dataset includes over 107,000 hair cells which have been identified and annotated as either inner or outer hair cells. This dataset is the result of a collaborative effort from multiple laboratories and has been carefully curated to represent a variety of imaging techniques. With suggested usage parameters and a well-described annotation procedure, this collection can facilitate the development of generalizable cochlear hair-cell detection models or serve as a starting point for fine-tuning models for other analysis tasks. By providing this dataset, we aim to give other hearing research groups the opportunity to develop their own tools with which to analyze cochlear imaging data more fully, accurately, and with greater ease.

Large-scale annotated dataset for cochlear hair cell detection and classification.

Our sense of hearing is mediated by cochlear hair cells, localized within the sensory epithelium called the organ of Corti. There are two types of hair cells in the cochlea, which are organized in one row of inner hair cells and three rows of outer hair cells. Each cochlea contains a few thousands of hair cells, and their survival is essential for our perception of sound because they are terminally differentiated and do not regenerate after insult. It is often desirable in hearing research to quantify the number of hair cells within cochlear samples, in both pathological conditions, and in response to treatment. However, the sheer number of cells along the cochlea makes manual quantification impractical. Machine learning can be used to overcome this challenge by automating the quantification process but requires a vast and diverse dataset for effective training. In this study, we present a large collection of annotated cochlear hair-cell datasets, labeled with commonly used hair-cell markers and imaged using various fluorescence microscopy techniques. The collection includes samples from mouse, human, pig and guinea pig cochlear tissue, from normal conditions and following in-vivo and in-vitro ototoxic drug application. The dataset includes over 90'000 hair cells, all of which have been manually identified and annotated as one of two cell types: inner hair cells and outer hair cells. This dataset is the result of a collaborative effort from multiple laboratories and has been carefully curated to represent a variety of imaging techniques. With suggested usage parameters and a well-described annotation procedure, this collection can facilitate the development of generalizable cochlear hair cell detection models or serve as a starting point for fine-tuning models for other analysis tasks. By providing this dataset, we aim to supply other groups within the hearing research community with the opportunity to develop their own tools with which to analyze cochlear imaging data more fully, accurately, and with greater ease.

Morphological and functional correlates of vestibular synaptic deafferentation and repair in a mouse model of acute-onset vertigo.

Damage to cochlear primary afferent synapses has been shown to be a key factor in various auditory pathologies. Similarly, the selective lesioning of primary vestibular synapses might be an underlying cause of peripheral vestibulopathies that cause vertigo and dizziness, for which the pathophysiology is currently unknown. To thoroughly address this possibility, we selectively damaged the synaptic contacts between hair cells and primary vestibular neurons in mice through the transtympanic administration of a glutamate receptor agonist. Using a combination of histological and functional approaches, we demonstrated four key findings: (1) selective synaptic deafferentation is sufficient to generate acute vestibular syndrome with characteristics similar to those reported in patients; (2) the reduction of the vestibulo-ocular reflex and posturo-locomotor deficits mainly depends on spared synapses; (3) damaged primary vestibular synapses can be repaired over the days and weeks following deafferentation; and (4) the synaptic repair process occurs through the re-expression and re-pairing of synaptic proteins such as CtBP2 and SHANK-1. Primary synapse repair might contribute to re-establishing the initial sensory network. Deciphering the molecular mechanism that supports synaptic repair could offer a therapeutic opportunity to rescue full vestibular input and restore gait and balance in patients.