Animal-to-Human Translation Difficulties and Problems With Proposed Coding-in-Noise Deficits in Noise-Induced Synaptopathy and Hidden Hearing Loss

Abstract

Noise induced synaptopathy (NIS) and hidden hearing loss (NIHHL) have been hot topic in hearing research since a massive synaptic loss was identified in CBA mice after a brief noise exposure that did not cause permanent threshold shift (PTS) in 2009. Based upon the amount of synaptic loss and the bias of it to synapses with a group of auditory nerve fibers (ANFs) with low spontaneous rate (LSR), coding-in-noise deficit (CIND) has been speculated as the major difficult of hearing in subjects with NIS and NIHHL. This speculation is based upon the idea that the coding of sound at high level against background noise relies mainly on the LSR ANFs. However, the translation from animal data to humans for NIS remains to be justified due to the difference in noise exposure between laboratory animals and human subjects in real life, the lack of morphological data and reliable functional methods to quantify or estimate the loss of the afferent synapses by noise. Moreover, there is no clear, robust data revealing the CIND even in animals with the synaptic loss but no PTS. In humans, both positive and negative reports are available. The difficulty in verifying CINDs has led a re-examination of the hypothesis that CIND is the major deficit associated with NIS and NIHHL, and the theoretical basis of this idea on the role of LSR ANFs. This review summarized the current status of research in NIS and NIHHL, with focus on the translational difficulty from animal data to human clinicals, the technical difficulties in quantifying NIS in humans, and the problems with the SR theory on signal coding. Temporal fluctuation profile model was discussed as a potential alternative for signal coding at high sound level against background noise, in association with the mechanisms of efferent control on the cochlea gain.

Keywords: auditory nerve; cochlear efferent; coding-in-noise deficit; fluctuation profile; noise induced synaptopathy (NIS); ribbon synapses; temporal processing.

FIGURE 1

Fluctuation profile of ANF response to vowel /ae/ spectrum, which is in the foreground. The model peristimulus time histograms (PSTHs) of HSR ANFs are presented at formant peaks (F1 = 700 and F2 = 1800 Hz) and troughs. Temporal fluctuation is large at trough frequencies and small nor none at the formants, forming the dips in the fluctuation amplitude that mirrors the formants. Adapted from Carney (2018).

FIGURE 2

The efferent feedback loops controlling the OHC gain. The short loops going through lower brainstem are marked by redlines. The thickness of the line represents the relative strength in the typical loop from PVCN to MOCNs (green dots). The loop from the small cell cap in AVCN to MOCN is thought to be selective receiving input from L/MSR ANFs. The relative strength of this loop is unknown. The long feedback loop (blue lines) includes the projection from both AVCN and PVCN cores to IC, which is sensitive to the low-frequency temporal fluctuation. The fluctuation is inherited and enhanced in the descending projection from IC to MOCNs. AVCN/PVCN, anterior/posterior ventral cochlear nucleus; DCN, dorsal cochlear nucleus; MOCN, medium olive cochlea neurons; MSO, medium superior olive; IC, inferior colliculus.

FIGURE 3

Summary on what we know and what we do not know in the research of NIS and NIHHL. Note that NIS without PTS is overlapped with NIHHL of peripheral origin. The dashed lines without question markers indicate where the connection remain to be speculation and need to be verified.