Coding-In-Noise Deficits After Exposure to Noise Mimicking Real-Life Parameters
Abstract
Noise induced synaptopathy (NIS) has been thoroughly researched in animals since the first observation of significant synaptic loss without permanent threshold shift (PTS) in CBA mice after brief noise exposure. However, it remains a challenge to translate these animal findings to human data, since the noise used to establish NIS in previous animal studies is unlike the noise experienced by humans in everyday life. A total of 32 albino guinea pigs were separated into a control and a noise group. The noise group was exposed to noise mimicking what is experienced by humans (relatively low in level, fluctuated and intermittent) to investigate whether NIS without PTS could be established by such noise. It was also examined whether coding-in-noise deficits (CIND) are the major difficulty associated with NIS without PTS, which has previously been speculated based on evidence for disproportionate synaptic loss for auditory nerve fibers (ANFs) with low spontaneous rates (LSR). This was done by examining the impact of the NIS on temporal processing under masking. Furthermore, since robust evidence supporting CIND as the major problem associated with NIS is limited, the role of LSR ANFs in signal coding of high-level noise has been reexamined (see review (Carney, 2018)): the fluctuation profile model has been proposed to support a role for high-SR ANFs in the coding of high-level noise in combination with efferent control of cochlear gain. This study evaluated the role of temporal fluctuation in evoking efferent feedback and the effects of NIS on this feedback. Results showed that noise exposure experienced by humans in daily life is less effective in causing NIS, and that the NIS causes temporal processing deficits that are likely of a central origin. Additionally, results demonstrated no apparent evidence suggesting that NIS deteriorates the signal detection ability in noise using temporal cues. Finally, the results did not provide sufficient evidence supporting the MOC regulation in the fluctuation profile model.