Authors: Juan M. Fuentes¹
¹Universitat Pompeu Fabra
Background: Sensory systems must represent vast stimulus ranges under metabolic constraints. Efficient-coding theory predicts that neural adaptation re-allocates activity toward the most informative stimulus values. However, it remains unclear how hidden hearing loss (HHL) affects this operating point in central auditory circuits, particularly given that sound levels vary dramatically across environments and clinical thresholds often miss listening deficits in noise.
Method: Extracellular recordings were analyzed from single neurons in the gerbil auditory midbrain across four experimental groups. Animals were exposed to two sound-level distributions: a uniform range (24–96 dB SPL) and “high-probability” contexts where 80% of levels fell within a narrow 12-dB range. Neuronal rate-intensity functions were summarized by effective threshold and gain, then interpreted through an information-cost model that trades stimulus information against metabolic spiking costs.
Results: Noise exposure consistent with HHL altered gain modulation across acoustic contexts. Exposed animals demonstrated compressed gain adjustments compared to controls. Within the information-cost framework, a utility advantage was observed in quiet contexts, specifically concentrated in low-threshold neurons, while group differences were weaker or absent in louder contexts. Temporary conductive hearing loss shifted thresholds to higher levels, with incomplete recovery following the removal of earplugs.
Conclusion: These findings provide an efficient-coding perspective on how hidden hearing loss alters central auditory representations. The study establishes a context-based framework for understanding hearing difficulties, suggesting that neural coding efficiency is compromised in noise-exposed listeners even when traditional threshold-only tests fail to detect an impairment.
