Figure 6.

A Phenomenological Model of Synaptopathy and Gain Increase Reproduces the Effects of Noise-Induced HHL on Neural Encoding of Speech

(A) The effect of synaptopathy affecting predominantly high-threshold fibers was modeled through a saturation of the spiking probability of IC neurons.

(B) Gain increase was modeled through a multiplicative increase of spike probability restoring the maximum spike probability to the normal (non-synaptopathic) value.

(C) The HHL+gain function was applied to PSTHs from control animals to generate the corresponding HL-model PSTHs. Poisson spikes were generated from both the control and HL-model PSTHs to generate model neurograms, which were then subjected to the discrimination algorithm to generate model results for the control and hearing loss condition.

(D and E) Neurograms from the HL model (red) showed better discriminability than neurograms from the control model (black) at 60 dB SPL (D) but reduced discriminability at 75 dB SPL (E), producing a qualitative match to the results obtained with the experimental neurograms (Figure 4).