The CWN had no significant effect on the PTCs at 4 kHz (Fig. 6.2, bottom). At 500 Hz, by contrast, the CWN led to lower masker levels at masked threshold in some conditions (Fig. 6.2, top). This effect occurred for all masker frequencies at the longest masker-probe time interval (50 ms). For the shorter intervals (2 and 10 ms), it only occurred for masker frequencies remote from the probe frequency, thus broadening the near-threshold PTCs.

The present results appear inconsistent with the study of Vinay and Moore (2008) on the effect of a CWN on near-threshold PTCs. They showed that the CWN had a different effect on the PTCs depending on the probe frequency. At 500 Hz, the CWN typically shifted the low-frequency side of the PTCs upwards and increased the tuning significantly. The difference with the present results may reflect methodological differences between studies. Indeed, Vinay and Moore (2008) measured PTCs using simultaneous rather than forward masking, and their probe and CWN levels differed from those used here.

At first sight, the pattern of the present results appears inconsistent with the effects of electrical activation of the MOCR on high-frequency basilar membrane (BM) responses, which shifts only the tip of the tuning curves upwards (Cooper and Guinan 2006). The computer model simulations described below will show that this inconsistency is more apparent than real.

A computer model of forward masking with efferent control was developed and used to test the assumption that the pattern of experimental data was consistent with the hypothesis that the CWN reduces cochlear gain by activating the MOCR. The model was inspired by the BM-temporal window model (Plack et al. 2002). In the current version of the model, the dual-resonance nonlinear (DRNL) filter (Meddis et al. 2001) was replaced by a version with efferent attenuation (Ferry and Meddis 2007). The latter simulates physiological observations at the level of the BM and auditory nerve by means of a single parameter that attenuates the input signal to the nonlinear path of the standard DRNL filter. Another novelty of the current model is that it accounts for the off-frequency listening effects at 500 Hz. This was deemed necessary because no precaution was taken experimentally to minimize off-­frequency listening effects on PTCs that may have occurred due to the brief duration of the probe (10 ms).

The model was implemented in the time domain and evaluated for identical stimuli and conditions as used in the experiments. Its parameters were optimized automatically as follows. First, the parameters of the standard DRNL filter (without efferent attenuation) and the temporal window were optimized simultaneously to mimic the 4-kHz PTCs and the linear reference TMCs measured without the CWN. The resulting temporal window parameters were held constant for the other test frequencies and conditions. It was assumed that the rate of recovery from forward masking is constant across probe frequencies and that it is unaffected by CWN (see Fig. 6.1). Second, the parameters of the standard DRNL filter (without efferent attenuation) were optimized at 500 Hz using the experimental PTCs measured ­without the CWN. Lastly, the parameter controlling the amount of efferent attenuation was optimized to maximize the fit between simulated and experimental PTCs measured with CWN. The value of this parameter was allowed to vary across probe frequencies.

Importantly, rather than fitting the model to the mean data, a different set of model parameters was obtained for each individual data set, and the individual model responses were averaged and compared to the mean experimental PTCs.