Accounting for nonmonotonic precursor duration effects with gain reduction in the temporal window model

Abstract

The mechanisms of forward masking are not clearly understood. The temporal window model (TWM) proposes that masking occurs via a neural mechanism that integrates within a temporal window. The medial olivocochlear reflex (MOCR), a sound-evoked reflex that reduces cochlear amplifier gain, may also contribute to forward masking if the preceding sound reduces gain for the signal. Psychophysical evidence of gain reduction can be observed using a growth of masking (GOM) paradigm with an off-frequency forward masker and a precursor. The basilar membrane input/output (I/O) function is estimated from the GOM function, and the I/O function gain is reduced by the precursor. In this study, the effect of precursor duration on this gain reduction effect was examined for on-and off-frequency precursors. With on-frequency precursors, thresholds increased with increasing precursor duration, then decreased (rolled over) for longer durations. Thresholds with off-frequency precursors continued to increase with increasing precursor duration. These results are not consistent with solely neural masking, but may reflect gain reduction that selectively affects on-frequency stimuli. The TWM was modified to include history-dependent gain reduction to simulate the MOCR, called the temporal window model-gain reduction (TWM-GR). The TWM-GR predicted rollover and the differences with on-and off-frequency precursors whereas the TWM did not.

Auditory Time-Frequency Masking for Spectrally and Temporally Maximally-Compact Stimuli

“…To predict masking data involving longer Δ T s, for instance previous TF masking data for long maskers, models based on gain reduction are presumably necessary. Although the temporal window model could well account for some masking data for long maskers ( D M > 100 ms) [52, 63], the present findings together with [29, 37] suggest that the prediction accuracy might be improved if a gain reduction stage were incorporated into the temporal window model. To examine this, our three-step simulation procedure was applied to the TF masking data reported in [18] using model 1, which performed better than model 2 in all conditions of Fig 5.…”

“…This adds support to the interpretation that forward masking can be well described by combining cochlear nonlinearities with a temporal integrator [51]. Note that another implementation of the temporal window model that features a gain reduction stage, and that has also been tested on TF conditions, was proposed in [29]. To fit their data, the authors allowed all model parameters (i.e.…”

“…those of the cochlear filter, gain reduction module, temporal integrator, and detection device) to freely vary. Because of the likely strong interaction between parameters, the choice of an adequate set of parameters for the gain reduction module to analyze the present data based on the results in [29] would have been critical. Thus, we did not test this model.…”

“…[27, 30, 40, 41]). Moreover, recent modeling work has shown that adding a gain reduction stage in current models of masking could qualitatively account for some of the changes in spectral and temporal masking associated with D M , Δ T , and the presence of a precursor [29, 37, 48, 49]. Based on these considerations we concluded that the spread of TF masking for a well-localized signal can hardly be derived from existing data and has therefore to be measured.…”

“…A few studies using short sinusoidal maskers involved TF conditions, including temporal masking functions measured for Δ F ≠ 0 (e.g. [26–29]) and spectral masking functions measured for Δ T ≠ 0 [30]. Because these studies used a small set of Δ F s and Δ T s (at most two values tested), their results do not provide sufficient information on the spread of TF masking produced by such a well-localized masker.…”