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Comparison of level discrimination, increment detection, and comodulation masking release in the audio- and envelope-frequency domains
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View: Figures


Image of FIG. 1.
FIG. 1.

Comparison of the gated-continuous difference in the audio (left) and envelope (right) frequency domains. Schematic illustrations of stimulus waveforms in the two experiments are shown in (a) and (c) (horizontal bars between the stimuli indicate the timing of the observation intervals). (b) Audio-frequency level discrimination thresholds measured with gated (closed circles) and quasi-continuous pedestals (closed squares). (d) AM depth discrimination thresholds for a modulated standard obtained with traditional gated intervals (open circles), and with quasi-continuous modulation presented before, between, and after the observation intervals (open squares). For both (b) and (d): ; standard . Each symbol is the average threshold for four listeners; error bars indicate standard deviation of the individual mean thresholds.

Image of FIG. 2.
FIG. 2.

(a) Mean audio-frequency level discrimination thresholds (solid symbols) and envelope-frequency detection thresholds (open symbols) under different gating conditions. Squares represent performance with a quasi-continuous carrier; circles correspond to thresholds with gated carriers. Conditions AM1 and AM2 are distinguishable based on the presence (AM1) or absence (AM2) of a dc component in the target interval. (b) Schematic illustrations of the stimulus envelopes used in each condition. Conditions INC and ID are re-plotted from Fig. 1(b). Error bars represent across-listener standard deviations (as in Fig. 1).

Image of FIG. 3.
FIG. 3.

Example temporal envelopes of the stimuli used to test for envelope-domain comodulation masking release. Standard-interval envelopes (left) are defined by the masker-alone waveform; target interval envelopes (right) are made up of an additive combination of masker and sinusoidal signal AM. R: Baseline (unmodulated, or random masker) condition. : Sinusoidal venelope fluctuations. : Square-wave venelope fluctuations. For all stimuli, ; standard ; masker , geometrically centered on the signal frequency; observation interval ; signal depth ; venelope fluctuation .

Image of FIG. 4.
FIG. 4.

Effects of imposing slow and regular fluctuations on the masker amplitude in the envelope- and audio-frequency domains. Conditions correspond to different temporal shapes imposed on the masker amplitude. Left panel: Audio-frequency thresholds. R: random flat masker envelope (unmodulated). C: SAM masker envelope, filtered after modulation and not equalized for overall energy increment caused by modulation. Right panel: Envelope-frequency thresholds. R: flat venelope masker (unmodulated). : SAM venelope, noise filtered after modulation. : SAM venelope, noise only filtered prior to modulation. : square-wave venelope, noise filtered after imposing the fluctuations. Conditions , , and were compensated for the small overall increase in masker energy caused by the modulation. Error bars indicate standard deviation of the individual mean thresholds

Image of FIG. 5.
FIG. 5.

Individual and mean SAM detection thresholds as a function of the frequency of the square-wave venelope fluctuations imposed on the first-order masker modulation. Stimulus parameters were the same as those in condition of Fig. 4, except the overall duration was increased to . Error bars plotted with individual listener data represent across-track standard deviations; those with the mean data indicate across-listener standard deviations.

Image of FIG. 6.
FIG. 6.

Simulated responses to standard and target stimuli for the AN and IC levels of the SFIE model. Upper panels: SPL standard level; lower panels: SPL standard level. The target interval level was higher than the standard. Left panels: gated stimuli; right panels: fringe presentation mode.

Image of FIG. 7.
FIG. 7.

Rate difference profiles for different gating modes (left and right panels) and levels of the model (upper and lower panels) in response to a level increment. Each curve represents changes in the model rate responses for a tone with a fixed standard SPL. Twenty-five model cells, log-spaced from , were simulated for each standard level and gating mode.

Image of FIG. 8.
FIG. 8.

Across-frequency information profiles, arranged in the same format as Fig. 7. This measure of sensitivity takes both neural variance and changes in average rates into account.

Image of FIG. 9.
FIG. 9.

SFIE model responses are qualitatively consistent with a fringe advantage in AM detection and no fringe advantage in AM depth discrimination. Model responses are shown for a window centered on the presentation of a standard followed by a target modulation. Simulated PSTHs are shown for an AM detection paradigm (top two panels) and an AM depth discrimination task (bottom two panels); gated and fringe conditions are included for both tasks. Stimulus parameters: ; ; ; detection ; discrimination , . Key model parameters: ; ; ; AN .

Image of FIG. 10.
FIG. 10.

Model IC cell average rates and example IFR functions in response to the stimuli used in the envelope-frequency CMR paradigm. Model parameters were the same as those used to generate the responses in Fig. 9, except the AN , , and , which resulted in a cell rate-tuned to the signal AM frequency. The signal depth was fixed at in the target interval, and a square-wave venelope was imposed on the masker in the comodulated conditions (as in the extension to experiment II). For comparison, rates and IFRs elicited by the random (R), or unmodulated, condition are also included in the plot. The duration of stimuli and IFRs was .


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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Comparison of level discrimination, increment detection, and comodulation masking release in the audio- and envelope-frequency domains