Figure 1.

(A) Schematic illustration of the stimulus-construction procedure. Envelopes (e) and fine structures (f) were separated from the E₁F₁ and E₂F₂ stimulus sets using the Hilbert transform. The envelopes and fine structures were exchanged and recombined to create chimeric stimulus sets E₁F₂ and E₂F₁. Detection patterns are shown to remind the reader that each stimulus wave form illustrated is a single member of an entire set of wave forms. A more detailed description of the stimuli (including distortion-control procedures) is given in the text. (B) Illustration of the multiple regression procedure for the E₁F₁ stimulus sets. Chimeric detection patterns sharing envelopes (E₁ in the example above) and sharing fine structure (F₁ above) were used to predict the detection pattern residuals (see text) for the base line stimulus set (E₁F₁ above). The b coefficients represent the slopes of the regression lines used in the multiple regression statistical model and also indicate how strongly the subject weighted the information associated with that cue. The b₀ coefficient is always equal to zero because variability linearly associated with the base line stimulus set not in the model (E₂F₂ above) was removed (see text for details). The ε term represents error variance. R² values were computed for envelope (gray), fine structure (black), and a linear combination of envelope and fine structure $\left(R_{\text{EF}}^2\right)$. If envelope completely dominated the detection process, it was expected that the E₁F₁ and E₁F₂ detection patterns (and the related patterns of residuals) would be the same and the $R_{\text{envelope}}^2=1$. If fine structure completely dominated the detection process, it was expected that the E₁F₁ and E₂F₁ detection patterns (and residuals) would be the same and the $R_{\text{fine}\text{structure}}^2=1$.