Comparison of Conditions

The overall objective of this study was to determine whether parallel stimulus presentation provides better place specificity than serial presentation. To allow conditions to be compared at a glance, we required a summary metric to describe the place specificity of each response. Due to the asymmetric and often irregular shape of the responses (when viewed across CF), common measures of bandwidth were not applicable here. We designed our metric to describe the place specificity of each response (w from Equation 1), penalizing response spread to CFs away from the stimulus frequency as well as off-place peaks.

Each response started as a firing rate which varied over time and CF that we eventually reduced to a single quantity. To collapse across time, the lags corresponding to the maximum response value at each CF in the serial condition were determined (black dotted line, leftmost panel Figure 3). The value of the response at this lag was then selected for both the serial and parallel conditions, resulting in a single magnitude for each CF for each condition. Using the peak time from the serial condition was important because the parallel responses contained some residual noise from the other stimulus sequences. This noise was small and disappeared as stimulus length increased, but at CFs where the response was also small, the noise had the potential to bias the maximum value across time spuriously higher.

Computation of summary metric to compare conditions. The example shown is from the Zilany et al. model, with a test frequency of 1 kHz and stimulus rate of 120 stim/s at 75 dB SPL. Time lags are selected for each CF where the maximum value occurs in the serial condition (black dotted line in the serial panel). These time lags are used to select values from both the serial and parallel condition (green dotted line in parallel panel) to avoid bias, which are then normalized such that the value at the test frequency is equal to one, penalizing responses which are stronger in off-frequency regions. The values are then integrated across CFs in octaves to determine PS (rightmost panel), which serves as a single number descriptor of place specificity. PS = place specificity metric; CF = characteristic frequency; SPL = sound pressure level.

We then normalized all magnitude values by dividing them by the magnitude at the CF corresponding to the stimulus frequency (such that the latter became equal to one). This normalization allowed for comparison across conditions (where response magnitude can vary significantly) and penalized cases where the strongest responses were not at the CF matching the stimulus frequency. Next, the response was integrated across CF, with CF expressed in octaves (reflecting the roughly logarithmic spacing of CF on the cochlea), to produce a single number related to the contribution of off-place responses for each rate-intensity pair. Lastly, we inverted the number to make it interpretable in a similar manner as a Quality Factor, with larger numbers corresponding to more place-specific responses. Hereafter we refer to this numerical place specificity metric simply as PS. This process is illustrated in Figure 3. To compare the serial and parallel conditions, the ratio of the PS for the parallel to the serial condition was calculated. A ratio greater than one indicates an improvement in PS for the parallel stimulus relative to the corresponding serial stimulus with the same parameters.

Since this study uses modeled responses, for which arbitrarily small confidence intervals could be obtained by generating more data, no significance testing was performed. Instead, we comment on grossly observable trends. These trends will be tested using data recorded from human subjects in a future study.