Combining 1-D components to extract pattern information: It is about more than component similarity

Abstract

At least under some conditions, plaid stimuli are processed by combining information first extracted in orientation and scale-selective channels. The rules that govern this combination across channels are only partially understood. Although the available data suggests that only components having similar spatial frequency and contrast are combined, the extent to which this holds has not been firmly established. To address this question, we measured, in human subjects, the short-latency reflexive vergence eye movements induced by stereo plaids in which spatial frequency and contrast of the components are independently varied. We found that, although similarity in component spatial frequency and contrast matter, they interact in a nonseparable way. One way in which this relationship might arise is if the internal estimate of contrast is not a faithful representation of stimulus contrast but is instead spatial frequency-dependent (with higher spatial frequencies being boosted). We propose that such weighting might have been put in place by a mechanism that, in an effort of achieve contrast constancy and/or coding efficiency, regulates the gain of detectors in early visual cortex to equalize their long-term average response to natural images.

Figure 1

PDR to unidisparity plaids with unequal SF and contrast. The SF of the oblique grating associated with the strongest response varies as a function of the contrast of the oblique component. (A) PDR in each of the three subjects. Each curve (log-Gaussian fit to the data) shows the magnitude of the PDR (±SEM) for different values of the SF of the oblique grating for one contrast of the oblique grating (see legend). SF and contrast of the vertical grating are always the same. Dashed line indicates SF of the vertical grating. Horizontal line indicates zero response. The scale is different in the three subjects so that the axis top corresponds to 0.9 °/s for BMS, 0.32 °/s for CQ, and 0.58 °/s for JH. (B) The peak of each curve fit in panel A shifts to lower SFs as the contrast of the oblique grating increases. Linear fit in log–log coordinates is shown. Dashed lines indicate SF and contrast of vertical grating.

Figure 2

PDR to unidisparity plaids with unequal SF or contrast. (A) PDR in two subjects when the SF of the two gratings is varied and the contrast is the same (32%). Each curve shows the magnitude of the PDR (±SEM) for different values of the SF of the oblique grating, for one SF of the vertical grating (see legend). Horizontal line indicates zero response. The scale is different in the two subjects so that the axis top corresponds to 0.8 °/s for BMS and 0.4 °/s for CQ. (B) PDR in two subjects when the contrast of the two gratings is varied and the SF is the same (0.25 c/°). Each curve shows the magnitude of the PDR (±SEM) for different values of the contrast of the oblique grating for one contrast of the vertical grating (see legend). Horizontal line indicates zero response. The scale is different in the two subjects so that the axis top corresponds to 0.9 °/s for BMS and 0.35 °/s for CQ.

Figure 3

Model fits for subject BMS. Data (black circles, mean ± SEM) and model fits (orange lines for model E, blue lines for model L) to the experimental results presented in Figure 1A (top row), Figure 2A (middle row), and Figure 2B (bottom row). The numbers in each panel indicate, for each model, the error (average z score) on that data set, a measure of goodness of fit (lower is better).

Figure 4

Model fits for subject CQ. Same format as in Figure 3.

Figure 5

Model fits for subject JH. Data (black circles) and model fits (orange lines for model E, blue lines for model L) to the experimental results presented in Figure 1.