How much of noise masking derives from noise?

In masking studies, external luminance noise is often used to estimate an observer’s level of internal (neural) noise. However, the standard noise model fails three important empirical tests: noise does not fully linearise the slope of the psychometric function, masking occurs even when the noise is identical in both 2AFC intervals, and double pass consistency is too low. This implies the involvement of additional processes such as suppression from contrast gain control or increased uncertainty, either of which invalidate estimates of equivalent internal noise. We propose that jittering the target contrast (cf Cohn, 1426–1428) provides a ’cleaner’ source of noise because it excites only the detecting mechanism. We compare the jitter condition to masking from 1D and 2D (white and pink) pixel noise, pedestals and orthogonal masks, in double pass masking and (novel) contrast matching experiments. The results show that contrast jitter produced the strongest masking, greatest double pass consistency, and no suppression of perceived contrast: just as the standard model of noise masking predicts (and unlike pixel noise). We attribute the remainder of the masking from pixel noise to contrast gain control, raising concerns about its use in equivalent noise masking experiments.