Does the moving attention paradigm improve all tasks that are limited by exposure time? Our assumption is that moving attention avoids local temporal limits by allowing access to an unchanging stimulus in a moving window (sidestepping the interruption masking that would occur at a stationary location). Moreover, as we showed in the accumulation results (
Figures 8 and
10), the information picked up in the moving window appears to be partial at each location and accumulated across locations. This accumulation could call on high-level visual areas with large receptive fields to mediate the continued analysis of the stimulus across time and space. In this experiment we use a moving attention window with a forward- and backward-masked stimulus to see whether moving attention can reduce the effects of a noise mask. In the display, a high-contrast mask and low-contrast target (a letter or a digit) alternate at each location (
Figure 11). Because the alternations are 180° out of phase at each successive location, the moving ring can be set to always encircle the target. Thus, in the moving frame of the attention window, the masks and the target are never superimposed (except by virtue of any imprecisions in attentional tracking, Hogendoorn, Carlson, & Verstraten,
2007); whereas in retinotopic coordinates, the masks and targets are always superimposed. If the mask acts through a low-level process, such as integration masking, which is retinotopic (Breitmeyer,
1984; Schiller,
1966), moving attention should not be able to avoid this local stimulus loss. However, if the masking occurs at a higher level, like interruption masking (Breitmeyer,
1984) or object substitution masking (Lleras & Moore,
2003), then moving attention may dodge the effects of the mask by keeping the target separate from the mask in the attended stream. In any case, even if moving attention cannot evade the masking, it may still allow accumulation of partial information across locations. Finally, a performance benefit, if it occurs, may also reflect probability summation. We already noted that the shape of the accumulation curves in
Figure 8 (and to some extent
Figure 10) do not show the initial negative acceleration predicted by probability summation. Nevertheless, we will evaluate this possibility again.