Spatial probability aids visual stimulus discrimination

Abstract

We investigated whether the statistical predictability of a target's location would influence how quickly and accurately it was classified. Recent results have suggested that spatial probability can be a cue for the allocation of attention in visual search. One explanation for probability cuing is spatial repetition priming. In our two experiments we used probability distributions that were continuous across the display rather than relying on a few arbitrary screen locations. This produced fewer spatial repeats and allowed us to dissociate the effect of a high-probability location from that of short-term spatial repetition. The task required participants to quickly judge the color of a single dot presented on a computer screen. In Experiment 1, targets were more probable in an off-center hotspot of high-probability that gradually declined to a background rate. Targets garnered faster responses if they were near earlier target locations (priming) and if they were near the high-probability hotspot (probability cuing). In Experiment 2, target locations were chosen on three concentric circles around fixation. One circle contained 80% of targets. The value of this ring distribution is that it allowed for a spatially restricted high-probability zone in which sequentially repeated trials were not likely to be physically close. Participant performance was sensitive to the high-probability circle in addition to the expected effects of eccentricity and the distance to recent targets. These two experiments suggest that inhomogeneities in spatial probability can be learned and used by participants on-line and without prompting as an aid for visual stimulus discrimination and that spatial repetition priming is not a sufficient explanation for this effect. Future models of attention should consider explicitly incorporating the probabilities of targets locations and features.

Attentional cartography: mapping the distribution of attention across time and space

“…Whereas most studies use a handful of cue and target locations, making even uninformative cues somewhat reliable, the likelihood of the target appearing at the cued location in our study was low: 1/121, to be exact (or a 25/121 likelihood of appearing in the cued quadrant). It is reasonable to suppose that the unreliability of the cue affected the distribution of attention (e.g., Druker & Anderson, 2010). However, even though the likelihood of the target appearing at the cued location was very low (1/121), we still replicated the typical facilitation-then-inhibition crossover pattern at the cued versus the opposite location (see Fig.…”

Body and head tilt reveals multiple frames of reference for spatial attention

“…Unbeknownst to participants, across multiple trials, the T target is more often found in a highprobability, ''rich'' quadrant than in the other ''sparse'' quadrants. Previous research has shown that participants rapidly acquire a spatial bias toward the rich quadrant (Druker & Anderson, 2010;Geng & Behrmann, 2002;Umemoto, Scolari, Vogel, & Awh, 2010). In addition, this spatial bias persists for several hundred trials of extinction training (Jiang, Swallow, Rosenbaum, et al, 2013).…”

Spatial priming in ecologically relevant reference frames

“…However, some researchers have posited a longer-term role for spatial priming, specifically claiming that it forms the building blocks of probability cueing (Walthew & Gilchrist, 2006), in which stable locations of interest in the environment gain prolonged prioritization. If Walthew and Gilchrist are correct (but see Druker & Anderson, 2010;Geng & Behrmann, 2005;Jiang, Swallow, Rosenbaum & Herzig, 2013, for debate on this point), it is plausible that the purpose of spatial priming is to constantly increment spatial priority at recent locations of interest in space, ultimately producing the long-term biases when spatial statistical regularities are present. This idea is consistent with instance-based theories of learning (Logan, 1988), in which learning becomes stronger over time because with each instance a separate memory trace is laid down that can be recruited at retrieval.…”