A third possible mechanism to explain the observed cueing effect is
differential-weighting, where the allocation of visual attention can be described as the distribution of weights assigned to the sensory evidence for a state of the world (Dayan & Zemel,
1999; Eckstein, Abbey, et al.,
2004; Eckstein, Pham, et al.,
2004; Eckstein et al.,
2002; Kinchla, Chen, & Evert,
1995; Shaw,
1982; Shimozaki, Eckstein, & Abbey,
2003). In this framework, visual information is encoded with equal quality, saliency, or signal-to-noise ratio, across the possible target locations, but information arising from more probable locations is given more weight towards the decision of detecting or rejecting the target. Thus, this weighting model incorporates both the raw sensory information in the image (e.g. contrast value), as well as internal estimates of the likelihood of this sensory information occurring, given an observer's prior knowledge of the probability that the state of the world (e.g. target presence) would give rise to this stimulus. A differential-weighting model captures psychophysical demonstrations of cueing (Eckstein, Pham, et al.,
2004; Eckstein et al.,
2002), context effect of saccadic deployment in natural scenes (Eckstein et al.,
2006; Torralba et al.,
2006) as well as neurophysiology data (Eckstein, Liston, & Krauzlis,
2007), and quantitative models of eye movements (Carpenter & Williams,
1995). Differential weighting is also compatible with theories of selective attention that consider the computational challenge of monitoring uncertainty in dynamic environments and the role of prediction in guiding perceptual decisions (Dayan, Kakade, & Montague,
2000). Observers' distribution of saccadic and perceptual decisions in the present task is consistent with this model: cues more likely to contain the target were increasingly likely to be selected (
Figure 6). Thus, this cue effect is likely a reflection of a prior expectation of target presence, influencing the value of an internal decision variable used for saccades and perceptual decisions. We next explore how these expectations may be learned.