Abstract
Effects of attention have been widely tested in low precision tasks that discriminate quite different stimuli (i.e., horizontal and vertical pattern orientations), but far less often in high precision tasks that discriminate similar stimuli (i.e., with very similar angles). Without explicitly testing higher precision tasks and an associated observer model, effects of attention on the asymptotes of psychometric functions lack a principled account. Here we show that an elaborated perceptual template model (ePTM; Jeon et al, 2009; Liu et al, 2009) identifies the mechanisms of dual-object attention—deficits in reporting one feature each for two objects compared to two features of one object. Dual object conditions report the orientation of one Gabor object and phase of another; single object conditions report orientation and phase of the same object. Object attention effects were examined in a large data set comprising dual object and single object tests, each with a family of psychometric functions in six different levels of external noise, yielding threshold versus external noise curves for modestly high precision judgments of Gabor orientation and phase. The ePTM accounts for 84 conditions each for phase and orientation judgments (2 object x 6 external noise x 7 Gabor contrast conditions) by a narrowing of the attended template compared to the unattended template—resulting in both asymptotic effects of attention in all conditions and substantial effects across the psychometric function in high external noise associated with external noise filtering. The ePTM, composed of two overlapping templates, nonlinearity, internal multiplicative and additive noise, and decision, provides a principled account of patterns of the effects of attention on the psychometric function sometimes associated with response and contrast gain. The use of higher precision judgments revealed the impact of the narrowing of the attention template in the dimension of judgment on the asymptotes of psychometric functions.
Meeting abstract presented at VSS 2014