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Richard S. Hetley, Barbara Anne Dosher, Zhong-Lin Lu; Parallel Processing in Difficult Visual Search in both Noisy and Noiseless Displays. Journal of Vision 2013;13(9):691. doi: 10.1167/13.9.691.
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Visual search accuracy in time-limited displays often shows a set size effect, decreasing as the number of distractors increases. This is especially so for difficult visual searches, e.g., searching for an O among C's. Original models proposed a serial search processing architecture for difficult search (Treisman & Gelade, 1980, and many others), but a growing body of evidence shows an unlimited-capacity parallel probabilistic model provides a better account of the time course of visual search in the absence of external visual noise (for time-limited displays) (Dosher, Han, & Lu, 2004; Dosher, Han, & Lu, 2010; McElree & Carrasco, 1999). Because spatial attention has been shown primarily to exclude external noise (Dosher & Lu, 2001), the current experiment tested whether a parallel probabilistic model (PPM) of search dynamics also accounts for visual search in external (masking) noise, or whether external noise induces different processing demands with capacity limits. We performed a visual search task for an O among C's in a cued-response speed-accuracy experiment, manipulating set size (2, 4, and 8), delay to the response cue (0.05 s through 1.8 s) and the presence or absence of external noise; accuracy, d', was measured as a function of processing time. Stimulus contrasts (100% and 30% contrast) were set to approximately equate overall asymptotic discrimination in the presence and absence of external noise. In the PPM, the probability of hits and false alarms at different processing times (and therefore d') depends on the independent finishing times of processing for all items simultaneously, while requiring different decision criteria for each set size. For all observers and conditions, the unlimited-capacity PPM provided an excellent account of both time course and asymptotic accuracy. External noise does not alter the dynamics of information accumulation in visual search.
Meeting abstract presented at VSS 2013
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