Further evidence and understanding for the contrast signal theory of parallel processing in visual search
Human vision relies on massive parallel processes to make sense of visual information in the world. There has been increasing evidence in the literature that the visual attention affects and depends on early, parallel visual processing. However, understanding of the cognitive mechanism and temporal dynamics of parallel vision has been lacking. Specifically, in the visual search literature, major models of the search process have established a convention that parallel processing during visual search does not have meaningful time cost variations. Recent results have demonstrated that, to the contrary, parallel processing in fixed-target search tasks produce systematic, logarithmic RT variations depending on set size and target-distractor similarity. The Contrast Signal Theory (CST) of visual search was proposed to account for these variations and elucidate the potential processing mechanism during the parallel stage of visual search. The core proposals of CST include that 1) objects are categorized as unlikely or likely to be the target based on accumulation of a contrast signal between each object’s visual features and the target template and 2) termination of the parallel stage is based on a ‘time out’ mechanism. This dissertation research started with numerical simulations that elucidated properties and predictions of CST in addition to previously published results. Based on these predictions, we investigated whether previously uncontrolled-for effects of target eccentricity could have been the source of log-like RT by set size functions. Our results suggested that eccentricity and cortical magnification affect the processing efficiency of individual items, but they were not responsible for the specific form of RT variability found in fixed-target efficient search tasks. Further, we adapted the Systems Factorial Technology methods to further examine two key hypotheses of CST, and found converging evidence that different types of low-similarity distractors (‘lures’) are processed exhaustively in parallel, while lures and candidates as two groups of distractors are processed exhaustively and serially. Finally, two event-related potential (ERP) components, the visual N1 and the N2pc, were found to index the attentive resource allocation of parallel stage processing and the termination of parallel stage respectively. N1 amplitude was shown to be sensitive to target-distractor similarity, supporting the idea that parallel processing during visual search depends on target template information. N2pc onset latency was found to be modulated by both similarity and set size, consistent with CST’s prediction. Variations in parallel stage processing time was found to account for the majority of behavioral response time variability. Contrast Signal Theory is therefore the most detailed and successful model of parallel processing during visual search to date, and should be incorporated in a complete model of visual search and visual attention.
Visual search, Visual attention, Parallel processing, Computational model, Reaction time, Processing mechanism
University of Illinois - Urbana-Champaign
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University of Illinois at Urbana-Champaign