Further evidence and understanding for the contrast signal theory of parallel processing in visual search
type: CreativeWork
description: 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’)…
abstract: 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’)…
author: Wang, Zhiyuan
language: en
keywords: Visual search, Visual attention, Parallel processing, Computational model, Reaction time, Processing mechanism
date published: 2020-03-02T22:15:07Z
date modified: 2026-07-22T22:24:45Z
provider: University of Illinois - Urbana-Champaign
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Illinois at Urbana-Champaign

PropertyValue
property ID: Handle
value: http://hdl.handle.net/2142/106371