Towards a Better Understanding of Parallel Visual Processing in Human Vision

Evidence for Exhaustive Analysis of Visual Information

Buetti, Simona
Cronin, Deborah A.
Madison, Anna M.
Wang, Zhiyuan
Lleras, Alejandro

Department of Psychology, University of Illinois at Urbana-Champaign

The data and Matlab code are available on the Open Science Framework website at http://osf.io/xcw4f. Author contributions: Simona Buetti and Alejandro Lleras wrote the paper and equally contributed to the paper. Simona Buetti and Alejandro Lleras developed the theoretical framework; Simona Buetti, Alejandro Lleras and Deborah A. Cronin designed experiments 2, 3A-D; Simona Buetti, Alejandro Lleras and Anna M. Madison designed experiments 1 and 4. Anna M. Madison programed and analyzed experiments 1 and 4. Deborah A. Cronin programed and analyzed experiments 2 and 3. Zhiyuan Wang performed the simulations and eccentricity analyses and wrote the appendices.

We thank Gordon Logan, Cathleen Moore, and Toby Mordkoff for valuable feedback during the development of this project, as well as James Townsend, Ruth Rosenholtz, Todd Horowitz, and two anonymous reviewers for their helpful comments on a previous version of the manuscript.

Simona Buetti, Department of Psychology, University of Illinois at Urbana-Champaign, 603 East Daniel Street, Champaign, IL 61820 [email protected]

Received March 4, 2015

revised February 2, 2016

Accepted February 18, 2016

Journal of Experimental Psychology: General 145(6):p 672-707, June 2016. | DOI: 10.1037/xge0000163

Most current models of visual processing propose that there are 2 main stages of visual processing, the first consisting of a parallel visual analysis of the scene and the second being a precise scrutiny of a few elements in the scene. Here, we present novel evidence that the first stage of processing adds systematic variance to visual processing times. When searching for a specific target, it has a behaviorally unique signature: RTs increase logarithmically with the number of items in the display and this increase is modulated by target-distractor similarity. This signature is characteristic of unlimited capacity parallel and exhaustive processing of all the elements in the scene. The function of this processing is to identify the locations in the scene containing items that are sufficiently similar to the target as to merit focused scrutiny, while discarding those that do not. We also demonstrate that stage-1 variability is sensitive to the observers’ top-down goals: with identical displays, whereas RTs increase logarithmically with set size when observers are asked to find a specific target, they decrease exponentially when asked to find a unique item in the scene.