University of Iowa Honors Theses

Major Department

Psychology

College

College of Liberal Arts & Sciences

Degree

BS (Bachelor of Science)

Session and Year of Graduation

Spring 2018

Honors Major Advisor

Toby Mordkoff

Thesis Mentor

Shaun Vecera

Abstract

Visual attention can be influenced through statistical learning of information in the environment, and over time, extracted visual patterns relevant to the current task can be used to guide attention. Specifically, within a visual search paradigm, statistical learning of feature information (e.g. color) can be implicitly extracted to make attentional guidance more efficient. In addition, we know that the system can use explicitly provided information, such as the contents of visual working memory (VWM) to bias attention. We hypothesized that feature-based statistical learning might interact with the contents of VWM. In the present study, participants searched through displays containing target features (i.e. shape) that were more likely to contain the target of the search than another feature. In order to examine the interaction between VWM and previously learned attentional biases, in Experiment 2, we trained participants on the same implicit learning task as Experiment 1. We introduced a color to be remembered that either matched the color of the target, of the distractor, or was a color that was not present in the search display. We found that when a color was stored in VWM and present in the search display, all attentional biases based on the previously learned statistics disappeared. Therefore, we hypothesize that VWM dominates attentional guidance. In other words, feature-based statistical learning disappears when there is a concurrent strong VWM bias.

Keywords

visual working memory, attention, statistical learning, features

Total Pages

22

Copyright

Copyright © 2018 Eli Schmidt

COinS
 

URL

https://ir.uiowa.edu/honors_theses/195